Inês Barroso

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and ∼2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 × 10−14), CDC123-CAMK1D (P = 1.2 × 10−10), TSPAN8-LGR5 (P = 1.1 × 10−9), THADA (P = 1.1 × 10−9), ADAMTS9 (P = 1.2 × 10−8) and NOTCH2 (P = 4.1 × 10−8) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Dominant negative mutations in human PPARγ associated with severe insulin resistance, diabetes mellitus and hypertension

Thiazolidinediones are a new class of antidiabetic agent that improve insulin sensitivity and reduce plasma glucose and blood pressure in subjects with type 2 diabetes. Although these agents can bind and activate an orphan nuclear receptor, peroxisome proliferator-activated receptor gamma (PPARγ), there is no direct evidence to conclusively implicate this receptor in the regulation of mammalian glucose homeostasis. Here we report two different heterozygous mutations in the ligand-binding domain of PPARγ in three subjects with severe insulin resistance. In the PPARγ crystal structure, the mutations destabilize helix 12 which mediates transactivation. Consistent with this, both receptor mutants are markedly transcriptionally impaired and, moreover, are able to inhibit the action of coexpressed wild-type PPARγ in a dominant negative manner. In addition to insulin resistance, all three subjects developed type 2 diabetes mellitus and hypertension at an unusually early age. Our findings represent the first germline loss-of-function mutations in PPARγ and provide compelling genetic evidence that this receptor is important in the control of insulin sensitivity, glucose homeostasis and blood pressure in man.

The Obesity-Associated FTO Gene Encodes a 2-Oxoglutarate–Dependent Nucleic Acid Demethylase

Variants in the FTO (fat mass and obesity associated) gene are associated with increased body mass index in humans. Here, we show by bioinformatics analysis that FTO shares sequence motifs with Fe(II)- and 2-oxoglutarate–dependent oxygenases. We find that recombinant murine Fto catalyzes the Fe(II)- and 2OG-dependent demethylation of 3-methylthymine in single-stranded DNA, with concomitant production of succinate, formaldehyde, and carbon dioxide. Consistent with a potential role in nucleic acid demethylation, Fto localizes to the nucleus in transfected cells. Studies of wild-type mice indicate that Fto messenger RNA (mRNA) is most abundant in the brain, particularly in hypothalamic nuclei governing energy balance, and that Fto mRNA levels in the arcuate nucleus are regulated by feeding and fasting. Studies can now be directed toward determining the physiologically relevant FTO substrate and how nucleic acid methylation status is linked to increased fat mass.

The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits

Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the “Metabochip,” a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.

The architecture of gene regulatory variation across multiple human tissues: the MuTHER study.

While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis—MCTA) permits immediate replication of eQTLs using co-twins (93%–98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%–20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.

LDL-cholesterol concentrations: a genome-wide association study

Summary Background LDL cholesterol has a causal role in the development of cardiovascular disease. Improved understanding of the biological mechanisms that underlie the metabolism and regulation of LDL cholesterol might help to identify novel therapeutic targets. We therefore did a genome-wide association study of LDL-cholesterol concentrations. Methods We used genome-wide association data from up to 11 685 participants with measures of circulating LDL-cholesterol concentrations across five studies, including data for 293 461 autosomal single nucleotide polymorphisms (SNPs) with a minor allele frequency of 5% or more that passed our quality control criteria. We also used data from a second genome-wide array in up to 4337 participants from three of these five studies, with data for 290 140 SNPs. We did replication studies in two independent populations consisting of up to 4979 participants. Statistical approaches, including meta-analysis and linkage disequilibrium plots, were used to refine association signals; we analysed pooled data from all seven populations to determine the effect of each SNP on variations in circulating LDL-cholesterol concentrations. Findings In our initial scan, we found two SNPs (rs599839 [p=1·7×10−15] and rs4970834 [p=3·0×10−11]) that showed genome-wide statistical association with LDL cholesterol at chromosomal locus 1p13.3. The second genome screen found a third statistically associated SNP at the same locus (rs646776 [p=4·3×10−9]). Meta-analysis of data from all studies showed an association of SNPs rs599839 (combined p=1·2×10−33) and rs646776 (p=4·8×10−20) with LDL-cholesterol concentrations. SNPs rs599839 and rs646776 both explained around 1% of the variation in circulating LDL-cholesterol concentrations and were associated with about 15% of an SD change in LDL cholesterol per allele, assuming an SD of 1 mmol/L. Interpretation We found evidence for a novel locus for LDL cholesterol on chromosome 1p13.3. These results potentially provide insight into the biological mechanisms that underlie the regulation of LDL cholesterol and might help in the discovery of novel therapeutic targets for cardiovascular disease.

Common variants in WFS1 confer risk of type 2 diabetes

We studied genes involved in pancreatic β cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.

Candidate Gene Association Study in Type 2 Diabetes Indicates a Role for Genes Involved in β-Cell Function as Well as Insulin Action

Type 2 diabetes is an increasingly common, serious metabolic disorder with a substantial inherited component. It is characterised by defects in both insulin secretion and action. Progress in identification of specific genetic variants predisposing to the disease has been limited. To complement ongoing positional cloning efforts, we have undertaken a large-scale candidate gene association study. We examined 152 SNPs in 71 candidate genes for association with diabetes status and related phenotypes in 2,134 Caucasians in a case-control study and an independent quantitative trait (QT) cohort in the United Kingdom. Polymorphisms in five of 15 genes (33%) encoding molecules known to primarily influence pancreatic β-cell function—ABCC8 (sulphonylurea receptor), KCNJ11 (KIR6.2), SLC2A2 (GLUT2), HNF4A (HNF4α), and INS (insulin)—significantly altered disease risk, and in three genes, the risk allele, haplotype, or both had a biologically consistent effect on a relevant physiological trait in the QT study. We examined 35 genes predicted to have their major influence on insulin action, and three (9%)—INSR, PIK3R1, and SOS1—showed significant associations with diabetes. These results confirm the genetic complexity of Type 2 diabetes and provide evidence that common variants in genes influencing pancreatic β-cell function may make a significant contribution to the inherited component of this disease. This study additionally demonstrates that the systematic examination of panels of biological candidate genes in large, well-characterised populations can be an effective complement to positional cloning approaches. The absence of large single-gene effects and the detection of multiple small effects accentuate the need for the study of larger populations in order to reliably identify the size of effect we now expect for complex diseases.

A Comprehensive Evaluation of Potential Lung Function Associated Genes in the SpiroMeta General Population Sample

Rationale Lung function measures are heritable traits that predict population morbidity and mortality and are essential for the diagnosis of chronic obstructive pulmonary disease (COPD). Variations in many genes have been reported to affect these traits, but attempts at replication have provided conflicting results. Recently, we undertook a meta-analysis of Genome Wide Association Study (GWAS) results for lung function measures in 20,288 individuals from the general population (the SpiroMeta consortium). Objectives To comprehensively analyse previously reported genetic associations with lung function measures, and to investigate whether single nucleotide polymorphisms (SNPs) in these genomic regions are associated with lung function in a large population sample. Methods We analysed association for SNPs tagging 130 genes and 48 intergenic regions (+/−10 kb), after conducting a systematic review of the literature in the PubMed database for genetic association studies reporting lung function associations. Results The analysis included 16,936 genotyped and imputed SNPs. No loci showed overall significant association for FEV1 or FEV1/FVC traits using a carefully defined significance threshold of 1.3×10−5. The most significant loci associated with FEV1 include SNPs tagging MACROD2 (P = 6.81×10−5), CNTN5 (P = 4.37×10−4), and TRPV4 (P = 1.58×10−3). Among ever-smokers, SERPINA1 showed the most significant association with FEV1 (P = 8.41×10−5), followed by PDE4D (P = 1.22×10−4). The strongest association with FEV1/FVC ratio was observed with ABCC1 (P = 4.38×10−4), and ESR1 (P = 5.42×10−4) among ever-smokers. Conclusions Polymorphisms spanning previously associated lung function genes did not show strong evidence for association with lung function measures in the SpiroMeta consortium population. Common SERPINA1 polymorphisms may affect FEV1 among smokers in the general population.

Genetics of Type 2 diabetes.

Type 2 diabetes (T2D) has become a health‐care problem worldwide, with the rise in disease prevalence being all the more worrying as it not only affects the developed world but also developing nations with fewer resources to cope with yet another major disease burden. Furthermore, the problem is no longer restricted to the ageing population, as young adults and children are also being diagnosed with T2D. In recent years, there has been a surge in the number of genetic studies of T2D in attempts to identify some of the underlying risk factors. In this review, I highlight the main genes known to cause uncommon monogenic forms of diabetes (e.g. maturity‐onset diabetes of the young—MODY—and insulin resistance syndromes), as well as describe some of the main approaches used to identify genes involved in the more common forms of T2D that result from the interaction between environmental risk factors and predisposing genotypes. Linkage and candidate gene studies have been highly successful in the identification of genes that cause the monogenic variants of diabetes and, although progress in the more common forms of T2D has been slow, a number of genes have now been reproducibly associated with T2D risk in multiple studies. These are discussed, as well as the main implications that the diabetes gene discoveries will have in diabetes treatment and prevention.