Mexican Biobank advances population and medical genomics of diverse ancestries.

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2-6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.

Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

Novel diabetes gene discovery through comprehensive characterization and integrative analysis of longitudinal gene expression changes.

Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource.

Dynamin deficiency causes insulin secretion failure and hyperglycemia.

Pancreatic ß cells operate with a high rate of membrane recycling for insulin secretion, yet endocytosis in these cells is not fully understood. We investigate this process in mature mouse ß cells by genetically deleting dynamin GTPase, the membrane fission machinery essential for clathrin-mediated endocytosis. Unexpectedly, the mice lacking all three dynamin genes (DNM1, DNM2, DNM3) in their ß cells are viable, and their ß cells still contain numerous insulin granules. Endocytosis in these ß cells is severely impaired, resulting in abnormal endocytic intermediates on the plasma membrane. Although insulin granules are abundant, their release upon glucose stimulation is blunted in both the first and second phases, leading to hyperglycemia and glucose intolerance in mice. Dynamin triple deletion impairs insulin granule exocytosis and decreases intracellular Ca2+ responses and granule docking. The docking defect is correlated with reduced expression of Munc13-1 and RIM1 and reorganization of cortical F-actin in ß cells. Collectively, these findings uncover the role of dynamin in dense-core vesicle endocytosis and secretory capacity. Insulin secretion deficiency in the absence of dynamin-mediated endocytosis highlights the risk of impaired membrane trafficking in endocrine failure and diabetes pathogenesis.

Gene-environment interaction in type 2 diabetes in Korean cohorts: Interaction of a type 2 diabetes polygenic risk score with triglyceride and cholesterol on fasting glucose levels.

Type 2 diabetes (T2D) is caused by genetic and environmental factors as well as gene-environment interactions. However, these interactions have not been systematically investigated. We analyzed these interactions for T2D and fasting glucose levels in three Korean cohorts, HEXA, KARE, and CAVAS, using the baseline data with a multiple regression model. Two polygenic risk scores for T2D (PRST2D ) and fasting glucose (PRSFG ) were calculated using 488 and 82 single nucleotide polymorphisms (SNP) for T2D and fasting glucose, respectively, which were extracted from large-scaled genome-wide association studies with multiethnic data. Both lifestyle risk factors and T2D-related biochemical measurements were assessed. The effect of interactions between PRST2D -triglyceride (TG) and PRST2D -total cholesterol (TC) on fasting glucose levels was observed as follows: ß ± SE = 0.0005 ± 0.0001, p = 1.06 × 10-19 in HEXA, ß ± SE = 0.0008 ± 0.0001, p = 2.08 × 10-8 in KARE for TG; ß ± SE = 0.0006 ± 0.0001, p = 2.00 × 10-6 in HEXA, ß ± SE = 0.0020 ± 0.0004, p = 2.11 × 10-6 in KARE, ß ± SE = 0.0007 ± 0.0004, p = 0.045 in CAVAS for TC. PRST2D -based classification of the participants into four groups showed that the fasting glucose levels in groups with higher PRST2D were more adversely affected by both the TG and TC. In conclusion, blood TG and TC levels may affect the fasting glucose level through interaction with T2D genetic factors, suggesting the importance of consideration of gene-environment interaction in the preventive medicine of T2D.

Polymorphisms of mtDNA in the D-loop region moderate the associations of BMI with HOMA-IR and HOMA-ß among women with polycystic ovary syndrome: a cross-sectional study.

PURPOSE: Polycystic ovary syndrome (PCOS) is one of the leading causes of infertility in women of childbearing age, and many patients with PCOS have obesity and insulin resistance (IR). Although obesity is related to an increased risk of IR, in clinical practice, PCOS patients exhibit different effects on improving insulin sensitivity after weight loss. Therefore, in the present study, we aimed to examine the moderating effect of polymorphisms of mtDNA in the D-loop region on the associations of body mass index (BMI) with the homeostasis model assessment of insulin resistance index (HOMA-IR) and pancreatic ß cell function index (HOMA-ß) among women with PCOS. METHODS: Based on a cross-sectional study, women with PCOS were recruited from the Reproductive Center of the First Affiliated Hospital of Anhui Medical University from 2015 to 2018. A total of 520 women who were diagnosed with PCOS based on the revised 2003 Rotterdam criteria were included in the study. Peripheral blood was collected from these patients, followed by DNA extraction, PCR amplification, and sequencing at baseline. HOMA-IR and HOMA-ß were calculated according to blood glucose-related indices. Moderating effect models were performed with BMI as an independent variable, polymorphisms of mtDNA in the D-loop region as moderators, and ln (HOMA-IR) and ln (HOMA-ß) as dependent variables. To verify the stability of moderating effect, sensitivity analysis was performed with the quantitative insulin sensitivity check index (QUICKI), fasting plasma glucose/fasting insulin (G/I), and fasting insulin as dependent variables. RESULTS: BMI was positively associated with ln (HOMA-IR) and ln (HOMA-ß) (ß = 0.090, p < 0.001; ß = 0.059, p < 0.001, respectively), and the relationship between BMI and ln (HOMA-IR) or ln (HOMA-ß) was moderated by the polymorphisms of mtDNA in the D-loop region. Compared with the respective wild-type, the variant -type of m.16217 T > C enhanced the association between BMI and HOMA-IR, while the variant-type of m.16316 A > G weakened the association. On the other hand, the variant-type of m.16316 A > G and m.16203 A > G weakened the association between BMI and HOMA-ß, respectively. The results of QUICKI and fasting insulin as dependent variables were generally consistent with HOMA-IR, and the results of G/I as dependent variables were generally consistent with HOMA-ß. CONCLUSION: Polymorphisms of mtDNA in the D-loop region moderate the associations of BMI with HOMA-IR and HOMA-ß among women with PCOS.

Reducing sarcolipin expression improves muscle metabolism in mdx mice.

Duchenne muscular dystrophy (DMD) is an inherited muscle wasting disease. Metabolic impairments and oxidative stress are major secondary mechanisms that severely worsen muscle function in DMD. Here, we sought to determine whether germline reduction or ablation of sarcolipin (SLN), an inhibitor of sarco/endoplasmic reticulum (SR) Ca2+ ATPase (SERCA), improves muscle metabolism and ameliorates muscle pathology in the mdx mouse model of DMD. Glucose and insulin tolerance tests show that glucose clearance rate and insulin sensitivity were improved in the SLN haploinsufficient mdx (mdx:sln+/-) and SLN-deficient mdx (mdx:sln-/-) mice. The histopathological analysis shows that fibrosis and necrosis were significantly reduced in muscles of mdx:sln+/- and mdx:sln-/- mice. SR Ca2+ uptake, mitochondrial complex protein levels, complex activities, mitochondrial Ca2+ uptake and release, and mitochondrial metabolism were significantly improved, and lipid peroxidation and protein carbonylation were reduced in the muscles of mdx:sln+/- and mdx:sln-/- mice. These data demonstrate that reduction or ablation of SLN expression can improve muscle metabolism, reduce oxidative stress, decrease muscle pathology, and protects the mdx mice from glucose intolerance.

Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study.

AIMS/HYPOTHESIS: Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study. METHODS: We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci. RESULTS: Four novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis. CONCLUSIONS/INTERPRETATION: Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations. DATA AVAILABILITY: Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Mice lacking the proton channel Hv1 exhibit sex-specific differences in glucose homeostasis.

Sex as a physiologic factor has a strong association with the features of metabolic syndrome. Our previous study showed that loss of the voltage-gated proton channel Hv1 inhibits insulin secretion and leads to hyperglycemia and glucose intolerance in male mice. However, there are significant differences in blood glucose between male and female Hv1-knockout (KO) mice. Here, we investigated the differences in glucose metabolism and insulin sensitivity between male and female KO mice and how sex steroids contribute to these differences. We found that the fasting blood glucose in female KO mice was visibly lower than that in male KO mice, which was accompanied by hypotestosteronemia. KO mice in both sexes exhibited higher expression of gluconeogenesis-related genes in liver compared with WT mice. Also, the livers from KO males displayed a decrease in glycolysis-related gene expression and an increase in gluconeogenesis-related gene expression compared with KO females. Furthermore, exogenous testosterone supplementation decreased blood glucose levels in male KO mice, as well as enhancing insulin signaling. Taken together, our data demonstrate that knockout of Hv1 results in higher blood glucose levels in male than female mice, despite a decreased insulin secretion in both sexes. This sex-related difference in glucose homeostasis is associated with the glucose metabolism in liver tissue, likely due to the physiological levels of testosterone in KO male mice.

Genes controlling skeletal muscle glucose uptake and their regulation by endurance and resistance exercise.

Exercise improves the insulin sensitivity of glucose uptake in skeletal muscle. Due to that, exercise has become a cornerstone treatment for type 2 diabetes mellitus (T2DM). The mechanisms by which exercise improves skeletal muscle insulin sensitivity are, however, incompletely understood. We conducted a systematic review to identify all genes whose gain or loss of function alters skeletal muscle glucose uptake. We subsequently cross-referenced these genes with recently generated data sets on exercise-induced gene expression and signaling. Our search revealed 176 muscle glucose-uptake genes, meaning that their genetic manipulation altered glucose uptake in skeletal muscle. Notably, exercise regulates the expression or phosphorylation of more than 50% of the glucose-uptake genes or their protein products. This included many genes that previously have not been associated with exercise-induced insulin sensitivity. Interestingly, endurance and resistance exercise triggered some common but mostly unique changes in expression and phosphorylation of glucose-uptake genes or their protein products. Collectively, our work provides a resource of potentially new molecular effectors that play a role in the incompletely understood regulation of muscle insulin sensitivity by exercise.

Quantitative trait loci, G×E and G×G for glycemic traits: response to metformin and placebo in the Diabetes Prevention Program (DPP).

The complex genetic architecture of type-2-diabetes (T2D) includes gene-by-environment (G×E) and gene-by-gene (G×G) interactions. To identify G×E and G×G, we screened markers for patterns indicative of interactions (relationship loci [rQTL] and variance heterogeneity loci [vQTL]). rQTL exist when the correlation between multiple traits varies by genotype and vQTL occur when the variance of a trait differs by genotype (potentially flagging G×G and G×E). In the metformin and placebo arms of the DPP (n = 1762) we screened 280,965 exomic and intergenic SNPs, for rQTL and vQTL patterns in association with year one changes from baseline in glycemia and related traits (insulinogenic index [IGI], insulin sensitivity index [ISI], fasting glucose and fasting insulin). Significant (p < 1.8 × 10-7) rQTL and vQTL generated a priori hypotheses of individual G×E tests for a SNP × metformin treatment interaction and secondarily for G×G screens. Several rQTL and vQTL identified led to 6 nominally significant (p < 0.05) metformin treatment × SNP interactions (4 for IGI, one insulin, and one glucose) and 12G×G interactions (all IGI) that exceeded experiment-wide significance (p < 4.1 × 10-9). Some loci are directly associated with incident diabetes, and others are rQTL and modify a trait's relationship with diabetes (2 diabetes/glucose, 2 diabetes/insulin, 1 diabetes/IGI). rs3197999, an ISI/insulin rQTL, is a possible gene damaging missense mutation in MST1, is associated with ulcerative colitis, sclerosing cholangitis, Crohn's disease, BMI and coronary artery disease. This study demonstrates evidence for context-dependent effects (G×G & G×E) and the complexity of these T2D-related traits.

No association between a common type 2 diabetes risk gene variant in the melatonin receptor gene (MTNR1B) and mortality among type 2 diabetes patients.

The minor G risk allele in the common melatonin receptor gene (MTNR1B, rs10830963) has been associated with an increased risk of myocardial infarction among patients with type 2 diabetes (T2D). Furthermore, activating the melatonin receptor 1B through melatonin has been shown to promote cell proliferation, which could be hypothesized to increase cancer risk. Cardiovascular disease (CVD) and cancer are common causes of death among patients with T2D. Using data from 14 736  patients with T2D who participated in the UK Biobank investigation, we hypothesized an additive effect of the G risk allele on all-cause mortality, CVD mortality, and cancer mortality. As shown by Cox regression adjusted for confounders such as age, glucose-lowering medication, and socioeconomic status, no significant trend between the number of G risk alleles and mortality outcomes was found during the follow-up period of 11.1 years. Our negative findings do not speak against the role of this gene variant in the development of T2D, as repeatedly shown by previous large-scale studies. Instead, they may suggest that rs10830963 is less relevant for mortality risk in patients with T2D.

Growth hormone acts on liver to stimulate autophagy, support glucose production, and preserve blood glucose in chronically starved mice.

When mice are subjected to 60% calorie restriction for several days, they lose nearly all of their body fat. Although the animals lack energy stores, their livers produce enough glucose to maintain blood glucose at viable levels even after a 23-hour fast. This adaptation is mediated by a marked increase in plasma growth hormone (GH), which is elicited by an increase in plasma ghrelin, a GH secretagogue. In the absence of ghrelin, calorie-restricted mice develop hypoglycemia, owing to diminished glucose production. To determine the site of GH action, in the current study we used CRISPR/Cas9 and Cre recombinase technology to produce mice that lack GH receptors selectively in liver (L-Ghr-/- mice) or in adipose tissue (Fat-Ghr-/- mice). When subjected to calorie restriction and then fasted for 23 hours, the L-Ghr-/- mice, but not the Fat-Ghr-/- mice, developed hypoglycemia. The fall in blood glucose in L-Ghr-/- mice was correlated with a profound drop in hepatic triglycerides. Hypoglycemia was prevented by injection of lactate or octanoate, two sources of energy to support gluconeogenesis. Electron microscopy revealed extensive autophagy in livers of calorie-restricted control mice but not in L-Ghr-/- mice. We conclude that GH acts through its receptor in the liver to activate autophagy, preserve triglycerides, enhance gluconeogenesis, and prevent hypoglycemia in calorie-restricted mice, a model of famine.

Reverse GWAS: Using genetics to identify and model phenotypic subtypes.

Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automated statistical approaches to subtype definition valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a novel decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show that modelling these features can be crucial for power and calibration. We validate RGWAS in practice by recovering a recently discovered stress subtype in major depression. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests subtypes may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting the subtypes have potential translational value.

Metabolites and Genes behind Cardiac Metabolic Remodeling in Mice with Type 1 Diabetes Mellitus.

Metabolic remodeling is at the heart of diabetic cardiomyopathy. High glycemic fluctuations increase metabolic stress in the type 1 diabetes mellitus (T1DM) heart. There is a lack of understanding on how metabolites and genes affect metabolic remodeling in the T1DM heart. We hypothesize that differential expression of metabolic genes and metabolites synergistically influence metabolic remodeling preceding T1DM cardiomyopathy. To test our hypothesis, we conducted high throughput analysis of hearts from adult male hyperglycemic Ins2+/- (Akita) and littermate normoglycemic Ins2+/+ (WT) mice. The Akita mouse is a spontaneous, genetic model of T1DM that develops increased levels of consistent glycemic variability without the off-target cardiotoxic effects present in chemically- induced models of T1DM. After validating the presence of a T1DM phenotype, we conducted metabolomics via LC-MS analysis and genomics via next-generation sequencing in left ventricle tissue from the Akita heart. Ingenuity Pathway Analyses revealed that 108 and 30 metabolic pathways were disrupted within the metabolomics and genomics datasets, respectively. Notably, a comparison between the two analyses showed 15 commonly disrupted pathways, including ketogenesis, ketolysis, cholesterol biosynthesis, acetyl CoA hydrolysis, and fatty acid biosynthesis and beta-oxidation. These identified metabolic pathways predicted by the differential expression of metabolites and genes provide the foundation for understanding metabolic remodeling in the T1DM heart. By limited experiment, we revealed a predicted disruption in the metabolites and genes behind T1DM cardiac metabolic derangement. Future studies targeting these genes and metabolites will unravel novel therapies to prevent/improve metabolic remodeling in the T1DM heart.

Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose.

AIMS/HYPOTHESIS: An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses. METHODS: We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data. RESULTS: Our meta-analysis identified 18 significant (p < 5 × 10-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument. CONCLUSIONS/INTERPRETATION: Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.

Sexually dimorphic roles for the type 2 diabetes-associated C2cd4b gene in murine glucose homeostasis.

AIMS/HYPOTHESIS: Variants close to the VPS13C/C2CD4A/C2CD4B locus are associated with altered risk of type 2 diabetes in genome-wide association studies. While previous functional work has suggested roles for VPS13C and C2CD4A in disease development, none has explored the role of C2CD4B. METHODS: CRISPR/Cas9-induced global C2cd4b-knockout mice and zebrafish larvae with c2cd4a deletion were used to study the role of this gene in glucose homeostasis. C2 calcium dependent domain containing protein (C2CD)4A and C2CD4B constructs tagged with FLAG or green fluorescent protein were generated to investigate subcellular dynamics using confocal or near-field microscopy and to identify interacting partners by mass spectrometry. RESULTS: Systemic inactivation of C2cd4b in mice led to marked, but highly sexually dimorphic changes in body weight and glucose homeostasis. Female C2cd4b mice displayed unchanged body weight compared with control littermates, but abnormal glucose tolerance (AUC, p = 0.01) and defective in vivo, but not in vitro, insulin secretion (p = 0.02). This was associated with a marked decrease in follicle-stimulating hormone levels as compared with wild-type (WT) littermates (p = 0.003). In sharp contrast, male C2cd4b null mice displayed essentially normal glucose tolerance but an increase in body weight (p < 0.001) and fasting blood glucose (p = 0.003) after maintenance on a high-fat and -sucrose diet vs WT littermates. No metabolic disturbances were observed after global inactivation of C2cd4a in mice, or in pancreatic beta cell function at larval stages in C2cd4a null zebrafish. Fasting blood glucose levels were also unaltered in adult C2cd4a-null fish. C2CD4B and C2CD4A were partially localised to the plasma membrane, with the latter under the control of intracellular Ca2+. Binding partners for both included secretory-granule-localised PTPRN2/phogrin. CONCLUSIONS/INTERPRETATION: Our studies suggest that C2cd4b may act centrally in the pituitary to influence sex-dependent circuits that control pancreatic beta cell function and glucose tolerance in rodents. However, the absence of sexual dimorphism in the impact of diabetes risk variants argues for additional roles for C2CD4A or VPS13C in the control of glucose homeostasis in humans. DATA AVAILABILITY: The datasets generated and/or analysed during the current study are available in the Biorxiv repository ( www.biorxiv.org/content/10.1101/2020.05.18.099200v1 ). RNA-Seq (GSE152576) and proteomics (PXD021597) data have been deposited to GEO ( www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152576 ) and ProteomeXchange ( www.ebi.ac.uk/pride/archive/projects/PXD021597 ) repositories, respectively.

Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study.

BACKGROUND: Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases). METHOD: We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method. RESULTS: We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval. CONCLUSION: We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.

Alternative exon splicing and differential expression in pancreatic islets reveals candidate genes and pathways implicated in early diabetes development.

Type 2 diabetes (T2D) has a strong genetic component. Most of the gene variants driving the pathogenesis of T2D seem to target pancreatic ß-cell function. To identify novel gene variants acting at early stage of the disease, we analyzed whole transcriptome data to identify differential expression (DE) and alternative exon splicing (AS) transcripts in pancreatic islets collected from two metabolically diverse mouse strains at 6 weeks of age after three weeks of high-fat-diet intervention. Our analysis revealed 1218 DE and 436 AS genes in islets from NZO/Hl vs C3HeB/FeJ. Whereas some of the revealed genes present well-established markers for ß-cell failure, such as Cd36 or Aldh1a3, we identified numerous DE/AS genes that have not been described in context with ß-cell function before. The gene Lgals2, previously associated with human T2D development, was DE as well as AS and localizes in a quantitative trait locus (QTL) for blood glucose on Chr.15 that we reported recently in our N2(NZOxC3H) population. In addition, pathway enrichment analysis of DE and AS genes showed an overlap of only half of the revealed pathways, indicating that DE and AS in large parts influence different pathways in T2D development. PPARG and adipogenesis pathways, two well-established metabolic pathways, were overrepresented for both DE and AS genes, probably as an adaptive mechanism to cope for increased cellular stress. Our results provide guidance for the identification of novel T2D candidate genes and demonstrate the presence of numerous AS transcripts possibly involved in islet function and maintenance of glucose homeostasis.

Mendelian Randomization Study of Obesity and Cerebrovascular Disease.

OBJECTIVE: To systematically investigate causal relationships between obesity and cerebrovascular disease and the extent to which hypertension and hyperglycemia mediate the effect of obesity on cerebrovascular disease. METHODS: We used summary statistics from genome-wide association studies for body mass index (BMI), waist-to-hip ratio (WHR), and multiple cerebrovascular disease phenotypes. We explored causal associations with 2-sample Mendelian randomization (MR) accounting for genetic covariation between BMI and WHR, and we assessed what proportion of the association between obesity and cerebrovascular disease was mediated by systolic blood pressure (SBP) and blood glucose levels, respectively. RESULTS: Genetic predisposition to higher BMI did not increase the risk of cerebrovascular disease. In contrast, for each 10% increase in WHR there was a 75% increase (95% confidence interval [CI] = 44-113%) in risk for large artery ischemic stroke, a 57% (95% CI = 29-91%) increase in risk for small vessel ischemic stroke, a 197% increase (95% CI = 59-457%) in risk of intracerebral hemorrhage, and an increase in white matter hyperintensity volume (ß = 0.11, 95% CI = 0.01-0.21). These WHR associations persisted after adjusting for genetic determinants of BMI. Approximately one-tenth of the observed effect of WHR was mediated by SBP for ischemic stroke (proportion mediated: 12%, 95% CI = 4-20%), but no evidence of mediation was found for average blood glucose. INTERPRETATION: Abdominal adiposity may trigger causal pathological processes, partially independent from blood pressure and totally independent from glucose levels, that lead to cerebrovascular disease. Potential targets of these pathological processes could represent novel therapeutic opportunities for stroke. ANN NEUROL 2020;87:516-524.