Performance and Stability of New Class of Fetal Bovine Sera (FBS) and Its Lyophilized Form in ELISpot and FluoroSpot Assays: Applications for Monitoring the Immune Response in Vaccine, and Cell and Gene Immunotherapy in Clinical Trials

Interferon-gamma (IFNγ) ELISpot and FluoroSpot are widely used assays to detect functional cell responses in immunotherapy clinical studies. Recognized for their importance in vaccine development studies to quantitate immune responses, these assays have more recently risen to the forefront in cell and gene therapy as well as cancer immunotherapy fields where responses against cancer neoantigens are not easily detectable above assay background. Here, we test a new class of fetal bovine serum (FBS), CultraPure FBS, in ex vivo ELISpot and FluoroSpot assays and cultured FluoroSpot assays following in vitro expansion. Several CultraPure FBS lots that have been specially formulated through the process of lyophilization (lyo-FBS) were compared to liquid CultraPure FBS. We stimulated human PBMCs with antigen-specific peptide pools diluted in media supplemented with liquid CultraPure FBS or lyo-FBS and found equivalent cytokine production with negligible to no assay background with both liquid and lyo-FBS formats. Moreover, the lyo-FBS showed lot-to-lot consistency and 90-day refrigerated (4 °C) stability in both ex vivo direct and in vitro cultured assays. In addition, we present here a method using lyo-FBS for the expansion of low-frequency antigen-specific T cells, mimicking the low frequency seen with cancer neoantigens by utilizing a cultured FluoroSpot assay. Our results demonstrate the presence of Granzyme B, interferon-gamma (IFNγ), and tumor necrosis factor (TNF) production by antigen-specific polyfunctional T cells following a 9-day culture using media supplemented with lyo-FBS.

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in 2020. Testing is crucial for mitigating public health and economic effects. Serology is considered key to population-level surveillance and potentially individual-level risk assessment. However, immunoassay performance has not been compared on large, identical sample sets. We aimed to investigate the performance of four high-throughput commercial SARS-CoV-2 antibody immunoassays and a novel 384-well ELISA.

METHODS

We did a head-to-head assessment of SARS-CoV-2 IgG assay (Abbott, Chicago, IL, USA), LIAISON SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Saluggia, Italy), Elecsys Anti-SARS-CoV-2 assay (Roche, Basel, Switzerland), SARS-CoV-2 Total assay (Siemens, Munich, Germany), and a novel 384-well ELISA (the Oxford immunoassay). We derived sensitivity and specificity from 976 pre-pandemic blood samples (collected between Sept 4, 2014, and Oct 4, 2016) and 536 blood samples from patients with laboratory-confirmed SARS-CoV-2 infection, collected at least 20 days post symptom onset (collected between Feb 1, 2020, and May 31, 2020). Receiver operating characteristic (ROC) curves were used to assess assay thresholds.

FINDINGS

At the manufacturers' thresholds, for the Abbott assay sensitivity was 92·7% (95% CI 90·2-94·8) and specificity was 99·9% (99·4-100%); for the DiaSorin assay sensitivity was 96·2% (94·2-97·7) and specificity was 98·9% (98·0-99·4); for the Oxford immunoassay sensitivity was 99·1% (97·8-99·7) and specificity was 99·0% (98·1-99·5); for the Roche assay sensitivity was 97·2% (95·4-98·4) and specificity was 99·8% (99·3-100); and for the Siemens assay sensitivity was 98·1% (96·6-99·1) and specificity was 99·9% (99·4-100%). All assays achieved a sensitivity of at least 98% with thresholds optimised to achieve a specificity of at least 98% on samples taken 30 days or more post symptom onset.

INTERPRETATION

Four commercial, widely available assays and a scalable 384-well ELISA can be used for SARS-CoV-2 serological testing to achieve sensitivity and specificity of at least 98%. The Siemens assay and Oxford immunoassay achieved these metrics without further optimisation. This benchmark study in immunoassay assessment should enable refinements of testing strategies and the best use of serological testing resource to benefit individuals and population health.

FUNDING

Public Health England and UK National Institute for Health Research.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium

AIMS/HYPOTHESIS

Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up).

METHODS

From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe.

RESULTS

Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m²; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m²; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants' clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l.

CONCLUSIONS/INTERPRETATION

The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes.

Plasma Fucosylated Glycans and C-Reactive Protein as Biomarkers of HNF1A-MODY in Young Adult-Onset Nonautoimmune Diabetes

OBJECTIVE

Maturity-onset diabetes of the young (MODY) due to variants in HNF1A is the most common type of monogenic diabetes. Frequent misdiagnosis results in missed opportunity to use sulfonylureas as first-line treatment. A nongenetic biomarker could improve selection of subjects for genetic testing and increase diagnosis rates. We previously reported that plasma levels of antennary fucosylated N-glycans and high-sensitivity C-reactive protein (hs-CRP) are reduced in individuals with HNF1A-MODY. In this study, we examined the potential use of N-glycans and hs-CRP in discriminating individuals with damaging HNF1A alleles from those without HNF1A variants in an unselected population of young adults with nonautoimmune diabetes.

RESEARCH DESIGN AND METHODS

We analyzed the plasma N-glycan profile, measured hs-CRP, and sequenced HNF1A in 989 individuals with diabetes diagnosed when younger than age 45, persistent endogenous insulin production, and absence of pancreatic autoimmunity. Systematic assessment of rare HNF1A variants was performed.

RESULTS

We identified 29 individuals harboring 25 rare HNF1A alleles, of which 3 were novel, and 12 (in 16 probands) were considered pathogenic. Antennary fucosylated N-glycans and hs-CRP were able to differentiate subjects with damaging HNF1A alleles from those without rare HNF1A alleles. Glycan GP30 had a receiver operating characteristic curve area under the curve (AUC) of 0.90 (88% sensitivity, 80% specificity, cutoff 0.70%), whereas hs-CRP had an AUC of 0.83 (88% sensitivity, 69% specificity, cutoff 0.81 mg/L).

CONCLUSIONS

Half of rare HNF1A sequence variants do not cause MODY. N-glycan profile and hs-CRP could both be used as tools, alone or as adjuncts to existing pathways, for identifying individuals at high risk of carrying a damaging HNF1A allele.

Baseline Plasma Cell Gene Signature Predicts Improvement in Systemic Sclerosis Skin Scores Following Treatment With Inebilizumab (MEDI-551) and Correlates With Disease Activity in Systemic Lupus Erythematosus and Chronic Obstructive Pulmonary Disease

OBJECTIVE

B cells impact the progression of systemic sclerosis (SSc; scleroderma) through multiple pathogenic mechanisms. CD19 inhibition in mice reduced skin thickness, collagen production, and autoantibody levels, consistent with CD19 expression on plasma cells (PCs), the source of antibody production. PC depletion could effectively reduce collagen deposition and inflammation in SSc; therefore, we investigated the effects of PC depletion on SSc disease activity.

METHODS

A PC gene signature was evaluated in SSc skin biopsy samples in 2 phase I clinical trials. We assessed microarray data from tissue from public studies of chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), dermatomyositis (DM), systemic lupus erythematosus (SLE), and atopic dermatitis, as well as blood from a phase IIb clinical trial in SLE.

RESULTS

The PC signature was elevated in SSc skin specimens compared to healthy donor skin (P = 2.28 × 10^-6 ) and correlated with the baseline modified Rodnan skin thickness score (MRSS) (r = 0.64, P = 0.0004). Patients with a high PC signature at baseline showed greater improvement in the MRSS (mean ± SD change 35 ± 16%; P = 6.30 × 10^-4 ) following anti-CD19 treatment with inebilizumab (MEDI-551) than did patients with a low PC signature at baseline (mean ± SD change 8 ± 12%; P = 0.104). The PC signature was overexpressed in tissue from patients with SLE, DM, COPD, interstitial lung disease, and IPF relative to controls (all fold change >2; P < 0.001). The PC signature also differed significantly between SLE patients with mild-to-moderate disease and those with severe disease (SLE Disease Activity Index cutoff at 10) (fold change 1.44; P = 3.90 × 10^-3 ) and correlated significantly with the degree of emphysema in COPD (r = 0.53, P = 7.55 × 10^-8 ).

CONCLUSION

Our results support the notion that PCs have a role in the pathogenesis of SSc and other autoimmune or pulmonary indications. An elevated pretreatment PC signature was associated with increased benefit from MEDI-551 in SSc.

Type 2 diabetes risk alleles in PAM impact insulin release from human pancreatic β-cells

The molecular mechanisms underpinning susceptibility loci for type 2 diabetes (T2D) remain poorly understood. Coding variants in peptidylglycine α-amidating monooxygenase (PAM) are associated with both T2D risk and insulinogenic index. Here, we demonstrate that the T2D risk alleles impact negatively on overall PAM activity via defects in expression and catalytic function. PAM deficiency results in reduced insulin content and altered dynamics of insulin secretion in a human β-cell model and primary islets from cadaveric donors. Thus, our results demonstrate a role for PAM in β-cell function, and establish molecular mechanisms for T2D risk alleles at this locus.

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

This corrects the article DOI: 10.1038/sdata.2017.179.

Integrative network analysis highlights biological processes underlying GLP-1 stimulated insulin secretion: A DIRECT study

Glucagon-like peptide 1 (GLP-1) stimulated insulin secretion has a considerable heritable component as estimated from twin studies, yet few genetic variants influencing this phenotype have been identified. We performed the first genome-wide association study (GWAS) of GLP-1 stimulated insulin secretion in non-diabetic individuals from the Netherlands Twin register (n = 126). This GWAS was enhanced using a tissue-specific protein-protein interaction network approach. We identified a beta-cell protein-protein interaction module that was significantly enriched for low gene scores based on the GWAS P-values and found support at the network level in an independent cohort from Tübingen, Germany (n = 100). Additionally, a polygenic risk score based on SNPs prioritized from the network was associated (P < 0.05) with glucose-stimulated insulin secretion phenotypes in up to 5,318 individuals in MAGIC cohorts. The network contains both known and novel genes in the context of insulin secretion and is enriched for members of the focal adhesion, extracellular-matrix receptor interaction, actin cytoskeleton regulation, Rap1 and PI3K-Akt signaling pathways. Adipose tissue is, like the beta-cell, one of the target tissues of GLP-1 and we thus hypothesized that similar networks might be functional in both tissues. In order to verify peripheral effects of GLP-1 stimulation, we compared the transcriptome profiling of ob/ob mice treated with liraglutide, a clinically used GLP-1 receptor agonist, versus baseline controls. Some of the upstream regulators of differentially expressed genes in the white adipose tissue of ob/ob mice were also detected in the human beta-cell network of genes associated with GLP-1 stimulated insulin secretion. The findings provide biological insight into the mechanisms through which the effects of GLP-1 may be modulated and highlight a potential role of the beta-cell expressed genes RYR2, GDI2, KIAA0232, COL4A1 and COL4A2 in GLP-1 stimulated insulin secretion.

Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose-raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.

A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication. We identified 30 new blood pressure- or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.

Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin

Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10^-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Human genetic studies have demonstrated that quantitative human anthropometric and metabolic traits, including body mass index, waist-hip ratio, and plasma concentrations of glucose and insulin, are highly heritable, and are established risk factors for type 2 diabetes and cardiovascular diseases. Although many regions of the genome have been associated with these traits, the specific genes responsible have not yet been identified. By making use of advanced statistical “imputation” techniques applied to more than 87,000 individuals of European ancestry, and publicly available “reference panels” of more than 37 million genetic variants, we have been able to identify novel regions of the genome associated with these glycaemic and obesity-related traits and localise genes within these regions that are most likely to be causal. This improved understanding of the biological mechanisms underlying glycaemic and obesity-related traits is extremely important because it may advance drug development for downstream disease endpoints, ultimately leading to public health benefits.

New genetic loci link adipose and insulin biology to body fat distribution

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted genome-wide association meta-analyses of waist and hip circumference-related traits in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (WHRadjBMI) and an additional 19 loci newly associated with related waist and hip circumference measures (P<5×10⁻⁸). Twenty of the 49 WHRadjBMI loci showed significant sexual dimorphism, 19 of which displayed a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation, and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

Understanding how FI and FG levels are regulated is important because their derangement is a feature of T2D. Despite recent success from GWAS in identifying regions of the genome influencing glycemic traits, collectively these loci explain only a small proportion of trait variance. Unlocking the biological mechanisms driving these associations has been challenging because the vast majority of variants map to non-coding sequence, and the genes through which they exert their impact are largely unknown. In the current study, we sought to increase our understanding of the physiological pathways influencing both traits using exome-array genotyping in up to 33,231 non-diabetic individuals to identify coding variants and consequently genes associated with either FG or FI levels. We identified novel association signals for both traits including the receptor for GLP-1 agonists which are a widely used therapy for T2D. Furthermore, we identified coding variants at several GWAS loci which point to the genes underlying these association signals. Importantly, we found that multiple coding variants in G6PC2 result in a loss of protein function and lower fasting glucose levels.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Evaluation of common type 2 diabetes risk variants in a South Asian population of Sri Lankan descent

INTRODUCTION

Most studies seeking common variant associations with type 2 diabetes (T2D) have focused on individuals of European ancestry. These discoveries need to be evaluated in other major ancestral groups, to understand ethnic differences in predisposition, and establish whether these contribute to variation in T2D prevalence and presentation. This study aims to establish whether common variants conferring T2D-risk in Europeans contribute to T2D-susceptibility in the South Asian population of Sri Lanka.

METHODOLOGY

Lead single nucleotide polymorphism (SNPs) at 37 T2D-risk loci attaining genome-wide significance in Europeans were genotyped in 878 T2D cases and 1523 normoglycaemic controls from Sri Lanka. Association testing was performed by logistic regression adjusting for age and sex and by the Cochran-Mantel-Haenszel test after stratifying according to self-identified ethnolinguistic subgroup. A weighted genetic risk score was generated to examine the combined effect of these SNPs on T2D-risk in the Sri Lankan population.

RESULTS

Of the 36 SNPs passing quality control, sixteen showed nominal (p<0.05) association in Sri Lankan samples, fifteen of those directionally-consistent with the original signal. Overall, these association findings were robust to analyses that accounted for membership of ethnolinguistic subgroups. Overall, the odds ratios for 31 of the 36 SNPs were directionally-consistent with those observed in Europeans (p = 3.2×10(-6)). Allelic odds ratios and risk allele frequencies in Sri Lankan subjects were not systematically different to those reported in Europeans. Genetic risk score and risk of T2D were strongly related in Sri Lankans (per allele OR 1.10 [95%CI 1.08-1.13], p = 1.2×10(-17)).

CONCLUSION

Our data indicate that most T2D-risk variants identified in Europeans have similar effects in South Asians from Sri Lanka, and that systematic difference in common variant associations are unlikely to explain inter-ethnic differences in prevalence or presentation of T2D.

The plasma cell signature in autoimmune disease

OBJECTIVE

Production of pathogenic autoantibodies by self-reactive plasma cells (PCs) is a hallmark of autoimmune diseases. We undertook this study to investigate the prevalence of PCs and their relationship to known pathogenic pathways to increase our understanding of the role of PCs in disease progression and treatment response.

METHODS

We developed a sensitive gene expression-based method to overcome the challenges of measuring PCs using flow cytometry. Whole-genome microarray analysis of sorted cellular fractions identified a panel of genes, IGHA1, IGJ, IGKC, IGKV4-1, and TNFRSF17, expressed predominantly in PCs. The sensitivity of the PC signature score created from the combined expression levels of these genes was assessed through ex vivo experiments with sorted cells. This PC gene expression signature was used for monitoring changes in PC levels following anti-CD19 therapy, for evaluating the relationship between PCs and other autoimmune disease-related genes, and for estimating PC levels in affected blood and tissue from patients with multiple autoimmune diseases.

RESULTS

The PC signature was highly sensitive and capable of detecting a change in as few as 360 PCs. The PC signature was reduced more than 90% in scleroderma patients following anti-CD19 treatment, and this reduction was highly correlated (r = 0.80) with inhibition of collagen gene expression. Evaluation of multiple autoimmune diseases revealed that 30-35% of lupus and rheumatoid arthritis patients had increased levels of PCs.

CONCLUSION

This newly developed PC signature provides a robust and accurate method of measuring PC levels in the clinic. Our results highlight subsets of patients across multiple autoimmune diseases who may benefit from PC-depleting therapy.

BMI-associated alleles do not constitute risk alleles for polycystic ovary syndrome independently of BMI: a case-control study

Introduction

Polycystic Ovary Syndrome (PCOS) has a strong genetic background and the majority of patients with PCOS have elevated BMI levels. The aim of this study was to determine to which extent BMI-increasing alleles contribute to risk of PCOS when contemporaneous BMI is taken into consideration.

Methods

Patients with PCOS and controls were recruited from the United Kingdom (563 cases and 791 controls) and The Netherlands (510 cases and 2720 controls). Cases and controls were of similar BMI. SNPs mapping to 12 BMI-associated loci which have been extensively replicated across different ethnicities, i.e., BDNF, FAIM2, ETV5, FTO, GNPDA2, KCTD15, MC4R, MTCH2, NEGR1, SEC16B, SH2B1, and TMEM18, were studied in association with PCOS within each cohort using the additive genetic model followed by a combined analysis. A genetic allelic count risk score model was used to determine the risk of PCOS for individuals carrying increasing numbers of BMI-increasing alleles.

Results

None of the genetic variants, including FTO and MC4R, was associated with PCOS independently of BMI in the meta-analysis. Moreover, no differences were observed between cases and controls in the number of BMI-risk alleles present and no overall trend across the risk score groups was observed.

Conclusion

In this combined analysis of over 4,000 BMI-matched individuals from the United Kingdom and the Netherlands, we observed no association of BMI risk alleles with PCOS independent of BMI.

Discovery and refinement of loci associated with lipid levels

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Common variants associated with plasma triglycerides and risk for coronary artery disease

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10⁻⁸ for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies

Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.

Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts

Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 U.S. and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = -0.004 mmol/L, 95% confidence interval: -0.005, -0.003) and FI (β = -0.008 ln-pmol/L, 95% confidence interval: -0.009, -0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.

Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis.

A genome-wide association search for type 2 diabetes genes in African Americans

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

A role for coding functional variants in HNF4A in type 2 diabetes susceptibility

AIMS/HYPOTHESIS

Rare mutations in the gene HNF4A, encoding the transcription factor hepatocyte nuclear factor 4α (HNF-4A), account for ~5% of cases of MODY and more frequent variants in this gene may be involved in multifactorial forms of diabetes. Two low-frequency, non-synonymous variants in HNF4A (V255M, minor allele frequency [MAF] ~0.1%; T130I, MAF ~3.0%)-known to influence downstream HNF-4A target gene expression-are of interest, but previous type 2 diabetes association reports were inconclusive. We aimed to evaluate the contribution of these variants to type 2 diabetes susceptibility through large-scale association analysis.

METHODS

We genotyped both variants in at least 5,745 cases and 14,756 population controls from the UK and Denmark. We also undertook an expanded association analysis that included previously reported and novel genotype data obtained in Danish, Finnish, Canadian and Swedish samples. A meta-analysis incorporating all published association studies of the T130I variant was subsequently carried out in a maximum sample size of 14,279 cases and 26,835 controls.

RESULTS

We found no association between V255M and type 2 diabetes in either the initial (p = 0.28) or the expanded analysis (p = 0.44). However, T130I demonstrated a modest association with type 2 diabetes in the UK and Danish samples (additive per allele OR 1.17 [95% CI 1.08-1.28]; p = 1.5 × 10⁻⁴), which was strengthened in the meta-analysis (OR 1.20 [95% CI 1.10-1.30]; p = 2.1 × 10⁻⁵).

CONCLUSIONS/INTERPRETATION

Our data are consistent with T130I as a low-frequency variant influencing type 2 diabetes risk, but are not conclusive when judged against stringent standards for genome-wide significance. This study exemplifies the difficulties encountered in association testing of low-frequency variants.

Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies

OBJECTIVE

Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.

RESEARCH DESIGN AND METHODS

Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.

RESULTS

Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.

CONCLUSIONS

Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis

By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P<5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.

Large-scale association analysis of TNF/LTA gene region polymorphisms in type 2 diabetes

Background

The TNF/LTA locus has been a long-standing T2D candidate gene. Several studies have examined association of TNF/LTA SNPs with T2D but the majority have been small-scale and produced no convincing evidence of association. The purpose of this study is to examine T2D association of tag SNPs in the TNF/LTA region capturing the majority of common variation in a large-scale sample set of UK/Irish origin.

Methods

This study comprised a case-control (1520 cases and 2570 control samples) and a family-based component (423 parent-offspring trios). Eleven tag SNPs (rs928815, rs909253, rs746868, rs1041981 (T60N), rs1800750, rs1800629 (G-308A), rs361525 (G-238A), rs3093662, rs3093664, rs3093665, and rs3093668) were selected across the TNF/LTA locus and genotyped using a fluorescence-based competitive allele specific assay. Quality control of the obtained genotypes was performed prior to single- and multi-point association analyses under the additive model.

Results

We did not find any consistent SNP associations with T2D in the case-control or family-based datasets.

Conclusions

The present study, designed to analyse a set of tag SNPs specifically selected to capture the majority of common variation in the TNF/LTA gene region, found no robust evidence for association with T2D. To investigate the presence of smaller effects of TNF/LTA gene variation with T2D, a large-scale meta-analysis will be required.

Meta-analysis and functional effects of the SLC30A8 rs13266634 polymorphism on isolated human pancreatic islets

BACKGROUND

The C-allele of rs13266634 located in SLC30A8 (ZNT8) has been strongly associated with decreased insulin release and with type 2 diabetes (T2D) susceptibility in some but not all studies. To shed further light on this issue, we performed a meta-analysis of the association between rs13266634 and T2D in different ethnic groups and assessed the relationships between SLC30A8 genotypes and some properties of isolated human islets.

METHODS

From 32 original articles, a total of 77,234 control individuals and 44,945 subjects with T2D were studied in meta-analysis. To assess the relationships between SLC30A8 genotype and islet cell phenotype, insulin secretion in response to glucose, glucose plus arginine and glucose plus glibenclamide was determined in pancreatic islets isolated from 82 multiorgan donors genotyped for the rs13266634 polymorphism. Quantitative expression of SLC30A8, Insulin and Glucagon mRNA was also measured.

RESULTS

Overall, each SLC30A8 risk allele was associated with a 14% increased risk for T2D (P=2.78 x 10(-34)). The population risk of T2D attributable to this polymorphism was estimated at 9.5% in Europeans and 8.1% in East Asians. Basal and stimulated insulin secretion from human islets as well as islet expressions of SLC30A8, Insulin and Glucagon were not affected by the presence of the polymorphism. However, SLC30A8 expression was positively correlated with Insulin (r=0.75, P=6.43 x 10(-6)) and Glucagon (r: 0.70, P=4.89 x 10(-5)) levels.

CONCLUSIONS

The SLC30A8 rs13266634 polymorphism is among the most confirmed genetic markers of T2D in Europeans and East Asians. In isolated human islets, the risk C-allele does not affect ex-vivo insulin secretion and SLC30A8 expression, which is correlated with that of insulin and glucagon.

Musculoskeletal Ultrasound: Audit of Sonographer Reporting

Musculoskeletal (MSK) ultrasound performed by non-medical practitioners is a developing practice. The aim of this paper is: (1) to audit an experienced sonographer's (SJR) performance after one year's independent reporting against two experienced MSK radiologists (CJG, MC); and (2) to establish an audit standard against which such role development might be contrived. Images and reports from 250 MSK ultrasound examinations performed by a sonographer (SJR) were reviewed independently by two consultant MSK radiologists (CJG and MC). The examinations were graded for discrepancy, e.g. grade 1 – agree with the sonographer report; grade 2 – minor discrepancy unlikely to alter patient care; grade 3 – potentially significant discrepancy; grade 4 – definite, significant discrepancy likely to have adverse consequences for patient care. Two of 250 (0.8%) cases were excluded. Both radiologists agreed completely with the sonographer (grade 1) in 235 of the 248 cases (94.8%). In 13 cases there was discrepancy between the reports of SJR and the radiologists. The discrepancy was grade 2 in six of the 248 cases (2.4%), grade 3 in six of the 248 cases (2.4%) and grade 4 in one of the 248 cases (0.4%). In conclusion, this audit shows a high level of agreement between the sonographer and the consultant MSK radiologist reporting of MSK ultrasound. This level of agreement may set the standard for future quality assurance audit of sonographer MSK reporting.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

Genetic evidence that raised sex hormone binding globulin (SHBG) levels reduce the risk of type 2 diabetes

Epidemiological studies consistently show that circulating sex hormone binding globulin (SHBG) levels are lower in type 2 diabetes patients than non-diabetic individuals, but the causal nature of this association is controversial. Genetic studies can help dissect causal directions of epidemiological associations because genotypes are much less likely to be confounded, biased or influenced by disease processes. Using this Mendelian randomization principle, we selected a common single nucleotide polymorphism (SNP) near the SHBG gene, rs1799941, that is strongly associated with SHBG levels. We used data from this SNP, or closely correlated SNPs, in 27 657 type 2 diabetes patients and 58 481 controls from 15 studies. We then used data from additional studies to estimate the difference in SHBG levels between type 2 diabetes patients and controls. The SHBG SNP rs1799941 was associated with type 2 diabetes [odds ratio (OR) 0.94, 95% CI: 0.91, 0.97; P = 2 x 10(-5)], with the SHBG raising allele associated with reduced risk of type 2 diabetes. This effect was very similar to that expected (OR 0.92, 95% CI: 0.88, 0.96), given the SHBG-SNP versus SHBG levels association (SHBG levels are 0.2 standard deviations higher per copy of the A allele) and the SHBG levels versus type 2 diabetes association (SHBG levels are 0.23 standard deviations lower in type 2 diabetic patients compared to controls). Results were very similar in men and women. There was no evidence that this variant is associated with diabetes-related intermediate traits, including several measures of insulin secretion and resistance. Our results, together with those from another recent genetic study, strengthen evidence that SHBG and sex hormones are involved in the aetiology of type 2 diabetes.

Sequencing of candidate genes selected by beta cell experts in monogenic diabetes of unknown aetiology

CONTEXT

Approximately 39% of cases with permanent neonatal diabetes (PNDM) and about 11% with maturity onset diabetes of the young (MODY) have an unknown genetic aetiology. Many of the known genes causing MODY and PNDM were identified as being critical for beta cell function before their identification as a cause of monogenic diabetes.

OBJECTIVE

We used nominations from the EU beta cell consortium EURODIA project partners to guide gene candidacy.

SUBJECTS

Seventeen cases with permanent neonatal diabetes and 8 cases with maturity onset diabetes of the young.

MAIN OUTCOME MEASURES

The beta cell experts within the EURODIA consortium were asked to nominate 3 "gold", 3 "silver" and 4 "bronze" genes based on biological or genetic grounds. We sequenced twelve candidate genes from the list based on evidence for candidacy.

RESULTS

Sequencing ISL1, LMX1A, MAFA, NGN3, NKX2.2, NKX6.1, PAX4, PAX6, SOX2, SREBF1, SYT9 and UCP2 did not identify any pathogenic mutations.

CONCLUSION

Further work is needed to identify novel causes of permanent neonatal diabetes and maturity onset diabetes of the young utilising genetic approaches as well as further candidate genes.

Low frequency variants in the exons only encoding isoform A of HNF1A do not contribute to susceptibility to type 2 diabetes

Background

There is considerable interest in the hypothesis that low frequency, intermediate penetrance variants contribute to the proportion of Type 2 Diabetes (T2D) susceptibility not attributable to the common variants uncovered through genome-wide association approaches. Genes previously implicated in monogenic and multifactorial forms of diabetes are obvious candidates in this respect. In this study, we focussed on exons 8–10 of the HNF1A gene since rare, penetrant mutations in these exons (which are only transcribed in selected HNF1A isoforms) are associated with a later age of diagnosis of Maturity onset diabetes of the young (MODY) than mutations in exons 1–7. The age of diagnosis in the subgroup of HNF1A-MODY individuals with exon 8–10 mutations overlaps with that of early multifactorial T2D, and we set out to test the hypothesis that these exons might also harbour low-frequency coding variants of intermediate penetrance that contribute to risk of multifactorial T2D.

Methodology and Principal Findings

We performed targeted capillary resequencing of HNF1A exons 8–10 in 591 European T2D subjects enriched for genetic aetiology on the basis of an early age of diagnosis (≤45 years) and/or family history of T2D (≥1 affected sibling). PCR products were sequenced and compared to the published HNF1A sequence. We identified several variants (rs735396 [IVS9−24T>C], rs1169304 [IVS8+29T>C], c.1768+44C>T [IVS9+44C>T] and rs61953349 [c.1545G>A, p.T515T] but no novel non-synonymous coding variants were detected.

Conclusions and Significance

We conclude that low frequency, nonsynonymous coding variants in the terminal exons of HNF1A are unlikely to contribute to T2D-susceptibility in European samples. Nevertheless, the rationale for seeking low-frequency causal variants in genes known to contain rare, penetrant mutations remains strong and should motivate efforts to screen other genes in a similar fashion.

Linkage disequilibrium mapping of the replicated type 2 diabetes linkage signal on chromosome 1q

OBJECTIVE

Linkage of the chromosome 1q21-25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23-Mb interval in a multiethnic sample to search for variants responsible for this linkage signal.

RESEARCH DESIGN AND METHODS

In all, 5,290 single nucleotide polymorphisms (SNPs) were successfully genotyped in 3,179 type 2 diabetes case and control subjects from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q linkage. After imputation, we estimate approximately 80% coverage of common variation across the region (r (2) > 0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in approximately 8,500 case subjects and 12,400 control subjects.

RESULTS

Association mapping of the 23-Mb region identified two strong signals, both of which were restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, odds ratio 1.38 [95% CI 1.21-1.57], P = 1.4 x 10(-6), in 999 case subjects and 1,190 control subjects); the second mapped within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, odds ratio 1.48 [1.18-1.76], P = 1.0 x 10(-5), under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), there was no indication that these variants were causally related to type 2 diabetes status.

CONCLUSIONS

Detailed fine-mapping of the 23-Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.

Type 2 diabetes risk alleles are associated with reduced size at birth

OBJECTIVE

Low birth weight is associated with an increased risk of type 2 diabetes. The mechanisms underlying this association are unknown and may represent intrauterine programming or two phenotypes of one genotype. The fetal insulin hypothesis proposes that common genetic variants that reduce insulin secretion or action may predispose to type 2 diabetes and also reduce birth weight, since insulin is a key fetal growth factor. We tested whether common genetic variants that predispose to type 2 diabetes also reduce birth weight.

RESEARCH DESIGN AND METHODS

We genotyped single-nucleotide polymorphisms (SNPs) at five recently identified type 2 diabetes loci (CDKAL1, CDKN2A/B, HHEX-IDE, IGF2BP2, and SLC30A8) in 7,986 mothers and 19,200 offspring from four studies of white Europeans. We tested the association between maternal or fetal genotype at each locus and birth weight of the offspring.

RESULTS

We found that type 2 diabetes risk alleles at the CDKAL1 and HHEX-IDE loci were associated with reduced birth weight when inherited by the fetus (21 g [95% CI 11-31], P = 2 x 10(-5), and 14 g [4-23], P = 0.004, lower birth weight per risk allele, respectively). The 4% of offspring carrying four risk alleles at these two loci were 80 g (95% CI 39-120) lighter at birth than the 8% carrying none (P(trend) = 5 x 10(-7)). There were no associations between birth weight and fetal genotypes at the three other loci or maternal genotypes at any locus.

CONCLUSIONS

Our results are in keeping with the fetal insulin hypothesis and provide robust evidence that common disease-associated variants can alter size at birth directly through the fetal genotype.

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Association of variants in the fat mass and obesity associated (FTO) gene with polycystic ovary syndrome

AIMS/HYPOTHESIS

Variants in the fat-mass and obesity-associated gene (FTO) influence susceptibility to type 2 diabetes via an effect on adiposity/obesity. Given the important role of obesity in the aetiology of both polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus, our aim was to establish whether FTO variants are also implicated in PCOS susceptibility.

METHODS

We performed a genetic association study of FTO variant rs9939609 using case-control analyses, conducted in 463 PCOS patients (geometric mean BMI 27.5 kg/m(2)) and 1,336 female controls (geometric mean BMI 25.3 kg/m(2)) of UK British/Irish origin. We also sought evidence for associations between FTO variation and circulating testosterone levels in 324 UK PCOS patients and 1,000 women from the Northern Finland Birth Cohort of 1966. Outcome measures included FTO rs9939609 genotype frequencies by participant group and androgen measures (testosterone, free androgen index) by genotype.

RESULTS

There was a significant association between FTO genotype and PCOS status in the UK case-control analysis, which was attenuated by adjustment for BMI (Cochran-Armitage test, odds ratio [per minor allele copy] 1.30 [95% CI 1.12, 1.51], p = 7.2 x 10(-4) [unadjusted], p = 2.9 x 10(-3) [adjusted]). This association was most evident in obese PCOS patients (PCOS patients below median BMI vs UK controls, p = 0.11; above median BMI vs controls, p = 2.9 x 10(-4)). No relationship between FTO genotype and androgen levels was seen.

CONCLUSIONS/INTERPRETATION

We provide the first evidence that variants that predispose to common obesity also result in altered susceptibility to PCOS, confirming the mechanistic link between these conditions. The predominant effect of FTO variants on PCOS susceptibility is probably mediated through adiposity.

Common variants near MC4R are associated with fat mass, weight and risk of obesity

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.

Prevalence and clinical characteristics of maternally inherited diabetes and deafness caused by the mt3243A > G mutation in young adult diabetic subjects in Sri Lanka

AIMS

The maternally inherited mt3243A > G mutation is associated with a variable clinical phenotype including diabetes and deafness (MIDD). We aimed to determine the prevalence and clinical characteristics of MIDD in a large South Asian cohort of young adult-onset diabetic patients from Sri Lanka.

METHODS

DNA was available from 994 subjects (age of diagnosis 16-40 years, age at recruitment < or = 45 years). Mutation screening was performed using a QRT-PCR method on an ABI 7900HT system using sequence-specific probes. Samples with heteroplasm > or = 5.0% were considered positive.

RESULTS

Nine (four males) mutation-positive subjects were identified (prevalence 0.9%). They were diagnosed at a younger age (25.9 +/- 4.8 years vs. 31.9 +/- 5.6 years, P = 0.002) and were lean (body mass index [BMI] 18.7 +/- 2.7 kg/m(2) vs. 24.7 +/- 4.0 kg/m(2), P < 0.001) compared to NMCs. One mutation-positive subject (11.1%) had metabolic syndrome, compared to 633 (64.3%) of NMCs. Insulin therapy within 6 months of diagnosis was used in four (44.0%) carriers compared to 6.9% of NMCs (P = 0.002). Combined screening criteria of any two of maternal history of diabetes, personal history of hearing impairment and family history of hearing impairment only identified five (55%) of the carriers, with a positive predictive value of 7.4%.

CONCLUSIONS

The prevalence of mt3243A > G mutation among young adult-onset diabetic subjects from Sri Lanka was 0.9%. Our study demonstrates that a maternal family history of diabetes and either a personal and/or family history of deafness only distinguish half of patients with MIDD from Sri Lankan subjects with young-onset diabetes.

Disparate genetic influences on polycystic ovary syndrome (PCOS) and type 2 diabetes revealed by a lack of association between common variants within the TCF7L2 gene and PCOS

AIMS/HYPOTHESIS

Common variants of the gene encoding transcription factor 7-like 2 (TCF7L2) have a powerful effect on individual risk of type 2 diabetes (per allele odds ratio approximately 1.35). Polycystic ovary syndrome (PCOS) and type 2 diabetes are familial conditions sharing common features. Based on this, the aim of the present study was to establish whether variation in TCF7L2 also influences the development of PCOS.

METHODS

We conducted a genetic association study of variants of TCF7L2 (rs7903146 and rs12255372) using both case-control and quantitative trait approaches. Case-control analyses were conducted in (1) 369 PCOS cases and 2574 controls of UK British/Irish origin, and (2) 540 women with PCOS symptoms and 1083 controls from the Northern Finland Birth Cohort of 1966. Quantitative trait analyses (androgen levels) were also performed (1249 individuals).

RESULTS

There was no association between rs7903146 and PCOS in the UK case-control study (Cochran-Armitage test, p = 0.51); nor with symptomatic status in the Finnish cohort (p = 0.36). In addition, there were no relationships between the TCF7L2 single nucleotide polymorphism rs7903146 and androgen levels (UK cases, p = 0.99; Finnish controls, p = 0.57; Finnish symptomatic cases, p = 0.80). Results at rs12255372 were similar, reflecting strong linkage disequilibrium with rs7903146.

CONCLUSIONS/INTERPRETATION

Our study was powered to detect an effect on PCOS susceptibility similar to that previously reported for these variants on type 2 diabetes. Failure to detect any evident association with PCOS provides the strongest evidence yet that the genetic architecture of these related conditions is qualitatively distinct.