Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understanding their biological functions and clinical value. However, many challenges still need to be addressed for their application, including developing specific analysis methods and translating cfRNA fragments with biological support into clinical applications.

We present cfPeak, a novel method combining statistics and machine learning models to detect the fragmented cfRNA signals effectively. When test in real and artificial cfRNA sequencing (cfRNA-seq) data, cfPeak shows an improved performance compared with other applicable methods. We reveal that narrow cfRNA peaks preferentially overlap with protein binding sites, vesicle-sorting sites, structural sites, and novel small non-coding RNAs (sncRNAs). When applied in clinical cohorts, cfPeak identified cfRNA peaks in patients' plasma that enable cancer detection and are informative of cancer types and metastasis.

Our study fills the gap in the current small cfRNA-seq analysis at fragment-scale and builds a bridge to the scientific discovery in cfRNA fragmentomics. We demonstrate the significance of finding low abundant tissue-derived signals in small cfRNA and prove the feasibility for application in liquid biopsy.

Virtually all individuals aged 65 or older develop at least early pathology of Alzheimer's disease (AD), yet most lack disease-causing mutations in APP, PSEN, or MAPT, and many do not carry the APOE4 risk allele. This raises questions about AD development in the general population. Although transcriptional dysregulation has not traditionally been a hallmark of AD, recent studies reveal significant epigenomic changes in late-onset AD (LOAD) patients. We show that altered expression of the LOAD biomarker phosphoglycerate dehydrogenase (PHGDH) modulates AD pathology in mice and human brain organoids independent of its enzymatic activity. PHGDH has an uncharacterized role in transcriptional regulation, promoting the transcription of inhibitor of nuclear factor kappa-B kinase subunit alpha (IKKa) and high-mobility group box 1 (HMGB1) in astrocytes, which suppress autophagy and accelerate amyloid pathology. A blood-brain-barrier-permeable small-molecule inhibitor targeting PHGDH's transcriptional function reduces amyloid pathology and improves AD-related behavioral deficits. These findings highlight transcriptional regulation in LOAD and suggest therapeutic strategies beyond targeting familial mutations.

The prevalence of Alzheimer's disease (AD) is increasing as society ages. The details of AD pathogenesis have not been fully elucidated, and a comprehensive gene expression analysis of the process leading up to the onset of AD would be helpful for understanding the mechanism. We performed an RNA sequencing analysis on a cohort of 1227 Japanese blood samples, representing 424 AD patients, 543 individuals with mild cognitive impairment (MCI), and 260 cognitively normal (CN) individuals. A total of 883 and 1169 statistically significant differentially expressed genes (DEGs) were identified between CN and MCI (CN-MCI) and between MCI and AD (MCI-AD), respectively. Pathway analyses using these DEGs, followed by protein-protein interaction network analysis, revealed key roles of ribosomal function in MCI progression, whereas immune responses, cell cycle, and protein processing in endoplasmic reticulum were involved in AD progression. Our findings indicate that the onset of AD might be associated with gene expression changes in the immune system, cell cycle, and protein processing following alterations in the expression of ribosomal protein genes during the MCI stage, although validation using brain tissue samples will be necessary in the future. Given the known effectiveness of delaying MCI progression in preventing AD, the genes related to ribosomal function might emerge as biomarkers for early diagnosis.

D-3-phosphoglycerate dehydrogenase (PHGDH) catalyzes the NAD+-dependent conversion of D-3-phospho-glycerate to 3-phosphohydroxypyruvate, the first step in the phosphorylated pathway for L-serine (L-Ser) biosynthesis. L-Ser plays different relevant metabolic roles in eukaryotic cells: alterations in L-Ser metabolism have been linked to serious neurological disorders. The human PHGDH (hPHGDH), showing a homotetrameric state in solution, is made of four domains, among which there are two regulatory domains at the C-terminus: the aspartate kinase-chorismate mutase-tyrA prephenate dehydrogenase (ACT) and allosteric substrate-binding (ASB) domains. The structure of hPHGDH was solved only for a truncated, dimeric form harboring the N-terminal end containing the substrate and the cofactor binding domains. A model ensemble of the tetrameric hPHGDH was generated using AlphaFold coupled with molecular dynamics refinement. By analyzing the inter-subunit interactions at the tetrameric interface, the residues F418, L478, P479, R454, and Y495 were selected and their role was studied by the alanine-scanning mutagenesis approach. The F418A variant modifies the putative ASB, slightly alters the activity, the fraction of protein in the tetrameric state, and the protein stability; it seems relevant in dimers' recognition to yield the tetrameric oligomer. On the contrary, the R454A, L478A, P479A, and Y495A variants (ACT domain) determine a loss of the tetrameric assembly, resulting in low stability and misfolding, triggering the aggregation and hampering the activity. The predicted tetrameric interface seems mediated by residues at the ACT domain, and the tetramer formation seems crucial for proper folding of hPHGDH, which, in turn, is essential for both stability and functionality.

Despite gene-expression profiling being one of the most common methods to evaluate molecular dysregulation in tissues, the utilization of cell-free messenger RNA (cf-mRNA) as a blood-based non-invasive biomarker analyte has been limited compared to other RNA classes. Recent advancements in low-input RNA-sequencing and normalization techniques, however, have enabled characterization as well as accurate quantification of cf-mRNAs allowing direct pathological insights. The molecular profile of the cell-free transcriptome in multiple diseases has subsequently been characterized including, prenatal diseases, neurological disorders, liver diseases and cancers suggesting this biological compartment may serve as a disease agnostic platform. With mRNAs packaged in a myriad of extracellular vesicles and particles, these signals may be used to develop clinically actionable, non-invasive disease biomarkers. Here, we summarize the recent scientific developments of extracellular mRNA, biology of extracellular mRNA carriers, clinical utility of cf-mRNA as disease biomarkers, as well as proposed functions in cell and tissue pathophysiology.

Non-invasively evaluating gene expression products in human pre-implantation embryos remains a significant challenge. Here, we develop a non-invasive method for comprehensive characterization of the extracellular RNAs (exRNAs) in a single droplet of spent media that was used to culture human in vitro fertilization embryos. We generate the temporal extracellular transcriptome atlas (TETA) of human pre-implantation development. TETA consists of 245 exRNA sequencing datasets for five developmental stages. These data reveal approximately 4,000 exRNAs at each stage. The exRNAs of the developmentally arrested embryos are enriched with the genes involved in negative regulation of the cell cycle, revealing an exRNA signature of developmental arrest. Furthermore, a machine-learning model can approximate the morphology-based rating of embryo quality based on the exRNA levels. These data reveal the widespread presence of coding gene-derived exRNAs at every stage of human pre-implantation development, and these exRNAs provide rich information on the physiology of the embryo.

Circulating cell-free RNA (cfRNA) is a potential hallmark for early diagnosis of Alzheimer's Disease (AD) as it construes the genetic expression level, giving insights into the pathological progress from the outset. Profiles of cfRNA in Caucasian AD patients have been investigated thoroughly, yet there was no report exploring cfRNAs in the ASEAN groups. This study examined the gap, expecting to support the development of point-of-care AD diagnosis.

cfRNA profiles were characterized from 20 Vietnamese plasma samples (10 probable AD and 10 age-matched controls). RNA reads were subjected to differential expression (DE) analysis. Weighted gene correlation network analysis (WGCNA) was performed to identify gene modules that were significantly co-expressed. These modules' expression profiles were then correlated with AD status to identify relevant modules. Genes with the highest intramodular connectivity (module membership) were selected as hub genes. Transcript counts of differentially expressed genes were correlated with key AD measures-MMSE and MTA scores-to identify potential biomarkers.

136 genes were identified as significant AD hallmarks (p < 0.05), with 52 downregulated and 84 upregulated in the AD cohort. 45.6% of these genes are highly expressed in the hippocampus, cerebellum, and cerebral cortex. Notably, all markers related to chronic inflammation were upregulated, and there was a significant shift in all apoptotic markers. Three co-expressed modules were found to be significantly correlated with Alzheimer's status (p < 0.05; R2> 0.5). Functional enrichment analysis on these modules reveals an association with focal adhesion, nucleocytoplasmic transport, and metal ion response leading to apoptosis, suggesting the potential participation of these pathways in AD pathology. 47 significant hub genes were found to be differentially expressed genes with the highest connectivity. Six significant hub genes (CREB1, YTHDC1, IL1RL1, PHACTR2, ANKRD36B, RNF213) were found to be significantly correlated with MTA and MMSE scores. Other significant transcripts (XRN1, UBB, CHP1, THBS1, S100A9) were found to be involved in inflammation and neuronal death. Overall, we have identified candidate transcripts in plasma cf-RNA that are differentially expressed and are implicated in inflammation and apoptosis, which can jumpstart further investigations into applying cf-RNA as an AD biomarker in Vietnam and ASEAN countries.

Liquid biopsies provide a means for the profiling of cell-free RNAs secreted by cells throughout the body. Although well-annotated coding and non-coding transcripts in blood are readily detectable and can serve as biomarkers of disease, the overall diagnostic utility of the cell-free transcriptome remains unclear. Here we show that RNAs derived from transposable elements and other repeat elements are enriched in the cell-free transcriptome of patients with cancer, and that they serve as signatures for the accurate classification of the disease. We used repeat-element-aware liquid-biopsy technology and single-molecule nanopore sequencing to profile the cell-free transcriptome in plasma from patients with cancer and to examine millions of genomic features comprising all annotated genes and repeat elements throughout the genome. By aggregating individual repeat elements to the subfamily level, we found that samples with pancreatic cancer are enriched with specific Alu subfamilies, whereas other cancers have their own characteristic cell-free RNA profile. Our findings show that repetitive RNA sequences are abundant in blood and can be used as disease-specific diagnostic biomarkers.

The most recent and non-invasive approach for studying early-stage biomarkers is liquid biopsy. This implies the extraction and analysis of non-solid biological tissues (serum, plasma, saliva, urine, and cerebrospinal fluid) without undergoing invasive procedures to determine disease prognosis. Liquid biopsy can be used for the screening of several components, such as extracellular vesicles, microRNAs, cell-free DNA, cell-free mitochondrial and nuclear DNA, circulating tumour cells, circulating tumour DNA, transfer RNA, and circular DNA or RNA derived from body fluids. Its application includes early disease diagnosis, the surveillance of disease activity, and treatment response monitoring, with growing evidence for validating this methodology in cancer, liver disease, and central nervous system (CNS) disorders. This review will provide an overview of mentioned liquid biopsy components, which could serve as valuable biomarkers for the evaluation of complex neurological conditions, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis, epilepsy, stroke, traumatic brain injury, CNS tumours, and neuroinfectious diseases. Furthermore, this review highlights the future directions and potential limitations associated with liquid biopsy.

Neurodegenerative processes in Alzheimer's disease (AD) are associated with excitotoxicity mediated by the N-methyl-D-aspartate receptor (NMDAR). D-Serine is an endogenous co-agonist necessary for NMDAR-mediated excitotoxicity. In the mammalian brain, it is produced by serine racemase (SRR) from L-serine, suggesting that dysregulation of L-serine, D-serine, or SRR may contribute to AD pathogenesis.

We examined the contributions of D-serine to AD pathology in the App^{NL-G-F/NL-G-F} gene knock-in (APPKI) mouse model of AD. We first examined brain SRR expression levels and neuropathology in APPKI mice and then assessed the effects of long-term D-serine supplementation in drinking water on neurodegeneration. To further confirm the involvement of endogenous D-serine in AD progression, we generated Srr gene-deleted APPKI (APPKI-SRRKO) mice. Finally, to examine the levels of brain amino acids, we conducted liquid chromatography-tandem mass spectrometry.

Expression of SRR was markedly reduced in the retrosplenial cortex (RSC) of APPKI mice at 12 months of age compared with age-matched wild-type mice. Neuronal density was decreased in the hippocampal CA1 region but not altered significantly in the RSC. D-Serine supplementation exacerbated neuronal loss in the hippocampal CA1 of APPKI mice, while APPKI-SRRKO mice exhibited attenuated astrogliosis and reduced neuronal death in the hippocampal CA1 compared with APPKI mice. Furthermore, APPKI mice demonstrated marked abnormalities in the cortical amino acid levels that were partially reversed in APPKI-SRRKO mice.

These findings suggest that D-serine participates in the regional neurodegenerative process in the hippocampal CA1 during the amyloid pathology of AD and that reducing brain D-serine can partially attenuate neuronal loss and reactive astrogliosis. Therefore, regulating SRR could be an effective strategy to mitigate NMDAR-dependent neurodegeneration during AD progression.

Major depressive disorder (MDD) is a major international public health issue; thus, investigating its underlying mechanisms and identifying suitable biomarkers to enable its early detection are imperative. Using data-independent acquisition-mass spectrometry-based proteomics, the plasma of 44 patients with MDD and 25 healthy controls was studied to detect differentially expressed proteins. Bioinformatics analyses, such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, Protein-Protein Interaction network, and weighted gene co-expression network analysis were employed. Moreover, an ensemble learning technique was used to build a prediction model. A panel of two biomarkers, L-selectin and an isoform of the Ras oncogene family was identified. With an area under the receiver operating characteristic curve of 0.925 and 0.901 for the training and test sets, respectively, the panel was able to distinguish MDD from the controls. Our investigation revealed numerous potential biomarkers and a diagnostic panel based on several algorithms, which may contribute to the future development of a plasma-based diagnostic approach and better understanding of the molecular mechanisms of MDD.

Upon microbial infections with the subsequent host response of innate immunity, a variety of fragmented RNA- and DNA-based "Pathogen-associated molecular patterns" (PAMPs) are recognized mainly by endosomal or cytoplasmic host cell "Pattern recognition receptors" (PRRs), particularly "Toll-like receptors" (TLRs). Concomitantly, various self-extracellular RNA species (exRNAs) are present in extracellular body fluids where they contribute to diverse physiological and homeostatic processes. In principle, such exRNAs, including the most abundant one, ribosomal exRNA (rexRNA), are designated as "Danger-associated molecular patterns" (DAMPs) and are prevented by e.g. natural modifications from uncontrolled signaling via TLRs to avoid hyper-inflammatory responses or autoimmunity. Upon cellular stress or tissue damage/necrosis, the levels and composition of released self-exRNA species, either in free form, in complex with proteins or in association with extracellular vesicles (EVs), can change considerably. Among the self-exRNAs, rexRNA is considered as a non-typical DAMP, since it may induce inflammatory responses by cell membrane receptors, both in the absence or presence of PAMPs. Yet, its mode of receptor activation to mount inflammatory responses remains obscure. RexRNA also serves as a universal damaging factor in cardiovascular and other diseases independent of PRRs. In general, RNase1 provides a profound antagonist in these pathologies and in rexRNA-mediated inflammatory cell responses. Based on the extrapolation of the here described aspects of rexRNA-biology, further activities of this molecular entity are hypothesized that may stimulate additional research in this area.

Aging-related cognitive decline is an early symptom of Alzheimer's disease and other dementias, and on its own can have substantial consequences on an individual's ability to perform important everyday functions. Despite increasing interest in the potential roles of extracellular microRNAs (miRNAs) in central nervous system (CNS) pathologies, there has been little research on extracellular miRNAs in early stages of cognitive decline. We leverage the longitudinal Normative Aging Study (NAS) cohort to investigate associations between plasma miRNAs and cognitive function among cognitively normal men.

This study includes data from up to 530 NAS participants (median age: 71.0 years) collected from 1996 to 2013, with a total of 1,331 person-visits (equal to 2,471 years of follow up). Global cognitive function was assessed using the Mini-Mental State Examination (MMSE). Plasma miRNAs were profiled using small RNA sequencing. Associations of expression of 381 miRNAs with current cognitive function and rate of change in cognitive function were assessed using linear regression (N = 457) and linear mixed models (N = 530), respectively.

In adjusted models, levels of 2 plasma miRNAs were associated with higher MMSE scores (p < 0.05). Expression of 33 plasma miRNAs was associated with rate of change in MMSE scores over time (p < 0.05). Enriched KEGG pathways for miRNAs associated with concurrent MMSE and MMSE trajectory included Hippo signaling and extracellular matrix-receptor interactions. Gene targets of miRNAs associated with MMSE trajectory were additionally associated with prion diseases and fatty acid biosynthesis.

Circulating miRNAs were associated with both cross-sectional cognitive function and rate of change in cognitive function among cognitively normal men. Further research is needed to elucidate the potential functions of these miRNAs in the CNS and investigate relationships with other neurological outcomes.

Healthy aging is an ambitious aspiration for humans, but neurodegenerative disorders, such as Alzheimer's disease (AD), strongly affect quality of life. Using an integrated omics approach, we investigate alterations in the molecular composition of postmortem hippocampus samples of healthy persons and individuals with AD. Profound differences are apparent between control and AD male and female cohorts in terms of up- and downregulated metabolic pathways. A decrease in the insulin response is evident in AD when comparing the female with the male group. The serine metabolism (linked to the glycolytic pathway and generating the N-methyl-D-aspartate [NMDA] receptor coagonist D-serine) is also significantly modulated: the D-Ser/total serine ratio represents a way to counteract age-related cognitive decline in healthy men and during AD onset in women. These results show how AD changes and, in certain respects, almost reverses sex-specific proteomic and metabolomic profiles, highlighting how different pathophysiological mechanisms are active in men and women.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

The preclinical diagnosis and clinical practice for Alzheimer's disease (AD) based on liquid biopsy have made great progress in recent years. As liquid biopsy is a fast, low-cost, and easy way to get the phase of AD, continual efforts from intense multidisciplinary studies have been made to move the research tools to routine clinical diagnostics. On one hand, technological breakthroughs have brought new detection methods to the outputs of liquid biopsy to stratify AD cases, resulting in higher accuracy and efficiency of diagnosis. On the other hand, diversiform biofluid biomarkers derived from cerebrospinal fluid (CSF), blood, urine, Saliva, and exosome were screened out and biologically verified. As a result, more detailed knowledge about the molecular pathogenesis of AD was discovered and elucidated. However, to date, how to weigh the reports derived from liquid biopsy for preclinical AD diagnosis is an ongoing question. In this review, we briefly introduce liquid biopsy and the role it plays in research and clinical practice. Then, we summarize the established fluid-based assays of the current state for AD diagnostic such as ELISA, single-molecule array (Simoa), Immunoprecipitation-Mass Spectrometry (IP-MS), liquid chromatography-MS, immunomagnetic reduction (IMR), multimer detection system (MDS). In addition, we give an updated list of fluid biomarkers in the AD research field. Lastly, the current outstanding challenges and the feasibility to use a stand-alone biomarker in the joint diagnostic strategy are discussed.

Cell-free messenger RNA (cf-mRNA) and long non-coding RNA (cf-lncRNA) are becoming increasingly important in liquid biopsy by providing biomarkers for disease prediction, diagnosis and prognosis, but the simultaneous characterization of coding and non-coding RNAs in human biofluids remains challenging.

Here, we developed polyadenylation ligation-mediated sequencing (PALM-Seq), an RNA sequencing strategy employing treatment of RNA with T4 polynucleotide kinase to generate cell-free RNA (cfRNA) fragments with 5' phosphate and 3' hydroxyl and RNase H to deplete abundant RNAs, achieving simultaneous quantification and characterization of cfRNAs.

Using PALM-Seq, we successfully identified well-known differentially abundant mRNA, lncRNA and microRNA in the blood plasma of pregnant women. We further characterized cfRNAs in blood plasma, saliva, urine, seminal plasma and amniotic fluid and found that the detected numbers of different RNA biotypes varied with body fluids. The profiles of cf-mRNA reflected the function of originated tissues, and immune cells significantly contributed RNA to blood plasma and saliva. Short fragments (<50 nt) of mRNA and lncRNA were major in biofluids, whereas seminal plasma and amniotic fluid tended to retain long RNA. Body fluids showed distinct preferences of pyrimidine at the 3' end and adenine at the 5' end of cf-mRNA and cf-lncRNA, which were correlated with the proportions of short fragments.

Together, PALM-Seq enables a simultaneous characterization of cf-mRNA and cf-lncRNA, contributing to elucidating the biology and promoting the application of cfRNAs.

Chen et al. reveal an increase of phosphoglycerate dehydrogenase (PHGDH) mRNA and protein levels in two mouse models and four human cohorts in Alzheimer's disease brains compared to age- and sex-matched control brains. The increase of PHGDH expression in human brain correlates with symptomatic development and disease pathology.

Long noncoding RNAs (lncRNAs) are promising candidates as biomarkers of inflammation and cancer. LncRNAs have several properties that make them well-suited as molecular markers of disease: (1) many lncRNAs are expressed in a tissue-specific manner, (2) distinct lncRNAs are upregulated based on different inflammatory or oncogenic stimuli, (3) lncRNAs released from cells are packaged and protected in extracellular vesicles, and (4) circulating lncRNAs in the blood are detectable using various RNA sequencing approaches. Here we focus on the potential for lncRNA biomarkers to detect inflammation and cancer, highlighting key biological, technological, and analytical considerations that will help advance the development of lncRNA-based liquid biopsies.

Mental illness remains the greatest chronic health burden globally with few in-roads having been made despite significant advances in genomic knowledge in recent decades. The field of psychiatry is constantly challenged to bring new approaches and tools to address and treat the needs of vulnerable individuals and subpopulations, and that has to be supported by a continuous growth in knowledge. The majority of neuropsychiatric symptoms reflect complex gene-environment interactions, with epigenetics bridging the gap between genetic susceptibility and environmental stressors that trigger disease onset and drive the advancement of symptoms. It has more recently been demonstrated in preclinical models that epigenetics underpins the transgenerational inheritance of stress-related behavioural phenotypes in both paternal and maternal lineages, providing further supporting evidence for heritability in humans. However, unbiased prospective studies of this nature are practically impossible to conduct in humans so preclinical models remain our best option for researching the molecular pathophysiologies underlying many neuropsychiatric conditions. While rodents will remain the dominant model system for preclinical studies (especially for addressing complex behavioural phenotypes), there is scope to expand current research of the molecular and epigenetic pathologies by using invertebrate models. Here, we will discuss the utility and advantages of two alternative model organisms-Caenorhabditis elegans and Drosophila melanogaster-and summarise the compelling insights of the epigenetic regulation of transgenerational inheritance that are potentially relevant to human psychiatry.

A combination of different risk factors, such as genetic, environmental and psychological factors, together with immune system, stress response, brain neuroplasticity and the regulation of neurotransmitters, is thought to lead to the development of major depressive disorder (MDD). A growing number of studies have tried to investigate the underlying mechanisms of MDD by analysing the expression levels of genes involved in such biological processes. These studies have shown that MDD is not just a brain disorder, but also a body disorder, and this is mainly due to the interplay between the periphery and the Central Nervous System (CNS). To this purpose, most of the studies conducted so far have mainly dedicated to the analysis of the gene expression levels using postmortem brain tissue as well as peripheral blood samples of MDD patients. In this paper, we reviewed the current literature on candidate gene expression alterations and the few existing transcriptomics studies in MDD focusing on inflammation, neuroplasticity, neurotransmitters and stress-related genes. Moreover, we focused our attention on studies, which have investigated mRNA levels as biomarkers to predict therapy outcomes. This is important as many patients do not respond to antidepressant medication or could experience adverse side effects, leading to the interruption of treatment. Unfortunately, the right choice of antidepressant for each individual still remains largely a matter of taking an educated guess.

The accumulation and propagation of hyperphosphorylated tau (p-Tau) is a neuropathological hallmark occurring with neurodegeneration of Alzheimer's disease (AD). Extracellular vesicles, exosomes, have been shown to initiate tau propagation in the brain. Notably, exosomes from human-induced pluripotent stem cell (iPSC) neurons expressing the AD familial A246E mutant form of presenilin 1 (mPS1) are capable of inducing tau deposits in the mouse brain after in vivo injection. To gain insights into the exosome proteome cargo that participates in propagating tau pathology, this study conducted proteomic analysis of exosomes produced by human iPSC neurons expressing A246E mPS1. Significantly, mPS1 altered the profile of exosome cargo proteins to result in (1) proteins present only in mPS1 exosomes and not in controls, (2) the absence of proteins in the mPS1 exosomes which were present only in controls, and (3) shared proteins which were upregulated or downregulated in the mPS1 exosomes compared to controls. These results show that mPS1 dysregulates the proteome cargo of exosomes to result in the acquisition of proteins involved in the extracellular matrix and protease functions, deletion of proteins involved in RNA and protein translation systems along with proteasome and related functions, combined with the upregulation and downregulation of shared proteins, including the upregulation of amyloid precursor protein. Notably, mPS1 neuron-derived exosomes displayed altered profiles of protein phosphatases and kinases involved in regulating the status of p-tau. The dysregulation of exosome cargo proteins by mPS1 may be associated with the ability of mPS1 neuron-derived exosomes to propagate tau pathology.

It has become increasingly clear that retrotransposons (RTEs) are more widely expressed in somatic tissues than previously appreciated. RTE expression has been implicated in a myriad of biological processes ranging from normal development and aging, to age related diseases such as cancer and neurodegeneration. Long Terminal Repeat (LTR)-RTEs are evolutionary ancestors to, and share many features with, exogenous retroviruses. In fact, many organisms contain endogenous retroviruses (ERVs) derived from exogenous retroviruses that integrated into the germ line. These ERVs are inherited in Mendelian fashion like RTEs, and some retain the ability to transmit between cells like viruses, while others develop the ability to act as RTEs. The process of evolutionary transition between LTR-RTE and retroviruses is thought to involve multiple steps by which the element loses or gains the ability to transmit copies between cells versus the ability to replicate intracellularly. But, typically, these two modes of transmission are incompatible because they require assembly in different sub-cellular compartments. Like murine IAP/IAP-E elements, the gypsy family of retroelements in arthropods appear to sit along this evolutionary transition. Indeed, there is some evidence that gypsy may exhibit retroviral properties. Given that gypsy elements have been found to actively mobilize in neurons and glial cells during normal aging and in models of neurodegeneration, this raises the question of whether gypsy replication in somatic cells occurs via intracellular retrotransposition, intercellular viral spread, or some combination of the two. These modes of replication in somatic tissues would have quite different biological implications. Here, we demonstrate that Drosophila gypsy is capable of both cell-associated and cell-free viral transmission between cultured S2 cells of somatic origin. Further, we demonstrate that the ability of gypsy to move between cells is dependent upon a functional copy of its viral envelope protein. This argues that the gypsy element has transitioned from an RTE into a functional endogenous retrovirus with the acquisition of its envelope gene. On the other hand, we also find that intracellular retrotransposition of the same genomic copy of gypsy can occur in the absence of the Env protein. Thus, gypsy exhibits both intracellular retrotransposition and intercellular viral transmission as modes of replicating its genome.

This review highlights current developments, challenges, and future directions for the use of invasive and noninvasive biosample-based small biosensors for early diagnosis of Alzheimer's disease (AD) with biomarkers to incite a conceptual idea from a broad number of readers in this field. We provide the most promising concept about biosensors on the basis of detection scale (from femto to micro) using invasive and noninvasive biosamples such as cerebrospinal fluid (CSF), blood, urine, sweat, and tear. It also summarizes sensor types and detailed analyzing techniques for ultrasensitive detection of multiple target biomarkers (i.e., amyloid beta (Aβ) peptide, tau protein, Acetylcholine (Ach), microRNA137, etc.) of AD in terms of detection ranges and limit of detections (LODs). As the most significant disadvantage of CSF and blood-based detection of AD is associated with the invasiveness of sample collection which limits future strategy with home-based early screening of AD, we extensively reviewed the future trend of new noninvasive detection techniques (such as optical screening and bio-imaging process). To overcome the limitation of non-invasive biosamples with low concentrations of AD biomarkers, current efforts to enhance the sensitivity of biosensors and discover new types of biomarkers using non-invasive body fluids are presented. We also introduced future trends facing an infection point in early diagnosis of AD with simultaneous emergence of addressable innovative technologies.

Alzheimer's disease (AD) is the most common cause of dementia, yet there is no cure or diagnostics available prior to the onset of clinical symptoms. Extracellular vesicles (EVs) are lipid bilayer-delimited particles that are released from almost all types of cell. Genome-wide association studies have linked multiple AD genetic risk factors to microglia-specific pathways. It is plausible that microglia-derived EVs may play a role in the progression of AD by contributing to the dissemination of insoluble pathogenic proteins, such as tau and Aβ. Despite the potential utility of EVs as a diagnostic tool, our knowledge of human brain EV subpopulations is limited. Here we present a method for isolating microglial CD11b-positive small EVs from cryopreserved human brain tissue, as well as an integrated multiomics analysis of microglial EVs enriched from the parietal cortex of four late-stage AD (Braak V-VI) and three age-matched normal/low pathology (NL) cases. This integrated analysis revealed 1,000 proteins, 594 lipids, and 105 miRNAs using shotgun proteomics, targeted lipidomics, and NanoString nCounter technology, respectively. The results showed a significant reduction in the abundance of homeostatic microglia markers P2RY12 and TMEM119, and increased levels of disease-associated microglia markers FTH1 and TREM2, in CD11b-positive EVs from AD brain compared to NL cases. Tau abundance was significantly higher in AD brain-derived microglial EVs. These changes were accompanied by the upregulation of synaptic and neuron-specific proteins in the AD group. Levels of free cholesterol were elevated in microglial EVs from the AD brain. Lipidomic analysis also revealed a proinflammatory lipid profile, endolysosomal dysfunction, and a significant AD-associated decrease in levels of docosahexaenoic acid (DHA)-containing polyunsaturated lipids, suggesting a potential defect in acyl-chain remodeling. Additionally, four miRNAs associated with immune and cellular senescence signaling pathways were significantly upregulated in the AD group. Our data suggest that loss of the homeostatic microglia signature in late AD stages may be accompanied by endolysosomal impairment and the release of undigested neuronal and myelin debris, including tau, through extracellular vesicles. We suggest that the analysis of microglia-derived EVs has merit for identifying novel EV-associated biomarkers and providing a framework for future larger-scale multiomics studies on patient-derived cell-type-specific EVs.

Among aging-induced impairments, those affecting cognitive functions certainly represent one the most major challenge to face to improve elderly quality of life. In last decades, our knowledge on changes in the morphology and function of neuronal networks associated with normal and pathological brain aging has rapidly progressed, initiating the development of different pharmacological and behavioural strategies to alleviate cognitive aging. In particular, experimental evidences have accumulated indicating that the communication between neurons and its plasticity gradually weakens with aging. Because of its pivotal role for brain functional plasticity, the N-Methyl‑d-Aspartate receptor subtype of glutamate receptors (NMDAr) has gathered much of the experimental interest. NMDAr activation is regulated by many mechanisms. Among is the mandatory binding of a co-agonist, such as the amino acid d-serine, in order to activate NMDAr. This mini-review presents the most recent information indicating how d-serine could contribute to mechanisms of physiological cognitive aging and also considers the divergent views relative of the role of the NMDAr co-agonist in Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia, affecting the central nervous system (CNS) through the accumulation of intraneuronal neurofibrillary tau tangles (NFTs) and β-amyloid plaques. By the time AD is clinically diagnosed, neuronal loss has already occurred in many brain and retinal regions. Therefore, the availability of early and reliable diagnosis markers of the disease would allow its detection and taking preventive measures to avoid neuronal loss. Current diagnostic tools in the brain, such as magnetic resonance imaging (MRI), positron emission tomography (PET) imaging, and cerebrospinal fluid (CSF) biomarkers (Aβ and tau) detection are invasive and expensive. Brain-secreted extracellular vesicles (BEVs) isolated from peripheral blood have emerged as novel strategies in the study of AD, with enormous potential as a diagnostic evaluation of therapeutics and treatment tools. In addition; similar mechanisms of neurodegeneration have been demonstrated in the brain and the eyes of AD patients. Since the eyes are more accessible than the brain, several eye tests that detect cellular and vascular changes in the retina have also been proposed as potential screening biomarkers. The aim of this study is to summarize and discuss several potential markers in the brain, eye, blood, and other accessible biofluids like saliva and urine, and correlate them with earlier diagnosis and prognosis to identify individuals with mild symptoms prior to dementia.

The Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimer's disease patients and is included in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We divided 741 ADNI participants with blood microarray data into three groups based on their most recent CDR assessment: cognitive normal (CDR = 0), mild cognitive impairment (CDR = 0.5), and probable Alzheimer's disease (CDR ≥ 1.0). We then used machine learning to predict cognitive status using only blood RNA levels. Only one probe for chloride intracellular channel 1 (CLIC1) was significant after correction. However, by combining individually nonsignificant probes with p-values less than 0.1, we averaged 87.87% (s = 1.02) predictive accuracy for classifying the three groups, compared to a 55.46% baseline for this study due to unequal group sizes. The best model had an overall precision of 0.902, recall of 0.895, and a receiver operating characteristic (ROC) curve area of 0.904. Although we identified one significant probe in CLIC1, CLIC1 levels alone were not sufficient to predict dementia status and cannot be used alone in a clinical setting. Additional analyses combining individually suggestive, but nonsignificant, blood RNA levels were significantly predictive and may improve diagnostic accuracy for Alzheimer's disease. Therefore, we propose that patient features that do not individually predict cognitive status might still contribute to overall cognitive decline through interactions that can be elucidated through machine learning.