Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Epigenetic and Transcriptomic Programming of HSC Quiescence Signaling in Large for Gestational Age Neonates.

Excessive fetal growth is associated with DNA methylation alterations in human hematopoietic stem and progenitor cells (HSPC), but their functional impact remains elusive. We implemented an integrative analysis combining single-cell epigenomics, single-cell transcriptomics, and in vitro analyses to functionally link DNA methylation changes to putative alterations of HSPC functions. We showed in hematopoietic stem cells (HSC) from large for gestational age neonates that both DNA hypermethylation and chromatin rearrangements target a specific network of transcription factors known to sustain stem cell quiescence. In parallel, we found a decreased expression of key genes regulating HSC differentiation including EGR1, KLF2, SOCS3, and JUNB. Our functional analyses showed that this epigenetic programming was associated with a decreased ability for HSCs to remain quiescent. Taken together, our multimodal approach using single-cell (epi)genomics showed that human fetal overgrowth affects hematopoietic stem cells' quiescence signaling via epigenetic programming.

A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity.

Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13 005 cases (≥95th percentile of body mass index (BMI) achieved 2-18 years old) and 15 599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1888 cases and 4689 controls from seven cohorts of European and North/South American ancestry. In addition to observing 18 previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene, METTL15). The variant was nominally associated with only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than 10 single nucleotide polymorphisms (SNPs) (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

NACHO: an R package for quality control of NanoString nCounter data.

SUMMARY: The NanoStringTM nCounter® is a platform for the targeted quantification of expression data in biofluids and tissues. While software by the manufacturer is available in addition to third parties packages, they do not provide a complete quality control (QC) pipeline. Here, we present NACHO ('NAnostring quality Control dasHbOard'), a comprehensive QC R-package. The package consists of three subsequent steps: summarize, visualize and normalize. The summarize function collects all the relevant data and stores it in a tidy format, the visualize function initiates a dashboard with plots of the relevant QC outcomes. It contains QC metrics that are measured by default by the manufacturer, but also calculates other insightful measures, including the scaling factors that are needed in the normalization step. In this normalization step, different normalization methods can be chosen to optimally preprocess data. Together, NACHO is a comprehensive method that optimizes insight and preprocessing of nCounter® data. AVAILABILITY AND IMPLEMENTATION: NACHO is available as an R-package on CRAN and the development version on GitHub https://github.com/mcanouil/NACHO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

General regression model: A "model-free" association test for quantitative traits allowing to test for the underlying genetic model.

Most genome-wide association studies used genetic-model-based tests assuming an additive mode of inheritance, leading to underpowered association tests in case of departure from additivity. The general regression model (GRM) association test proposed by Fisher and Wilson in 1980 makes no assumption on the genetic model. Interestingly, it also allows formal testing of the underlying genetic model. We conducted a simulation study of quantitative traits to compare the power of the GRM test to the classical linear regression tests, the maximum of the three statistics (MAX), and the allele-based (allelic) tests. Simulations were performed on two samples sizes, using a large panel of genetic models, varying genetic models, minor allele frequencies, and the percentage of explained variance. In case of departure from additivity, the GRM was more powerful than the additive regression tests (power gain reaching 80%) and had similar power when the true model is additive. GRM was also as or more powerful than the MAX or allelic tests. The true simulated model was mostly retained by the GRM test. Application of GRM to HbA1c illustrates its gain in power. To conclude, GRM increases power to detect association for quantitative traits, allows determining the genetic model and is easily applicable.

Decreased STARD10 Expression Is Associated with Defective Insulin Secretion in Humans and Mice.

Genetic variants near ARAP1 (CENTD2) and STARD10 influence type 2 diabetes (T2D) risk. The risk alleles impair glucose-induced insulin secretion and, paradoxically but characteristically, are associated with decreased proinsulin:insulin ratios, indicating improved proinsulin conversion. Neither the identity of the causal variants nor the gene(s) through which risk is conferred have been firmly established. Whereas ARAP1 encodes a GTPase activating protein, STARD10 is a member of the steroidogenic acute regulatory protein (StAR)-related lipid transfer protein family. By integrating genetic fine-mapping and epigenomic annotation data and performing promoter-reporter and chromatin conformational capture (3C) studies in ß cell lines, we localize the causal variant(s) at this locus to a 5 kb region that overlaps a stretch-enhancer active in islets. This region contains several highly correlated T2D-risk variants, including the rs140130268 indel. Expression QTL analysis of islet transcriptomes from three independent subject groups demonstrated that T2D-risk allele carriers displayed reduced levels of STARD10 mRNA, with no concomitant change in ARAP1 mRNA levels. Correspondingly, ß-cell-selective deletion of StarD10 in mice led to impaired glucose-stimulated Ca2+ dynamics and insulin secretion and recapitulated the pattern of improved proinsulin processing observed at the human GWAS signal. Conversely, overexpression of StarD10 in the adult ß cell improved glucose tolerance in high fat-fed animals. In contrast, manipulation of Arap1 in ß cells had no impact on insulin secretion or proinsulin conversion in mice. This convergence of human and murine data provides compelling evidence that the T2D risk associated with variation at this locus is mediated through reduction in STARD10 expression in the ß cell.

The expression of genes in top obesity-associated loci is enriched in insula and substantia nigra brain regions involved in addiction and reward.

BACKGROUND: Genome-wide association studies (GWAS) have identified more than 250 loci associated with body mass index (BMI) and obesity. However, post-GWAS functional genomic investigations have been inadequate for understanding how these genetic loci physiologically impact disease development. METHODS: We performed a PCR-free expression assay targeting genes located nearby the GWAS-identified SNPs associated with BMI/obesity in a large panel of human tissues. Furthermore, we analyzed several genetic risk scores (GRS) summing GWAS-identified alleles associated with increased BMI in 4236 individuals. RESULTS: We found that the expression of BMI/obesity susceptibility genes was strongly enriched in the brain, especially in the insula (p = 4.7 × 10-9) and substantia nigra (p = 6.8 × 10-7), which are two brain regions involved in addiction and reward. Inversely, we found that top obesity/BMI-associated loci, including FTO, showed the strongest gene expression enrichment in the two brain regions. CONCLUSIONS: Our data suggest for the first time that the susceptibility genes for common obesity may have an effect on eating addiction and reward behaviors through their high expression in substantia nigra and insula, i.e., a different pattern from monogenic obesity genes that act in the hypothalamus and cause hyperphagia. Further epidemiological studies with relevant food behavior phenotypes are necessary to confirm these findings.

Relationship between salivary/pancreatic amylase and body mass index: a systems biology approach.

BACKGROUND: Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach. METHODS: We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity. RESULTS: We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation. CONCLUSIONS: These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.

A framework for conducting time-varying genome-wide association studies: An application to body mass index across childhood in six multiethnic cohorts.

Genetic effects on changes in human traits over time are understudied and may have important pathophysiological impact. We propose a framework that enables data quality control, implements mixed models to evaluate trajectories of change in traits, and estimates phenotypes to identify age-varying genetic effects in genome-wide association studies (GWASs). Using childhood body mass index (BMI) as an example, we included 71,336 participants from six cohorts and estimated the slope and area under the BMI curve within four time periods (infancy, early childhood, late childhood and adolescence) for each participant, in addition to the age and BMI at the adiposity peak and the adiposity rebound. GWAS on each of the estimated phenotypes identified 28 genome-wide significant variants at 13 loci across the 12 estimated phenotypes, one of which was novel (in DAOA) and had not been previously associated with childhood or adult BMI. Genetic studies of changes in human traits over time could uncover novel biological mechanisms influencing quantitative traits.

Identification of myokines susceptible to improve glucose homeostasis after bariatric surgery.

IMPORTANCE AND OBJECTIVE: The identification of myokines susceptible to improve glucose homeostasis following bariatric surgery could lead to new therapeutic approaches for type 2 diabetes. METHODS: Changes in the homeostasis model assessment (HOMA) test were assessed in patients before and 3 months after bariatric surgery. Changes in myokines expression and circulating levels were assessed using real-time quantitative polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). Myokines known to regulate glucose homeostasis were identified using literature (targeted study) and putative myokines using RNA-sequencing (untargeted study). A linear regression analysis adjusted for age and sex was used to search for associations between changes in the HOMA test and changes in myokines. RESULTS: In the targeted study, brain-derived neurotrophic factor (BDNF) expression was upregulated (+30%, P = .006) while BDNF circulating levels were decreased (-12%, P = .001). Upregulated BDNF expression was associated with decreased HOMA of insulin resistance (HOMA-IR) (adjusted estimate [95% confidence interval {CI}]: -0.51 [-0.88 to -0.13], P = .010). Decreased BDNF serum levels were associated with decreased HOMA of beta-cell function (HOMA-B) (adjusted estimate [95% CI] = 0.002 [0.00002-0.0031], P = .046). In the untargeted study, upregulated putative myokines included XYLT1 (+64%, P < .001), LGR5 (+57, P< .001), and SPINK5 (+46%, P < .001). Upregulated LGR5 was associated with decreased HOMA-IR (adjusted estimate [95% CI] = -0.50 [-0.86 to -0.13], P = .009). Upregulated XYLT1 and SPINK5 were associated with increased HOMA of insulin sensitivity (HOMA-S) (respectively, adjusted estimate [95% CI] = 109.1 [28.5-189.8], P = .009 and 16.5 [0.87-32.19], P = .039). CONCLUSIONS: Improved glucose homeostasis following bariatric surgery is associated with changes in myokines expression and circulating levels. In particular, upregulation of BDNF, XYLT1, SPINK5, and LGR5 is associated with improved insulin sensitivity. These results suggest that these myokines could contribute to improved glucose homeostasis following bariatric surgery. STUDY REGISTRATION: NCT03341793 on ClinicalTrials.gov (https://clinicaltrials.gov/).

Contribution of heterozygous PCSK1 variants to obesity and implications for precision medicine: a case-control study.

BACKGROUND: Rare biallelic pathogenic mutations in PCSK1 (encoding proprotein convertase subtilisin/kexin type 1 [PC1/3]) cause early-onset obesity associated with various endocrinopathies. Setmelanotide has been approved for carriers of these biallelic mutations in the past 3 years. We aimed to perform a large-scale functional genomic study focusing on rare heterozygous variants of PCSK1 to decipher their putative impact on obesity risk. METHODS: This case-control study included all participants with overweight and obesity (ie, cases) or healthy weight (ie, controls) from the RaDiO study of three community-based and one hospital-based cohort in France recruited between Jan 1, 1995, and Dec 31, 2000. In adults older than 18 years, healthy weight was defined as BMI of less than 25·0 kg/m2, overweight as 25·0-29·9 kg/m2, and obesity as 30·0 kg/m2 or higher. Participants with type 2 diabetes had fasting glucose of 7·0 mmol/L or higher or used treatment for hyperglycaemia (or both) and were negative for islet or insulin autoantibodies. Functional assessment of rare missense variants of PCSK1 was performed. Pathogenicity clusters of variants were determined with machine learning. The effect of each cluster of PCSK1 variants on obesity was assessed using the adjusted mixed-effects score test. FINDINGS: All 13 coding exons of PCSK1 were sequenced in 9320 participants (including 7260 adults and 2060 children and adolescents) recruited from the RaDiO study. We detected 65 rare heterozygous PCSK1 variants, including four null variants and 61 missense variants that were analysed in vitro and clustered into five groups (A-E), according to enzymatic activity. Compared with the wild-type, 15 missense variants led to complete PC1/3 loss of function (group A; reference) and rare exome variant ensemble learner (REVEL) led to 15 (25%) false positives and four (7%) false negatives. Carrying complete loss-of-function or null PCSK1 variants was significantly associated with obesity (six [86%] of seven carriers vs 1518 [35%] of 4395 non-carriers; OR 9·3 [95% CI 1·5-177·4]; p=0·014) and higher BMI (32·0 kg/m2 [SD 9·3] in carriers vs 27·3 kg/m2 [6·5] in non-carriers; mean effect π 6·94 [SE 1·95]; p=0·00029). Clusters of PCSK1 variants with partial or neutral effect on PC1/3 activity did not have an effect on obesity or overweight and on BMI. INTERPRETATION: Only carriers of heterozygous, null, or complete loss-of-function PCSK1 variants cause monogenic obesity and, therefore, might be eligible for setmelanotide. In silico tests were unable to accurately detect these variants, which suggests that in vitro assays are necessary to determine the variant pathogenicity for genetic diagnosis and precision medicine purposes. FUNDING: Agence Nationale de la Recherche, European Research Council, National Center for Precision Diabetic Medicine, European Regional Development Fund, Hauts-de-France Regional Council, and the European Metropolis of Lille.

High morbidity and mortality in children with untreated congenital deficiency of leptin or its receptor.

The long-term clinical outcomes of severe obesity due to leptin signaling deficiency are unknown. We carry out a retrospective cross-sectional investigation of a large cohort of children with leptin (LEP), LEP receptor (LEPR), or melanocortin 4 receptor (MC4R) deficiency (n = 145) to evaluate the progression of the disease. The affected individuals undergo physical, clinical, and metabolic evaluations. We report a very high mortality in children with LEP (26%) or LEPR deficiency (9%), mainly due to severe pulmonary and gastrointestinal infections. In addition, 40% of surviving children with LEP or LEPR deficiency experience life-threatening episodes of lung or gastrointestinal infections. Although precision drugs are currently available for LEP and LEPR deficiencies, as yet, they are not accessible in Pakistan. An appreciation of the severe impact of LEP or LEPR deficiency on morbidity and early mortality, educational attainment, and the attendant stigmatization should spur efforts to deliver the available life-saving drugs to these children as a matter of urgency.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Epigenetic changes associated with hyperglycaemia exposure in the longitudinal D.E.S.I.R. cohort.

AIM: - Understanding DNA methylation dynamics associated with progressive hyperglycaemia exposure could provide early diagnostic biomarkers and an avenue for delaying type 2 diabetes mellitus (T2DM). We aimed to identify DNA methylation changes during a 6-year period associated with early hyperglycaemia exposure using the longitudinal D.E.S.I.R. METHODS: - We selected individuals with progressive hyperglycaemia exposure based on T2DM diagnostic criteria: 27 with long-term exposure, 34 with short-term exposure and 34 normoglycaemic controls. DNA from blood at inclusion and at the 6-year visit was subjected to methylation analysis using 850K methylation-EPIC arrays. A linear mixed model was used to perform an epigenome-wide association study (EWAS) and identify methylated changes associated with hyperglycaemia exposure during a 6-year time-period. RESULTS: - We did not identify differentially methylated sites that reached false discovery rate (FDR)-significance in our cohort. Based on EWAS, we focused our analysis on methylation sites that had a constant effect during the 6 years across the hyperglycaemia groups compared to controls and found the most statistically significant site was the reported cg19693031 probe (TXNIP). We also performed an EWAS with HbA1c, using the inclusion and the 6-year methylation data and did not identify any FDR-significant CpGs. CONCLUSIONS: - Our study reveals that DNA methylation changes are not robustly associated with hyperglycaemia exposure or HbA1c during a short-term period, however, our top loci indicate potential interest and should be replicated in larger cohorts.

Rare Variant Analysis of Obesity-Associated Genes in Young Adults With Severe Obesity From a Consanguineous Population of Pakistan.

Recent advances in genetic analysis have significantly helped in progressively attenuating the heritability gap of obesity and have brought into focus monogenic variants that disrupt the melanocortin signaling. In a previous study, next-generation sequencing revealed a monogenic etiology in ∼50% of the children with severe obesity from a consanguineous population in Pakistan. Here we assess rare variants in obesity-causing genes in young adults with severe obesity from the same region. Genomic DNA from 126 randomly selected young adult obese subjects (BMI 37.2 ± 0.3 kg/m2; age 18.4 ± 0.3 years) was screened by conventional or augmented whole-exome analysis for point mutations and copy number variants (CNVs). Leptin, insulin, and cortisol levels were measured by ELISA. We identified 13 subjects carrying 13 different pathogenic or likely pathogenic variants in LEPR, PCSK1, MC4R, NTRK2, POMC, SH2B1, and SIM1. We also identified for the first time in the human, two homozygous stop-gain mutations in ASNSD1 and IFI16 genes. Inactivation of these genes in mouse models has been shown to result in obesity. Additionally, we describe nine homozygous mutations (seven missense, one stop-gain, and one stop-loss) and four copy-loss CNVs in genes or genomic regions previously linked to obesity-associated traits by genome-wide association studies. Unexpectedly, in contrast to obese children, pathogenic mutations in LEP and LEPR were either absent or rare in this cohort of young adults. High morbidity and mortality risks and social disadvantage of children with LEP or LEPR deficiency may in part explain this difference between the two cohorts.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Maternal Glycemic Dysregulation During Pregnancy and Neonatal Blood DNA Methylation: Meta-analyses of Epigenome-Wide Association Studies.

OBJECTIVE: Maternal glycemic dysregulation during pregnancy increases the risk of adverse health outcomes in her offspring, a risk thought to be linearly related to maternal hyperglycemia. It is hypothesized that changes in offspring DNA methylation (DNAm) underline these associations. RESEARCH DESIGN AND METHODS: To address this hypothesis, we conducted fixed-effects meta-analyses of epigenome-wide association study (EWAS) results from eight birth cohorts investigating relationships between cord blood DNAm and fetal exposure to maternal glucose (Nmaximum = 3,503), insulin (Nmaximum = 2,062), and area under the curve of glucose (AUCgluc) following oral glucose tolerance tests (Nmaximum = 1,505). We performed lookup analyses for identified cytosine-guanine dinucleotides (CpGs) in independent observational cohorts to examine associations between DNAm and cardiometabolic traits as well as tissue-specific gene expression. RESULTS: Greater maternal AUCgluc was associated with lower cord blood DNAm at neighboring CpGs cg26974062 (ß [SE] -0.013 [2.1 × 10-3], P value corrected for false discovery rate [PFDR] = 5.1 × 10-3) and cg02988288 (ß [SE]-0.013 [2.3 × 10-3], PFDR = 0.031) in TXNIP. These associations were attenuated in women with GDM. Lower blood DNAm at these two CpGs near TXNIP was associated with multiple metabolic traits later in life, including type 2 diabetes. TXNIP DNAm in liver biopsies was associated with hepatic expression of TXNIP. We observed little evidence of associations between either maternal glucose or insulin and cord blood DNAm. CONCLUSIONS: Maternal hyperglycemia, as reflected by AUCgluc, was associated with lower cord blood DNAm at TXNIP. Associations between DNAm at these CpGs and metabolic traits in subsequent lookup analyses suggest that these may be candidate loci to investigate in future causal and mediation analyses.

Epigenome-Wide Association Study Reveals Methylation Loci Associated With Offspring Gestational Diabetes Mellitus Exposure and Maternal Methylome.

OBJECTIVE: Gestational diabetes mellitus (GDM) is associated with an increased risk of obesity and insulin resistance in offspring later in life, which might be explained by epigenetic changes in response to maternal hyperglycemic exposure. RESEARCH DESIGN AND METHODS: We explored the association between GDM exposure and maternal blood and newborn cord blood methylation in 536 mother-offspring pairs from the prospective FinnGeDi cohort using Illumina MethylationEPIC 850K BeadChip arrays. We assessed two hypotheses. First, we tested for shared maternal and offspring epigenetic effects resulting from GDM exposure. Second, we tested whether GDM exposure and maternal methylation had an epigenetic effect on the offspring. RESULTS: We did not find any epigenetic marks (differentially methylated CpG probes) with shared and consistent effects between mothers and offspring. After including maternal methylation in the model, we identified a single significant (false discovery rate 1.38 × 10-2) CpG at the cg22790973 probe (TFCP2) associated with GDM. We identified seven additional FDR-significant interactions of maternal methylation and GDM status, with the strongest association at the same cg22790973 probe (TFCP2), as well as cg03456133, cg24440941 (H3C6), cg20002843 (LOC127841), cg19107264, and cg11493553 located within the UBE3C gene and cg17065901 in FAM13A, both susceptibility genes for type 2 diabetes and BMI, and cg23355087 within the DLGAP2 gene, known to be involved in insulin resistance during pregnancy. CONCLUSIONS: Our study reveals the potential complexity of the epigenetic transmission between mothers with GDM and their offspring, likely determined by not only GDM exposure but also other factors indicated by maternal epigenetic status, such as maternal metabolic history.

Chromatin 3D interaction analysis of the STARD10 locus unveils FCHSD2 as a regulator of insulin secretion.

Using chromatin conformation capture, we show that an enhancer cluster in the STARD10 type 2 diabetes (T2D) locus forms a defined 3-dimensional (3D) chromatin domain. A 4.1-kb region within this locus, carrying 5 T2D-associated variants, physically interacts with CTCF-binding regions and with an enhancer possessing strong transcriptional activity. Analysis of human islet 3D chromatin interaction maps identifies the FCHSD2 gene as an additional target of the enhancer cluster. CRISPR-Cas9-mediated deletion of the variant region, or of the associated enhancer, from human pancreas-derived EndoC-ßH1 cells impairs glucose-stimulated insulin secretion. Expression of both STARD10 and FCHSD2 is reduced in cells harboring CRISPR deletions, and lower expression of STARD10 and FCHSD2 is associated, the latter nominally, with the possession of risk variant alleles in human islets. Finally, CRISPR-Cas9-mediated loss of STARD10 or FCHSD2, but not ARAP1, impairs regulated insulin secretion. Thus, multiple genes at the STARD10 locus influence ß cell function.

Identification of Key Regions Mediating Human Melatonin Type 1 Receptor Functional Selectivity Revealed by Natural Variants.

Melatonin is a hormone mainly produced by the pineal gland and MT1 is one of the two G protein-coupled receptors (GPCRs) mediating its action. Despite an increasing number of available GPCR crystal structures, the molecular mechanism of activation of a large number of receptors, including MT1, remains poorly understood. The purpose of this study is to elucidate the structural elements involved in the process of MT1's activation using naturally occurring variants affecting its function. Thirty-six nonsynonymous variants, including 34 rare ones, were identified in MTNR1A (encoding MT1) from a cohort of 8687 individuals and their signaling profiles were characterized using Bioluminescence Resonance Energy Transfer-based sensors probing 11 different signaling pathways. Computational analysis of the experimental data allowed us to group the variants in clusters according to their signaling profiles and to analyze the position of each variant in the context of the three-dimensional structure of MT1 to link functional selectivity to structure. MT1 variant signaling profiles revealed three clusters characterized by (1) wild-type-like variants, (2) variants with selective defect of ßarrestin-2 recruitment, and (3) severely defective variants on all pathways. Our structural analysis allows us to identify important regions for ßarrestin-2 recruitment as well as for Gα12 and Gα15 activation. In addition to identifying MT1 domains differentially controlling the activation of the various signaling effectors, this study illustrates how natural variants can be used as tools to study the molecular mechanisms of receptor activation.