Hexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified hexokinase domain containing 1 (HKDC1) as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis.

We found that, compared to HK1 and HK2, the other 2 commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from 2 liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in HCC and cholangiocarcinoma patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models. Molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3β to stabilize β-catenin, leading to enhanced stemness of HCC cells.

Overall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

Gestational diabetes mellitus (GDM) is common in Japanese women, posing serious risks to mothers and offspring. This study investigated the influence of maternal genotypes on the risk of GDM and examined how these genotypes modify the effects of psychological and dietary factors during pregnancy. We analyzed data from 20,399 women in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort. Utilizing two customized SNP arrays for the Japanese population (Affymetrix Axiom Japonica Array v2 and NEO), we performed a meta-analysis to combine the datasets. Gene-environment interactions were assessed by modeling interaction terms between genome-wide significant single nucleotide polymorphisms (SNPs) and psychological and dietary factors. Our analysis identified two SNP variants, rs7643571 (p = 9.14 × 10-9) and rs140353742 (p = 1.24 × 10-8), located in an intron of the MDFIC2 gene, as being associated with an increased risk of GDM. Additionally, although there were suggestive patterns for interactions between these SNPs and both dietary factors (e.g., carbohydrate and fruit intake) and psychological distress, none of the interaction terms remained significant after Bonferroni correction (p < 0.05/8). While nominal significance was observed in some models (e.g., psychological distress, p = 0.04), the data did not provide robust evidence of effect modification on GDM risk once adjusted for multiple comparisons. These findings reveal novel genetic associations with GDM in Japanese women and highlight the importance of gene-environment interactions in its etiology. Given that previous genome-wide association studies (GWAS) on GDM have primarily focused on Western populations, our study provides new insights by examining an Asian population using a population-specific array.

The global prevalence of Metabolic Dysfunction-Associated Steatohepatitis (MASH) has been rising sharply, closely mirroring the increasing rates of obesity and metabolic syndrome. MASH exhibits a strong sexual dimorphism where females are affected with more severe forms after menopause. Hexokinase domain-containing protein 1 (HKDC1) has recently been recognized for its role in liver diseases, where its expression is minimal under normal conditions but significantly increases in response to metabolic stressors like obesity and liver injury. This selective upregulation suggests HKDC1's potential specialization in hepatic glucose and lipid dysregulation, linking it closely to the progression of MASH. This study aims to clarify the role of HKDC1 in Western diet-induced MASH in female mice by examining its impact on hepatic glucose and lipid metabolism, offering insights into its potential as a therapeutic target and addressing the need for sex-specific research in liver disease. This study reveals that HKDC1 expression is elevated in obese women with MASH and correlates with liver pathology. In a mouse model, liver-specific HKDC1 knockout (HKDC1LKO) protected against Western diet-induced obesity, glucose intolerance, and MASH features, including steatosis, inflammation, and fibrosis. Transcriptomic analysis showed that HKDC1 deletion reduced pro-inflammatory and pro-fibrotic gene expression, while gut microbiome analysis indicated a shift toward MASH-protective bacteria. These findings suggest that HKDC1 may exacerbate MASH progression through its role in metabolic and inflammatory pathways, making it a potential therapeutic target.

The global prevalence of Metabolic dysfunction-associated steatohepatitis (MASH) has been rising sharply, closely mirroring the increasing rates of obesity and metabolic syndrome. MASH exhibits a strong sexual dimorphism where females are affected with more severe forms after menopause. Hexokinase domain-containing protein 1 (HKDC1) has recently been recognized for its role in liver diseases, where its expression is minimal under normal conditions but significantly increases in response to metabolic stressors like obesity and liver injury. This selective upregulation suggests HKDC1s potential specialization in hepatic glucose and lipid dysregulation, linking it closely to the progression of MASLD and MASH. This study aims to clarify the role of HKDC1 in Western diet-induced MASH in female mice by examining its impact on hepatic glucose and lipid metabolism, offering insights into its potential as a therapeutic target and addressing the need for sex-specific research in liver disease. This study reveals that HKDC1 expression is elevated in obese women with MASH and correlates with liver pathology. In a mouse model, liver-specific HKDC1 knockout (HKDC1LKO) protected against Western diet-induced obesity, glucose intolerance, and MASH features, including steatosis, inflammation, and fibrosis. Transcriptomic analysis showed that HKDC1 deletion reduced pro-inflammatory and pro-fibrotic gene expression, while gut microbiome analysis indicated a shift toward MASH-protective bacteria. These findings suggest that HKDC1 may exacerbate MASH progression through its role in metabolic and inflammatory pathways, making it a potential therapeutic target.

This study examined the association of gravida C-peptide with progeny islet function and insulin sensitivity in the Hyperglycemia and Adverse Pregnancy Outcome Follow-up Study (HAPO FUS).

Pregnancy 3rd trimester oral glucose tolerance test (OGTT), cord blood, and offspring OGTT glucose, C-peptide and insulin at age 10-14 years were analyzed for 4,121 mother-child dyads. Gravida fasting and 1-hour C-peptide concentration correlations with cord blood and childhood C-peptide, insulin, insulinogenic index and insulin sensitivity, and insulin resistance [HOMA-IR]), were assessed by multiple linear regression. Maternal covariates included age, gestational age, BMI and glucose at OGTT; child covariates included age, sex, pubertal stage, BMI z score and glucose.

Gravida fasting and 1-hour OGTT C-peptide was positively correlated with cord blood C-peptide, offspring OGTT C-peptide and insulin concentrations at fasting, 30 min, 1-hour and 2-hour at 10-14 years of age. Maternal fasting and 1-hour C-peptide concentrations were positively correlated with the insulinogenic index and HOMA-IR but inversely correlated with insulin sensitivity. Maternal C-peptide explained more variance than maternal glucose concentrations (3.0-17.9 % vs 0.2-3.5 %).

The correlation between gravida and offspring C-peptide suggests that without crossing the placenta, insulin may influence the offspring pancreatic beta-cell development and insulin sensitivity.

There is increasing need for effective incorporation of high-dimensional genetics data from individuals with varied ancestry in genome-wide association (GWAS) analyses. Classically, multi-ancestry GWAS analyses are performed using statistical meta-analysis to combine results conducted within homogeneous ancestry groups. The emergence of cosmopolitan reference panels makes collective preprocessing of GWAS data possible, but impact on downstream GWAS results in a mega-analysis framework merits investigation. We utilized GWAS data from the multi-national Hyperglycemia and Adverse Pregnancy Outcome Study to investigate differences in GWAS findings using a homogeneous ancestry meta-analysis versus a heterogeneous ancestry mega-analysis pipeline. Maternal fasting and 1-hr glucose and metabolomics measured during a 2-hr 75-gram oral glucose tolerance test during early third trimester pregnancy were evaluated as phenotypes.

For the homogeneous ancestry meta-analysis pipeline, variant data were prepared by identifying sets of individuals with similar ancestry and imputing to ancestry-specific reference panels. GWAS was conducted within each ancestry group and results were combined using random-effects meta-analysis. For the heterogeneous ancestry mega-analysis pipeline, data for all individuals were collectively imputed to the Trans-Omics for Precision Medicine (TOPMed) cosmopolitan reference panel, and GWAS was conducted using a unified mega-analysis. The meta-analysis pipeline identified genome-wide significant associations for 15 variants in a region close to GCK on chromosome 7 with maternal fasting glucose and no significant findings for 1-hr glucose. Associations in this same region were identified using the mega-analysis pipeline, along with a well-documented association at MTNR1B on chromosome 11 with both fasting and 1-hr maternal glucose. For metabolomics analyses, the number of significant findings in the heterogeneous ancestry mega-analysis far exceeded those from the homogeneous ancestry meta-analysis and confirmed many previously documented associations, but genomic inflation factors were much more variable.

For multi-ancestry GWAS, heterogeneous ancestry mega-analysis generates a rich set of variants for analysis using a cosmopolitan reference panel and results in vastly more significant, biologically credible and previously documented associations than a homogeneous ancestry meta-analysis approach. Genomic inflation factors do indicate that findings from the mega-analysis pipeline may merit cautious interpretation and further follow-up.

Pregnancy is accompanied by maternal metabolic adaptations to ensure fetal growth and development, including insulin resistance, which occurs primarily during the second and third trimesters of pregnancy, and a decrease in fasting blood sugar levels over the course of pregnancy. Glucose-related traits are regulated by genetic and environmental factors and modulated by physiological variations throughout the life course. We addressed the hypothesis that there are both overlaps and differences between genetic variants associated with glycaemia-related traits during and outside of pregnancy.

Genome-wide SNP data were used to identify genetic variations associated with glycaemia-related traits measured during an OGTT performed at ~28 weeks' gestation in 8067 participants in the Hyperglycaemia and Adverse Pregnancy Outcome (HAPO) Study. Associations outside of pregnancy were determined in 3977 individuals who also participated in the HAPO Follow-Up Study at 11-14 years postpartum. A Bayesian classification algorithm was used to determine whether SNPs associated with fasting and 2 h glucose and fasting C-peptide during pregnancy had a pregnancy-predominant effect vs a similar effect during pregnancy and postpartum.

SNPs in six loci (GCKR, G6PC2, GCK, PPP1R3B, PCSK1 and MTNR1B) were significantly associated with fasting glucose during pregnancy, while SNPs in CDKAL1 and MTNR1B were associated with 1 h glucose and SNPs in MTNR1B and HKDC1 were associated with 2 h glucose. Variants in CDKAL1 and MTNR1B were associated with insulin secretion during pregnancy. Variants in multiple loci were associated with fasting C-peptide during pregnancy, including GCKR, IQSEC1, PPP1R3B, IGF1 and BACE2. GCKR and BACE2 were associated with 1 h C-peptide and GCKR, IQSEC1 and BACE2 with insulin sensitivity during pregnancy. The associations of MTNR1B with 2 h glucose, BACE2 with fasting and 1 h C-peptide and insulin sensitivity, and IQSEC1 with fasting C-peptide and insulin sensitivity that we identified during pregnancy have not been previously reported in non-pregnancy cohorts. The Bayesian classification algorithm demonstrated that the magnitude of effect of the lead SNP was greater during pregnancy compared with 11-14 years postpartum in PCSK1 and PPP1R3B with fasting glucose, in three loci, including MTNR1B, with 2 h glucose, and in six loci, including IGF1, with fasting C-peptide.

Our findings support the hypothesis that there are both overlaps and differences between the genetic architecture of glycaemia-related traits during and outside of pregnancy. Genetic variants at several loci, including PCSK1, PPP1R3B, MTNR1B and IGF1, appear to influence glycaemic regulation in a unique fashion during pregnancy. Future studies in larger cohorts will be needed to replicate the present findings, fully characterise the genetics of maternal glycaemia during pregnancy and determine similarities to and differences from the non-gravid state.

Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.

Background/Objectives: During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. Methods: In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. Results/Conclusions: Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.

Gestational diabetes mellitus (GDM) is a common condition observed globally, and previous studies have suggested a link between GDM and insomnia. The objective of this study was to elucidate the causative relationship between insomnia and GDM, and to investigate the influence of factors related to insomnia on GDM.

We performed bidirectional Mendelian randomization (MR) analyses using single nucleotide polymorphisms (SNPs) as genetic instruments for exposure and mediators, thereby minimizing bias due to confounding and reverse causation. The Cochran Q test was utilized for heterogeneity analysis, MR-Egger regression for pleiotropy assessment, and the leave-one-out method for evaluating the robustness of the results. Additionally, we determined the causal relationships between GDM and other factors such as coffee consumption, alcohol intake, and household income.

Insomnia was positively associated with GDM, as indicated by 39 SNPs (OR = 1.27, 95 % CI 1.12-1.439, P-value = 0.008). Conversely, the MR analysis did not reveal any causal relationship between GDM and insomnia (OR = 1.032, 95 % CI 0.994-1.071, P-value = 0.99). Additionally, no causal relationship was observed between coffee consumption, alcohol intake, household income, and GDM (all P-values >0.05).

Our study indicates that insomnia elevates the risk of GDM, thereby establishing a causal link with GDM, independent of coffee consumption, alcohol intake, and household income.

Gestational diabetes is the most common medical complication in pregnancy. Historically, gestational diabetes was considered a pregnancy complication involving treatment of rising glycaemia late in the second trimester. However, recent evidence challenges this view. Pre-pregnancy and pregnancy-specific factors influence gestational glycaemia, with open questions regarding roles of non-glycaemic factors in the aetiology and consequences of gestational diabetes. Varying patterns of insulin secretion and resistance in early and late pregnancy underlie a heterogeneity of gestational diabetes in the timing and pathophysiological subtypes with clinical implications: early gestational diabetes and insulin resistant gestational diabetes subtypes are associated with a higher risk of pregnancy complications. Metabolic perturbations of early gestational diabetes can affect early placental development, affecting maternal metabolism and fetal development. Fetal hyperinsulinaemia can affect the development of multiple fetal tissues, with short-term and long-term consequences. Pregnancy complications are prevented by managing glycaemia in early and late pregnancy in some, but not all women with gestational diabetes. A better understanding of the pathophysiology and heterogeneity of gestational diabetes will help to develop novel management approaches with focus on improved prevention of maternal and offspring short-term and long-term complications, from pre-conception, throughout pregnancy, and beyond.

Interactions between multiple genes or cis-regulatory elements (CREs) underlie a wide range of biological processes in both health and disease. High-throughput screens using dCas9 fused to epigenome editing domains have allowed researchers to assess the impact of activation or repression of both coding and non-coding genomic regions on a phenotype of interest, but assessment of genetic interactions between those elements has been limited to pairs. Here, we combine a hyper-efficient version of Lachnospiraceae bacterium dCas12a (dHyperLbCas12a) with RNA Polymerase II expression of long CRISPR RNA (crRNA) arrays to enable efficient highly-multiplexed epigenome editing. We demonstrate that this system is compatible with several activation and repression domains, including the P300 histone acetyltransferase domain and SIN3A interacting domain (SID). We also show that the dCas12a platform can perform simultaneous activation and repression using a single crRNA array via co-expression of multiple dCas12a orthologues. Lastly, demonstrate that the dCas12a system is highly effective for high-throughput screens. We use dHyperLbCas12a-KRAB and a ~19,000-member barcoded library of crRNA arrays containing six crRNAs each to dissect the independent and combinatorial contributions of CREs to the dose-dependent control of gene expression at a glucocorticoid-responsive locus. The tools and methods introduced here create new possibilities for highly multiplexed control of gene expression in a wide variety of biological systems.

Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes.

This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM).

Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM.

This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

The pathophysiology of gestational diabetes mellitus (GDM) comprises clinical and genetic factors. In fact, GDM is associated with several single nucleotide polymorphisms (SNPs). This study aimed to build a prediction model of GDM combining clinical and genetic risk factors. A total of 1588 pregnant women from the San Carlos Cohort participated in the present study, including 1069 (67.3%) Caucasian (CAU) and 519 (32.7%) Latin American (LAT) individuals, and 255 (16.1%) had GDM. The incidence of GDM was similar in both groups (16.1% CAU and 16.0% LAT). Genotyping was performed via IPLEX Mass ARRAY PCR, selecting 110 SNPs based on literature references. SNPs showing the strongest likelihood of developing GDM were rs10830963, rs7651090, and rs1371614 in CAU and rs1387153 and rs9368222 in LAT. Clinical variables, including age, pre-pregnancy body mass index, and fasting plasma glucose (FPG) at 12 gestational weeks, predicted the risk of GDM (AUC 0.648, 95% CI 0.601-0.695 in CAU; AUC 0.688, 95% CI 0.628-9.748 in LAT), and adding SNPs modestly improved prediction (AUC 0.722, 95%CI 0.680-0.764 in CAU; AUC 0.769, 95% CI 0.711-0.826 in LAT). In conclusion, adding genetic variants enhanced the prediction model of GDM risk in CAU and LAT pregnant women.

Polycystic ovary syndrome (PCOS) is an endocrine disease, and its pathogenesis and treatment are still unclear. Hexokinase domain component 1 (HKDC1) participates in regulating mitochondrial function and glycolysis. However, its role in PCOS development remains unrevealed. Here, female C57BL/6 mice were intraperitoneally injected with dehydroepiandrosterone (DHEA; 60 mg/kg body weight) to establish an in vivo model of PCOS. In vitro, KGN cells, a human ovarian granular cell line, were used to explore the potential mechanisms. DHEA-treated mice exhibited a disrupted estrus cycle, abnormal hormone levels, and insulin resistance. Dysfunction in mitochondria and glycolysis is the main reason for PCOS-related growth inhibition of ovarian granular cells. Here, we found that the structure of mitochondria was impaired, less ATP was generated and more mitochondrial Reactive Oxygen Species were produced in HKDC1-silenced KGN cells. Moreover, HKDC1 knockdown inhibited glucose consumption and decreased the production of glucose-6-phosphate and lactic acid. Conclusively, HKDC1 protects ovarian granulocyte cells from DHEA-related damage at least partly by preserving mitochondrial function and maintaining glycolysis.

Background: Understanding the molecular mechanisms of pancreatic adenocarcinoma (PAAD) development is vital for treating this disease, as the current prognosis and treatment options are highly discouraging. Objective: This study aimed to examine the involvement of Hexokinase Domain Containing 1 (HKDC1) in the progression of PAAD. Methods: The study utilized bioinformatics techniques to evaluate the relationship between the expression of HKDC1 and clinical characteristics. In vitro experiments were conducted to investigate the molecular mechanisms and biological functions of HKDC1 in PAAD. Results: The findings of this research indicate that the expression of HKDC1 was increased in various types of human cancers, and a significant correlation was observed between elevated HKDC1 expression in PAAD and unfavorable prognosis. According to the findings from univariate and multivariate Cox regression analyses, HKDC1 could potentially serve as a standalone prognostic indicator for individuals diagnosed with PAAD. After performing calculations, we determined that the HKDC1 high-expression group exhibited lower immunologic score and higher ESTIMATE score, indicating a difference in immune infiltration score. In order to validate the expression of HKDC1 in PAAD cell lines, we analyzed the PAAD cell lines through qPCR and protein blotting. The expression of HKDC1 in human PAAD tissues was also detected by western blotting. Additionally, we explored the involvement of HKDC1 in PAAD by conducting experiments such as colony formation, 5-ethynyl-2'-deoxyuridine (EdU), transwell, and wound healing assays. In our study, we discovered that disruption of HKDC1 expression in PAAD cell types resulted in a decrease in cell growth rate and inhibited cell movement and invasion. Conclusion: To conclude, our findings indicate that HKDC1 has a significant impact on the tumor microenvironment (TME) of PAAD and could potentially be a promising target for PAAD treatment, offering fresh perspectives on the management of PAAD.

Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.

Mitochondrial and lysosomal functions are intimately linked and are critical for cellular homeostasis, as evidenced by the fact that cellular senescence, aging, and multiple prominent diseases are associated with concomitant dysfunction of both organelles. However, it is not well understood how the two important organelles are regulated. Transcription factor EB (TFEB) is the master regulator of lysosomal function and is also implicated in regulating mitochondrial function; however, the mechanism underlying the maintenance of both organelles remains to be fully elucidated. Here, by comprehensive transcriptome analysis and subsequent chromatin immunoprecipitation-qPCR, we identified hexokinase domain containing 1 (HKDC1), which is known to function in the glycolysis pathway as a direct TFEB target. Moreover, HKDC1 was upregulated in both mitochondrial and lysosomal stress in a TFEB-dependent manner, and its function was critical for the maintenance of both organelles under stress conditions. Mechanistically, the TFEB-HKDC1 axis was essential for PINK1 (PTEN-induced kinase 1)/Parkin-dependent mitophagy via its initial step, PINK1 stabilization. In addition, the functions of HKDC1 and voltage-dependent anion channels, with which HKDC1 interacts, were essential for the clearance of damaged lysosomes and maintaining mitochondria-lysosome contact. Interestingly, HKDC1 regulated mitophagy and lysosomal repair independently of its prospective function in glycolysis. Furthermore, loss function of HKDC1 accelerated DNA damage-induced cellular senescence with the accumulation of hyperfused mitochondria and damaged lysosomes. Our results show that HKDC1, a factor downstream of TFEB, maintains both mitochondrial and lysosomal homeostasis, which is critical to prevent cellular senescence.

Gestational diabetes mellitus (GDM) affects the metabolism of both the mother and fetus during and after pregnancy. Genetic factors are important in the pathogenesis of GDM, and associations vary by ethnicity. However, related studies about the relationship between the susceptibility genes and glucose traits remain limited in China. This study aimed to identify genes associated with GDM susceptibility in Chinese Han women and validate those findings using clinical data during pregnancy and postpartum period.

A genome-wide association study (GWAS) of 398 Chinese Han women (199 each with and without GDM) was conducted and associations between single nucleotide polymorphisms (SNPs) and glucose metabolism were identified by searching public databases. Relationships between filtered differential SNPs and glucose metabolism were verified using clinical data during pregnancy. The GDM group were followed up postpartum to evaluate the progression of glucose metabolism.

We identified five novel SNPs with genome-wide significant associations with GDM: rs62069863 in TRPV3 gene and rs2232016 in PRMT6 gene were positive correlated with 1 h plasma glucose (1hPG) and 2 h plasma glucose (2hPG), rs1112718 in HHEX/EXOC6 gene and rs10460009 in LPIN2 gene were positive associated with fasting plasma glucose, 1hPG and 2hPG, rs927316 in GLIS3 gene was negative correlated with 2hPG. Of the 166 GDM women followed up postpartum, rs62069863 in TRPV3 gene was positively associated with fasting insulin, homoeostasis model assessment of insulin resistance.

The variants of rs62069863 in TRPV3 gene, rs2232016 in PRMT6 gene, rs1112718 in HHEX/EXOC6 gene, rs927316 in GLIS3 gene, and rs10460009 in LPIN2 gene were newly-identified susceptibility loci for GDM in the Chinese Han population. TRPV3 was associated with worse insulin resistance postpartum.

This study was registered in the Chinese Clinical Trial Registry.

ChiCTR2100043762. Date of first registration: 28/02/2021.

During the perinatal period, unique metabolic adaptations support energetic requirements for rapid growth. To gain insight into perinatal adaptations, quantitative proteomics was performed comparing the livers of Yorkshire pigs at postnatal day 7 and adult. These data revealed differences in the metabolic control of liver function including significant changes in lipid and carbohydrate metabolic pathways. Newborn livers showed an enrichment of proteins in lipid catabolism and gluconeogenesis concomitant with elevated liver carnitine and acylcarnitines levels. Sugar kinases were some of the most dramatically differentially enriched proteins compared with neonatal and adult pigs including galactokinase 1 (Galk1), ketohexokinase (KHK), hexokinase 1 (HK1), and hexokinase 4 (GCK). Interestingly, hexokinase domain containing 1 (HKDC1), a newly identified fifth hexokinase associated with glucose disturbances in pregnant women, was highly enriched in the liver during the prenatal and perinatal periods and continuously declined throughout postnatal development in pigs and mice. These changes were confirmed via Western blot and mRNA expression. These data provide new insights into the developmental and metabolic adaptations in the liver during the transition from the perinatal period to adulthood in multiple mammalian species.

A primary role of the liver is to regulate whole body glucose homeostasis. Glucokinase (GCK) is the main hexokinase (HK) expressed in hepatocytes and functions to phosphorylate the glucose that enters via GLUT transporters to become glucose-6-phosphate (G6P), which subsequently commits glucose to enter downstream anabolic and catabolic pathways. In the recent years, hexokinase domain-containing-1 (HKDC1), a novel 5th HK, has been characterized by our group and others. Its expression profile varies but has been identified to have low basal expression in normal liver but increases during states of stress including pregnancy, nonalcoholic fatty liver disease (NAFLD), and liver cancer. Here, we have developed a stable overexpression model of hepatic HKDC1 in mice to examine its effect on metabolic regulation. We found that HKDC1 overexpression, over time, causes impaired glucose homeostasis in male mice and shifts glucose metabolism towards anabolic pathways with an increase in nucleotide synthesis. Furthermore, we observed these mice to have larger liver sizes due to greater hepatocyte proliferative potential and cell size, which in part, is mediated via yes-associated protein (YAP) signaling.

Hexokinases (HKs) convert hexose sugars to hexose-6-phosphate, thus trapping them inside cells to meet the synthetic and energetic demands. HKs participate in various standard and altered physiological processes, including cancer, primarily through the reprogramming of cellular metabolism. Four canonical HKs have been identified with different expression patterns across tissues. HKs 1-3 play a role in glucose utilization, whereas HK 4 (glucokinase, GCK) also acts as a glucose sensor. Recently, a novel fifth HK, hexokinase domain containing 1 (HKDC1), has been identified, which plays a role in whole-body glucose utilization and insulin sensitivity. Beyond the metabolic functions, HKDC1 is differentially expressed in many forms of human cancer. This review focuses on the role of HKs, particularly HKDC1, in metabolic reprogramming and cancer progression.

Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables.

Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort.

Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively.

We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

The in utero environment is important for newborn size at birth, which is associated with childhood adiposity. We examined associations between maternal metabolite levels and newborn birthweight, sum of skinfolds (SSF), and cord C-peptide in a multinational and multi-ancestry cohort of 2337 mother-newborn dyads. Targeted and untargeted metabolomic assays were performed on fasting and 1 h maternal serum samples collected during an oral glucose tolerance test performed at 24-32 week gestation in women participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Anthropometric measurements were obtained on newborns at birth. Following adjustment for maternal BMI and glucose, per-metabolite analyses demonstrated significant associations between maternal metabolite levels and birthweight, SSF, and cord C-peptide. In the fasting state, triglycerides were positively associated and several long-chain acylcarnitines were inversely associated with birthweight and SSF. At 1 h, additional metabolites including branched-chain amino acids, proline, and alanine were positively associated with newborn outcomes. Network analyses demonstrated distinct clusters of inter-connected metabolites significantly associated with newborn phenotypes. In conclusion, numerous maternal metabolites during pregnancy are significantly associated with newborn birthweight, SSF, and cord C-peptide independent of maternal BMI and glucose, suggesting that metabolites in addition to glucose contribute to newborn size at birth and adiposity.

Genomics can reveal essential features about the demographic evolution of a population that may not be apparent from historical elements. In recent years, there has been a significant increase in the number of studies applying genomic epidemiological approaches to understand the genetic structure and diversity of human populations in the context of demographic history and for implementing precision medicine. These efforts have traditionally been applied predominantly to populations of European origin. More recently, initiatives in the United States and Africa are including more diverse populations, establishing new horizons for research in human populations with African and/or Native ancestries. Still, even in the most recent projects, the under-representation of genomic data from Latin America and the Caribbean (LAC) is remarkable. In addition, because the region presents the most recent global miscegenation, genomics data from LAC may add relevant information to understand population admixture better. Admixture in LAC started during the colonial period, in the 15th century, with intense miscegenation between European settlers, mainly from Portugal and Spain, with local indigenous and sub-Saharan Africans brought through the slave trade. Since, there are descendants of formerly enslaved and Native American populations in the LAC territory; they are considered vulnerable populations because of their history and current living conditions. In this context, studying LAC Native American and African descendant populations is important for several reasons. First, studying human populations from different origins makes it possible to understand the diversity of the human genome better. Second, it also has an immediate application to these populations, such as empowering communities with the knowledge of their ancestral origins. Furthermore, because knowledge of the population genomic structure is an essential requirement for implementing genomic medicine and precision health practices, population genomics studies may ensure that these communities have access to genomic information for risk assessment, prevention, and the delivery of optimized treatment; thus, helping to reduce inequalities in the Western Hemisphere. Hoping to set the stage for future studies, we review different aspects related to genetic and genomic research in vulnerable populations from LAC countries.

There is growing evidence that sex and gender differences play an important role in risk and pathophysiology of type 2 diabetes (T2D). Men develop T2D earlier than women, even though there is more obesity in young women than men. This difference in T2D prevalence is attenuated after the menopause. However, not all women are equally protected against T2D before the menopause, and gestational diabetes represents an important risk factor for future T2D. Biological mechanisms underlying sex and gender differences on T2D physiopathology are not yet fully understood. Sex hormones affect behavior and biological changes, and can have implications on lifestyle; thus, both sex-specific environmental and biological risk factors interact within a complex network to explain the differences in T2D risk and physiopathology in men and women. In addition, lifetime hormone fluctuations and body changes due to reproductive factors are generally more dramatic in women than men (ovarian cycle, pregnancy, and menopause). Progress in genetic studies and rodent models have significantly advanced our understanding of the biological pathways involved in the physiopathology of T2D. However, evidence of the sex-specific effects on genetic factors involved in T2D is still limited, and this gap of knowledge is even more important when investigating sex-specific differences during the life course. In this narrative review, we will focus on the current state of knowledge on the sex-specific effects of genetic factors associated with T2D over a lifetime, as well as the biological effects of these different hormonal stages on T2D risk. We will also discuss how biological insights from rodent models complement the genetic insights into the sex-dimorphism effects on T2D. Finally, we will suggest future directions to cover the knowledge gaps.

South Asian women are at increased risk of developing gestational diabetes mellitus (GDM). Few studies have investigated the genetic contributions to GDM risk. We investigated the association of a type 2 diabetes (T2D) polygenic risk score (PRS), on its own, and with GDM risk factors, on GDM-related traits using data from two birth cohorts in which South Asian women were enrolled during pregnancy. 837 and 4372 pregnant South Asian women from the SouTh Asian BiRth CohorT (START) and Born in Bradford (BiB) cohort studies underwent a 75-g glucose tolerance test. PRSs were derived using genome-wide association study results from an independent multi-ethnic study (~18% South Asians). Associations with fasting plasma glucose (FPG); 2 hr post-load glucose (2hG); area under the curve glucose; and GDM were tested using linear and logistic regressions. The population attributable fraction (PAF) of the PRS was calculated. Every 1 SD increase in the PRS was associated with a 0.085 mmol/L increase in FPG ([95% confidence interval, CI=0.07-0.10], p=2.85×10^-20); 0.21 mmol/L increase in 2hG ([95% CI=0.16-0.26], p=5.49×10^-16); and a 45% increase in the risk of GDM ([95% CI=32-60%], p=2.27×10^-14), independent of parental history of diabetes and other GDM risk factors. PRS tertile 3 accounted for 12.5% of the population's GDM alone, and 21.7% when combined with family history. A few weak PRS and GDM risk factors interactions modulating FPG and GDM were observed. Taken together, these results show that a T2D PRS and family history of diabetes are strongly and independently associated with multiple GDM-related traits in women of South Asian descent, an effect that could be modulated by other environmental factors.

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

The effect of compound probiotics on the caecum of broilers under heat stress was assessed in this study. A total of 400 twenty-eight-day-old AA male broilers were randomly divided into 4 treatment groups, where each group had 5 replicates of 20 broilers. The 4 treatment groups were a heat stress control group (broilers receiving a normal diet) and groups HP I, HP II, and HP Ⅲ, consisting of broilers receiving 1, 5, and 10 g of compound probiotics added to each kilogram of feed, respectively. Compound probiotics (L. casei, L. acidophilus, and B. lactis at a ratio of 1:1:2) were used to formulate a compound probiotic powder, with 1 × 10¹⁰ CFU/g of effective viable bacteria. Heat stress treatment was performed at 32 ± 1°C from 9:00 to 17:00 every day from 28 d to 42 d. In d 28 to 42, compared with the HC group, the ADG of broilers in the HP II and III groups was significantly increased (P < 0.05); the ADFI difference between groups was not significant (P > 0.05); the FCR of HP II and III broilers was significantly decreased (P < 0.05); and the FCR of the HP I group increased, but the difference was not significant (P > 0.05). Transcriptome results demonstrate that 665 differential genes were screened (DEGs; upregulated: 366, downregulated: 299). The DEGs were enriched in the B cell receptor signaling pathway, the intestinal immune network for IgA synthesis, the Fc epsilon RI signaling pathway, and other signaling pathways, according to KEGG enrichment analysis. Metabolome analysis identified 92 differential metabolites (DAMs; upregulated: 48, downregulated: 44). KEGG enrichment analysis indicated significant enrichment of Pantothenate and CoA biosynthesis and beta-Alanine metabolism. The combined transcriptome and metabolome analysis revealed that the DAMs and DEGs were mostly involved in beta-alanine metabolism, arginine biosynthesis, amino sugar and nucleotide sugar, and alanine, aspartate, and glutamate metabolism. The results of this study suggest that the addition of compound probiotics has a positive effect on intestinal metabolites, improving the growth performance and contributing to the overall health of broilers under heat stress.

Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet.

2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5.

Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM.

We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.