Andrew Tym Hattersley

Andrew Tym Hattersley

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Andrew Tym Hattersley

Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2015 in Nature
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Journal Article
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ALAdam E Locke
Adam E Locke
BKBratati Kahali
Bratati Kahali
SBSonja I Berndt
Sonja I Berndt
AJAnne E Justice
Anne E Justice
TPTune H Pers
Tune H Pers
ESElizabeth K. Speliotes
Elizabeth K. Speliotes

11 May 2007 in Science
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Journal Article
Closed access
TFTimothy M. Frayling
Timothy M. Frayling
NTNicholas J. Timpson
Nicholas J. Timpson
MWMichael N. Weedon
Michael N. Weedon
EZEleftheria Zeggini
Eleftheria Zeggini
RFRachel M. Freathy
Rachel M. Freathy
MMMark I. McCarthy
Mark I. McCarthy
Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.

5 October 2014 in Nature Genetics
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TCThe Electronic Medical Records and Genomics (eMERGE) Consortium
The Electronic Medical Records and Genomics (eMERGE) Consortium
AWAndrew R Wood
Andrew R Wood
TCThe MIGen Consortium
The MIGen Consortium
TCThe PAGE Consortium
The PAGE Consortium
TSThe LifeLines Cohort Study
The LifeLines Cohort Study
TFTimothy M Frayling
Timothy M Frayling
Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait. 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.

12 August 2012 in Nature Genetics
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TCthe DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
AMAndrew P Morris
Andrew P Morris
BVBenjamin F Voight
Benjamin F Voight
TTTanya M Teslovich
Tanya M Teslovich
TFTeresa Ferreira
Teresa Ferreira
MMMark I McCarthy
Mark I McCarthy
Mark McCarthy, Michael Boehnke, Andrew Morris and colleagues perform large-scale association analyses using the Metabochip to gain insights into the genetic architecture of type 2 diabetes. They report several new susceptibility loci, including two that show sex-differentiated effects on disease risk. 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.

8 October 2018 in Nature Genetics
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AMAnubha Mahajan
Anubha Mahajan
DTDaniel Taliun
Daniel Taliun
MTMatthias Thurner
Matthias Thurner
NRNeil R. Robertson
Neil R. Robertson
JTJason M. Torres
Jason M. Torres
MMMark I. McCarthy
Mark I. McCarthy
We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

11 February 2015 in Nature
Verified
Journal Article
Open access
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DSDmitry Shungin
Dmitry Shungin
TWThomas W. Winkler
Thomas W. Winkler
DCDamien C. Croteau-Chonka
Damien C. Croteau-Chonka
TFTeresa Ferreira
Teresa Ferreira
ALAdam E. Locke
Adam E. Locke
TCThe ReproGen Consortium
The ReproGen Consortium
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, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10−8). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display 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. Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution. In the first of a pair of Articles in this issue from the GIANT Consortium, genome-wide association meta-analyses of waist and hip circumference-related traits in more than 200,000 individuals have been used to identify 49 loci — 33 of them new — associated with waist-to-hip ratio adjusted for body mass index and an additional 19 loci associated with related waist and hip circumference measures. A subset of these loci shows significant sexual dimorphism, with many showing a stronger effect in women. Analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms and offer potential targets for interventions in the risks associated with abdominal fat accumulation.