Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

CDKN2A/B T2D Genome-Wide Association Study Risk SNPs Impact Locus Gene Expression and Proliferation in Human Islets

Genome-wide association studies link the CDKN2A/B locus with type 2 diabetes (T2D) risk, but mechanisms increasing risk remain unknown. The CDKN2A/B locus encodes cell cycle inhibitors p14, p15, and p16; MTAP; and ANRIL, a long noncoding RNA. The goal of this study was to determine whether CDKN2A/B T2D risk SNPs impact locus gene expression, insulin secretion, or β-cell proliferation in human islets. Islets from donors without diabetes (n = 95) were tested for SNP genotype (rs10811661, rs2383208, rs564398, and rs10757283), gene expression (p14, p15, p16, MTAP, ANRIL, PCNA, KI67, and CCND2), insulin secretion (n = 61), and β-cell proliferation (n = 47). Intriguingly, locus genes were coregulated in islets in two physically overlapping cassettes: p14-p16-ANRIL, which increased with age, and MTAP-p15, which did not. Risk alleles at rs10811661 and rs2383208 were differentially associated with expression of ANRIL, but not p14, p15, p16, or MTAP, in age-dependent fashion, such that younger homozygous risk donors had higher ANRIL expression, equivalent to older donor levels. We identified several risk SNP combinations that may impact locus gene expression, suggesting possible mechanisms by which SNPs impact locus biology. Risk allele carriers at ANRIL coding SNP rs564398 had reduced β-cell proliferation index. In conclusion, CDKN2A/B locus SNPs may impact T2D risk by modulating islet gene expression and β-cell proliferation.

Association of melatonin &MTNR1B variants with type 2 diabetes in Gujarat population

AIM/HYPOTHESIS

Melatonin is a circadian rhythm regulator and any imbalance in its levels can be related to various metabolic disorders. Melatonin and the genetic variants of Melatonin Receptor 1B (MTNR1B) are reported to be associated with Type 2 Diabetes (T2D) susceptibility. The aim of the present study was to investigate i) plasma melatonin levels ii) Single Nucleotide Polymorphisms (SNPs) of MTNR1B and iii) Genotype-phenotype correlation analysis in T2D patients.

METHODS

Plasma and PBMCs were separated from venous blood of 478 diabetes patients and 502 controls. Genomic DNA was isolated from PBMCs. PCR-RFLP was used for genotyping. Melatonin was estimated from plasma samples by ELISA.

RESULTS

Our study suggests: i) decreased plasma melatonin levels in T2D patients and, ii) association of MTNR1B rs10830963 GG genotype with increased Fasting Blood Glucose (FBG).

CONCLUSION

It can be concluded that reduced titer of melatonin along with altered FBG due to MTNR1B genetic variant could act as a potent risk factor towards T2D in Gujarat population.

Implications of publicly available genomic data resources in searching for therapeutic targets of obesity and type 2 diabetes

Obesity and type 2 diabetes (T2D) are two major conditions that are related to metabolic disorders and affect a large population. Although there have been significant efforts to identify their therapeutic targets, few benefits have come from comprehensive molecular profiling. This limited availability of comprehensive molecular profiling of obesity and T2D may be due to multiple challenges, as these conditions involve multiple organs and collecting tissue samples from subjects is more difficult in obesity and T2D than in other diseases, where surgical treatments are popular choices. While there is no repository of comprehensive molecular profiling data for obesity and T2D, multiple existing data resources can be utilized to cover various aspects of these conditions. This review presents studies with available genomic data resources for obesity and T2D and discusses genome-wide association studies (GWAS), a knockout (KO)-based phenotyping study, and gene expression profiles. These studies, based on their assessed coverage and characteristics, can provide insights into how such data can be utilized to identify therapeutic targets for obesity and T2D.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.

A Common Type 2 Diabetes Risk Variant Potentiates Activity of an Evolutionarily Conserved Islet Stretch Enhancer and Increases C2CD4A and C2CD4B Expression

Genome-wide association studies (GWASs) and functional genomics approaches implicate enhancer disruption in islet dysfunction and type 2 diabetes (T2D) risk. We applied genetic fine-mapping and functional (epi)genomic approaches to a T2D- and proinsulin-associated 15q22.2 locus to identify a most likely causal variant, determine its direction of effect, and elucidate plausible target genes. Fine-mapping and conditional analyses of proinsulin levels of 8,635 non-diabetic individuals from the METSIM study support a single association signal represented by a cluster of 16 strongly associated (p < 10^-17) variants in high linkage disequilibrium (r² > 0.8) with the GWAS index SNP rs7172432. These variants reside in an evolutionarily and functionally conserved islet and β cell stretch or super enhancer; the most strongly associated variant (rs7163757, p = 3 × 10^-19) overlaps a conserved islet open chromatin site. DNA sequence containing the rs7163757 risk allele displayed 2-fold higher enhancer activity than the non-risk allele in reporter assays (p < 0.01) and was differentially bound by β cell nuclear extract proteins. Transcription factor NFAT specifically potentiated risk-allele enhancer activity and altered patterns of nuclear protein binding to the risk allele in vitro, suggesting that it could be a factor mediating risk-allele effects. Finally, the rs7163757 proinsulin-raising and T2D risk allele (C) was associated with increased expression of C2CD4B, and possibly C2CD4A, both of which were induced by inflammatory cytokines, in human islets. Together, these data suggest that rs7163757 contributes to genetic risk of islet dysfunction and T2D by increasing NFAT-mediated islet enhancer activity and modulating C2CD4B, and possibly C2CD4A, expression in (patho)physiologic states.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Influence of obesity-related risk factors in the aetiology of glioma

BACKGROUND

Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation.

METHODS

Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship.

RESULTS

No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours.

CONCLUSIONS

This study provides no evidence to implicate obesity-related factors as causes of glioma.

Pathways to understanding the genomic aetiology of osteoarthritis

Osteoarthritis is a common, complex disease with no curative therapy. In this review, we summarize current knowledge on disease aetiopathogenesis and outline genetics and genomics approaches that are helping catalyse a much-needed improved understanding of the biological underpinning of disease development and progression.

The pathogenetic role of β-cell mitochondria in type 2 diabetes

Mitochondrial metabolism is a major determinant of insulin secretion from pancreatic β-cells. Type 2 diabetes evolves when β-cells fail to release appropriate amounts of insulin in response to glucose. This results in hyperglycemia and metabolic dysregulation. Evidence has recently been mounting that mitochondrial dysfunction plays an important role in these processes. Monogenic dysfunction of mitochondria is a rare condition but causes a type 2 diabetes-like syndrome owing to β-cell failure. Here, we describe novel advances in research on mitochondrial dysfunction in the β-cell in type 2 diabetes, with a focus on human studies. Relevant studies in animal and cell models of the disease are described. Transcriptional and translational regulation in mitochondria are particularly emphasized. The role of metabolic enzymes and pathways and their impact on β-cell function in type 2 diabetes pathophysiology are discussed. The role of genetic variation in mitochondrial function leading to type 2 diabetes is highlighted. We argue that alterations in mitochondria may be a culprit in the pathogenetic processes culminating in type 2 diabetes.

Genetic risk for Alzheimer's disease is concentrated in specific macrophage and microglial transcriptional networks

Background

Genome-wide association studies of Alzheimer’s disease (AD) have identified a number of significant risk loci, the majority of which lie in non-coding regions of the genome. The lack of causal alleles and considerable polygenicity remains a significant barrier to translation into mechanistic understanding. This includes identifying causal variants and the cell/tissue types in which they operate. A fuller understanding of the cell types and transcriptional networks involved in AD genetic risk mechanisms will provide important insights into pathogenesis.

Methods

We assessed the significance of the overlap between genome-wide significant AD risk variants and sites of open chromatin from data sets representing diverse tissue types. We then focussed on macrophages and microglia to investigate the role of open chromatin sites containing motifs for specific transcription factors. Partitioned heritability using LDscore regression was used to investigate the contribution of specific macrophage and microglia transcription factor motif-containing open chromatin sites to the heritability of AD.

Results

AD risk single nucleotide polymorphisms (SNPs) are preferentially located at sites of open chromatin in immune cells, particularly monocytes (z score = 4.43; corrected P = 5.88 × 10^{− 3}). Similar enrichments are observed for macrophages (z score = 4.10; corrected P < 2.40 × 10^{− 3}) and microglia (z score = 4.34, corrected P = 0.011). In both macrophages and microglia, AD risk variants are enriched at a subset of open chromatin sites that contain DNA binding motifs for specific transcription factors, e.g. SPI1 and MEF2. Genetic variation at many of these motif-containing sites also mediate a substantial proportion of AD heritability, with SPI1-containing sites capturing the majority of the common variant SNP-chip heritability (microglia enrichment = 16.28, corrected enrichment P = 0.0044).

Conclusions

AD risk alleles plausibly operate in immune cells, including microglia, and are concentrated in specific transcriptional networks. Combined with primary genetic association results, the SPI1 and MEF2 transcriptional networks appear central to AD risk mechanisms. Investigation of transcription factors targeting AD risk SNP associated regulatory elements could provide powerful insights into the molecular processes affected by AD polygenic risk. More broadly, our findings support a model of polygenic disease risk that arises from variants located in specific transcriptional networks.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0523-8) contains supplementary material, which is available to authorized users.

A novel variant associated with HDL-C levels by modifying DAGLB expression levels: An annotation-based genome-wide association study

Although numbers of genome-wide association studies (GWAS) have been performed for serum lipid levels, limited heritability has been explained. Studies showed that combining data from GWAS and expression quantitative trait loci (eQTLs) signals can both enhance the discovery of trait-associated SNPs and gain a better understanding of the mechanism. We performed an annotation-based, multistage genome-wide screening for serum-lipid-level-associated loci in totally 6863 Han Chinese. A serum high-density lipoprotein cholesterol (HDL-C) associated variant rs1880118 (hg19 chr7:g. 6435220G>C) was replicated (P_combined = 1.4E-10). rs1880118 was associated with DAGLB (diacylglycerol lipase, beta) expression levels in subcutaneous adipose tissue (P = 5.9E-42) and explained 47.7% of the expression variance. After the replication, an active segment covering variants tagged by rs1880118 near 5' of DAGLB was annotated using histone modification and transcription factor binding signals. The luciferase report assay revealed that the segment containing the minor alleles showed increased transcriptional activity compared with segment contains the major alleles, which was consistent with the eQTL analyses. The expression-trait association tests indicated the association between the DAGLB and serum HDL-C levels using gene-based approaches called "TWAS" (P = 3.0E-8), "SMR" (P = 1.1E-4), and "Sherlock" (P = 1.6E-6). To summarize, we identified a novel HDL-C-associated variant which explained nearly half of the expression variance of DAGLB. Integrated analyses established a genotype-gene-phenotype three-way association and expanded our knowledge of DAGLB in lipid metabolism.

PARP-1 Inhibition Rescues Short Lifespan in Hyperglycemic C. Elegans And Improves GLP-1 Secretion in Human Cells

TCF7L2 is located at one of the most strongly associated type 2 diabetes loci reported to date. We previously reported that the most abundant member of a specific protein complex to bind across the presumed causal variant at this locus, rs7903146, was poly [ADP-ribose] polymerase type 1 (PARP-1). We analyzed the impact of PARP-1 inhibition on C. elegans health in the setting of hyperglycemia and on glucose-stimulated GLP-1 secretion in human intestinal cells. Given that high glucose concentrations progressively shorten the lifespan of C. elegans, in part by impacting key well-conserved insulin-modulated signaling pathways, we investigated the effect of PARP-1 inhibition with Olaparib on the lifespan of C. elegans nematodes under varying hyperglycemic conditions. Subsequently, we investigated whether Olaparib treatment had any effect on glucose-stimulated GLP-1 secretion in the human NCI-H716 intestinal cell line, a model system for the investigation of enteroendocrine function. Treatment with 100uM Olaparib in nematodes exposed to high concentrations of glucose led to significant lifespan rescue. The beneficial lifespan effect of Olaparib appeared to require both PARP-1 and TCF7L2, since treatment had no effect in hyperglycemic conditions in knock-out worm strains for either of these homologs. Further investigation using the NCI-H716 cells revealed that Olaparib significantly enhanced secretion of the incretin, GLP-1, plus the gene expression of TCF7L2, GCG and PC1. These data from studies in both C. elegans and a human cell line suggest that PARP-1 inhibition offers a novel therapeutic avenue to treat type 2 diabetes.

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662075, associated with a twofold increased risk for T2D in males. rs146662075 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

Genome-wide association studies have uncovered several loci associated with diabetes risk. Here, the authors reanalyse public type 2 diabetes GWAS data to fine map 50 known loci and identify seven new ones, including one near ATGR2 on the X-chromosome that doubles the risk of diabetes in men.

Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution

Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals.

Identification of key gene pathways and coexpression networks of islets in human type 2 diabetes

PURPOSE

The number of people with type 2 diabetes (T2D) is growing rapidly worldwide. Islet β-cell dysfunction and failure are the main causes of T2D pathological processes. The aim of this study was to elucidate the underlying pathways and coexpression networks in T2D islets.

MATERIALS AND METHODS

We analyzed the differentially expressed genes (DEGs) in the data set GSE41762, which contained 57 nondiabetic and 20 diabetic samples, and developed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed as well. Moreover, a weighted correlation network analysis (WGCNA) was applied to screen critical gene modules and coexpression networks and explore the biological significance.

RESULTS

We filtered 957 DEGs in T2D islets. Then GO and KEGG analyses identified that key pathways like inflammatory response, type B pancreatic cell differentiation, and calcium ion-dependent exocytosis were involved in human T2D. Three significant modules were filtered from the PPI network. Ribosome biogenesis, extrinsic apoptotic signaling pathway, and membrane depolarization during action potential were associated with the modules, respectively. Furthermore, coexpression network analysis by WGCNA identified 13 distinct gene modules of T2D islets and revealed four modules, which were strongly correlated with T2D and T2D biomarker hemoglobin A1c (HbA1c). Functional annotation showed that these modules mainly enriched KEGG pathways such as NF-kappa B signaling pathway, tumor necrosis factor signaling pathway, cyclic adenosine monophosphate signaling pathway, and peroxisome proliferators-activated receptor signaling pathway.

CONCLUSION

The results provide potential gene pathways and underlying molecular mechanisms for the prevention, diagnosis, and treatment of T2D.

Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

Circadian Transcription from Beta Cell Function to Diabetes Pathophysiology

The mammalian circadian clock plays a central role in the temporal coordination of physiology across the 24-h light-dark cycle. A major function of the clock is to maintain energy constancy in anticipation of alternating periods of fasting and feeding that correspond with sleep and wakefulness. While it has long been recognized that humans exhibit robust variation in glucose tolerance and insulin sensitivity across the sleep-wake cycle, experimental genetic analysis has now revealed that the clock transcription cycle plays an essential role in insulin secretion and metabolic function within pancreatic beta cells. This review addresses how studies of the beta cell clock may elucidate the etiology of subtypes of diabetes associated with circadian and sleep cycle disruption, in addition to more general forms of the disease.

Two novel susceptibility loci for type 2 diabetes mellitus identified by longitudinal exome-wide association studies in a Japanese population

Recent genome-wide association studies identified genetic variants that confer susceptibility to type 2 diabetes mellitus (T2DM). However, few longitudinal genome-wide association studies of this metabolic disorder have been reported to date. Therefore, we performed a longitudinal exome-wide association study of T2DM, using 24,579 single nucleotide polymorphisms (SNPs) and repeated measurements from 6022 Japanese individuals. The generalized estimating equation model was applied to test relations of SNPs to three T2DM-related parameters: prevalence of T2DM, fasting plasma glucose level, and blood glycosylated hemoglobin content. Three SNPs that passed quality control were significantly (P<2.26×10^-7) associated with two of the three T2DM-related parameters in additive and recessive models. Of the three SNPs, rs6414624 in EVC and rs78338345 in GGA3 were novel susceptibility loci for T2DM. In the present study, the SNP of GGA3 was predicted to be a genetic variant whose minor allele frequency has recently increased in East Asia.

The Genetic Basis of Type 2 Diabetes in Hispanics and Latin Americans: Challenges and Opportunities

Type 2 diabetes (T2D) affects 415 million people worldwide, and has a much higher prevalence in Hispanics (16.9%), compared to non-Hispanic whites (10.2%). Genome-wide association studies and whole-genome and whole-exome sequencing studies have discovered more than 100 genetic regions associated with modified risk for T2D. However, the identified genetic factors explain a very small fraction of the estimated heritability. Until recently, little attention has been put in studying other non European populations that suffer from a higher burden of T2D, such as Hispanics/Latinos. In the past few years, genetic studies in Hispanic populations have started to provide new insights into the genetic architecture of T2D in this ancestry group. Of note, several genetic variants that are absent or very rare in non-Hispanic populations but more common in Hispanics have shown from moderate to strong association with T2D and have provided new insights into the biology of T2D, which may be ultimately useful for developing novel therapeutic strategies applicable to all populations. Studying diverse populations can also improve the ability to find the causal variants in known T2D loci by a multi-ancestry fine-mapping approach, which leverages the different patterns of linkage disequilibrium between the causal and the ascertained genetic variants. In this mini-review, we summarize the main genetic findings discovered in Hispanics and discuss the limitations and challenges of performing genetic studies in these populations. Finally, we present possible next steps to make studies in Latino populations more valuable in providing a deeper understanding of T2D and anticipate their future application to the development of predictive and preventive medicine and personalized therapies.

A Selection Operator for Summary Association Statistics Reveals Allelic Heterogeneity of Complex Traits

In recent years, as a secondary analysis in genome-wide association studies (GWASs), conditional and joint multiple-SNP analysis (GCTA-COJO) has been successful in allowing the discovery of additional association signals within detected loci. This suggests that many loci mapped in GWASs harbor more than a single causal variant. In order to interpret the underlying mechanism regulating a complex trait of interest in each discovered locus, researchers must assess the magnitude of allelic heterogeneity within the locus. We developed a penalized selection operator for jointly analyzing multiple variants (SOJO) within each mapped locus on the basis of LASSO (least absolute shrinkage and selection operator) regression derived from summary association statistics. We found that, compared to stepwise conditional multiple-SNP analysis, SOJO provided better sensitivity and specificity in predicting the number of alleles associated with complex traits in each locus. SOJO suggested causal variants potentially missed by GCTA-COJO. Compared to using top variants from genome-wide significant loci in GWAS, using SOJO increased the proportion of variance prediction for height by 65% without additional discovery samples or additional loci in the genome. Our empirical results indicate that human height is not only a highly polygenic trait, but also has high allelic heterogeneity within its established hundreds of loci.

Exome-wide association study of plasma lipids in >300,000 individuals

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

Novel Common Variants Associated with Obesity and Type 2 Diabetes Detected Using a cFDR Method

Genome-wide association studies (GWASs) have been performed extensively in diverse populations to identify single nucleotide polymorphisms (SNPs) associated with complex diseases or traits. However, to date, the SNPs identified fail to explain a large proportion of the variance of the traits/diseases. GWASs on type 2 diabetes (T2D) and obesity are generally focused on individual traits independently, and genetic intercommunity (common genetic contributions or the product of over correlated phenotypic world) between them are largely unknown, despite extensive data showing that these two phenotypes share both genetic and environmental risk factors. Here, we applied a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with BMI and T2D by incorporating the summary statistics from existing GWASs of these two traits. Conditional Q-Q and fold enrichment plots were used to visually demonstrate the strength of pleiotropic enrichment. Adopting a cFDR nominal significance level of 0.05, 287 loci were identified for BMI and 75 loci for T2D, 23 of which for both traits. By incorporating related traits into a conditional analysis framework, we observed significant pleiotropic enrichment between obesity and T2D. These findings may provide novel insights into the etiology of obesity and T2D, individually and jointly.

Association of CpG-SNP and 3'UTR-SNP of WFS1 with the Risk of Type 2 Diabetes Mellitus in an Iranian Population

Type 2 diabetes mellitus (T2DM) is one of the most common multifactorial disorders in Iran. Recent genome wide association studies (GWASs) and functional studies have suggested that WFS1 may predispose individuals to T2DM. However, to date, the possible association of such variants with T2DM in Iranians remained unknown. Here, we investigated the association of the two polymorphisms of WFS1 (rs1801214 a CpG-SNP, and rs1046320 a 3’UTR-SNP) with T2DM in an Iranian population. The study population comprised 432 unrelated Iranian individuals including 220 patients with T2DM, and 211 unrelated healthy control subjects. Genotyping was performed using PCR-RFLP, and confirmed with sequencing. In a logistic regression analysis, the rs1801214-T allele was associated with a significantly lower risk of T2DM assuming the log-additive model (OR: 0.68, 95% CI: 0.52-0.91, P= 0.007539). Moreover, the G allele of rs1046320 was associated with a lower risk of T2DM assuming the log-additive model (OR: 0.68, 95% CI: 0.50- 0.91, P= 0.008313). Haplotype analysis revealed that haplotypes that carry at least one protective allele are associated with a lower risk of T2DM. This is a first evidence for the association of WFS1 rs1801214, and rs1046320 with T2DM in an Iranian population.

Genetic variants and acute kidney injury: A review of the literature

PURPOSE

Limited data exists on potential genetic contributors to acute kidney injury. This review examines current knowledge of AKI genomics.

MATERIALS AND METHODS

32 studies were selected from PubMed and GWAS Catalog queries for original data studies of human AKI genetics. Hand search of references identified 3 additional manuscripts.

RESULTS

33 of 35 studies were hypothesis-driven investigations of candidate polymorphisms that either did not consistently replicate statistically significant findings, or obtained significant results only in few small-scale studies. Vote-counting meta-analysis of 9 variants examined in >1 candidate gene study showed ≥50% non-significant studies, with larger studies generally finding non-significant results. The remaining 2 studies were large-scale unbiased investigations: One examining 2,100 genes linked with cardiovascular, metabolic, and inflammatory syndromes identified BCL2, SERPINA4, and SIK3 variants, while a genome-wide association study (GWAS) identified variants in BBS9 and the GRM7|LMCD1-AS1 intergenic region. All studies had relatively small sample sizes (<2300 subjects). Study heterogeneity precluded candidate gene and GWA meta-analysis.

CONCLUSIONS

Most studies of AKI genetics involve hypothesis-driven (rather than hypothesis-generating) candidate gene investigations that have failed to identify contributory variants consistently. A limited number of unbiased, larger-scale studies have been carried out, but there remains a pressing need for additional GWA studies.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PURPOSE OF REVIEW

The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction.

RECENT FINDINGS

In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.

Peripheral Arterial Disease Genetics: Progress to Date and Challenges Ahead

PURPOSE OF REVIEW

In this paper, we review the progress made thus far in research related to the genetics of peripheral arterial disease (PAD) by detailing efforts to date in heritability, linkage analyses, and candidate gene studies. We further summarize more contemporary genome-wide association studies (GWAS) and epigenetic studies of PAD. Finally, we review current challenges and future avenues of advanced research in PAD genetics including whole genome sequencing studies.

RECENT FINDINGS

Studies have estimated the heritability of PAD to be moderate, though the contribution to this heritability that is independent of traditional cardiovascular risk factors remains unclear. Recent efforts have identified SNPs associated with PAD in GWAS analyses, but these have yet to be replicated in independent studies. Much remains to be discovered in the field of PAD genetics. An improved understanding of the genetic foundation for PAD will allow for earlier diagnosis of disease and a more complete pathophysiological understanding of the mechanisms of the disease leading to novel therapeutic interventions. Future avenues for success will likely arise from very large-scale GWAS, whole genome sequencing, and epigenetic studies involving very well-characterized cohorts.

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10^-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia.

The genetic underpinnings of body fat distribution

Obesity, defined as a body mass index (BMI) ≥ 30 kg/m², has reached epidemic proportions; people who are overweight (BMI > 25 kg/m²) or obese now comprise more than 25% of the world's population. Obese individuals have a higher risk of comorbidity development including type 2 diabetes, cardiovascular disease, cancer, and fertility complications. Areas covered: The study of monogenic and syndromic forms of obesity have revealed a small number of genes key to metabolic perturbations. Further, obesity and body shape in the general population are highly heritable phenotypes. Study of obesity at the population level, through genome-wide association studies of BMI and waist-to-hip ratio (WHR), have revealed > 150 genomic loci that associate with these traits, and highlight the role of adipose tissue and the central nervous system in obesity-related traits. Studies in animal models and cell lines have helped further elucidate the potential biological mechanisms underlying obesity. In particular, these studies implicate adipogenesis and expansion of adipose tissue as key biological pathways in obesity and weight gain. Expert commentary: Further work, including a focus on integrating genetic and additional genomic data types, as well as modeling obesity-like features in vitro, will be crucial in translating genome-wide association signals to the causal mechanisms driving disease.

Phenome-wide association study using research participants' self-reported data provides insight into the Th17 and IL-17 pathway

A phenome-wide association study of variants in genes in the Th17 and IL-17 pathway was performed using self-reported phenotypes and genetic data from 521,000 research participants of 23andMe. Results replicated known associations with similar effect sizes for autoimmune traits illustrating self-reported traits can be a surrogate for clinically assessed conditions. Novel associations controlling for a false discovery rate of 5% included the association of the variant encoding p.Ile684Ser in TYK2 with increased risk of tonsillectomy, strep throat occurrences and teen acne, the variant encoding p.Arg381Gln in IL23R with a decrease in dandruff frequency, the variant encoding p.Asp10Asn in TRAF3IP2 with risk of male-pattern balding, and the RORC regulatory variant (rs4845604) with protection from allergies. This approach enabled rapid assessment of association with a wide variety of traits and investigation of traits with limited reported associations to overlay meaningful phenotypic context on the range of conditions being considered for drugs targeting this pathway.

GWAS identifies population-specific new regulatory variants in FUT6 associated with plasma B12 concentrations in Indians

Vitamin B12 is an important cofactor in one-carbon metabolism whose dysregulation is associated with various clinical conditions. Indians have a high prevalence of B12 deficiency but little is known about the genetic determinants of circulating B12 concentrations in Indians. We performed a genome-wide association study in 1001 healthy participants in the Pune Maternal Nutrition Study (PMNS), replication studies in 3418 individuals from other Indian cohorts and by meta-analysis identified new variants, rs3760775 (P = 1.2 × 10⁻²³) and rs78060698 (P = 8.3 × 10⁻¹⁷) in FUT6 to be associated with circulating B12 concentrations. Although in-silico analysis replicated both variants in Europeans, differences in the effect allele frequency, effect size and the linkage disequilibrium structure of credible set variants with the reported variants suggest population-specific characteristics in this region. We replicated previously reported variants rs602662, rs601338 in FUT2, rs3760776, rs708686 in FUT6, rs34324219 in TCN1 (all P < 5 × 10⁻⁸), rs1131603 in TCN2 (P = 3.4 × 10⁻⁵), rs12780845 in CUBN (P = 3.0 × 10⁻³) and rs2270655 in MMAA (P = 2.0 × 10⁻³). Circulating B12 concentrations in the PMNS and Parthenon study showed a significant decline with increasing age (P < 0.001), however, the genetic contribution to B12 concentrations remained constant. Luciferase reporter and electrophoretic-mobility shift assay for the FUT6 variant rs78060698 using HepG2 cell line demonstrated strong allele-specific promoter and enhancer activity and differential binding of HNF4α, a key regulator of expression of various fucosyltransferases. Hence, the rs78060698 variant, through regulation of fucosylation may control intestinal host-microbial interaction which could influence B12 concentrations. Our results suggest that in addition to established genetic variants, population-specific variants are important in determining plasma B12 concentrations.

Disentangling the Role of Melatonin and its Receptor MTNR1B in Type 2 Diabetes: Still a Long Way to Go?

PURPOSE OF REVIEW

Type 2 diabetes (T2D) is a complex genetic metabolic disorder. T2D heritability has been estimated around 40-70%. In the last decade, exponential progress has been made in identifying T2D genetic determinants, through genome-wide association studies (GWAS). Among single-nucleotide polymorphisms mostly associated with T2D risk, rs10830963 is located in the MTNR1B gene, encoding one of the two receptors of melatonin, a neurohormone involved in circadian rhythms. Subsequent studies aiming to disentangle the role of MTNR1B in T2D pathophysiology led to controversies. In this review, we will tackle them and will try to give some directions to get a better view of MTNR1B contribution to T2D pathophysiology.

RECENT FINDINGS

Recent studies either based on genetic/genomic analyses, clinical/epidemiology data, functional analyses at rs10830963 locus, insulin secretion assays in response to melatonin (involving or not MTNR1B) or animal model analyses have led to strong controversies at each level of interpretation. We discuss possible caveats in these studies and present ways to go beyond these issues, towards a better understanding of T2D molecular mechanisms, keeping in mind that melatonin is a versatile hormone and regulates many functions via its primary role in the body clock.

Improved Progression-Free Survival in Irinotecan-Treated Metastatic Colorectal Cancer Patients Carrying the HNF1A Coding Variant p.I27L

Hepatocyte nuclear factor 1-alpha (HNF1A) is a liver-enriched transcription factor that plays a key role in many aspects of hepatic functions including detoxification processes. We examined whether HNF1A polymorphisms are associated with clinical outcomes in two independent cohorts combining 417 European ancestry patients with metastatic colorectal cancer (mCRC) treated with irinotecan-based chemotherapy. The intronic rs2244608A>G marker was predictive of an improved progression-free survival with a trend in the Canadian cohort and reaching significance in the Italian cohort, with hazard ratios (HR) of 0.74 and 0.72, P = 0.076 and 0.038, respectively. A strong association between rs2244608A>G and improved PFS was found in the combined analysis of both cohorts (HR = 0.72; P = 0.002). Consistent with an altered HNF1A function, mCRC carriers of the rs2244608G minor allele displayed enhanced drug exposure by 45% (P = 0.032) compared to non-carriers. In Caucasians, rs2244608A>G is in strong linkage with the coding variant rs1169288c.79A>C (HNF1A p.I27L). In healthy donors, we observed an altered hepatic (ABCC1, P = 0.009, ABCC2, P = 0.048 and CYP3A5, P = 0.001; n = 89) and intestinal (TOP1, P = 0.004; n = 75) gene expression associated with the rs1169288C allele. In addition, the rs1169288C polymorphism could significantly increase the ABCC1 promoter activity by 27% (P = 0.008) and 15% (P = 0.041) in the human kidney HEK293 and the human liver HepG2 cell lines, respectively. Our findings suggest that the HNF1A rs2244608, or the tightly linked functional coding variant p.I27L, might be a potential prognostic marker with irinotecan-based regimens.

Gene Editing and Human Pluripotent Stem Cells: Tools for Advancing Diabetes Disease Modeling and Beta-Cell Development

PURPOSE OF REVIEW

This review will focus on the multiple approaches to gene editing and address the potential use of genetically modified human pluripotent stem cell-derived beta cells (SC-β) as a tool to study human beta-cell development and model their function in diabetes. We will explore how new variations of CRISPR/Cas9 gene editing may accelerate our understanding of beta-cell developmental biology, elucidate novel mechanisms that establish and regulate beta-cell function, and assist in pioneering new therapeutic modalities for treating diabetes.

RECENT FINDINGS

Improvements in CRISPR/Cas9 target specificity and homology-directed recombination continue to advance its use in engineering stem cells to model and potentially treat disease. We will review how CRISPR/Cas9 gene editing is informing our understanding of beta-cell development and expanding the therapeutic possibilities for treating diabetes and other diseases. Here we focus on the emerging use of gene editing technology, specifically CRISPR/Cas9, as a means of manipulating human gene expression to gain novel insights into the roles of key factors in beta-cell development and function. Taken together, the combined use of SC-β cells and CRISPR/Cas9 gene editing will shed new light on human beta-cell development and function and accelerate our progress towards developing new therapies for patients with diabetes.

The β-cell assassin: IAPP cytotoxicity

Islet amyloid polypeptide (IAPP) forms cytotoxic oligomers and amyloid fibrils in islets in type 2 diabetes (T2DM). The causal factors for amyloid formation are largely unknown. Mechanisms of molecular folding and assembly of human IAPP (hIAPP) into β-sheets, oligomers and fibrils have been assessed by detailed biophysical studies of hIAPP and non-fibrillogenic, rodent IAPP (rIAPP); cytotoxicity is associated with the early phases (oligomers/multimers) of fibrillogenesis. Interaction with synthetic membranes promotes β-sheet assembly possibly via a transient α-helical molecular conformation. Cellular hIAPP cytotoxicity can be activated from intracellular or extracellular sites. In transgenic rodents overexpressing hIAPP, intracellular pro-apoptotic signals can be generated at different points in β-cell protein synthesis. Increased cellular trafficking of proIAPP, failure of the unfolded protein response (UPR) or excess trafficking of misfolded peptide via the degradation pathways can induce apoptosis; these data indicate that defects in intracellular handling of hIAPP can induce cytotoxicity. However, there is no evidence for IAPP overexpression in T2DM. Extracellular amyloidosis is directly related to the degree of β-cell apoptosis in islets in T2DM. IAPP fragments, fibrils and multimers interact with membranes causing disruption in vivo and in vitro These findings support a role for extracellular IAPP in β-sheet conformation in cytotoxicity. Inhibitors of fibrillogenesis are useful tools to determine the aberrant mechanisms that result in hIAPP molecular refolding and islet amyloidosis. However, currently, their role as therapeutic agents remains uncertain.

An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome

We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of 411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.

DNA methylation in blood from neonatal screening cards and the association with BMI and insulin sensitivity in early childhood

BACKGROUND/OBJECTIVES

There is increasing evidence that metabolic diseases originate in early life, and epigenetic changes have been implicated as key drivers of this early life programming. This led to the hypothesis that epigenetic marks present at birth may predict an individual's future risk of obesity and type 2 diabetes. In this study, we assessed whether epigenetic marks in blood of newborn children were associated with body mass index (BMI) and insulin sensitivity later in childhood.

SUBJECTS/METHODS

DNA methylation was measured in neonatal blood spot samples of 438 children using the Illumina Infinium 450 k BeadChip. Associations were assessed between DNA methylation at birth and BMI z-scores, body fat mass, fasting plasma glucose, insulin and homeostatic model assessment of insulin resistance (HOMA-IR) at age 5 years, as well as birth weight, maternal BMI and smoking status.

RESULTS

No individual methylation sites at birth were associated with obesity or insulin sensitivity measures at 5 years. DNA methylation in 69 genomic regions at birth was associated with BMI z-scores at age 5 years, and in 63 regions with HOMA-IR. The methylation changes were generally small (<5%), except for a region near the non-coding RNA nc886 (VTRNA2-1) where a clear link between methylation status at birth and BMI in childhood was observed (P=0.001). Associations were also found between DNA methylation, maternal smoking and birth weight.

CONCLUSIONS

We identified a number of DNA methylation regions at birth that were associated with obesity or insulin sensitivity measurements in childhood. These findings support the mounting evidence on the role of epigenetics in programming of metabolic health. Whether many of these small changes in DNA methylation are causally related to the health outcomes, and of clinical relevance, remains to be determined, but the nc886 region represents a promising obesity risk marker that warrants further investigation.

Alpha TC1 and Beta-TC-6 genomic profiling uncovers both shared and distinct transcriptional regulatory features with their primary islet counterparts

Alpha TC1 (αTC1) and Beta-TC-6 (βTC6) mouse islet cell lines are cellular models of islet (dys)function and type 2 diabetes (T2D). However, genomic characteristics of these cells, and their similarities to primary islet alpha and beta cells, are undefined. Here, we report the epigenomic (ATAC-seq) and transcriptomic (RNA-seq) landscapes of αTC1 and βTC6 cells. Each cell type exhibits hallmarks of its primary islet cell counterpart including cell-specific expression of beta (e.g., Pdx1) and alpha (e.g., Arx) cell transcription factors (TFs), and enrichment of binding motifs for these TFs in αTC1/βTC6 cis-regulatory elements. αTC1/βTC6 transcriptomes overlap significantly with the transcriptomes of primary mouse/human alpha and beta cells. Our data further indicate that ATAC-seq detects cell-specific regulatory elements for cell types comprising ≥ 20% of a mixed cell population. We identified αTC1/βTC6 cis-regulatory elements orthologous to those containing type 2 diabetes (T2D)-associated SNPs in human islets for 33 loci, suggesting these cells’ utility to dissect T2D molecular genetics in these regions. Together, these maps provide important insights into the conserved regulatory architecture between αTC1/βTC6 and primary islet cells that can be leveraged in functional (epi)genomic approaches to dissect the genetic and molecular factors controlling islet cell identity and function.

Advancing stroke genomic research in the age of Trans-Omics big data science: Emerging priorities and opportunities

BACKGROUND

We systematically reviewed the genetic variants associated with stroke in genome-wide association studies (GWAS) and examined the emerging priorities and opportunities for rapidly advancing stroke research in the era of Trans-Omics science.

METHODS

Using the PRISMA guideline, we searched PubMed and NHGRI- EBI GWAS catalog for stroke studies from 2007 till May 2017.

RESULTS

We included 31 studies. The major challenge is that the few validated variants could not account for the full genetic risk of stroke and have not been translated for clinical use. None of the studies included continental Africans. Genomic study of stroke among Africans presents a unique opportunity for the discovery, validation, functional annotation, Trans-Omics study and translation of genomic determinants of stroke with implications for global populations. This is because all humans originated from Africa, a continent with a unique genomic architecture and a distinctive epidemiology of stroke; as well as substantially higher heritability and resolution of fine mapping of stroke genes.

CONCLUSION

Understanding the genomic determinants of stroke and the corresponding molecular mechanisms will revolutionize the development of a new set of precise biomarkers for stroke prediction, diagnosis and prognostic estimates as well as personalized interventions for reducing the global burden of stroke.

Molecular and functional genetics of the proopiomelanocortin gene, food intake regulation and obesity

A specter is haunting the world, the specter of obesity. During the last decade, this pandemia has skyrocketed threatening children, adolescents and lower income families worldwide. Although driven by an increase in the consumption of ultraprocessed edibles of poor nutritional value, the obesogenic changes in contemporary human lifestyle affect people differently, revealing that some individuals are more prone to develop increased adiposity. During the last years, we performed a variety of genetic, evolutionary, biochemical and behavioral experiments that allowed us to understand how a group of neurons present in the arcuate nucleus of the hypothalamus regulate the expression of the proopiomelanocortin (Pomc) gene and induce satiety. We disentangled the neuronal transcriptional code of Pomc by identifying the cis-acting regulatory elements and primary transcription factors controlling hypothalamic Pomc expression and determined their functional importance in the regulation of food intake and adiposity. Altogether, our studies reviewed here shed light on the power and limitations of the mammalian central satiety pathways and may contribute to the development of individual and collective strategies to reduce the debilitating effects of the self-induced obesity pandemia.

Prioritising Causal Genes at Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Genome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.

RECENT FINDINGS

Candidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues. Prioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics.

The Role of Obesity, Type 2 Diabetes, and Metabolic Factors in Pancreatic Cancer: A Mendelian Randomization Study

Background

Risk factors for pancreatic cancer include a cluster of metabolic conditions such as obesity, hypertension, dyslipidemia, insulin resistance, and type 2 diabetes. Given that these risk factors are correlated, separating out causal from confounded effects is challenging. Mendelian randomization (MR), or the use of genetic instrumental variables, may facilitate the identification of the metabolic drivers of pancreatic cancer.

Methods

We identified genetic instruments for obesity, body shape, dyslipidemia, insulin resistance, and type 2 diabetes in order to evaluate their causal role in pancreatic cancer etiology. These instruments were analyzed in relation to risk using a likelihood-based MR approach within a series of 7110 pancreatic cancer patients and 7264 control subjects using genome-wide data from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Potential unknown pleiotropic effects were assessed using a weighted median approach and MR-Egger sensitivity analyses.

Results

Results indicated a robust causal association of increasing body mass index (BMI) with pancreatic cancer risk (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.09 to 1.65, for each standard deviation increase in BMI [4.6 kg/m2]). There was also evidence that genetically increased fasting insulin levels were causally associated with an increased risk of pancreatic cancer (OR = 1.66, 95% CI = 1.05 to 2.63, per SD [44.4 pmol/L]). Notably, no evidence of a causal relationship was observed for type 2 diabetes, nor for dyslipidemia. Sensitivity analyses did not indicate that pleiotropy was an important source of bias.

Conclusions

Our results suggest a causal role of BMI and fasting insulin in pancreatic cancer etiology.

Mechanisms of Type 2 Diabetes Risk Loci

PURPOSE OF REVIEW

Deciphering the mechanisms of type 2 diabetes (T2DM) risk loci can greatly inform on disease pathology. This review discusses current knowledge of mechanisms through which genetic variants influence T2DM risk and considerations for future studies.

RECENT FINDINGS

Over 100 T2DM risk loci to date have been identified. Candidate causal variants at risk loci map predominantly to non-coding sequence. Physiological, epigenomic and gene expression data suggest that variants at many known T2DM risk loci affect pancreatic islet regulation, although variants at other loci also affect protein function and regulatory processes in adipose, pre-adipose, liver, skeletal muscle and brain. The effects of T2DM variants on regulatory activity in these tissues appear largely, but not exclusively, due to altered transcription factor binding. Putative target genes of T2DM variants have been defined at an increasing number of loci and some, such as FTO, may entail several genes and multiple tissues. Gene networks in islets and adipocytes have been implicated in T2DM risk, although the molecular pathways of risk genes remain largely undefined. Efforts to fully define the mechanisms of T2DM risk loci are just beginning. Continued identification of risk mechanisms will benefit from combining genetic fine-mapping with detailed phenotypic association data, high-throughput epigenomics data from diabetes-relevant tissue, functional screening of candidate genes and genome editing of cellular and animal models.

Constraints on eQTL Fine Mapping in the Presence of Multisite Local Regulation of Gene Expression

Expression quantitative trait locus (eQTL) detection has emerged as an important tool for unraveling of the relationship between genetic risk factors and disease or clinical phenotypes. Most studies use single marker linear regression to discover primary signals, followed by sequential conditional modeling to detect secondary genetic variants affecting gene expression. However, this approach assumes that functional variants are sparsely distributed and that close linkage between them has little impact on estimation of their precise location and the magnitude of effects. We describe a series of simulation studies designed to evaluate the impact of linkage disequilibrium (LD) on the fine mapping of causal variants with typical eQTL effect sizes. In the presence of multisite regulation, even though between 80 and 90% of modeled eSNPs associate with normally distributed traits, up to 10% of all secondary signals could be statistical artifacts, and at least 5% but up to one-quarter of credible intervals of SNPs within r² > 0.8 of the peak may not even include a causal site. The Bayesian methods eCAVIAR and DAP (Deterministic Approximation of Posteriors) provide only modest improvement in resolution. Given the strong empirical evidence that gene expression is commonly regulated by more than one variant, we conclude that the fine mapping of causal variants needs to be adjusted for multisite influences, as conditional estimates can be highly biased by interference among linked sites, but ultimately experimental verification of individual effects is needed. Presumably similar conclusions apply not just to eQTL mapping, but to multisite influences on fine mapping of most types of quantitative trait.

10 Years of GWAS Discovery: Biology, Function, and Translation

Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

Fasting Insulin is Better Partitioned according to Family History of Type 2 Diabetes Mellitus than Post Glucose Load Insulin of Oral Glucose Tolerance Test in Young Adults

INTRODUCTION

Hyperinsulinemia is contributed by insulin resistance, hepatic insulin uptake, insulin secretion and rate of insulin degradation. Family history of type 2 diabetes mellitus has been reported to cause hyperinsulinemia.

AIM

Correlation of fasting insulin with post glucose load Oral Glucose Tolerance Test (OGTT) insulin in young adults and their partitioning according to family history of type 2 diabetes.

MATERIALS AND METHODS

In this observational cross-sectional study, clinical evaluation and biochemical assays of insulin and diabetes related parameters, and secondary clinical influences on type 2 diabetes in volunteers were done for inclusion as participants (n=90) or their exclusion. Cut off levels of quantitative biochemical variables were fixed such that they included the effects of insulin resistance, but excluded other secondary clinical influences. Distribution was analysed by Shapiro-Wilk test; equality of variances by Levene's test; Log₁₀ transformations for conversion of groups to Gaussian distribution and for equality of variances in the groups compared. When the groups compared had Gaussian distribution and there was equality of variance, parametric methods were used. Otherwise, non parametric methods were used.

RESULTS

Fasting insulin was correlating significantly with 30, 60 and 120 minute OGTT insulin showing that hyperinsulinemia in the fasting state was related to hyperinsulinemia in the post glucose load states. When fasting and post glucose load OGTT insulin were partitioned into those without and with family history of type 2 diabetes, maximum difference was seen in fasting insulin (p<0.001), followed by 120 (p=0.001) and 60 (p= 0.002) minute OGTT insulin. The 30 minute insulin could not be partitioned (p=0.574).

CONCLUSION

Fasting, 60 and 120 minute OGTT insulin can be partitioned according to family history of type 2 diabetes, demonstrating stratification and heterogeneity in the insulin sample. Of these, fasting insulin was better partitioned and could be used for baseline reference interval calculations.