Analysis of rare coding variants in 200,000 exome-sequenced subjects reveals novel genetic risk factors for type 2 diabetes

Whole exome sequencing analysis identifies genes for alcohol consumption

Alcohol consumption is a heritable behavior seriously endangers human health. However, genetic studies on alcohol consumption primarily focuses on common variants, while insights from rare coding variants are lacking. Here we leverage whole exome sequencing data across 304,119 white British individuals from UK Biobank to identify protein-coding variants associated with alcohol consumption. Twenty-five variants are associated with alcohol consumption through single variant analysis and thirteen genes through gene-based analysis, ten of which have not been reported previously. Notably, the two unreported alcohol consumption-related genes GIGYF1 and ANKRD12 show enrichment in brain function-related pathways including glial cell differentiation and are strongly expressed in the cerebellum. Phenome-wide association analyses reveal that alcohol consumption-related genes are associated with brain white matter integrity and risk of digestive and neuropsychiatric diseases. In summary, this study enhances the comprehension of the genetic architecture of alcohol consumption and implies biological mechanisms underlying alcohol-related adverse outcomes.

Investigation of Recessive Effects of Coding Variants on Common Clinical Phenotypes in Exome-Sequenced UK Biobank Participants

INTRODUCTION

Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes.

METHODS

In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency ≤0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes.

RESULTS

No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2.

CONCLUSION

It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.

The first exome wide association study in Tunisia: identification of candidate loci and pathways with biological relevance for type 2 diabetes

Introduction

Type 2 diabetes (T2D) is a multifactorial disease involving genetic and environmental components. Several genome-wide association studies (GWAS) have been conducted to decipher potential genetic aberrations promoting the onset of this metabolic disorder. These GWAS have identified over 400 associated variants, mostly in the intronic or intergenic regions. Recently, a growing number of exome genotyping or exome sequencing experiments have identified coding variants associated with T2D. Such studies were mainly conducted in European populations, and the few candidate-gene replication studies in North African populations revealed inconsistent results. In the present study, we aimed to discover the coding genetic etiology of T2D in the Tunisian population.

Methods

We carried out a pilot Exome Wide Association Study (EWAS) on 50 Tunisian individuals. Single variant analysis was performed as implemented in PLINK on potentially deleterious coding variants. Subsequently, we applied gene-based and gene-set analyses using MAGMA software to identify genes and pathways associated with T2D. Potential signals were further replicated in an existing large in-silico dataset, involving up to 177116 European individuals.

Results

Our analysis revealed, for the first time, promising associations between T2D and variations in MYORG gene, implicated in the skeletal muscle fiber development. Gene-set analysis identified two candidate pathways having nominal associations with T2D in our study samples, namely the positive regulation of neuron apoptotic process and the regulation of mucus secretion. These two pathways are implicated in the neurogenerative alterations and in the inflammatory mechanisms of metabolic diseases. In addition, replication analysis revealed nominal associations of the regulation of beta-cell development and the regulation of peptidase activity pathways with T2D, both in the Tunisian subjects and in the European in-silico dataset.

Conclusions

The present study is the first EWAS to investigate the impact of single genetic variants and their aggregate effects on T2D risk in Africa. The promising disease markers, revealed by our pilot EWAS, will promote the understanding of the T2D pathophysiology in North Africa as well as the discovery of potential treatments.

The inverse association between DNA gaps and HbA1c levels in type 2 diabetes mellitus

Naturally occurring DNA gaps have been observed in eukaryotic DNA, including DNA in nondividing cells. These DNA gaps are found less frequently in chronologically aging yeast, chemically induced senescence cells, naturally aged rats, D-galactose-induced aging model rats, and older people. These gaps function to protect DNA from damage, so we named them youth-associated genomic stabilization DNA gaps (youth-DNA-gaps). Type 2 diabetes mellitus (type 2 DM) is characterized by an early aging phenotype. Here, we explored the correlation between youth-DNA-gaps and the severity of type 2 DM. Here, we investigated youth-DNA-gaps in white blood cells from normal controls, pre-DM, and type 2 DM patients. We found significantly decreased youth-DNA-gap numbers in the type 2 DM patients compared to normal controls (P = 0.0377, P = 0.0018 adjusted age). In the type 2 DM group, youth-DNA-gaps correlate directly with HbA1c levels. (r = - 0.3027, P = 0.0023). Decreased youth-DNA-gap numbers were observed in patients with type 2 DM and associated with increased HbA1c levels. Therefore, the decrease in youth-DNA-gaps is associated with the molecular pathogenesis of high blood glucose levels. Furthermore, youth-DNA-gap number is another marker that could be used to determine the severity of type 2 DM.

Decreased Alu methylation in type 2 diabetes mellitus patients increases HbA1c levels

INTRODUCTION

Alu hypomethylation is a common epigenetic process that promotes genomic instability with aging phenotypes, which leads to type 2 diabetes mellitus (type 2 DM). Previously, our results showed significantly decreased Alu methylation levels in type 2 DM patients. In this study, we aimed to investigate the longitudinal changes in Alu methylation levels in these patients.

RESULTS

We observed significantly decreased Alu methylation levels in type 2 DM patients compared with normal (p = 0.0462). Moreover, our findings demonstrated changes in Alu hypomethylation over a follow-up period within the same individuals (p < 0.0001). A reduction in Alu methylation was found in patients with increasing HbA1c levels (p = 0.0013) and directly correlated with increased HbA1c levels in type 2 DM patients (r = -0.2273, p = 0.0387).

CONCLUSIONS

Alu methylation in type 2 DM patients progressively decreases with increasing HbA1c levels. This observation suggests a potential association between Alu hypomethylation and the underlying molecular mechanisms of elevated blood glucose. Furthermore, monitoring Alu methylation levels may serve as a valuable biomarker for assessing the clinical outcomes of type 2 DM.

Damaging missense variants in IGF1R implicate a role for IGF-1 resistance in the etiology of type 2 diabetes

Type 2 diabetes (T2D) is a heritable metabolic disorder. While population studies have identified hundreds of common genetic variants associated with T2D, the role of rare (frequency < 0.1%) protein-coding variation is less clear. We performed exome sequence analysis in 418,436 (n = 32,374 T2D cases) individuals in the UK Biobank. We identified previously reported genes (GCK, GIGYF1, HNF1A) in addition to missense variants in ZEB2 (n = 31 carriers; odds ratio [OR] = 5.5 [95% confidence interval = 2.5-12.0]; p = 6.4 × 10^-7), MLXIPL (n = 245; OR = 2.3 [1.6-3.2]; p = 3.2 × 10^-7), and IGF1R (n = 394; OR = 2.4 [1.8-3.2]; p = 1.3 × 10^-10). Carriers of damaging missense variants within IGF1R were also shorter (-2.2 cm [-1.8 to -2.7]; p = 1.2 × 10^-19) and had higher circulating insulin-like growth factor-1 (IGF-1) protein levels (2.3 nmol/L [1.7-2.9]; p = 2.8 × 10^-14), indicating relative IGF-1 resistance. A likely causal role of IGF-1 resistance was supported by Mendelian randomization analyses using common variants. These results increase understanding of the genetic architecture of T2D and highlight the growth hormone/IGF-1 axis as a potential therapeutic target.

Cerebral Polymorphisms for Lateralisation: Modelling the Genetic and Phenotypic Architectures of Multiple Functional Modules

Recent fMRI and fTCD studies have found that functional modules for aspects of language, praxis, and visuo-spatial functioning, while typically left, left and right hemispheric respectively, frequently show atypical lateralisation. Studies with increasing numbers of modules and participants are finding increasing numbers of module combinations, which here are termed cerebral polymorphisms—qualitatively different lateral organisations of cognitive functions. Polymorphisms are more frequent in left-handers than right-handers, but it is far from the case that right-handers all show the lateral organisation of modules described in introductory textbooks. In computational terms, this paper extends the original, monogenic McManus DC (dextral-chance) model of handedness and language dominance to multiple functional modules, and to a polygenic DC model compatible with the molecular genetics of handedness, and with the biology of visceral asymmetries found in primary ciliary dyskinesia. Distributions of cerebral polymorphisms are calculated for families and twins, and consequences and implications of cerebral polymorphisms are explored for explaining aphasia due to cerebral damage, as well as possible talents and deficits arising from atypical inter- and intra-hemispheric modular connections. The model is set in the broader context of the testing of psychological theories, of issues of laterality measurement, of mutation-selection balance, and the evolution of brain and visceral asymmetries.

Weighted burden analysis in 200,000 exome-sequenced subjects characterises rare variant effects on BMI

INTRODUCTION

A number of genes have been identified in which rare variants can cause obesity. Here we analyse a sample of exome sequenced subjects from UK Biobank using BMI as a phenotype with the aims of identifying genes in which rare, functional variants influence BMI and characterising the effects of different categories of variant.

METHODS

There were 199,807 exome sequenced subjects for whom BMI was recorded. Weighted burden analysis of rare, functional variants was carried out, incorporating population principal components and sex as covariates. For selected genes, additional analyses were carried out to clarify the contribution of different categories of variant. Statistical significance was summarised as the signed log 10 of the p value (SLP), given a positive sign if the weighted burden score was positively correlated with BMI.

RESULTS

Two genes were exome-wide significant, MC4R (SLP = 15.79) and PCSK1 (SLP = 6.61). In MC4R, disruptive variants were associated with an increase in BMI of 2.72 units and probably damaging nonsynonymous variants with an increase of 2.02 units. In PCSK1, disruptive variants were associated with a BMI increase of 2.29 and protein-altering variants with an increase of 0.34. Results for other genes were not formally significant after correction for multiple testing, although SIRT1, ZBED6 and NPC2 were noted to be of potential interest.

CONCLUSION

Because the UK Biobank consists of a self-selected sample of relatively healthy volunteers, the effect sizes noted may be underestimates. The results demonstrate the effects of very rare variants on BMI and suggest that other genes and variants will be definitively implicated when the sequence data for additional subjects becomes available.