Timothy M Frayling

University of Exeter, Exeter, England, United Kingdom

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Publications (253)2911.12 Total impact

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    ABSTRACT: Arising from G. Hemani et al. 508, 249-253 (2014); doi:10.1038/nature13005Epistasis occurs when the effect of a genetic variant on a trait is dependent on genotypes of other variants elsewhere in the genome. Hemani et al. recently reported the detection and replication of many instances of epistasis between pairs of variants influencing gene expression levels in humans. Using whole-genome sequencing data from 450 individuals we strongly replicated many of the reported interactions but, in each case, a single third variant captured by our sequencing data could explain all of the apparent epistasis. Our results provide an alternative explanation for the apparent epistasis observed for gene expression in humans. There is a Reply to this Brief Communication Arising by Hemani, G. et al. Nature 514, http://dx.doi.org/10.1038/nature13692 (2014).
    Nature 10/2014; 514(7520):E3-5. · 38.60 Impact Factor
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    Timothy M Frayling
    Lancet. 09/2014;
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    ABSTRACT: MicroRNAs (miRNA) play a crucial role in the regulation of diverse biological processes by post-transcriptional modulation of gene expression. Genetic polymorphisms in miRNA-related genes can potentially contribute to a wide range of phenotypes. The effect of such variants on cardiometabolic diseases has not yet been defined. We systematically investigated the association of genetic variants in the seed regions of miRNAs with cardiometabolic phenotypes, using the thus far largest genome wide association studies on 17 cardiometabolic traits/diseases. We found that rs2168518:G>A, a seed region variant of miR-4513, associates with fasting glucose, LDL-cholesterol and total cholesterol, systolic and diastolic blood pressure and risk of coronary artery disease. We experimentally showed that miR-4513 expression is significantly reduced in presence of the rs2168518 mutant allele. We sought to identify miR-4513 target genes that may mediate these associations and revealed five genes (PCSK1, BNC2, MTMR3, ANK3 and GOSR2) through which these effects might be taking place. Using luciferase reporter assays we validated GOSR2 as a target of miR-4513 and further demonstrated that the miRNA mediated regulation of this gene is changed by rs2168518. Our findings indicate a pleiotropic effect of miR-4513 on cardiometabolic phenotypes and may improve our understanding of the pathophysiology of cardiometabolic diseases.This article is protected by copyright. All rights reserved
    Human Mutation 09/2014; · 5.21 Impact Factor
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    ABSTRACT: The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.
    PLoS Genetics 07/2014; · 8.52 Impact Factor
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    ABSTRACT: The mechanisms that predispose to hypertension, coronary artery disease (CAD) and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy - a reduction in subcutaneous adipose tissue - it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, coronary artery disease and type 2 diabetes. We aimed to test the hypothesis that common alleles associated with insulin resistance also influence the wider clinical and biochemical profile of monogenic insulin resistance. We selected 19 common genetic variants associated with fasting insulin based measures of insulin resistance. We used hierarchical clustering and results from genome wide association studies of 8 non-disease outcomes of monogenic insulin resistance, to group these variants. We analysed genetic risk scores against disease outcomes including 12,171 T2D cases, 40,365 CAD cases and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle, form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (ß=0.018; p=4x10(-29)), lower HDL cholesterol (ß=-0.020; p=7x10(-37)), greater hepatic steatosis (ß=0.021; p=3x10(-4)) higher alanine transaminase (ß=0.002; p=3x10(-5)), lower SHBG (ß=-0.010; p=9x10(-13)) and lower adiponectin (ß=-0.015; p=2x10(-26)). The same risk alleles were associated with lower BMI (per-allele ß=-0.008; p=7x10(-8)), and increased visceral-to-subcutaneous adipose tissue ratio (ß=-0.015; p=6x10(-7)). Individuals carrying >= 17 fasting insulin raising alleles (5.5% population) were slimmer (0.30 kgm(-2)) but at increased risk of T2D (odds ratio [OR] 1.46, per-allele p=5x10(-13)), CAD (OR 1.12, per-allele p=1x10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg (per-allele p=2x10(-5)), and 0.67 mmHg (per-allele p=2x10(-4)), respectively, compared to individuals carrying <=9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism.
    Diabetes 07/2014; · 7.90 Impact Factor
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    ABSTRACT: Background Low plasma 25-hydroxyvitamin D (25[OH]D) concentration is associated with high arterial blood pressure and hypertension risk, but whether this association is causal is unknown. We used a mendelian randomisation approach to test whether 25(OH)D concentration is causally associated with blood pressure and hypertension risk. Methods In this mendelian randomisation study, we generated an allele score (25[OH]D synthesis score) based on variants of genes that affect 25(OH)D synthesis or substrate availability (CYP2R1 and DHCR7), which we used as a proxy for 25(OH)D concentration. We meta-analysed data for up to 108 173 individuals from 35 studies in the D-CarDia collaboration to investigate associations between the allele score and blood pressure measurements. We complemented these analyses with previously published summary statistics from the International Consortium on Blood Pressure (ICBP), the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and the Global Blood Pressure Genetics (Global BPGen) consortium. Findings In phenotypic analyses (up to n=49 363), increased 25(OH)D concentration was associated with decreased systolic blood pressure (β per 10% increase, −0·12 mm Hg, 95% CI −0·20 to −0·04; p=0·003) and reduced odds of hypertension (odds ratio [OR] 0·98, 95% CI 0·97—0·99; p=0·0003), but not with decreased diastolic blood pressure (β per 10% increase, −0·02 mm Hg, −0·08 to 0·03; p=0·37). In meta-analyses in which we combined data from D-CarDia and the ICBP (n=146 581, after exclusion of overlapping studies), each 25(OH)D-increasing allele of the synthesis score was associated with a change of −0·10 mm Hg in systolic blood pressure (−0·21 to −0·0001; p=0·0498) and a change of −0·08 mm Hg in diastolic blood pressure (−0·15 to −0·02; p=0·01). When D-CarDia and consortia data for hypertension were meta-analysed together (n=142 255), the synthesis score was associated with a reduced odds of hypertension (OR per allele, 0·98, 0·96—0·99; p=0·001). In instrumental variable analysis, each 10% increase in genetically instrumented 25(OH)D concentration was associated with a change of −0·29 mm Hg in diastolic blood pressure (−0·52 to −0·07; p=0·01), a change of −0·37 mm Hg in systolic blood pressure (−0·73 to 0·003; p=0·052), and an 8·1% decreased odds of hypertension (OR 0·92, 0·87—0·97; p=0·002). Interpretation Increased plasma concentrations of 25(OH)D might reduce the risk of hypertension. This finding warrants further investigation in an independent, similarly powered study.
    The Lancet Diabetes and Endocrinology. 06/2014;
  • Timothy M Frayling, Andrew T Hattersley
    Diabetes 06/2014; 63(6):1836-7. · 7.90 Impact Factor
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    ABSTRACT: Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion. Together, these findings suggest that tissue-specific methylation and possibly imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.
    PLoS Genetics 04/2014; 10(4):e1004235. · 8.52 Impact Factor
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    ABSTRACT: Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ~150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10−6), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (−0.17 s.d., P = 4.6 × 10−4). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.
    Nature Genetics 03/2014; · 35.21 Impact Factor
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    ABSTRACT: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
    Nature Genetics 03/2014; 46(3):234-244. · 35.21 Impact Factor
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    ABSTRACT: Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,990 individuals. Significant associations (P<5×10(-8)) were detected at TPO-rs11675434, ATXN2-rs653178, and BACH2-rs10944479 for TPOAb-positivity, and at TPO-rs11675434, MAGI3-rs1230666, and KALRN-rs2010099 for TPOAb levels. Individual and combined effects (genetic risk scores) of these variants on (subclinical) hypo- and hyperthyroidism, goiter and thyroid cancer were studied. Individuals with a high genetic risk score had, besides an increased risk of TPOAb-positivity (OR: 2.18, 95% CI 1.68-2.81, P = 8.1×10(-8)), a higher risk of increased thyroid-stimulating hormone levels (OR: 1.51, 95% CI 1.26-1.82, P = 2.9×10(-6)), as well as a decreased risk of goiter (OR: 0.77, 95% CI 0.66-0.89, P = 6.5×10(-4)). The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, which was replicated in an independent cohort of patients with Graves' disease (OR: 1.37, 95% CI 1.22-1.54, P = 1.2×10(-7) and OR: 1.25, 95% CI 1.12-1.39, P = 6.2×10(-5)). The MAGI3 variant was also associated with an increased risk of hypothyroidism (OR: 1.57, 95% CI 1.18-2.10, P = 1.9×10(-3)). This first GWAS meta-analysis for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. The results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which TPOAb-positives are particularly at risk of developing clinical thyroid dysfunction.
    PLoS Genetics 02/2014; 10(2):e1004123. · 8.52 Impact Factor
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    ABSTRACT: 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.
    PLoS ONE 01/2014; 9(6):e98608. · 3.53 Impact Factor
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    ABSTRACT: 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 approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 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/beta-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.
    Nat Genet. 01/2014;
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    ABSTRACT: Performing genetic studies in multiple human populations can identify disease risk alleles that are common in one population but rare in others, with the potential to illuminate pathophysiology, health disparities, and the population genetic origins of disease alleles. Here we analysed 9.2 million single nucleotide polymorphisms (SNPs) in each of 8,214 Mexicans and other Latin Americans: 3,848 with type 2 diabetes and 4,366 non-diabetic controls. In addition to replicating previous findings, we identified a novel locus associated with type 2 diabetes at genome-wide significance spanning the solute carriers SLC16A11 and SLC16A13 (P = 3.9 × 10−13; odds ratio (OR) = 1.29). The association was stronger in younger, leaner people with type 2 diabetes, and replicated in independent samples (P = 1.1 × 10−4; OR = 1.20). The risk haplotype carries four amino acid substitutions, all in SLC16A11; it is present at ~50% frequency in Native American samples and ~10% in east Asian, but is rare in European and African samples. Analysis of an archaic genome sequence indicated that the risk haplotype introgressed into modern humans via admixture with Neanderthals. The SLC16A11 messenger RNA is expressed in liver, and V5-tagged SLC16A11 protein localizes to the endoplasmic reticulum. Expression of SLC16A11 in heterologous cells alters lipid metabolism, most notably causing an increase in intracellular triacylglycerol levels. Despite type 2 diabetes having been well studied by genome-wide association studies in other populations, analysis in Mexican and Latin American individuals identified SLC16A11 as a novel candidate gene for type 2 diabetes with a possible role in triacylglycerol metabolism.
    Nature 12/2013; · 38.60 Impact Factor
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    ABSTRACT: The UK Biobank study provides a unique opportunity to study the causes and consequences of disease. We aimed to use the UK Biobank data to study the well-established, but poorly understood, association between low birthweight and type 2 diabetes. We used logistic regression to calculate the odds ratio for participants' risk of type 2 diabetes given a one standard deviation increase in birthweight. To test for an association between parental diabetes and birthweight, we performed linear regression of self-reported parental diabetes status against birthweight. We performed path and mediation analyses to test the hypothesis that birthweight partly mediates the association between parental diabetes and participant type 2 diabetes status. Of the UK Biobank participants, 277 261 reported their birthweight. Of 257 715 individuals of White ethnicity and singleton pregnancies, 6576 had type 2 diabetes, 19 478 reported maternal diabetes (but not paternal), 20 057 reported paternal diabetes (but not maternal) and 2754 participants reported both parents as having diabetes. Lower birthweight was associated with type 2 diabetes in the UK Biobank participants. A one kilogram increase in birthweight was associated with a lower risk of type 2 diabetes (odds ratio: 0.74; 95% CI: 0.71, 0.76; P = 2 × 10(-57)). Paternal diabetes was associated with lower birthweight (45 g lower; 95% CI: 36, 54; P = 2 × 10(-23)) relative to individuals with no parental diabetes. Maternal diabetes was associated with higher birthweight (59 g increase; 95% CI: 50, 68; P = 3 × 10(-37)). Participants' lower birthweight was a mediator of the association between reported paternal diabetes and participants' type 2 diabetes status, explaining 1.1% of the association, and participants' higher birthweight was a mediator of the association between reported maternal diabetes and participants' type 2 diabetes status, explaining 1.2% of the association. Data from the UK Biobank provides the strongest evidence by far that paternal diabetes is associated with lower birthweight, whereas maternal diabetes is associated with increased birthweight. Our findings with paternal diabetes are consistent with a role for the same genetic factors influencing foetal growth and type 2 diabetes.
    International Journal of Epidemiology 12/2013; · 6.98 Impact Factor
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    ABSTRACT: Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3' UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.
    Nature Genetics 09/2013; · 35.21 Impact Factor
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    ABSTRACT: Using a non-targeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycaemia in a large population-based cohort of 2,204 females (115 Type 2 Diabetes-T2D cases, 192 individuals with impaired fasting glucose- IFG and 1,897 controls) from TwinsUK.Forty-two metabolites from three major fuel sources, carbohydrates, lipids and proteins, were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain-keto-acid metabolite 3-methyl-2-oxovalerate, was the strongest predictive biomarker for IFG after glucose (OR=1.65, 95%CI=1.39,1.95, P=8.46x10(-9)) and was moderately heritable (h(2)=0.20). The association was replicated in an independent population (n=720, OR=1.68, 95%CI=1.34, 2.11, P=6.52x10(-6)) and validated in 189 Twins with urine metabolomics taken at the same time as plasma (OR=1.87, 95%CI=1.27,2.75, P=1x10(-3)). Results confirm an important role for catabolism of branched-chain-amino-acids in T2D and IFG.In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of non-targeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.
    Diabetes 07/2013; · 7.90 Impact Factor
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    ABSTRACT: Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes but its causal role remains controversial. We used a Mendelian randomisation approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics based genetic risk scores to test the associations with gold standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 cases and 64,731 controls). In conventional regression analyses a 1 SD decrease in adiponectin levels was correlated with a 0.31 SD (95%CIs: 0.26-0.35) increase in fasting insulin, a 0.34 SD (0.30-0.38) decrease in insulin sensitivity and a type 2 diabetes odds ratio of 1.75 (95%CIs: 1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD, 95%CI: -0.07, 0.11, N=29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95%CIs: -0.38, -0.02; N=1,860) and no evidence of a relationship with type 2 diabetes (odds ratio 0.94; 95%CIs: 0.75, 1.19; N= 2,777 cases and 13,011 controls). Using the ADIPOQ summary statistics genetic risk scores we found no evidence of an association between adiponectin lowering alleles and insulin sensitivity (effect per weighted adiponectin lowering allele: -0.03 SD, 95%CIs: -0.07, 0.01; N=2,969) or type 2 diabetes (odds ratio per weighted adiponectin lowering allele: 0.99; 95%CIs: 0.95, 1.04; 15,960 cases vs. 64,731 controls). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
    Diabetes 07/2013; · 7.90 Impact Factor
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    ABSTRACT: During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 x 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 x 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 x 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 x 10(-3) for 6q22 and 1.2 x 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.
    Nature Genetics 07/2013; 44:539-544. · 35.21 Impact Factor

Publication Stats

18k Citations
2,911.12 Total Impact Points

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Institutions

  • 1997–2014
    • University of Exeter
      • Peninsula College of Medicine and Dentistry
      Exeter, England, United Kingdom
  • 2012
    • University of Queensland
      Brisbane, Queensland, Australia
    • Aga Khan University Hospital, Karachi
      Kurrachee, Sindh, Pakistan
    • Wellcome Trust Sanger Institute
      Cambridge, England, United Kingdom
  • 2011–2012
    • Queensland Institute of Medical Research
      • Statistical Genetics laboratory
      Brisbane, Queensland, Australia
    • Harvard Medical School
      Boston, Massachusetts, United States
  • 2005–2012
    • University of Oxford
      • • Wellcome Trust Centre for Human Genetics
      • • Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM)
      Oxford, ENG, United Kingdom
  • 2010
    • University of Split-School of Medicine
      Spalato, Splitsko-Dalmatinska, Croatia
    • University Hospital Regensburg
      Ratisbon, Bavaria, Germany
  • 2000–2010
    • Imperial College London
      • Department of Medicine
      Londinium, England, United Kingdom
    • Queen Mary, University of London
      Londinium, England, United Kingdom
  • 2009
    • University of Cambridge
      • MRC Epidemiology Unit
      Cambridge, ENG, United Kingdom
    • National Institute on Aging
      Baltimore, Maryland, United States
  • 2008
    • University of Bristol
      • The Henry Wellcome Laboratories for Integrative Neuroscience and Endocrinology
      Bristol, ENG, United Kingdom
    • University of Western Australia
      • Centre for Genetic Epidemiology and Biostatistics
      Perth, Western Australia, Australia
    • Broad Institute of MIT and Harvard
      • Program in Medical and Population Genetics
      Cambridge, MA, United States
  • 2002–2008
    • Newcastle University
      Newcastle-on-Tyne, England, United Kingdom
    • University of Birmingham
      Birmingham, England, United Kingdom
  • 2006–2007
    • The Peninsula College of Medicine and Dentistry
      Plymouth, England, United Kingdom
    • The University of Edinburgh
      Edinburgh, Scotland, United Kingdom
    • Centre for Cellular and Molecular Biology
      Bhaganagar, Andhra Pradesh, India
  • 2003–2006
    • Institute of Genetics and Molecular Medicine
      Edinburgh, Scotland, United Kingdom
    • University Hospitals Birmingham NHS Foundation Trust
      Birmingham, England, United Kingdom
  • 2004
    • Wellcome Trust
      Londinium, England, United Kingdom
  • 2001
    • University Hospital Essen
      • Institut für Zellbiologie (Tumorforschung)
      Essen, North Rhine-Westphalia, Germany
  • 1999
    • University of Aberdeen
      • Institute of Medical Sciences
      Aberdeen, SCT, United Kingdom