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Rafehi H, Fearnley LG, Read J, Snell P, Davies KC, Scott L, Gillies G, Thompson GC, Field TA, Eldo A, Bodek S, Butler E, Chen L, Drago J, Goel H, Hackett A, Halmagyi GM, Hannaford A, Kotschet K, Kumar KR, Kumble S, Lee-Archer M, Malhotra A, Paine M, Poon M, Pope K, Reardon K, Ring S, Ronan A, Silsby M, Smyth R, Stutterd C, Wallis M, Waterston J, Wellings T, West K, Wools C, Wu KHC, Szmulewicz DJ, Delatycki MB, Bahlo M, Lockhart PJ. A prospective trial comparing programmable targeted long-read sequencing and short-read genome sequencing for genetic diagnosis of cerebellar ataxia. Genome Res 2025; 35:769-785. [PMID: 40015980 PMCID: PMC12047251 DOI: 10.1101/gr.279634.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 11/21/2024] [Indexed: 03/01/2025]
Abstract
The cerebellar ataxias (CAs) are a heterogeneous group of disorders characterized by progressive incoordination. Seventeen repeat expansion (RE) loci have been identified as the primary genetic cause and account for >80% of genetic diagnoses. Despite this, diagnostic testing is limited and inefficient, often utilizing single gene assays. This study evaluates the effectiveness of long- and short-read sequencing as diagnostic tools for CA. We recruited 110 individuals (48 females, 62 males) with a clinical diagnosis of CA. Short-read genome sequencing (SR-GS) was performed to identify pathogenic RE and also non-RE variants in 356 genes associated with CA. Independently, long-read sequencing with adaptive sampling (LR-AS) was performed to identify pathogenic RE. SR-GS provided a genetic diagnosis for 38% of the cohort (40/110) including seven non-RE pathogenic variants. RE causes disease in 33 individuals, with the most common condition being SCA27B (n = 24). In comparison, LR-AS identified pathogenic RE in 29 individuals. RE identification for the two methods was concordant apart from four SCA27B cases not detected by LR-AS due to low read depth. For both technologies manual review of the RE alignment enhances diagnostic outcomes. Orthogonal testing for SCA27B revealed a 15% and 0% false positive rate for SR-GS and LR-AS, respectively. In conclusion, both technologies are powerful screening tools for CA. SR-GS is a mature technology currently used by diagnostic providers, requiring only minor changes in bioinformatic workflows to enable CA diagnostics. LR-AS offers considerable advantages in the context of RE detection and characterization but requires optimization before clinical implementation.
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Affiliation(s)
- Haloom Rafehi
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Liam G Fearnley
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Justin Read
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Department of Neuroscience, Central Clinical School, Monash University, The Alfred Centre, Melbourne, Victoria 3004, Australia
| | - Penny Snell
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Kayli C Davies
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Liam Scott
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
| | - Greta Gillies
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Genevieve C Thompson
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Tess A Field
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Aleena Eldo
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Simon Bodek
- Austin Health, Heidelberg, Victoria 3084, Australia
| | - Ernest Butler
- Monash Medical Centre, Clayton, Victoria 3168, Australia
| | - Luke Chen
- Department of Neurology, Alfred Hospital, Melbourne, Victoria 3004, Australia
| | - John Drago
- Department of Medicine, St Vincent's Hospital, University of Melbourne, Fitzroy, Victoria 3065, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria 3052, Australia
| | - Himanshu Goel
- Hunter Genetics, Hunter New England Health Service, Waratah, New South Wales 2298, Australia
| | - Anna Hackett
- Hunter Genetics, Hunter New England Health Service, Waratah, New South Wales 2298, Australia
- University of Newcastle, Callaghan, New South Wales 2308, Australia
| | - G Michael Halmagyi
- Neurology Department, Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia
- Central Clinical School, University of Sydney, Camperdown, New South Wales 2050, Australia
| | - Andrew Hannaford
- Department of Neurology, Westmead Hospital, Hawkesbury Westmead, New South Wales 2145, Australia
- Brain and Nerve Research Centre, Concord Clinical School, University of Sydney, Camperdown, New South Wales 2050, Australia
- Department of Neurology, Concord Repatriation General Hospital, Concord, New South Wales 2139, Australia
| | - Katya Kotschet
- Department of Clinical Neurosciences, St Vincent's Hospital, University of Melbourne, Fitzroy, Victoria 3065, Australia
| | - Kishore R Kumar
- Molecular Medicine Laboratory and Neurology Department, Concord Repatriation General Hospital, Concord, New South Wales 2139, Australia
- Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales 2050, Australia
- Genomics and Inherited Disease Program, The Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia
- School of Medicine, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Smitha Kumble
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Department of Clinical Genetics, Austin Health, Viewbank, Victoria 3084, Australia
| | - Matthew Lee-Archer
- Department of Neurology, Launceston General Hospital, Launceston, Tasmania 7250, Australia
| | - Abhishek Malhotra
- Department of Neuroscience, University Hospital Geelong, Geelong, Victoria 3220, Australia
| | - Mark Paine
- Department of Neurology, Royal Brisbane and Women's Hospital, Herston, Queensland 4006, Australia
| | - Michael Poon
- Neurology Footscray, Footscray, Victoria 3011, Australia
| | - Kate Pope
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Katrina Reardon
- Department of Medicine, St Vincent's Hospital, University of Melbourne, Fitzroy, Victoria 3065, Australia
- Department of Neurology, St Vincent's Hospital, University of Melbourne, Fitzroy, Victoria 3065, Australia
| | - Steven Ring
- Albury Wodonga Health, West Albury, New South Wales 2640, Australia
| | - Anne Ronan
- University of Newcastle, Callaghan, New South Wales 2308, Australia
- Newcastle Medical Genetics, Lambton, New South Wales 2299, Australia
| | - Matthew Silsby
- Department of Neurology, Westmead Hospital, Hawkesbury Westmead, New South Wales 2145, Australia
- Brain and Nerve Research Centre, Concord Clinical School, University of Sydney, Camperdown, New South Wales 2050, Australia
- Department of Neurology, Concord Repatriation General Hospital, Concord, New South Wales 2139, Australia
| | - Renee Smyth
- St Vincent's Clinical Genomics, St Vincent's Hospital, Darlinghurst, New South Wales 2010, Australia
| | - Chloe Stutterd
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Mathew Wallis
- Tasmanian Clinical Genetics Service, Tasmanian Health Service, Royal Hobart Hospital, Hobart, Tasmania 7001, Australia
- School of Medicine and Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania 7000, Australia
| | - John Waterston
- Department of Neuroscience, Central Clinical School, Monash University, The Alfred Centre, Melbourne, Victoria 3004, Australia
| | - Thomas Wellings
- Department of Neurology, John Hunter Hospital, New Lambton Heights, New South Wales 2305, Australia
| | - Kirsty West
- Genomic Medicine, The Royal Melbourne Hospital, Parkville, Victoria 3052, Australia
| | - Christine Wools
- Department of Neurology, Calvary Health Care Bethlehem, Caulfield South Victoria 3162, Australia
- Department of Neurology, The Royal Melbourne Hospital, Parkville, Victoria 3052, Australia
| | - Kathy H C Wu
- St Vincent's Clinical Genomics, St Vincent's Hospital, Darlinghurst, New South Wales 2010, Australia
- School of Medicine, University of Notre Dame, Darlinghurst, New South Wales 2010, Australia
- Discipline of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales 2050, Australia
| | - David J Szmulewicz
- Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria 3002, Australia
- Bionics Institute, East Melbourne, Victoria 3002, Australia
| | - Martin B Delatycki
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria 3052, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Paul J Lockhart
- Bruce Lefroy Centre, Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia;
- Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria 3052, Australia
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El Jaddaoui I, Sehli S, Al Idrissi N, Bakri Y, Belyamani L, Ghazal H. The Gut Mycobiome for Precision Medicine. J Fungi (Basel) 2025; 11:279. [PMID: 40278100 PMCID: PMC12028274 DOI: 10.3390/jof11040279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2025] [Revised: 03/29/2025] [Accepted: 03/31/2025] [Indexed: 04/26/2025] Open
Abstract
The human gastrointestinal tract harbors a vast array of microorganisms, which play essential roles in maintaining metabolic balance and immune function. While bacteria dominate the gut microbiome, fungi represent a much smaller, often overlooked fraction. Despite their relatively low abundance, fungi may significantly influence both health and disease. Advances in next-generation sequencing, metagenomics, metatranscriptomics, metaproteomics, metabolomics, and computational biology have provided novel opportunities to study the gut mycobiome, shedding light on its composition, functional genes, and metabolite interactions. Emerging evidence links fungal dysbiosis to various diseases, including inflammatory bowel disease, colorectal cancer, metabolic disorders, and neurological conditions. The gut mycobiome also presents a promising avenue for precision medicine, particularly in biomarker discovery, disease diagnostics, and targeted therapeutics. Nonetheless, significant challenges remain in effectively integrating gut mycobiome knowledge into clinical practice. This review examines gut fungal microbiota, highlighting analytical methods, associations with human diseases, and its potential role in precision medicine. It also discusses pathways for clinical translation, particularly in diagnosis and treatment, while addressing key barriers to implementation.
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Affiliation(s)
- Islam El Jaddaoui
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, University Mohammed V, Rabat 10000, Morocco; (I.E.J.); (Y.B.)
- Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat 10000, Morocco
- Laboratory of Precision Medicine & One Health (MedPreOne), School of Medicine, Mohammed VI University of Sciences & Health, Casablanca 82403, Morocco; (S.S.); (N.A.I.)
| | - Sofia Sehli
- Laboratory of Precision Medicine & One Health (MedPreOne), School of Medicine, Mohammed VI University of Sciences & Health, Casablanca 82403, Morocco; (S.S.); (N.A.I.)
| | - Najib Al Idrissi
- Laboratory of Precision Medicine & One Health (MedPreOne), School of Medicine, Mohammed VI University of Sciences & Health, Casablanca 82403, Morocco; (S.S.); (N.A.I.)
| | - Youssef Bakri
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, University Mohammed V, Rabat 10000, Morocco; (I.E.J.); (Y.B.)
- Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat 10000, Morocco
| | - Lahcen Belyamani
- School of Medicine, Mohammed VI University of Sciences & Health, Casablanca 82403, Morocco;
| | - Hassan Ghazal
- Laboratory of Precision Medicine & One Health (MedPreOne), School of Medicine, Mohammed VI University of Sciences & Health, Casablanca 82403, Morocco; (S.S.); (N.A.I.)
- Laboratory of Sports Sciences and Performance Optimization, Royal Institute of Executive Management, Salé 10102, Morocco
- National Center for Scientific and Technical Research, Rabat 10102, Morocco
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Au-Yeung CCY, Cheung YT, Cheng JYT, Ip KWH, Lee SD, Yang VYT, Lau AYT, Lee CKC, Chong PKH, Lau KW, van Lunenburg JTJ, Zheng DFD, Ho BHM, Tik C, Ho KKK, Rajaby R, Au CH, Yu MHC, Sung WK. UniVar: A variant interpretation platform enhancing rare disease diagnosis through robust filtering and unified analysis of SNV, INDEL, CNV and SV. Comput Biol Med 2025; 185:109560. [PMID: 39700857 DOI: 10.1016/j.compbiomed.2024.109560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Revised: 11/24/2024] [Accepted: 12/08/2024] [Indexed: 12/21/2024]
Abstract
BACKGROUND Interpreting the pathogenicity of genetic variants associated with rare diseases is a laborious and time-consuming endeavour. To streamline the diagnostic process and lighten the burden of variant interpretation, it is crucial to automate variant annotation and prioritization. Unfortunately, currently available variant interpretation tools lack a unified and comprehensive workflow that can collectively assess the clinical significance of these types of variants together: small nucleotide variants (SNVs), small insertions/deletions (INDELs), copy number variants (CNVs) and structural variants (SVs). RESULTS The Unified Variant Interpretation Platform (UniVar) is a free web server tool that offers an automated and comprehensive workflow on annotation, filtering and prioritization for SNV, INDEL, CNV and SV collectively to identify disease-causing variants for rare diseases in one interface, ensuring accessibility for users even without programming expertise. To filter common CNVs/SVs, a diverse SV catalogue has been generated, that enables robust filtering of common SVs based on population allele frequency. Through benchmarking our SV catalogue, we showed that it is more complete and accurate than the state-of-the-art SV catalogues. Furthermore, to cope with those patients without detailed clinical information, we have developed a novel computational method that enables variant prioritization from gene panels. Our analysis shows that our approach could prioritize pathogenic variants as effective as using HPO terms assigned by clinicians, which adds value for cases without specific clinically assigned HPO terms. Lastly, through a practical case study of disease-causing compound heterozygous variants across SNV and SV, we demonstrated the uniqueness and effectiveness in variant interpretation of UniVar, edging over any existing interpretation tools. CONCLUSIONS UniVar is a unified and versatile platform that empowers researchers and clinicians to identify and interpret disease-causing variants in rare diseases efficiently through a single holistic interface and without a prerequisite for HPO terms. It is freely available without login and installation at https://univar.live/.
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Affiliation(s)
- Cherie C Y Au-Yeung
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Yuen-Ting Cheung
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Joshua Y T Cheng
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Ken W H Ip
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Sau-Dan Lee
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Victor Y T Yang
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Amy Y T Lau
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Chit K C Lee
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Peter K H Chong
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - King Wai Lau
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | | | - Damon F D Zheng
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Brian H M Ho
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Crystal Tik
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Kingsley K K Ho
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Ramesh Rajaby
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China; Shibuya Laboratory, Division of Medical Data Informatics, Human Genome Center, University of Tokyo, Japan
| | - Chun-Hang Au
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Mullin H C Yu
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China
| | - Wing-Kin Sung
- Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China; Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong, China; Laboratory of Computational Genomics, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China.
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Stellacci E, Martinelli S, Carbone P, Demuru E, Genuardi M, Ghiorzo P, Novelli G, Di Pucchio A, Regini FM, Guerrera D, Vittozzi A, Barbina D, Venanzi S, van den Bulcke M, Boccia S, Mazzaccara A, De Nicolo A, De Angelis R. Bridging the educational gaps of health professionals in oncogenomics: results from a pilot e-learning course. Front Med (Lausanne) 2024; 11:1422163. [PMID: 39640978 PMCID: PMC11617149 DOI: 10.3389/fmed.2024.1422163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 11/05/2024] [Indexed: 12/07/2024] Open
Abstract
BACKGROUND Genetic and genomic literacy of health professionals is of utmost importance to realize the full potential of personalized medicine. As part of a European Union project, we piloted an e-learning course on oncogenomics, primarily targeted to physicians, and we assessed both its effectiveness and users' satisfaction. METHODS The course materials were developed in English according to the Problem-Based Learning method. Learning objectives, covering the basic principles of genetics and the OMICS technologies applied to oncology, were defined based on previously identified core competencies. We used a pre-test vs. post-test study design to assess knowledge improvements. Performance results by demographic and professional characteristics of participants were analyzed using univariate or multivariate statistical methods. RESULTS Overall, 346 Italian professionals (61% physicians, 39% biologists) successfully completed the course. Their average post-test score was almost 19% higher than the pre-test (71.6% vs. 52.9%), with no significant differences by sex. Older age (>50 years) and southern area of residence were both correlated with higher gains. The average proportion of correct answers in the final certification test after three attempts was 85% (69% at first attempt), with some differences across professional categories. Methodology, quality of content and usability of the e-learning platform were all highly rated via satisfaction questionnaire (average scores between 4 and 5, scale 1 to 5). CONCLUSION The pilot phase confirmed the suitability of the e-learning as a cost-effective method to improve oncogenomic literacy of health professionals. Translation into natural languages and accreditation by European or country-specific Continuing Medical Education systems will be the main incentives for wider dissemination.
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Affiliation(s)
- Emilia Stellacci
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Simone Martinelli
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Pietro Carbone
- Training Service, Istituto Superiore di Sanità, Rome, Italy
| | - Elena Demuru
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | - Maurizio Genuardi
- Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
- Medical Genetics Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Paola Ghiorzo
- Department of Internal Medicine and Medical Specialties, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genetics of Rare Cancers, Genoa, Italy
| | - Giuseppe Novelli
- Department of Biomedicine and Prevention, Genetics Section, University of Rome “Tor Vergata”, Rome, Italy
| | | | | | | | | | | | - Serenella Venanzi
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
| | | | - Stefania Boccia
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | | | - Arcangela De Nicolo
- Center for Omics Sciences, IRCSS San Raffaele Scientific Institute, Milan, Italy
| | - Roberta De Angelis
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy
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Nibali L, Divaris K, Lu EMC. The promise and challenges of genomics-informed periodontal disease diagnoses. Periodontol 2000 2024; 95:194-202. [PMID: 39072804 DOI: 10.1111/prd.12587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 05/16/2024] [Accepted: 06/07/2024] [Indexed: 07/30/2024]
Abstract
Recent advances in human genomics and the advent of molecular medicine have catapulted our ability to characterize human and health and disease. Scientists and healthcare practitioners can now leverage information on genetic variation and gene expression at the tissue or even individual cell level, and an enormous potential exists to refine diagnostic categories, assess risk in unaffected individuals, and optimize disease management among those affected. This review investigates the progress made in the domains of molecular medicine and genomics as they relate to periodontology. The review summarizes the current evidence of association between genomics and periodontal diseases, including the current state of knowledge that approximately a third of the population variance of periodontitis may be attributable to genetic variation and the management of several monogenic forms of the disease can be augmented by knowledge of the underlying genetic cause. Finally, the paper discusses the potential utility of polygenic risk scores and genetic testing for periodontitis diagnosis now and in the future, in light of applications that currently exist in other areas of medicine and healthcare.
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Affiliation(s)
- Luigi Nibali
- Periodontology Unit, Centre for Host Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK
| | - Kimon Divaris
- Department of Pediatric Dentistry and Dental Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Emily Ming-Chieh Lu
- Periodontology Unit, Centre for Host Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London, UK
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Bhatia K, Sandhu V, Wong MH, Iyer P, Bhatt S. Therapeutic biomarkers in acute myeloid leukemia: functional and genomic approaches. Front Oncol 2024; 14:1275251. [PMID: 38410111 PMCID: PMC10894932 DOI: 10.3389/fonc.2024.1275251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 01/17/2024] [Indexed: 02/28/2024] Open
Abstract
Acute myeloid leukemia (AML) is clinically and genetically a heterogeneous disease characterized by clonal expansion of abnormal hematopoietic progenitors. Genomic approaches to precision medicine have been implemented to direct targeted therapy for subgroups of AML patients, for instance, IDH inhibitors for IDH1/2 mutated patients, and FLT3 inhibitors with FLT3 mutated patients. While next generation sequencing for genetic mutations has improved treatment outcomes, only a fraction of AML patients benefit due to the low prevalence of actionable targets. In recent years, the adoption of newer functional technologies for quantitative phenotypic analysis and patient-derived avatar models has strengthened the potential for generalized functional precision medicine approach. However, functional approach requires robust standardization for multiple variables such as functional parameters, time of drug exposure and drug concentration for making in vitro predictions. In this review, we first summarize genomic and functional therapeutic biomarkers adopted for AML therapy, followed by challenges associated with these approaches, and finally, the future strategies to enhance the implementation of precision medicine.
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Affiliation(s)
- Karanpreet Bhatia
- Department of Pharmacy, National University of Singapore, Singapore, Singapore
| | - Vedant Sandhu
- Department of Pharmacy, National University of Singapore, Singapore, Singapore
| | - Mei Hsuan Wong
- Department of Pharmacy, National University of Singapore, Singapore, Singapore
| | - Prasad Iyer
- Children's Blood and Cancer Centre, KK Women's and Children's Hospital, Singapore, Singapore
- Duke-National University of Singapore (NUS) Medical School, Singapore, Singapore
| | - Shruti Bhatt
- Department of Pharmacy, National University of Singapore, Singapore, Singapore
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Liu Q, Li G, Baladandayuthapani V. Pan-Cancer Drug Response Prediction Using Integrative Principal Component Regression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.03.560366. [PMID: 37873111 PMCID: PMC10592913 DOI: 10.1101/2023.10.03.560366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The pursuit of precision oncology heavily relies on large-scale genomic and pharmacological data garnered from preclinical cancer model systems such as cell lines. While cell lines are instrumental in understanding the interplay between genomic programs and drug response, it well-established that they are not fully representative of patient tumors. Development of integrative methods that can systematically assess the commonalities between patient tumors and cell-lines can help bridge this gap. To this end, we introduce the Integrative Principal Component Regression (iPCR) model which uncovers both joint and model-specific structured variations in the genomic data of cell lines and patient tumors through matrix decompositions. The extracted joint variation is then used to predict patient drug responses based on the pharmacological data from preclinical models. Moreover, the interpretability of our model allows for the identification of key driver genes and pathways associated with the treatment-specific response in patients across multiple cancers. We demonstrate that the outputs of the iPCR model can assist in inferring both model-specific and shared co-expression networks between cell lines and patients. We show that iPCR performs favorably compared to competing approaches in predicting patient drug responses, in both simulation studies and real-world applications, in addition to identifying key genomic drivers of cancer drug responses.
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Pal P, Shastry RP. Exploring the complex role of gut microbiome in the development of precision medicine strategies for targeting microbial imbalance-induced colon cancer. Folia Microbiol (Praha) 2023; 68:691-701. [PMID: 37624549 DOI: 10.1007/s12223-023-01085-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023]
Abstract
The gut microbiome has been increasingly recognized as a key player in the development and progression of colon cancer. Alterations in the gut microbiota, known as dysbiosis, can lead to a variety of medical issues. Microbial adaptation through signals and small molecules can enhance pathogen colonization and modulate host immunity, significantly impacting disease progression. Quorum sensing peptides and molecules have been linked to the progression of colon cancer. Various interventions, such as fecal microbiota transplantation, probiotics, prebiotics, synbiotics, and antibiotics, have been used to reverse dysbiosis with mixed results and potential side effects. Thus, a personalized approach to treatment selection based on patient characteristics, such as individual gut microbiota manipulation, is necessary to prevent and treat diseases like colon cancer. With advances in metagenomic sequencing and other omics technologies, there has been a growing interest in developing precision medicine strategies for microbial imbalance-induced colon cancer. This review serves as a comprehensive synthesis of current knowledge on the gut microbiome involvement in colon cancer. By exploring the potential of utilizing the gut microbiome as a target for precision medicine, this review underscores the exciting opportunities that lie ahead. Although challenges exist, the integration of microbiome data into precision medicine approaches has the potential to revolutionize the management of colon cancer, providing patients with more personalized and effective treatment options.
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Affiliation(s)
- Pamela Pal
- Division of Microbiology and Biotechnology, Yenepoya (Deemed to Be University), Yenepoya Research Centre, University Road, Mangaluru-575018, India
| | - Rajesh P Shastry
- Division of Microbiology and Biotechnology, Yenepoya (Deemed to Be University), Yenepoya Research Centre, University Road, Mangaluru-575018, India.
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Yang X, Zhang B, Wang S, Lu Y, Chen K, Luo C, Sun A, Zhang H. OTTM: an automated classification tool for translational drug discovery from omics data. Brief Bioinform 2023; 24:bbad301. [PMID: 37594310 PMCID: PMC10516341 DOI: 10.1093/bib/bbad301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/22/2023] [Accepted: 07/31/2023] [Indexed: 08/19/2023] Open
Abstract
Omics data from clinical samples are the predominant source of target discovery and drug development. Typically, hundreds or thousands of differentially expressed genes or proteins can be identified from omics data. This scale of possibilities is overwhelming for target discovery and validation using biochemical or cellular experiments. Most of these proteins and genes have no corresponding drugs or even active compounds. Moreover, a proportion of them may have been previously reported as being relevant to the disease of interest. To facilitate translational drug discovery from omics data, we have developed a new classification tool named Omics and Text driven Translational Medicine (OTTM). This tool can markedly narrow the range of proteins or genes that merit further validation via drug availability assessment and literature mining. For the 4489 candidate proteins identified in our previous proteomics study, OTTM recommended 40 FDA-approved or clinical trial drugs. Of these, 15 are available commercially and were tested on hepatocellular carcinoma Hep-G2 cells. Two drugs-tafenoquine succinate (an FDA-approved antimalarial drug targeting CYC1) and branaplam (a Phase 3 clinical drug targeting SMN1 for the treatment of spinal muscular atrophy)-showed potent inhibitory activity against Hep-G2 cell viability, suggesting that CYC1 and SMN1 may be potential therapeutic target proteins for hepatocellular carcinoma. In summary, OTTM is an efficient classification tool that can accelerate the discovery of effective drugs and targets using thousands of candidate proteins identified from omics data. The online and local versions of OTTM are available at http://otter-simm.com/ottm.html.
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Affiliation(s)
- Xiaobo Yang
- ShanghaiTech University
- School of Life Science and Technology, ShanghaiTech University, 393 Huaxiazhong Road, Shanghai 200031, China
| | - Bei Zhang
- Shanghai Institute of Materia Medica
- Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing 100049, China
| | - Siqi Wang
- Beijing Proteome Research Center
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, and National Center for Protein Sciences (Beijing)
| | - Ye Lu
- Nanjing University of Chinese Medicine
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China; Chemical Biology Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Kaixian Chen
- academician medicinal scientist of the Chinese Academy of Sciences
- Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China; School of Life Science and Technology, ShanghaiTech University, 393 Huaxiazhong Road, Shanghai 200031, China; School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Cheng Luo
- Shanghai Institute of Materia Medica
- Chemical Biology Research Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China; School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Aihua Sun
- Beijing Proteome Research Center
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics; Research Unit of Proteomics-driven Cancer Precision Medicine, Chinese Academy of Medical Sciences
| | - Hao Zhang
- Shanghai Institute of Materia Medica
- Chemical Biology Research Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
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10
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Moreau D, Wiebels K. Genomics might not be the solution, but epistemic validity remains a challenge in the social sciences. Behav Brain Sci 2023; 46:e221. [PMID: 37694987 DOI: 10.1017/s0140525x22002357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
We sympathize with many of the points Burt makes in challenging the value of genetics to advance our understanding of social science. Here, we discuss how recent reflections on epistemic validity in the behavioral sciences can further contribute to a reappraisal of the role of sociogenomics to explain and predict human traits, aptitudes, and achievement.
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Affiliation(s)
- David Moreau
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand https://braindynamicslab.com/ https://kwiebels.github.io/
| | - Kristina Wiebels
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand https://braindynamicslab.com/ https://kwiebels.github.io/
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11
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Gupta NS, Kumar P. Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine. Comput Biol Med 2023; 162:107051. [PMID: 37271113 DOI: 10.1016/j.compbiomed.2023.107051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/06/2023] [Accepted: 05/20/2023] [Indexed: 06/06/2023]
Abstract
Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
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Affiliation(s)
- Nancy Sanjay Gupta
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University, India.
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12
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Köksal M, Streppel R, Hauser S, Abramian A, Kaiser C, Gonzalez-Carmona M, Feldmann G, Schäfer N, Koob S, Banat M, Hamed M, Giordano FA, Schmeel LC. Impact of patient nationality on the severity of early side effects after radiotherapy. J Cancer Res Clin Oncol 2023; 149:5573-5582. [PMID: 36495329 PMCID: PMC10356627 DOI: 10.1007/s00432-022-04505-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Major demographical changes in Germany commenced in the 1960s. Ongoing humanitarian crises in the Ukraine with subsequent immigration will have also long-range effects on national provision of cancer treatment. Ensuring the best possible outcomes for each cancer patient undergoing radiotherapy requires the prediction and prevention of unfavorable side effects. Given that recent research has primarily focused on clinical outcome indicators solely, less is known regarding sociodemographic predictors of therapeutic outcomes, such as patient nationality. Here, we investigated whether the severity of early side effects after radiotherapy are associated with patient nationality and other sociodemographic and clinical characteristics. METHODS Out of 9187 patients treated at a German university medical center between 2017 and 2021, 178 German and 178 non-German patients were selected for matched-pair analysis based on diagnostic and demographic criteria. For all 356 patients, data on side effects from follow-up care after radiotherapy were collected. RESULTS Non-German patients were more likely to have severe side effects than German patients. Side effect severity was also associated with tumor entity, concomitant therapy, body mass index, and age. CONCLUSION Foreign cancer patients are at higher risk of experiencing severe side effects of radiotherapy, suggesting a need to develop and implement targeted preventive measures for these patients. Further research investigating factors predicting the occurrence of radiotherapy side effects, including other sociodemographic characteristics, is needed to better personalize therapy regimens for cancer.
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Affiliation(s)
- Mümtaz Köksal
- Department of Radiation Oncology, University Medical Center Bonn (UKB), Bonn, Germany.
| | - Romy Streppel
- Department of Radiation Oncology, University Medical Center Bonn (UKB), Bonn, Germany
| | - Stefan Hauser
- Department of Urology, University Medical Center Bonn (UKB), Bonn, Germany
| | - Alina Abramian
- Department of Senology and Breast Center, University Medical Center Bonn (UKB), Bonn, Germany
| | - Christina Kaiser
- Department of Senology and Breast Center, University Medical Center Bonn (UKB), Bonn, Germany
| | | | - Georg Feldmann
- Department of Internal Medicine, University Medical Center Bonn (UKB), Bonn, Germany
| | - Niklas Schäfer
- Department of Neuro-Oncology, University Medical Center Bonn (UKB), Bonn, Germany
| | - Sebastian Koob
- Department of Orthopedic Surgery, University Medical Center Bonn (UKB), Bonn, Germany
| | - Mohammed Banat
- Department of Neurosurgery, University Medical Center Bonn (UKB), Bonn, Germany
| | - Motaz Hamed
- Department of Neurosurgery, University Medical Center Bonn (UKB), Bonn, Germany
| | - Frank A Giordano
- Department of Radiation Oncology, University Medical Center Mannheim (UMM), Mannheim, Germany
| | - Leonard C Schmeel
- Department of Radiation Oncology, University Medical Center Bonn (UKB), Bonn, Germany
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13
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Abstract
Psoriasis is a chronic disease that is caused by multiple factors and is identified by itchiness, unpleasant, red, or white scaly patches on the skin, particularly on regularly chafed body regions such as the lateral areas of the limbs. Reports suggest that globally around 2%-3% of the population suffers from psoriasis. In this review, we have discussed the clinical classification of psoriasis and also the ideal characteristics of the biomarkers. An overview regarding the discovery of the biomarker and method for validating the study has been discussed. A growing body of research suggests a link to certain other systemic symptoms such as cardiovascular disorder, metabolic syndrome, and few other comorbidities such as hypertension and nonalcoholic fatty liver disease. Natural killer (NK) cells are lymphocyte cells that concentrate on the destruction of virally infected and malignant cells; these tend to produce a wide range of inflammatory cytokines, some of which are associated with the etiology of psoriasis. Detailed information on the molecular pathogenesis of psoriasis in which interleukin (IL)-17, IL-23, tumor necrosis factor-α (TNF-α), and CCL20 play a very significant role in the development of psoriasis. In this review, we have discussed an overview of the recent state of the biomarkers available for the diagnosis and treatment of psoriasis by emphasizing on the available biomarkers such as epigenomic, transcriptomic, glycomic, and metabolomic. The most recent advancements in molecular-targeted therapy utilizing biologics and oral systemic therapy (methotrexate, apremilast) enable to adequately treat the most serious psoriatic symptoms and also the studies have validated the efficacy of biologic therapy such as TNF-α antagonist (infliximab, adalimumab), IL-23 antagonist (guselkumab, risankizumab), and IL-17 antagonist (secukinumab, ixekizumab). Finally, an overview about the technological opportunities as well as various challenges has been discussed.
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Affiliation(s)
- Deblina Dan
- Department of Pharmaceutics, Amity Institute of Pharmacy, Lucknow, Amity University Uttar Pradesh, Noida, India
| | - Nimisha Srivastava
- Department of Pharmaceutics, Amity Institute of Pharmacy, Lucknow, Amity University Uttar Pradesh, Noida, India
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14
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Ray SK, Mukherjee S. Starring Role of Biomarkers and Anticancer Agents as a Major Driver in Precision Medicine of Cancer Therapy. Curr Mol Med 2023; 23:111-126. [PMID: 34939542 DOI: 10.2174/1566524022666211221152947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 10/18/2021] [Accepted: 10/26/2021] [Indexed: 12/16/2022]
Abstract
Precision medicine is the most modern contemporary medicine approach today, based on great amount of data on people's health, individual characteristics, and life circumstances, and employs the most effective ways to prevent and cure diseases. Precision medicine in cancer is the most precise and viable treatment for every cancer patient based on the disease's genetic profile. Precision medicine changes the standard one size fits all medication model, which focuses on average responses to care. Consolidating modern methodologies for streamlining and checking anticancer drugs can have long-term effects on understanding the results. Precision medicine can help explicit anticancer treatments using various drugs and even in discovery, thus becoming the paradigm of future cancer medicine. Cancer biomarkers are significant in precision medicine, and findings of different biomarkers make this field more promising and challenging. Naturally, genetic instability and the collection of extra changes in malignant growth cells are ways cancer cells adapt and survive in a hostile environment, for example, one made by these treatment modalities. Precision medicine centers on recognizing the best treatment for individual patients, dependent on their malignant growth and genetic characterization. This new era of genomics progressively referred to as precision medicine, has ignited a new episode in the relationship between genomics and anticancer drug development.
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Affiliation(s)
| | - Sukhes Mukherjee
- Department of Biochemistry. All India Institute of Medical Sciences. Bhopal, Madhya Pradesh-462020. India
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15
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Saha A, Ha MJ, Acharyya S, Baladandayuthapani V. A Bayesian precision medicine framework for calibrating individualized therapeutic indices in cancer. Ann Appl Stat 2022. [DOI: 10.1214/21-aoas1550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Abhisek Saha
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health
| | - Min Jin Ha
- Department of Biostatistics, Graduate School of Public Health, Yonsei University, Seoul, Korea
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16
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Cellina M, Cè M, Khenkina N, Sinichich P, Cervelli M, Poggi V, Boemi S, Ierardi AM, Carrafiello G. Artificial Intellgence in the Era of Precision Oncological Imaging. Technol Cancer Res Treat 2022; 21:15330338221141793. [PMID: 36426565 PMCID: PMC9703524 DOI: 10.1177/15330338221141793] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Rapid-paced development and adaptability of artificial intelligence algorithms have secured their almost ubiquitous presence in the field of oncological imaging. Artificial intelligence models have been created for a variety of tasks, including risk stratification, automated detection, and segmentation of lesions, characterization, grading and staging, prediction of prognosis, and treatment response. Soon, artificial intelligence could become an essential part of every step of oncological workup and patient management. Integration of neural networks and deep learning into radiological artificial intelligence algorithms allow for extrapolating imaging features otherwise inaccessible to human operators and pave the way to truly personalized management of oncological patients.Although a significant proportion of currently available artificial intelligence solutions belong to basic and translational cancer imaging research, their progressive transfer to clinical routine is imminent, contributing to the development of a personalized approach in oncology. We thereby review the main applications of artificial intelligence in oncological imaging, describe the example of their successful integration into research and clinical practice, and highlight the challenges and future perspectives that will shape the field of oncological radiology.
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Affiliation(s)
- Michaela Cellina
- Radiology Department, Fatebenefratelli Hospital, Milano, Italy,Michaela Cellina, MD, Radiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Milano, Piazza Principessa Clotilde 3, 20121, Milano, Italy.
| | - Maurizio Cè
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Natallia Khenkina
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Polina Sinichich
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Marco Cervelli
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Vittoria Poggi
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | - Sara Boemi
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy
| | | | - Gianpaolo Carrafiello
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy,Radiology Department, Fondazione IRCCS Cà Granda, Milan, Italy
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17
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Bolouri H, Ries RE, Wiedeman AE, Hylkema T, Scheiding S, Gersuk VH, O'Brien K, Nguyen QA, Smith JL, Alice Long S, Meshinchi S. Inflammatory bone marrow signaling in pediatric acute myeloid leukemia distinguishes patients with poor outcomes. Nat Commun 2022; 13:7186. [PMID: 36418348 PMCID: PMC9684530 DOI: 10.1038/s41467-022-34965-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 11/09/2022] [Indexed: 11/26/2022] Open
Abstract
High levels of the inflammatory cytokine IL-6 in the bone marrow are associated with poor outcomes in pediatric acute myeloid leukemia (pAML), but its etiology remains unknown. Using RNA-seq data from pre-treatment bone marrows of 1489 children with pAML, we show that > 20% of patients have concurrent IL-6, IL-1, IFNα/β, and TNFα signaling activity and poorer outcomes. Targeted sequencing of pre-treatment bone marrow samples from affected patients (n = 181) revealed 5 highly recurrent patterns of somatic mutation. Using differential expression analyses of the most common genomic subtypes (~60% of total), we identify high expression of multiple potential drivers of inflammation-related treatment resistance. Regardless of genomic subtype, we show that JAK1/2 inhibition reduces receptor-mediated inflammatory signaling by leukemic cells in-vitro. The large number of high-risk pAML genomic subtypes presents an obstacle to the development of mutation-specific therapies. Our findings suggest that therapies targeting inflammatory signaling may be effective across multiple genomic subtypes of pAML.
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Affiliation(s)
- Hamid Bolouri
- Center for Systems Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA.
| | - Rhonda E Ries
- Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA
| | - Alice E Wiedeman
- Center for Translational Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Tiffany Hylkema
- Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA
| | - Sheila Scheiding
- Center for Translational Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Vivian H Gersuk
- Center for Systems Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Kimberly O'Brien
- Center for Systems Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Quynh-Anh Nguyen
- Center for Systems Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Jenny L Smith
- Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA
- Research Scientific Computing, Seattle Children's Research Institute, 818 Stewart Street, Seattle, WA, USA
| | - S Alice Long
- Center for Translational Immunology, Benaroya Research Institute, 1201 9th Ave, Seattle, WA, USA
| | - Soheil Meshinchi
- Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA, USA.
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18
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Chen M, Hou L, Hu L, Tan C, Wang X, Bao P, Ran Q, Chen L, Li Z. Platelet detection as a new liquid biopsy tool for human cancers. Front Oncol 2022; 12:983724. [PMID: 36185270 PMCID: PMC9515491 DOI: 10.3389/fonc.2022.983724] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/09/2022] [Indexed: 12/16/2022] Open
Abstract
Cancer is still a leading cause of death worldwide and liquid biopsy is a powerful tool that can be applied to different stages of cancer screening and treatment. However, as the second most abundant cell type in the bloodstream, platelets are isolated through well-established and fast methods in clinic but their value as a BioSource of cancer biomarkers is relatively recent. Many studies demonstrated the bidirectional interaction between cancer cells and platelets. Platelets transfer various proteins (e.g., growth factors, cytokine, chemokines) and RNAs (e.g., mRNA, lncRNA, miRNA, circRNA) into the tumor cells and microenvironment, leading the stimulation of tumor growth and metastasis. In turn, the platelet clinical characteristics (e.g., count and volume) and contents (e.g., RNA and protein) are altered by the interactions with cancer cells and this enables the early cancer detection using these features of platelets. In addition, platelet-derived microparticles also demonstrate the prediction power of being cancer biomarkers. In this review, we focus on the clinical applications of platelet detection using the platelet count, mean platelet volume, platelet RNA and protein profiles for human cancers and discuss the gap in bringing these implementations into the clinic.
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Affiliation(s)
- Maoshan Chen
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
- *Correspondence: Maoshan Chen, ; Li Chen, ; Zhongjun Li,
| | - Lijia Hou
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Lanyue Hu
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Chengning Tan
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Xiaojie Wang
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Peipei Bao
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Qian Ran
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Li Chen
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
- *Correspondence: Maoshan Chen, ; Li Chen, ; Zhongjun Li,
| | - Zhongjun Li
- Laboratory of Radiation Biology, Department of Blood Transfusion, Laboratory Medicine Centre, The Second Affiliated Hospital, Army Medical University, Chongqing, China
- State Key Laboratory of Trauma, Burns and Combined Injuries, The Second Affiliated Hospital, Army Medical University, Chongqing, China
- *Correspondence: Maoshan Chen, ; Li Chen, ; Zhongjun Li,
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19
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Holloway K, Miller FA. The Consultant's intermediary role in the regulation of molecular diagnostics in the US. Soc Sci Med 2022; 304:112929. [PMID: 32201019 DOI: 10.1016/j.socscimed.2020.112929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 02/28/2020] [Accepted: 03/12/2020] [Indexed: 11/17/2022]
Abstract
Molecular diagnostics are fast becoming a big business, with the promise of personalized medicine fueling the growth of "blockbuster" tests with high expectations for health system impact and commercial success. We investigate the polycentric regulatory regime for molecular diagnostics in the US, drawing attention to the prominent role of coverage and reimbursement systems in setting regulatory standards for this industry. We hone in on the private consultants who assist molecular diagnostics companies to gain broad clinical uptake of their products. Through a web-based search of consulting companies, analysis of their online materials, and 13 qualitative interviews with consultants, we describe the role of these actors in the coverage and reimbursement of novel diagnostics and highlight the production of evidence as a critical part of the process. We argue that consultants operate as regulatory intermediaries, helping to develop the evidentiary standards for payment decisions that ultimately benefit their clients, the manufacturers. We suggest that public policy discussions over how best to realize the promise of personalized medicine should be re-oriented to consider whose interests are represented in the regulatory regime governing access to these technologies.
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20
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Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine. Cancers (Basel) 2022; 14:cancers14122860. [PMID: 35740526 PMCID: PMC9220825 DOI: 10.3390/cancers14122860] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 06/03/2022] [Accepted: 06/07/2022] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Recently, radiogenomics has played a significant role and offered a new understanding of cancer’s biology and behavior in response to standard therapy. It also provides a more precise prognosis, investigation, and analysis of the patient’s cancer. Over the years, Artificial Intelligence (AI) has provided a significant strength in radiogenomics. In this paper, we offer computational and oncological prospects of the role of AI in radiogenomics, as well as its offers, achievements, opportunities, and limitations in the current clinical practices. Abstract Radiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computational as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles.
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21
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Nkera-Gutabara CK, Kerr R, Scholefield J, Hazelhurst S, Naidoo J. Microbiomics: The Next Pillar of Precision Medicine and Its Role in African Healthcare. Front Genet 2022; 13:869610. [PMID: 35480328 PMCID: PMC9037082 DOI: 10.3389/fgene.2022.869610] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 03/04/2022] [Indexed: 11/26/2022] Open
Abstract
Limited access to technologies that support early monitoring of disease risk and a poor understanding of the geographically unique biological and environmental factors underlying disease, represent significant barriers to improved health outcomes and precision medicine efforts in low to middle income countries. These challenges are further compounded by the rich genetic diversity harboured within Southern Africa thus necessitating alternative strategies for the prediction of disease risk and clinical outcomes in regions where accessibility to personalized healthcare remains limited. The human microbiome refers to the community of microorganisms (bacteria, archaea, fungi and viruses) that co-inhabit the human body. Perturbation of the natural balance of the gut microbiome has been associated with a number of human pathologies, and the microbiome has recently emerged as a critical determinant of drug pharmacokinetics and immunomodulation. The human microbiome should therefore not be omitted from any comprehensive effort towards stratified healthcare and would provide an invaluable and orthogonal approach to existing precision medicine strategies. Recent studies have highlighted the overarching effect of geography on gut microbial diversity as it relates to human health. Health insights from international microbiome datasets are however not yet verified in context of the vast geographical diversity that exists throughout the African continent. In this commentary we discuss microbiome research in Africa and its role in future precision medicine initiatives across the African continent.
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Affiliation(s)
- C. K. Nkera-Gutabara
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Bioengineering and Integrated Genomics Research Group, Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - R. Kerr
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - J. Scholefield
- Bioengineering and Integrated Genomics Research Group, Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa
| | - S. Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - J. Naidoo
- Bioengineering and Integrated Genomics Research Group, Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa
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22
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Bangash H, Makkawy A, Gundelach JH, Miller AA, Jacobson KA, Kullo IJ. Web-Based Tool (FH Family Share) to Increase Uptake of Cascade Testing for Familial Hypercholesterolemia: Development and Evaluation. JMIR Hum Factors 2022; 9:e32568. [PMID: 35166678 PMCID: PMC8889478 DOI: 10.2196/32568] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/29/2021] [Accepted: 11/07/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Familial hypercholesterolemia, a prevalent genetic disorder, remains significantly underdiagnosed in the United States. Cascade testing, wherein individuals diagnosed with familial hypercholesterolemia- probands-contact their family members to inform them of their risk for familial hypercholesterolemia, has low uptake in the United States. Digital tools are needed to facilitate communication between familial hypercholesterolemia probands and their family members and to promote sharing of familial hypercholesterolemia-related risk information. OBJECTIVE We aimed to create and evaluate a web-based tool designed to enhance familial communication and promote cascade testing for familial hypercholesterolemia. METHODS A hybrid type 1 implementation science framework and a user-centered design process were used to develop an interactive web-based tool-FH Family Share-that enables familial hypercholesterolemia probands to communicate information about their familial hypercholesterolemia diagnosis with at-risk relatives. Probands can also use the tool to draw a family pedigree and learn more about familial hypercholesterolemia through education modules and curated knowledge resources. Usability guidelines and standards were taken into account during the design and development of the tool. The initial prototype underwent a cognitive walkthrough, which was followed by usability testing with key stakeholders including genetic counselors and patients with familial hypercholesterolemia. Participants navigated the prototype using the think-aloud technique, and their feedback was used to refine features of the tool. RESULTS Key themes that emerged from the cognitive walkthrough were design, format, navigation, terminology, instructions, and learnability. Expert feedback from the cognitive walkthrough resulted in a rebuild of the web-based tool to align it with institutional standards. Usability testing with genetic counselors and patients with familial hypercholesterolemia provided insights on user experience, satisfaction and interface design and highlighted specific modifications that were made to refine the features of FH Family Share. Genetic counselors and patients with familial hypercholesterolemia suggested inclusion of the following features in the web-based tool: (1) a letter-to-family-member email template, (2) education modules, and (3) knowledge resources. Surveys revealed that 6 of 9 (67%) genetic counselors found information within FH Family Share very easy to find, and 5 of 9 (56%) genetic counselors found information very easy to understand; 5 of 9 (56%) patients found information very easy to find within the website, and 7 of 9 (78%) patients found information very easy to understand. All genetic counselors and patients indicated that FH Family Share was a resource worth returning to. CONCLUSIONS FH Family Share facilitates communication between probands and their relatives. Once informed, at-risk family members have the option to seek testing and treatment for familial hypercholesterolemia.
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Affiliation(s)
| | - Ahmed Makkawy
- Saharafox Creative Agency, Rochester, MN, United States
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23
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Christensen KD, Schonman EF, Robinson JO, Roberts JS, Diamond PM, Lee KB, Green RC, McGuire AL. Behavioral and psychological impact of genome sequencing: a pilot randomized trial of primary care and cardiology patients. NPJ Genom Med 2021; 6:72. [PMID: 34429410 PMCID: PMC8384838 DOI: 10.1038/s41525-021-00236-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 07/30/2021] [Indexed: 12/20/2022] Open
Abstract
Many expect genome sequencing (GS) to become routine in patient care and preventive medicine, but uncertainties remain about its ability to motivate participants to improve health behaviors and the psychological impact of disclosing results. In a pilot trial with exploratory analyses, we randomized 100 apparently healthy, primary-care participants and 100 cardiology participants to receive a review of their family histories of disease, either alone or in addition to GS analyses. GS results included polygenic risk information for eight cardiometabolic conditions. Overall, no differences were observed between the percentage of participants in the GS and control arms, who reported changes to health behaviors such as diet and exercise at 6 months post disclosure (48% vs. 36%, respectively, p = 0.104). In the GS arm, however, the odds of reporting a behavior change increased by 52% per high-risk polygenic prediction (p = 0.032). Mean anxiety and depression scores for GS and control arms had confidence intervals within equivalence margins of ±1.5. Mediation analyses suggested an indirect impact of GS on health behaviors by causing positive psychological responses (p ≤ 0.001). Findings suggest that GS did not distress participants. Future research on GS in more diverse populations is needed to confirm that it does not raise risks for psychological harms and to confirm the ability of polygenic risk predictions to motivate preventive behaviors.
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Affiliation(s)
- Kurt D Christensen
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA. .,Department of Population Medicine, Harvard Medical School, Boston, MA, USA. .,Broad Institute of Harvard and MIT, Cambridge, MA, USA.
| | - Erica F Schonman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jill O Robinson
- Center for Medical Ethics and Health Policy at Baylor College of Medicine, Houston, TX, USA
| | - J Scott Roberts
- Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Pamela M Diamond
- Center for Health Promotion and Prevention Research, University of Texas Houston School of Public Health, Houston, TX, USA
| | - Kaitlyn B Lee
- Center for Medical Ethics and Health Policy at Baylor College of Medicine, Houston, TX, USA
| | - Robert C Green
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Partners Personalized Medicine, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Ariadne Labs, Boston, MA, USA
| | - Amy L McGuire
- Center for Medical Ethics and Health Policy at Baylor College of Medicine, Houston, TX, USA
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24
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Donohue KE, Dolan SM, Watnick D, Gallagher KM, Odgis JA, Suckiel SA, Teitelman N, Gelb BD, Kenny EE, Wasserstein MP, Horowitz CR, Bauman LJ. Hope versus reality: Parent expectations of genomic testing. PATIENT EDUCATION AND COUNSELING 2021; 104:2073-2079. [PMID: 33640235 PMCID: PMC8679507 DOI: 10.1016/j.pec.2021.01.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/26/2021] [Accepted: 01/27/2021] [Indexed: 05/11/2023]
Abstract
OBJECTIVE Genomics is increasingly used for diagnostic testing in children. This study describes the expectations of parents whose child received genomic testing and whether or not they were met. METHODS A diverse stratified, purposive sample of parents of 22 children in New York City was interviewed using a semi-structured guide. Genomic test results were positive, negative, or uncertain. RESULTS Parents expressed their expectations in narrative and numeric fashion. Parents expected that their child's test would have a direct effect on their child's diagnosis. Some believed that results would be definitive, while others recognized testing limitations. Expectations reflected parents' hope to find a diagnosis and led to disappointment when results were uninformative or did not impact clinical management. CONCLUSION Results suggest pre-test genetic counseling emphasize the low likelihood of actionable results; however, parents' expectations of genomics' diagnostic capabilities are strongly rooted in their need to end the diagnostic odyssey and may be difficult to manage. PRACTICE IMPLICATIONS Parents' hope for a resolution and effective treatment for their child is a powerful context in which genetic counseling is heard. Clinicians who provide genomic testing should continue to acknowledge parents' preconceptions. Additional research in other settings will help understand how to best address and manage parent expectations of genomic medicine.
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Affiliation(s)
- Katherine E Donohue
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Siobhan M Dolan
- Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Dana Watnick
- Department of Pediatrics, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States
| | - Katie M Gallagher
- Department of Pediatrics, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States
| | - Jacqueline A Odgis
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Sabrina A Suckiel
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Nehama Teitelman
- Department of Pediatrics, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States
| | - Bruce D Gelb
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Melissa P Wasserstein
- Department of Pediatrics, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States
| | - Carol R Horowitz
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Laurie J Bauman
- Department of Pediatrics, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States; Department of Psychiatry and Behavioral Sciences, Montefiore Medical Center / Albert Einstein College of Medicine, Bronx, NY, United States.
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25
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Singh A, Chitalia R, Kontos D. Radiogenomics in brain, breast, and lung cancer: opportunities and challenges. J Med Imaging (Bellingham) 2021; 8:031907. [PMID: 34164563 PMCID: PMC8212946 DOI: 10.1117/1.jmi.8.3.031907] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 06/04/2021] [Indexed: 01/06/2023] Open
Abstract
The field of radiogenomics largely focuses on developing imaging surrogates for genomic signatures and integrating imaging, genomic, and molecular data to develop combined personalized biomarkers for characterizing various diseases. Our study aims to highlight the current state-of-the-art and the role of radiogenomics in cancer research, focusing mainly on solid tumors, and is broadly divided into four sections. The first section reviews representative studies that establish the biologic basis of radiomic signatures using gene expression and molecular profiling information. The second section includes studies that aim to non-invasively predict molecular subtypes of tumors using radiomic signatures. The third section reviews studies that evaluate the potential to augment the performance of established prognostic signatures by combining complementary information encoded by radiomic and genomic signatures derived from cancer tumors. The fourth section includes studies that focus on ascertaining the biological significance of radiomic phenotypes. We conclude by discussing current challenges and opportunities in the field, such as the importance of coordination between imaging device manufacturers, regulatory organizations, health care providers, pharmaceutical companies, academic institutions, and physicians for the effective standardization of the results from radiogenomic signatures and for the potential use of these findings to improve precision care for cancer patients.
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Affiliation(s)
- Apurva Singh
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
| | - Rhea Chitalia
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
| | - Despina Kontos
- University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States
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26
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Sharma D, Subramaniam G, Sharma N, Sharma P. Cell-free DNA in the surveillance of heart transplant rejection. Indian J Thorac Cardiovasc Surg 2021; 37:257-264. [PMID: 33967413 PMCID: PMC8079572 DOI: 10.1007/s12055-020-01130-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 12/22/2020] [Accepted: 12/23/2020] [Indexed: 10/22/2022] Open
Abstract
BACKGROUND Circulating cell-free deoxyribonucleic acid (cfDNA) is promptly materializing as a highly useful tool for the surveillance of solid-organ transplant rejection. Donor-specific fraction (DF) cfDNA is a potential marker of selective donor organ injury. It is emerging as a promising analytical target in the near future. The aim of this systematic review is to throw light on the importance of cfDNA and future perspective in detecting acute rejection in heart transplantation. METHODS An exhaustive search was carried out for this review article on the basis of literature available including scientific databases of PubMed, Embase, and ClinicalTrials.gov. The search engines were systematically explored using the search terms "cell free DNA," "Heart transplant," and "Rejection" from inception until August 2020, and narrative analysis was accomplished. Majority of the studies described endomyocardial biopsy-proven acute rejection as reference standard. RESULTS After initial screening of 331 articles, 11 studies were included and discussed in detail in the present review article. Majority of the studies showed prospective designs. A firm correlation was noted between acute rejection (identified on endomyocardial biopsy) and cfDNA levels by most of the studies. CONCLUSIONS cfDNA is a promising tool to replace repeated biopsies to detect rejection. The development in the area of digital droplet polymerase chain reaction and massive parallel sequencing, along with the overall reduction in cost of sequencing with its automation, has helped establish its role in the transplant population.
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Affiliation(s)
- Dhruva Sharma
- Department of Cardiothoracic and Vascular Surgery, SMS Medical College & Attached Hospitals, J L N Marg, Jaipur, Rajasthan 302001 India
| | - Ganapathy Subramaniam
- Institute of Heart and Lung Transplant and Mechanical Circulatory Support, MGM Healthcare, No. 72, Nelson Manickam Road, Aminjikarai, Chennai, Tamil Nadu 600029 India
| | - Neha Sharma
- Department of Pharmacology, SMS Medical College & Attached Hospitals, J L N Marg, Jaipur, Rajasthan 302001 India
| | - Preksha Sharma
- Department of Anatomy, SMS Medical College & Attached Hospitals, J L N Marg, Jaipur, Rajasthan 302001 India
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27
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Christensen KD, Bell M, Zawatsky CLB, Galbraith LN, Green RC, Hutchinson AM, Jamal L, LeBlanc JL, Leonhard JR, Moore M, Mullineaux L, Petry N, Platt DM, Shaaban S, Schultz A, Tucker BD, Van Heukelom J, Wheeler E, Zoltick ES, Hajek C. Precision Population Medicine in Primary Care: The Sanford Chip Experience. Front Genet 2021; 12:626845. [PMID: 33777099 PMCID: PMC7994529 DOI: 10.3389/fgene.2021.626845] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 02/11/2021] [Indexed: 01/10/2023] Open
Abstract
Genetic testing has the potential to revolutionize primary care, but few health systems have developed the infrastructure to support precision population medicine applications or attempted to evaluate its impact on patient and provider outcomes. In 2018, Sanford Health, the nation's largest rural nonprofit health care system, began offering genetic testing to its primary care patients. To date, more than 11,000 patients have participated in the Sanford Chip Program, over 90% of whom have been identified with at least one informative pharmacogenomic variant, and about 1.5% of whom have been identified with a medically actionable predisposition for disease. This manuscript describes the rationale for offering the Sanford Chip, the programs and infrastructure implemented to support it, and evolving plans for research to evaluate its real-world impact.
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Affiliation(s)
- Kurt D Christensen
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States.,Department of Population Medicine, Harvard Medical School, Boston, MA, United States.,Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Megan Bell
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Carrie L B Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States
| | - Lauren N Galbraith
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Robert C Green
- Broad Institute of MIT and Harvard, Cambridge, MA, United States.,Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States.,Department of Medicine, Harvard Medical School, Boston, MA, United States
| | | | - Leila Jamal
- National Cancer Institute, Bethesda, MD, United States.,Department of Bioethics, National Institutes of Health, Bethesda, MD, United States
| | - Jessica L LeBlanc
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | | | - Michelle Moore
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Lisa Mullineaux
- Mayo Clinic Genomics Laboratory, Rochester, MN, United States
| | - Natasha Petry
- Sanford Health Imagenetics, Fargo, ND, United States.,Department of Pharmacy Practice, North Dakota State University, Fargo, ND, United States
| | - Dylan M Platt
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Sherin Shaaban
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, United States.,ARUP Laboratories, Salt Lake City, UT, United States
| | - April Schultz
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Joel Van Heukelom
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Emilie S Zoltick
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Catherine Hajek
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
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28
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Walcott SE, Miller FA, Dunsmore K, Lazor T, Feldman BM, Hayeems RZ. Measuring clinical utility in the context of genetic testing: a scoping review. Eur J Hum Genet 2021; 29:378-386. [PMID: 33087880 PMCID: PMC7940410 DOI: 10.1038/s41431-020-00744-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/30/2020] [Accepted: 10/07/2020] [Indexed: 01/20/2023] Open
Abstract
Standardized approaches to measuring clinical utility will enable more robust evaluations of genetic tests. To characterize how clinical utility has been measured, this scoping review examined outcomes used to operationalize this concept in the context of genetic testing, spanning relevant literature (2015-2017). The search strategy and analysis were guided by the Fryback and Thornbury hierarchical model of efficacy (FT Model). Through searches in Ovid MEDLINE, EMBASE and Web of Science, 194 publications were identified for inclusion. Two coders reviewed titles, abstracts, and full texts to determine eligibility. Results were analyzed using thematic and frequency analyses. This review generated a catalog of outcomes mapped to the efficacy domains of the FT Model. The degree of representation observed in each domain varied by the clinical purpose and clinical indication of genetic testing. Diagnostic accuracy (68%), technical (28.4%), and patient outcome (28.4%) efficacy studies were represented at the highest rate. Findings suggest that the FT Model is suitable for the genetics context however domain refinements may be warranted. More diverse clinical settings, robust study designs, and novel strategies for measuring clinical utility are needed.
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Affiliation(s)
- Shantel E Walcott
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Fiona A Miller
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Toronto Health Economics and Technology Assessment, Toronto, ON, Canada
| | - Kourtney Dunsmore
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Tanya Lazor
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Brian M Feldman
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Program in Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
- Department of Paediatrics, Division of Rheumatology, University of Toronto, Toronto, ON, Canada
| | - Robin Z Hayeems
- Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
- Program in Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, ON, Canada.
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29
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Guerrero-Gimenez ME, Fernandez-Muñoz JM, Lang BJ, Holton KM, Ciocca DR, Catania CA, Zoppino FCM. Galgo: a bi-objective evolutionary meta-heuristic identifies robust transcriptomic classifiers associated with patient outcome across multiple cancer types. Bioinformatics 2020; 36:5037-5044. [PMID: 32638009 DOI: 10.1093/bioinformatics/btaa619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 06/03/2020] [Accepted: 06/30/2020] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Statistical and machine-learning analyses of tumor transcriptomic profiles offer a powerful resource to gain deeper understanding of tumor subtypes and disease prognosis. Currently, prognostic gene-expression signatures do not exist for all cancer types, and most developed to date have been optimized for individual tumor types. In Galgo, we implement a bi-objective optimization approach that prioritizes gene signature cohesiveness and patient survival in parallel, which provides greater power to identify tumor transcriptomic phenotypes strongly associated with patient survival. RESULTS To compare the predictive power of the signatures obtained by Galgo with previously studied subtyping methods, we used a meta-analytic approach testing a total of 35 large population-based transcriptomic biobanks of four different cancer types. Galgo-generated colorectal and lung adenocarcinoma signatures were stronger predictors of patient survival compared to published molecular classification schemes. One Galgo-generated breast cancer signature outperformed PAM50, AIMS, SCMGENE and IntClust subtyping predictors. In high-grade serous ovarian cancer, Galgo signatures obtained similar predictive power to a consensus classification method. In all cases, Galgo subtypes reflected enrichment of gene sets related to the hallmarks of the disease, which highlights the biological relevance of the partitions found. AVAILABILITY AND IMPLEMENTATION The open-source R package is available on www.github.com/harpomaxx/galgo. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- M E Guerrero-Gimenez
- Laboratory of Oncology, Institute of Medicine and Experimental Biology of Cuyo (IMBECU), National Scientific and Technical Research Council (CONICET), Mendoza 5500, Argentina.,Institute of Biochemistry and Biotechnology, School of Medicine, National University of Cuyo, Mendoza 5500, Argentina
| | - J M Fernandez-Muñoz
- Laboratory of Oncology, Institute of Medicine and Experimental Biology of Cuyo (IMBECU), National Scientific and Technical Research Council (CONICET), Mendoza 5500, Argentina.,Institute of Biochemistry and Biotechnology, School of Medicine, National University of Cuyo, Mendoza 5500, Argentina
| | - B J Lang
- Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - K M Holton
- Harvard Department of Stem Cell and Regenerative Biology, Cambridge, MA 02138, USA
| | - D R Ciocca
- Laboratory of Oncology, Institute of Medicine and Experimental Biology of Cuyo (IMBECU), National Scientific and Technical Research Council (CONICET), Mendoza 5500, Argentina
| | - C A Catania
- Laboratory of Intelligent Systems (LABSIN), Engineering School, National University of Cuyo, Mendoza 5500, Argentina
| | - F C M Zoppino
- Laboratory of Oncology, Institute of Medicine and Experimental Biology of Cuyo (IMBECU), National Scientific and Technical Research Council (CONICET), Mendoza 5500, Argentina
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30
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Abstract
The aim of this integrative review is to investigate current literature regarding family health history (FHH) taking practices, attitudes, and challenges in the pediatric outpatient setting. FHH is a known clinical tool for providers; however, there are no explicit standards for pediatric FHH collection. The integrative review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. PubMed, Embase, CINAHL, PsycINFO, and Cochrane databases were searched for publications between January 2010 and December 2019, and 8 articles were selected for evaluation. Three themes are explored in this review: FHH collection practices, challenges, and tools. FHH collection practices were found to be inconsistent and the most commonly cited challenge was time. No validated FHH collection tools have been identified for the pediatric population. These findings suggest the need for standardization in FHH collection and further development of tools to improve FHH collection.
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31
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Flowers SA, Ward KM, Clark CT. The Gut Microbiome in Bipolar Disorder and Pharmacotherapy Management. Neuropsychobiology 2020; 79:43-49. [PMID: 31722343 DOI: 10.1159/000504496] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 10/31/2019] [Indexed: 11/19/2022]
Abstract
The gut microbiome is a complex and dynamic community of commensal, symbiotic, and pathogenic microorganisms that exist in a bidirectional relationship with the host. Bacterial functions in the gut play a critical role in healthy host functioning, and its disruption can contribute to many medical conditions. The relationship between gut microbiota and the brain has gained attention in mental health due to the mounting evidence supporting the association of gut bacteria with mood and behavior. Patients with bipolar disorder exhibit an increased frequency of gastrointestinal illnesses such as inflammatory bowel disease, which mechanistically has been linked to microbial community function. While the heterogeneity in microbial communities between individuals might be associated with disease risk, it may also moderate the efficacy or adverse effects associated with the use of medication. The following review highlights published evidence linking the function of gut microbiota both to bipolar disorder risk and to the effect of medications that influence microbiota, inflammation, and mood symptoms.
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Affiliation(s)
- Stephanie A Flowers
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA,
| | - Kristen M Ward
- Department of Clinical Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Crystal T Clark
- Department of Psychiatry, Northwestern University, Asher Center for the Study and Treatment of Depressive Disorders, Chicago, Illinois, USA
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32
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Jimenez JE, Nourbakhsh A, Colbert B, Mittal R, Yan D, Green CL, Nisenbaum E, Liu G, Bencie N, Rudman J, Blanton SH, Zhong Liu X. Diagnostic and therapeutic applications of genomic medicine in progressive, late-onset, nonsyndromic sensorineural hearing loss. Gene 2020; 747:144677. [PMID: 32304785 PMCID: PMC7244213 DOI: 10.1016/j.gene.2020.144677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 04/12/2020] [Accepted: 04/14/2020] [Indexed: 02/06/2023]
Abstract
The progressive, late-onset, nonsyndromic, sensorineural hearing loss (PNSHL) is the most common cause of sensory impairment globally, with presbycusis affecting greater than a third of individuals over the age of 65. The etiology underlying PNSHL include presbycusis, noise-induced hearing loss, drug ototoxicity, and delayed-onset autosomal dominant hearing loss (AD PNSHL). The objective of this article is to discuss the potential diagnostic and therapeutic applications of genomic medicine in PNSHL. Genomic factors contribute greatly to PNSHL. The heritability of presbycusis ranges from 25 to 75%. Current therapies for PNSHL range from sound amplification to cochlear implantation (CI). PNSHL is an excellent candidate for genomic medicine approaches as it is common, has well-described pathophysiology, has a wide time window for treatment, and is amenable to local gene therapy by currently utilized procedural approaches. AD PNSHL is especially suited to genomic medicine approaches that can disrupt the expression of an aberrant protein product. Gene therapy is emerging as a potential therapeutic strategy for the treatment of PNSHL. Viral gene delivery approaches have demonstrated promising results in human clinical trials for two inherited causes of blindness and are being used for PNSHL in animal models and a human trial. Non-viral gene therapy approaches are useful in situations where a transient biologic effect is needed or for delivery of genome editing reagents (such as CRISPR/Cas9) into the inner ear. Many gene therapy modalities that have proven efficacious in animal trials have potential to delay or prevent PNSHL in humans. The development of new treatment modalities for PNSHL will lead to improved quality of life of many affected individuals and their families.
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Affiliation(s)
- Joaquin E Jimenez
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Aida Nourbakhsh
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Brett Colbert
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Human Genetics and John P. Hussman Institute of Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Medical Scientist Training Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Rahul Mittal
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Denise Yan
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Carlos L Green
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Eric Nisenbaum
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - George Liu
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Nicole Bencie
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jason Rudman
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Susan H Blanton
- Department of Human Genetics and John P. Hussman Institute of Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Xue Zhong Liu
- Department of Otolaryngology, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Human Genetics and John P. Hussman Institute of Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA.
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Quintero-Ronderos P, Laissue P. Genetic Variants Contributing to Early Recurrent Pregnancy Loss Etiology Identified by Sequencing Approaches. Reprod Sci 2020; 27:1541-1552. [PMID: 32430708 DOI: 10.1007/s43032-020-00187-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Recurrent pregnancy loss (RPL) affects up to 5% of couples. It is believed that genetic factors contribute to the disease's etiology and pathophysiology. Hundreds of genes represent coherent RPL candidates due to mammalian implantation's inherent complexity. Sanger sequencing (direct sequencing) of candidate genes has identified potential RPL causative genes (and variants), including those regulating embryo implantation and pregnancy maintenance. Although this approach is a reliable technique, the simultaneous analysis of large genomic regions is challenging. Next-generation sequencing (NGS) technology has thus emerged as a useful alternative for determining genetic variants and transcriptomic disturbances contributing to monogenic and polygenic diseases pathogenesis. However, interpreting results remains challenging as NGS experiments provide an enormous amount of complex data. The molecular aspects of specific diseases must be fully understood for accurate interpretation of NGS data. This review was thus aimed at describing (for the first time) the most relevant studies involving Sanger and NGS sequencing, leading to the description of variants related to RPL pathogenesis. Successful RPL-related NGS initiatives (including RNAseq-based studies) and future challenges are discussed. We consider that the information given here should be useful for clinicians, scientists, and students to enable a better understanding of RPL etiology. It may also provide a basis for the development of diagnostic/prognostic approaches contributing toward translational medicine.
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Affiliation(s)
- Paula Quintero-Ronderos
- Center For Research in Genetics and Genomics (CIGGUR), GENIUROS Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Carrera 24 N° 63C-69, Bogotá, 1100100, Colombia
| | - Paul Laissue
- Center For Research in Genetics and Genomics (CIGGUR), GENIUROS Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Carrera 24 N° 63C-69, Bogotá, 1100100, Colombia.
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Stastny I, Zubor P, Kajo K, Kubatka P, Golubnitschaja O, Dankova Z. Aberrantly Methylated cfDNA in Body Fluids as a Promising Diagnostic Tool for Early Detection of Breast Cancer. Clin Breast Cancer 2020; 20:e711-e722. [PMID: 32792225 DOI: 10.1016/j.clbc.2020.05.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/29/2020] [Accepted: 05/11/2020] [Indexed: 12/24/2022]
Abstract
Breast malignancies are the leading type of cancer among women. Its prevention and early detection, particularly in young women, remains challenging. To this end, cell-free DNA (cfDNA) detected in body fluids demonstrates great potential for early detection of tissue transformation and altered molecular setup, such as epigenetic profiles. Aberrantly methylated cfDNA in body fluids could therefore serve as a potential diagnostic and prognostic tool in breast cancer management. Abnormal methylation may lead to both an activation of oncogenes via hypomethylation and an inactivation of tumor suppressor genes by hypermethylation. We update the state of the art in the area of aberrant cfDNA methylation analyses as a diagnostic and prognostic tool in breast cancer, report on the main technological challenges, and provide an outlook for advancing the overall management of breast malignancies based on cfDNA as a target for diagnosis and tailored therapies.
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Affiliation(s)
- Igor Stastny
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic; Department of Obstetrics and Gynaecology, Martin University Hospital and Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic.
| | - Pavol Zubor
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic; Department of Gynecologic Oncology, The Norwegian Radium Hospital, Oslo University Hospital, 0379 Oslo, Norway
| | - Karol Kajo
- Department of Pathology, St Elizabeth Cancer Institute Hospital, Bratislava, Slovak Republic; Biomedical Research Centre, Slovak Academy of Sciences, Bratislava, Slovak Republic
| | - Peter Kubatka
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic; Department of Medical Biology, Jessenius Faculty of Medicine, Comenius University in Bratislava, Martin, Slovak Republic
| | - Olga Golubnitschaja
- Radiological Hospital, Rheinische, Excellence University of Bonn, Bonn, Germany; Breast Cancer Research Centre, Rheinische, Excellence University of Bonn, Bonn, Germany; Centre for Integrated Oncology, Cologne-Bonn, Excellence University of Bonn, Bonn, Germany
| | - Zuzana Dankova
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovak Republic
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Laissue P, Vaiman D. Exploring the Molecular Aetiology of Preeclampsia by Massive Parallel Sequencing of DNA. Curr Hypertens Rep 2020; 22:31. [PMID: 32172383 DOI: 10.1007/s11906-020-01039-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE OF REVIEW This manuscript aims to review (for the first time) studies describing NGS sequencing of preeclampsia (PE) women's DNA. RECENT FINDINGS Describing markers for the early detection of PE is an essential task because, although associated molecular dysfunction begins early on during pregnancy, the disease's clinical signs usually appear late in pregnancy. Although several biochemical biomarkers have been proposed, their use in clinical environments is still limited, thereby encouraging research into PE's genetic origin. Hundreds of genes involved in numerous implantation- and placentation-related biological processes may be coherent candidates for PE aetiology. Next-generation sequencing (NGS) offers new technical possibilities for PE studying, as it enables large genomic regions to be analysed at affordable cost. This technique has facilitated the description of genes contributing to the molecular origin of a significant amount of monogenic and complex diseases. Regarding PE, NGS of DNA has been used in familial and isolated cases, thereby enabling new genes potentially related to the phenotype to be proposed. For a better understanding of NGS, technical aspects, applications and limitations are presented initially. Thereafter, NGS studies of DNA in familial and non-familial cases are described, including pitfalls and positive findings. The information given here should enable scientists and clinicians to analyse and design new studies permitting the identification of novel clinically useful molecular PE markers.
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Affiliation(s)
- Paul Laissue
- Biopas Laboratoires, Biopas Group, Bogotá, Colombia. .,Inserm U1016, CNRS UMR8104, Institut Cochin, équipe FGTB, 24, rue du faubourg Saint-Jacques, 75014, Paris, France. .,CIGGUR Genetics Group, School of Medicine and Health Sciences, El Rosario University, Bogotá, Colombia.
| | - Daniel Vaiman
- Inserm U1016, CNRS UMR8104, Institut Cochin, équipe FGTB, 24, rue du faubourg Saint-Jacques, 75014, Paris, France
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36
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Jiao Y, Preston S, Hofmann A, Taki A, Baell J, Chang BCH, Jabbar A, Gasser RB. A perspective on the discovery of selected compounds with anthelmintic activity against the barber's pole worm-Where to from here? ADVANCES IN PARASITOLOGY 2020; 108:1-45. [PMID: 32291083 DOI: 10.1016/bs.apar.2019.12.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Parasitic roundworms (nematodes) cause substantial morbidity and mortality in animals worldwide. Anthelmintic treatment is central to controlling these worms, but widespread resistance to most of the commercially available anthelmintics for veterinary and agricultural use is compromising control, such that there is an urgency to discover new and effective drugs. The purpose of this article is to review information on parasitic nematodes, the treatment and control of parasitic nematode infections and aspects of discovering new anthelmintics in the context of anthelmintic resistance problems, and then to discuss some progress that our group has made in identifying selected compounds with activity against nematodes. The focus of our recent work has been on discovering new chemical entities and known drugs with anthelmintic activities against Haemonchus contortus as well as other socioeconomically important parasitic nematodes for subsequent development. Using whole worm-based phenotypic assays, we have been screening compound collections obtained via product-development-partnerships and/or collaborators, and active compounds have been assessed for their potential as anthelmintic candidates. Following the screening of 15,333 chemicals from five distinct compound collections against H. contortus, we have discovered one new chemical entity (designated SN00797439), two human kinase inhibitors (SNS-032 and AG-1295), 14 tetrahydroquinoxaline analogues, one insecticide (tolfenpyrad) and two tolfenpyrad (pyrazole-5-carboxamide) derivatives (a-15 and a-17) with anthelmintic activity in vitro. Some of these 20 'hit' compounds have selectivity against H. contortus in vitro when compared to particular human cell lines. In our opinion, some of these compounds could represent starting points for 'lead' development. Accordingly, the next research steps to be pursued include: (i) chemical optimisation of representative chemicals via structure-activity relationship (SAR) evaluations; (ii) assessment of the breadth of spectrum of anthelmintic activity on a range of other parasitic nematodes, such as strongyloids, ascaridoids, enoplids and filarioids; (iii) detailed investigations of the absorption, distribution, metabolism, excretion and toxicity (ADMET) of optimised chemicals with broad nematocidal or nematostatic activity; and (iv) establishment of the modes of action of lead candidates.
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Affiliation(s)
- Yaqing Jiao
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Sarah Preston
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia; Faculty of Science and Technology, Federation University, Ballarat, VIC, Australia
| | - Andreas Hofmann
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Aya Taki
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Jonathan Baell
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
| | - Bill C H Chang
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia
| | - Abdul Jabbar
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia.
| | - Robin B Gasser
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC, Australia.
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37
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Brunette CA, Miller SJ, Majahalme N, Hau C, MacMullen L, Advani S, Ludin SA, Zimolzak AJ, Vassy JL. Pragmatic Trials in Genomic Medicine: The Integrating Pharmacogenetics In Clinical Care (I-PICC) Study. Clin Transl Sci 2020; 13:381-390. [PMID: 31808996 PMCID: PMC7070795 DOI: 10.1111/cts.12723] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 10/31/2019] [Indexed: 12/19/2022] Open
Abstract
Pragmatic clinical trials (PCTs) have an established presence in clinical research and yet have only recently garnered attention within the landscape of genomic medicine. Using the PRagmatic-Explanatory Continuum Indicator Summary 2 (PRECIS-2) as a framework, this paper illustrates the application of PCT principles to The Integrating Pharmacogenetics In Clinical Care (I-PICC) Study, a trial of pharmacogenetic testing prior to statin initiation for cardiovascular disease prevention in primary care. The trial achieved high engagement with providers (85% enrolled of those approached) and enrolled a representative sample of participants for which statin therapy would be recommended. The I-PICC Study has a high level of pragmatism, which should enhance the generalizability of its findings. The PRECIS-2 may be useful in the design and evaluation of PCTs of genomic medicine interventions, contributing to the generation of evidence that can bridge the gap between genomics innovation and clinical adoption.
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Affiliation(s)
| | | | | | - Cynthia Hau
- VA Boston Healthcare SystemBostonMassachusettsUSA
| | | | | | - Sophie A. Ludin
- VA Boston Healthcare SystemBostonMassachusettsUSA
- Cornell UniversityIthacaNew YorkUSA
| | - Andrew J. Zimolzak
- VA Boston Healthcare SystemBostonMassachusettsUSA
- Baylor College of MedicineHoustonTexasUSA
- Michael E. DeBakey VA Medical CenterHoustonTexasUSA
| | - Jason L. Vassy
- VA Boston Healthcare SystemBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
- Division of General Internal Medicine and Primary CareBrigham and Women's HospitalBostonMassachusettsUSA
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38
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Meloche M, Kwon HJ, Letarte N, Bussières JF, Vadnais B, Hurlimann T, Lavoie A, Beauchesne MF, de Denus S. Opinion, experience and educational preferences concerning pharmacogenomics: an exploratory study of Quebec pharmacists. Pharmacogenomics 2020; 21:235-245. [DOI: 10.2217/pgs-2019-0135] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Aim: To evaluate the current opinion, experience and educational preferences of pharmacists in Quebec concerning pharmacogenomics. Method: A web-based survey containing 25 questions was sent to all Quebec pharmacists. Results: Most pharmacists were willing to advise patients (81%) and physicians (84%) on treatment choices based on pharmacogenomic test results after proper training. Only 31% had been previously exposed to pharmacogenomic test results, and 91% were favorable to pharmacogenomics training, with e-learning through interactive video sessions (69%). The preferred training session length was between 1 and 3 h (59%). Hospital pharmacists were more often exposed to pharmacogenomic tests (p < 0.0001) and more frequently advised patients on treatment choices (p < 0.001) than community pharmacists. Conclusion: Pharmacists remain favorable toward pharmacogenomics, but its use in clinical practice stays limited. Identifying the educational preferences of pharmacists may help in the development of educational programs to help them integrate pharmacogenomics in their clinical practice.
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Affiliation(s)
- Maxime Meloche
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Montreal Heart Institute, Montreal, Canada
| | - Hyuk J Kwon
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
| | - Nathalie Letarte
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Department of Pharmacy, Centre Hospitalier de l’Université de Montréal, Montreal, Canada
| | - Jean-François Bussières
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Department of Pharmacy, Sainte-Justine University Hospital Center, Montreal, Canada
| | - Barbara Vadnais
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Department of Pharmacy, Hôpital Maisonneuve-Rosemont, Montreal, Canada
| | - Thierry Hurlimann
- Department of Social & Preventive Medicine, Bioethics Programs, Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - Annie Lavoie
- Department of Pharmacy, Sainte-Justine University Hospital Center, Montreal, Canada
| | - Marie-France Beauchesne
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Research Center, Centre Intégré Universitaire de Santé et de Services Sociaux de l’Estrie-Centre Hospitalier Universitaire de Sherbrooke, Installations Hôtel-Dieu et Fleurimont, Sherbrooke, Canada
| | - Simon de Denus
- Faculty of Pharmacy, Université de Montréal, Montreal, Canada
- Montreal Heart Institute, Montreal, Canada
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Best S, Stark Z, Phillips P, Wu Y, Long JC, Taylor N, Braithwaite J, Christodoulou J, Goranitis I. Clinical genomic testing: what matters to key stakeholders? Eur J Hum Genet 2020; 28:866-873. [PMID: 32024983 DOI: 10.1038/s41431-020-0576-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 01/02/2020] [Accepted: 01/14/2020] [Indexed: 11/09/2022] Open
Abstract
Beyond a narrow focus on cost and outcomes, robust evidence of what is valued in genomic medicine is scarce. We gathered views on value from key stakeholders (clinical genomic staff, operational genomic staff and community representatives) in relation to three testing contexts (General Healthcare, Acute Care and Neurodevelopmental Conditions). We conducted an iterative focus group in three stages over a week using a multiphase mixed methods study, i.e. quantitative ratings and qualitative discussion. For each testing context, the characteristics of genomic testing were generated and ranked by the group using a co-productive approach. Up to 17 characteristics were identified in one scenario with several characteristics featuring in all three testing contexts. The likelihood of getting an answer was consistently reported as most highly valued, followed by the potential for the test to impact on clinical management (or wellbeing/health for Neurodevelopmental Conditions). Risk of discrimination did not feature highly across the different settings (and not at all in Acute Care). While cost was an issue in the general health setting, it was one of the least-valued characteristics in the other two testing contexts. In conclusion, co-producing an understanding of what is valued in different testing contexts, and identifying the areas of differences or commonalities, is important to maximise value provision and inform future policy to ensure that clinical genomic services meet the needs of the community and service providers.
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Affiliation(s)
- Stephanie Best
- Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia. .,Australian Genomics, Murdoch Childrens Research Institute, Melbourne, VIC, Australia.
| | - Zornitza Stark
- Australian Genomics, Murdoch Childrens Research Institute, Melbourne, VIC, Australia.,Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, VIC, Australia.,University of Melbourne, Melbourne, VIC, Australia
| | - Peta Phillips
- Australian Genomics, Murdoch Childrens Research Institute, Melbourne, VIC, Australia
| | - You Wu
- Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Janet C Long
- Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia
| | - Natalie Taylor
- Cancer Council NSW, Woolloomooloo, Sydney, NSW, Australia.,Faculty of Health Science, University of Sydney, Sydney, Australia
| | - Jeffrey Braithwaite
- Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia
| | - John Christodoulou
- University of Melbourne, Melbourne, VIC, Australia.,Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Ilias Goranitis
- Australian Genomics, Murdoch Childrens Research Institute, Melbourne, VIC, Australia.,Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
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40
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Yan W, Xu T, Zhu H, Yu J. Clinical Applications of Cerebrospinal Fluid Circulating Tumor DNA as a Liquid Biopsy for Central Nervous System Tumors. Onco Targets Ther 2020; 13:719-731. [PMID: 32158224 PMCID: PMC6986252 DOI: 10.2147/ott.s229562] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 01/11/2020] [Indexed: 12/19/2022] Open
Abstract
Central nervous system (CNS) malignancies are associated with poor prognosis, as well as exceptional morbidity and mortality, likely as a result of low rates of early diagnosis and limited knowledge of the tumor growth and resistance mechanisms, dissemination, and evolution in the CNS. Monitoring patients with CNS malignancies for treatment response and tumor recurrence can be challenging because of the difficulty and risks of brain biopsies and the low specificity and sensitivity of the less invasive methodologies that are currently available. Therefore, there is an urgent need to detect and validate reliable and minimally invasive biomarkers for CNS tumors that can be used separately or in combination with current clinical practices. The circulating tumor DNA (ctDNA) of cerebrospinal fluid (CSF) samples can outline the genetic landscape of entire CNS tumors effectively and is a promising, suitable biomarker, though its role in managing CNS malignancies has not been studied extensively. This review summarizes recent studies that explore the diagnostic, prognostic, and predictive roles of CSF-ctDNA as a liquid biopsy with primary and metastatic CNS malignancies.
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Affiliation(s)
- Weiwei Yan
- School of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.,Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, People's Republic of China
| | - Tingting Xu
- Department of Respiratory Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong, People's Republic of China
| | - Hui Zhu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, People's Republic of China
| | - Jinming Yu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, People's Republic of China
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41
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Wu AC, Kiley JP, Noel PJ, Amur S, Burchard EG, Clancy JP, Galanter J, Inada M, Jones TK, Kropski JA, Loyd JE, Nogee LM, Raby BA, Rogers AJ, Schwartz DA, Sin DD, Spira A, Weiss ST, Young LR, Himes BE. Current Status and Future Opportunities in Lung Precision Medicine Research with a Focus on Biomarkers. An American Thoracic Society/National Heart, Lung, and Blood Institute Research Statement. Am J Respir Crit Care Med 2019; 198:e116-e136. [PMID: 30640517 DOI: 10.1164/rccm.201810-1895st] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Thousands of biomarker tests are either available or under development for lung diseases. In many cases, adoption of these tests into clinical practice is outpacing the generation and evaluation of sufficient data to determine clinical utility and ability to improve health outcomes. There is a need for a systematically organized report that provides guidance on how to understand and evaluate use of biomarker tests for lung diseases. METHODS We assembled a diverse group of clinicians and researchers from the American Thoracic Society and leaders from the National Heart, Lung, and Blood Institute with expertise in various aspects of precision medicine to review the current status of biomarker tests in lung diseases. Experts summarized existing biomarker tests that are available for lung cancer, pulmonary arterial hypertension, idiopathic pulmonary fibrosis, asthma, chronic obstructive pulmonary disease, sepsis, acute respiratory distress syndrome, cystic fibrosis, and other rare lung diseases. The group identified knowledge gaps that future research studies can address to efficiently translate biomarker tests into clinical practice, assess their cost-effectiveness, and ensure they apply to diverse, real-life populations. RESULTS We found that the status of biomarker tests in lung diseases is highly variable depending on the disease. Nevertheless, biomarker tests in lung diseases show great promise in improving clinical care. To efficiently translate biomarkers into tests used widely in clinical practice, researchers need to address specific clinical unmet needs, secure support for biomarker discovery efforts, conduct analytical and clinical validation studies, ensure tests have clinical utility, and facilitate appropriate adoption into routine clinical practice. CONCLUSIONS Although progress has been made toward implementation of precision medicine for lung diseases in clinical practice in certain settings, additional studies focused on addressing specific unmet clinical needs are required to evaluate the clinical utility of biomarkers; ensure their generalizability to diverse, real-life populations; and determine their cost-effectiveness.
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42
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Guo B, Zheng Q. Using Naïve Bayes Algorithm to Estimate the Response to Drug in Lung Cancer Patients. Comb Chem High Throughput Screen 2019; 21:734-748. [PMID: 30686250 DOI: 10.2174/1386207322666190125151624] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 09/11/2018] [Accepted: 11/02/2018] [Indexed: 11/22/2022]
Abstract
AIM AND OBJECTIVE Lung cancer is a highly heterogeneous cancer, due to the significant differences in molecular levels, resulting in different clinical manifestations of lung cancer patients there is a big difference. Including disease characterization, drug response, the risk of recurrence, survival, etc. Method Clinical patients with lung cancer do not have yet particularly effective treatment options, while patients with lung cancer resistance not only delayed the treatment cycle but also caused strong side effects. Therefore, if we can sum up the abnormalities of functional level from the molecular level, we can scientifically and effectively evaluate the patients' sensitivity to treatment and make the personalized treatment strategies to avoid the side effects caused by over-treatment and improve the prognosis. RESULT & CONCLUSION According to the different sensitivities of lung cancer patients to drug response, this study screened out genes that were significantly associated with drug resistance. The bayes model was used to assess patient resistance.
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Affiliation(s)
- Baoling Guo
- Department of Oncology, Longyan First Hospital, Affiliated to Fujian Medical University, Longyan, China
| | - Qiuxiang Zheng
- Department of Oncology, Longyan First Hospital, Affiliated to Fujian Medical University, Longyan, China
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43
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Zebrowski AM, Ellis DE, Barg FK, Sperber NR, Bernhardt BA, Denny JC, Dexter PR, Ginsburg GS, Horowitz CR, Johnson JA, Levy MA, Orlando LA, Pollin TI, Skaar TC, Kimmel SE. Qualitative study of system-level factors related to genomic implementation. Genet Med 2019; 21:1534-1540. [PMID: 30467402 PMCID: PMC6533158 DOI: 10.1038/s41436-018-0378-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 11/09/2018] [Indexed: 01/27/2023] Open
Abstract
PURPOSE Research on genomic medicine integration has focused on applications at the individual level, with less attention paid to implementation within clinical settings. Therefore, we conducted a qualitative study using the Consolidated Framework for Implementation Research (CFIR) to identify system-level factors that played a role in implementation of genomic medicine within Implementing GeNomics In PracTicE (IGNITE) Network projects. METHODS Up to four study personnel, including principal investigators and study coordinators from each of six IGNITE projects, were interviewed using a semistructured interview guide that asked interviewees to describe study site(s), progress at each site, and factors facilitating or impeding project implementation. Interviews were coded following CFIR inner-setting constructs. RESULTS Key barriers included (1) limitations in integrating genomic data and clinical decision support tools into electronic health records, (2) physician reluctance toward genomic research participation and clinical implementation due to a limited evidence base, (3) inadequate reimbursement for genomic medicine, (4) communication among and between investigators and clinicians, and (5) lack of clinical and leadership engagement. CONCLUSION Implementation of genomic medicine is hindered by several system-level barriers to both research and practice. Addressing these barriers may serve as important facilitators for studying and implementing genomics in practice.
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Affiliation(s)
- Alexis M Zebrowski
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - Darcy E Ellis
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Frances K Barg
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia, PA, USA
| | - Nina R Sperber
- Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Barbara A Bernhardt
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joshua C Denny
- Departments of Biomedical Informatics and Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
- Division of General Internal Medicine, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Paul R Dexter
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Geoffrey S Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Durham, NC, USA
| | - Carol R Horowitz
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida College of Pharmacy, Gainesville, FL, USA
| | - Mia A Levy
- Departments of Biomedical Informatics and Medicine, Division of Hematology and Oncology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Lori A Orlando
- Duke Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Durham, NC, USA
- Division of General Internal Medicine, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Toni I Pollin
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Stephen E Kimmel
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Medicine, Pearlman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Mintzer V, Moran-Gilad J, Simon-Tuval T. Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review. Clin Microbiol Infect 2019; 25:1086-1095. [PMID: 31039443 DOI: 10.1016/j.cmi.2019.04.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 04/17/2019] [Accepted: 04/18/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges. OBJECTIVES The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting. METHODS This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted. RESULTS A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures). CONCLUSIONS The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.
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Affiliation(s)
- V Mintzer
- Department of Health Systems Management, Guilford Glazer Faculty of Business and Management and Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel; Leumit Health Services, Israel
| | - J Moran-Gilad
- Department of Health Policy and Management, School of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel; ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD), Basel, Switzerland
| | - T Simon-Tuval
- Department of Health Systems Management, Guilford Glazer Faculty of Business and Management and Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel.
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Horrow C, Pacyna JE, Sutton EJ, Sperry BP, Breitkopf CR, Sharp RR. Assessing optimism and pessimism about genomic medicine: Development of a genomic orientation scale. Clin Genet 2019; 95:704-712. [DOI: 10.1111/cge.13535] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 03/08/2019] [Accepted: 03/12/2019] [Indexed: 01/29/2023]
Affiliation(s)
- Caroline Horrow
- Biomedical Ethics Research ProgramMayo Clinic Rochester Minnesota
| | - Joel E. Pacyna
- Biomedical Ethics Research ProgramMayo Clinic Rochester Minnesota
| | - Erica J. Sutton
- Biomedical Ethics Research ProgramMayo Clinic Rochester Minnesota
| | - Beau P. Sperry
- Biomedical Ethics Research ProgramMayo Clinic Rochester Minnesota
| | | | - Richard R. Sharp
- Biomedical Ethics Research ProgramMayo Clinic Rochester Minnesota
- Center for Individualized MedicineMayo Clinic Rochester Minnesota
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Quintero-Ronderos P, Laissue P. Genetic Variants Contributing to Early Recurrent Pregnancy Loss Etiology Identified by Sequencing Approaches. Reprod Sci 2019:1933719119831769. [PMID: 30879428 DOI: 10.1177/1933719119831769] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Recurrent pregnancy loss (RPL) affects up to 5% of couples. It is believed that genetic factors contribute to the disease's etiology and pathophysiology. Hundreds of genes represent coherent RPL candidates due to mammalian implantation's inherent complexity. Sanger sequencing (direct sequencing) of candidate genes has identified potential RPL causative genes (and variants), including those regulating embryo implantation and pregnancy maintenance. Although this approach is a reliable technique, the simultaneous analysis of large genomic regions is challenging. Next-generation sequencing (NGS) technology has thus emerged as a useful alternative for determining genetic variants and transcriptomic disturbances contributing to monogenic and polygenic diseases pathogenesis. However, interpreting results remains challenging as NGS experiments provide an enormous amount of complex data. The molecular aspects of specific diseases must be fully understood for accurate interpretation of NGS data. This review was thus aimed at describing (for the first time) the most relevant studies involving Sanger and NGS sequencing, leading to the description of variants related to RPL pathogenesis. Successful RPL-related NGS initiatives (including RNAseq-based studies) and future challenges are discussed. We consider that the information given here should be useful for clinicians, scientists, and students to enable a better understanding of RPL etiology. It may also provide a basis for the development of diagnostic/prognostic approaches contributing toward translational medicine.
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Affiliation(s)
- Paula Quintero-Ronderos
- 1 Center For Research in Genetics and Genomics (CIGGUR), GENIUROS Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Colombia
| | - Paul Laissue
- 1 Center For Research in Genetics and Genomics (CIGGUR), GENIUROS Research Group, School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Colombia
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Podzolkov VI, Tarzimanova AI. Personalized Medicine in the Treatment of Atrial Fibrillation: Myth or Reality? RATIONAL PHARMACOTHERAPY IN CARDIOLOGY 2019. [DOI: 10.20996/1819-6446-2019-15-1-90-94] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Due to the spectacular progress made in human genomic studies, molecular biology and genetics have become an essential part of modern medicine making it possible to early detect the risk factors and select the personalized treatment. The genetic studies have been widely used in the diagnosis and treatment of arrhythmias. Significant advances in the study of electrophysiological and genetic mechanisms of life-threatening arrhythmias have been achieved through studies of familial conditions with high risk of sudden cardiac death. However, the area of special interest for a practitioner is the identification of mutations associated with atrial fibrillation (AF). The novel methods enable us to study histological, structural, cellular and molecular causes of this arrhythmia. The two main directions of molecular genetic studies of AF are the identification of genetic mutations causing familial atrial fibrillation and the study of different genes polymorphism predisposing to arrhythmia in general population. Gene polymorphism screening helps both identify AF risk factors and predict its evolution from paroxysmal to chronic type. Emerging genetic studies provided explanation for the variable efficacy of antiarrhythmic drugs. It can be assumed that the clinical use of genetic methods will allow accurate and personalized selection of antiarrhythmics. Currently, therapeutic drug monitoring is widely recommended for a number of medications including cytostatics, aminoglycosides, anticonvulsants, and, by some researchers, antiarrhythmic and anticoagulant drugs. Medicine from the very beginning was intended to be personalized, but until recently it was a little more than a myth. The discovery of the human genome makes it possible to choose the most effective treatment with minimal adverse drug reactions for a particular patient.
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Affiliation(s)
- V. I. Podzolkov
- I.M. Sechenov First Moscow State Medical University (Sechenov University)
| | - A. I. Tarzimanova
- I.M. Sechenov First Moscow State Medical University (Sechenov University)
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Lunenburg CA, Guchelaar HJ, van Schaik RH, Neumaier M, Swen JJ. Confirmation practice in pharmacogenetic testing; how good is good enough? Clin Chim Acta 2019; 490:77-80. [DOI: 10.1016/j.cca.2018.12.023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 12/20/2018] [Indexed: 11/16/2022]
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Chang A, Nelson R, Brixner D. Advancing pharmacy practice by reducing gaps in pharmacogenetic education. Am J Health Syst Pharm 2019; 76:320-326. [PMID: 30753288 DOI: 10.1093/ajhp/zxy066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
- Annie Chang
- University of California, San Francisco School of Pharmacy, San Francisco, CA
| | - Ryan Nelson
- Department of Individualized Cancer Management, Moffitt Cancer Center, ?Tampa, FL
| | - Diana Brixner
- Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, UT.,Program in Personalized Healthcare, University of Utah, Salt Lake City, UT
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Abstract
Precision medicine is making an impact on patients, health care delivery systems, and research participants in ways that were only imagined fifteen years ago when the human genome was first sequenced. Discovery of disease-causing and drug-response genetic variants has accelerated, while adoption into clinical medicine has lagged. We define precision medicine and the stakeholder community required to enable its integration into research and health care. We explore the intersection of data science, analytics, and precision medicine in the formation of health systems that carry out research in the context of clinical care and that optimize the tools and information used to deliver improved patient outcomes. We provide examples of real-world impact and conclude with a policy and economic agenda necessary for the adoption of this new paradigm of health care both in the United States and globally.
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Affiliation(s)
- Geoffrey S Ginsburg
- Geoffrey S. Ginsburg ( ) is director of the Duke Center for Applied Genomics and Precision Medicine, Duke University, in Durham, North Carolina
| | - Kathryn A Phillips
- Kathryn A. Phillips is a professor of health economics and health services research at the University of California San Francisco
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