Genomics of inflammation and immunity

Carl Anderson's group seeks to identify correlations between genotype and disease risk by comparing genotype data from diseased and non-diseased individuals. His team adopts several statistical and computational approaches to highlight only the few sites in the genome associated with risk of a given disease.

[ www.wordle.net]

Background

Human geneticists have been seeking the causal genetic variants underlying human diseases for around fifty years. The hope is that this research will further our understanding of disease biology and, ultimately, allow us to identify those individuals at elevated risk and treat them in a way specific to their disease aetiology.

Until very recently, most of the causal genetic variants being identified were for Mendelian disorders (where single genetic variants of very large effect bring about disease). Because these genetic variants have such large deleterious effects on health, selection against their transmission to the next generation keeps them at a very low population frequency. Examples of Mendelian diseases include Cystic Fibrosis and Sickle Cell Anaemia.

For more common human diseases such as Crohn's Disease, Schizophrenia or Breast Cancer, it is much more difficult to identify specific genetic risk factors. This is because there is not one causal factor underlying disease susceptibility, rather there are multiple genetic and environmental factors underlying disease risk (with the potential for interactions between these factors). For example, all individuals with sickle cell anaemia (a Mendelian disease) carry a mutation in the beta globin gene but not all Crohn's disease sufferers will carry a NOD2 mutation (the greatest genetic risk factor for Crohn's disease). Compared to the variants underlying Mendelian disorders, genetic risk factors underlying common diseases have a much smaller effect, and this makes them difficult to detect.

The completion of the Human Genome Project and the International HapMap Project has significantly advanced our understanding of the human genome, both at the level of the individual and across populations. Subsequent advances in genotyping technology have made it possible (and reasonably cost-effective) to genotype around 1 million genetic markers for studies containing thousands of individuals. This has enabled human geneticists to conduct high-powered studies to compare the genomes of people with a given common disease to those of non-diseased individuals (so called genome-wide association studies). This huge breakthrough has lead to the discovery of more than 200 novel common disease variants in the last 3 years.

Research

Our aims

To aid understanding of common human disease by identifying and characterizing genetic mutations that underlie disease susceptibility, with a particular focus on autoimmune-related diseases.

There are both applied and methodolgocial components to our reseach.

GWAS

The group has played a central analytical role in many successful genome-wide association studies across a number of diseases, the majority of which are related to autoimmunity. Most recently, as part of the WTCCC3, we conducted the largest GWAS of Primary Biliary Cirrhosis (PBC) to date and identified 12 novel genetic susceptibility loci. PBC is a chronic, autoimmune liver disease and a well-established indication for liver transplantation. The biological mechanism underlying the disease is unknown but our study, which was conducted in collaboration with the UK PSC Consortium, suggests that NF-KB signaling, T-cell differentiation, and TLR and TNF signaling could all play a central role. In the near future we will be conducting a GWAS of another autoimmune liver disease, primary sclerosing cholangitis (PSC), which is characterized by bile duct strictures and progression to liver cirrhosis. This study is in collaboration with the UK PSC Consortium. Up to 70% of patients with PSC will also suffer from ulcerative colitis (UC), one of two common forms of inflammatory bowel disease (IBD).

Combining data from several GWAS datasets provides a cost efficient way of identifying susceptibility loci missed by index studies. Most recently, we lead the analysis of the first UC GWAS meta-analysis conducted by the International IBD Genetics Consortium and identified 29 novel risk loci, raising the number of confirmed associations to 47. In the future, together with many international collaborators, we aim to conduct similar studies for PBC and PSC.

Immunochip

The Immunochip is an Illumina iSelect HD Custom Genotyping array that contains around 200,000 SNPs from regions of the genome that have been associated with an autoimmune disease (such as T1D, MS and IBD). The chip represents a cost-effective way of fine-mapping known disease loci and more thoroughly surveying those that have been associated with related autoimmune diseases. Some of the SNP content is also devoted to deep-replication of GWAS and meta-analyses. Together with international collaborators we are currently involved in Immunochip studies of Crohn's disease, ulcerative colitis, PBC and PSC. To reduce the number of false-positive and false negative Immunochip results we have developed a novel genotype-calling algorithm, (optiCall), which can accurately call genotypes across the range of minor allele frequencies and in the presence of shifted genotype intensity clouds.

Next-generation sequencing

Over the next few years we aim to exploit falling next-generation sequencing costs to conduct association tests aimed at identifying low-frequency and rare variants associated with autoimmune disease. We will adopt two distinct approaches, a) we will use low-coverage whole-genome sequencing across thousands of cases and controls to identify low-frequency risk variants missed by current association studies and b) we will use high-coverage sequencing to detect rare and private mutations underlying severe disease subtypes.

UK10K

The group plays a key role in the statistical methods arm of the UK10K project and we are currently developing methods to aid many of the analyses the study has planned. We are also involved in the rare diseases arm of the project where we lead the analysis of whole-exome sequence data generated across three distinct diseases: coloboma, thyroid disorder and familial hypercholesterolemia. For more information on these diseases and the UK10K samples see http://www.uk10k.org/studies/rarediseases.html

Selected Publications

  • Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis.

    Liu JZ, Hov JR, Folseraas T, Ellinghaus E, Rushbrook SM, Doncheva NT, Andreassen OA, Weersma RK, Weismüller TJ, Eksteen B, Invernizzi P, Hirschfield GM, Gotthardt DN, Pares A, Ellinghaus D, Shah T, Juran BD, Milkiewicz P, Rust C, Schramm C, Müller T, Srivastava B, Dalekos G, Nöthen MM, Herms S, Winkelmann J, Mitrovic M, Braun F, Ponsioen CY, Croucher PJ, Sterneck M, Teufel A, Mason AL, Saarela J, Leppa V, Dorfman R, Alvaro D, Floreani A, Onengut-Gumuscu S, Rich SS, Thompson WK, Schork AJ, Næss S, Thomsen I, Mayr G, König IR, Hveem K, Cleynen I, Gutierrez-Achury J, Ricaño-Ponce I, van Heel D, Björnsson E, Sandford RN, Durie PR, Melum E, Vatn MH, Silverberg MS, Duerr RH, Padyukov L, Brand S, Sans M, Annese V, Achkar JP, Boberg KM, Marschall HU, Chazouillères O, Bowlus CL, Wijmenga C, Schrumpf E, Vermeire S, Albrecht M, UK-PSCSC Consortium, International IBD Genetics Consortium, Rioux JD, Alexander G, Bergquist A, Cho J, Schreiber S, Manns MP, Färkkilä M, Dale AM, Chapman RW, Lazaridis KN, International PSC Study Group, Franke A, Anderson CA and Karlsen TH

    Nature genetics 2013;45;6;670-5

  • Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis.

    Liu JZ, Almarri MA, Gaffney DJ, Mells GF, Jostins L, Cordell HJ, Ducker SJ, Day DB, Heneghan MA, Neuberger JM, Donaldson PT, Bathgate AJ, Burroughs A, Davies MH, Jones DE, Alexander GJ, Barrett JC, Sandford RN, Anderson CA, UK Primary Biliary Cirrhosis (PBC) Consortium and Wellcome Trust Case Control Consortium 3

    Nature genetics 2012;44;10;1137-41

  • optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variants.

    Shah TS, Liu JZ, Floyd JA, Morris JA, Wirth N, Barrett JC and Anderson CA

    Bioinformatics (Oxford, England) 2012;28;12;1598-603

  • Genome-wide association study identifies 12 new susceptibility loci for primary biliary cirrhosis.

    Mells GF, Floyd JA, Morley KI, Cordell HJ, Franklin CS, Shin SY, Heneghan MA, Neuberger JM, Donaldson PT, Day DB, Ducker SJ, Muriithi AW, Wheater EF, Hammond CJ, Dawwas MF, UK PBC Consortium, Wellcome Trust Case Control Consortium 3, Jones DE, Peltonen L, Alexander GJ, Sandford RN and Anderson CA

    Nature genetics 2011;43;4;329-32

  • Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47.

    Anderson CA, Boucher G, Lees CW, Franke A, D'Amato M, Taylor KD, Lee JC, Goyette P, Imielinski M, Latiano A, Lagacé C, Scott R, Amininejad L, Bumpstead S, Baidoo L, Baldassano RN, Barclay M, Bayless TM, Brand S, Büning C, Colombel JF, Denson LA, De Vos M, Dubinsky M, Edwards C, Ellinghaus D, Fehrmann RS, Floyd JA, Florin T, Franchimont D, Franke L, Georges M, Glas J, Glazer NL, Guthery SL, Haritunians T, Hayward NK, Hugot JP, Jobin G, Laukens D, Lawrance I, Lémann M, Levine A, Libioulle C, Louis E, McGovern DP, Milla M, Montgomery GW, Morley KI, Mowat C, Ng A, Newman W, Ophoff RA, Papi L, Palmieri O, Peyrin-Biroulet L, Panés J, Phillips A, Prescott NJ, Proctor DD, Roberts R, Russell R, Rutgeerts P, Sanderson J, Sans M, Schumm P, Seibold F, Sharma Y, Simms LA, Seielstad M, Steinhart AH, Targan SR, van den Berg LH, Vatn M, Verspaget H, Walters T, Wijmenga C, Wilson DC, Westra HJ, Xavier RJ, Zhao ZZ, Ponsioen CY, Andersen V, Torkvist L, Gazouli M, Anagnou NP, Karlsen TH, Kupcinskas L, Sventoraityte J, Mansfield JC, Kugathasan S, Silverberg MS, Halfvarson J, Rotter JI, Mathew CG, Griffiths AM, Gearry R, Ahmad T, Brant SR, Chamaillard M, Satsangi J, Cho JH, Schreiber S, Daly MJ, Barrett JC, Parkes M, Annese V, Hakonarson H, Radford-Smith G, Duerr RH, Vermeire S, Weersma RK and Rioux JD

    Nature genetics 2011;43;3;246-52

  • Synthetic associations are unlikely to account for many common disease genome-wide association signals.

    Anderson CA, Soranzo N, Zeggini E and Barrett JC

    PLoS biology 2011;9;1;e1000580

Team

Team members

James Floyd
unknown
Sean Ji
PhD Student
Jimmy Liu
Research Associate
Tejas Shah
Computational Biologist

James Floyd

- unknown

BSc (Hons) Genetics, University of Manchester

MSc Quantitative Genetics and Genome Analysis, University of Edinburgh

PhD Statistical Genetics, University of Edinburgh

After my PhD I joined the Sanger Institute as part of the Wellcome Trust Case Control Consortium 3 project, analysing genetic data for primary biliary cirrhosis and anorexia nervosa genome-wide association studies.

Research

I am a statistical genetics analyst currently working on the UK10K project. I am analysing high coverage exome data from patients with rare conditions such as thyroid disorders and Coloboma to detect causative genetic polymorphisms involved in these diseases.

References

  • Genome-wide association study identifies 12 new susceptibility loci for primary biliary cirrhosis.

    Mells GF, Floyd JA, Morley KI, Cordell HJ, Franklin CS, Shin SY, Heneghan MA, Neuberger JM, Donaldson PT, Day DB, Ducker SJ, Muriithi AW, Wheater EF, Hammond CJ, Dawwas MF, UK PBC Consortium, Wellcome Trust Case Control Consortium 3, Jones DE, Peltonen L, Alexander GJ, Sandford RN and Anderson CA

    Academic Department of Medical Genetics, Cambridge University, Cambridge, UK; Department of Hepatology, Cambridge University Hospitals National Health Service (NHS) Foundation Trust, Cambridge, UK.

    In addition to the HLA locus, six genetic risk factors for primary biliary cirrhosis (PBC) have been identified in recent genome-wide association studies (GWAS). To identify additional loci, we carried out a GWAS using 1,840 cases from the UK PBC Consortium and 5,163 UK population controls as part of the Wellcome Trust Case Control Consortium 3 (WTCCC3). We followed up 28 loci in an additional UK cohort of 620 PBC cases and 2,514 population controls. We identified 12 new susceptibility loci (at a genome-wide significance level of P < 5 × 10⁻⁸) and replicated all previously associated loci. We identified three further new loci in a meta-analysis of data from our study and previously published GWAS results. New candidate genes include STAT4, DENND1B, CD80, IL7R, CXCR5, TNFRSF1A, CLEC16A and NFKB1. This study has considerably expanded our knowledge of the genetic architecture of PBC.

    Funded by: Medical Research Council: G0500020, G0800460, G0802068; PHS HHS: 1R01LEY018246; Wellcome Trust: 085925/Z/08/Z, 091745, WT090355/B/09/Z, WT09355A/09/Z, WT91745/Z/10/Z

    Nature genetics 2011;43;4;329-32

  • Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47.

    Anderson CA, Boucher G, Lees CW, Franke A, D'Amato M, Taylor KD, Lee JC, Goyette P, Imielinski M, Latiano A, Lagacé C, Scott R, Amininejad L, Bumpstead S, Baidoo L, Baldassano RN, Barclay M, Bayless TM, Brand S, Büning C, Colombel JF, Denson LA, De Vos M, Dubinsky M, Edwards C, Ellinghaus D, Fehrmann RS, Floyd JA, Florin T, Franchimont D, Franke L, Georges M, Glas J, Glazer NL, Guthery SL, Haritunians T, Hayward NK, Hugot JP, Jobin G, Laukens D, Lawrance I, Lémann M, Levine A, Libioulle C, Louis E, McGovern DP, Milla M, Montgomery GW, Morley KI, Mowat C, Ng A, Newman W, Ophoff RA, Papi L, Palmieri O, Peyrin-Biroulet L, Panés J, Phillips A, Prescott NJ, Proctor DD, Roberts R, Russell R, Rutgeerts P, Sanderson J, Sans M, Schumm P, Seibold F, Sharma Y, Simms LA, Seielstad M, Steinhart AH, Targan SR, van den Berg LH, Vatn M, Verspaget H, Walters T, Wijmenga C, Wilson DC, Westra HJ, Xavier RJ, Zhao ZZ, Ponsioen CY, Andersen V, Torkvist L, Gazouli M, Anagnou NP, Karlsen TH, Kupcinskas L, Sventoraityte J, Mansfield JC, Kugathasan S, Silverberg MS, Halfvarson J, Rotter JI, Mathew CG, Griffiths AM, Gearry R, Ahmad T, Brant SR, Chamaillard M, Satsangi J, Cho JH, Schreiber S, Daly MJ, Barrett JC, Parkes M, Annese V, Hakonarson H, Radford-Smith G, Duerr RH, Vermeire S, Weersma RK and Rioux JD

    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.

    Genome-wide association studies and candidate gene studies in ulcerative colitis have identified 18 susceptibility loci. We conducted a meta-analysis of six ulcerative colitis genome-wide association study datasets, comprising 6,687 cases and 19,718 controls, and followed up the top association signals in 9,628 cases and 12,917 controls. We identified 29 additional risk loci (P < 5 × 10(-8)), increasing the number of ulcerative colitis-associated loci to 47. After annotating associated regions using GRAIL, expression quantitative trait loci data and correlations with non-synonymous SNPs, we identified many candidate genes that provide potentially important insights into disease pathogenesis, including IL1R2, IL8RA-IL8RB, IL7R, IL12B, DAP, PRDM1, JAK2, IRF5, GNA12 and LSP1. The total number of confirmed inflammatory bowel disease risk loci is now 99, including a minimum of 28 shared association signals between Crohn's disease and ulcerative colitis.

    Funded by: Chief Scientist Office: CZB/4/540, ETM/137, ETM/75; Medical Research Council: G0600329, G0800675, G0800759; NCRR NIH HHS: M01-RR00425; NIAID NIH HHS: AI062773; NIDDK NIH HHS: DK 063491, DK043351, DK062413, DK062420, DK062422, DK062423, DK062429, DK062431, DK062432, DK064869, DK069513, DK076984, DK084554, DK83756, P01-DK046763, P30 DK040561, P30 DK040561-15, P30 DK043351, R01 DK060049, R01 DK064869, R01 DK064869-05S1, R01 DK064869-06A1, R01 DK064869-07, R01 DK064869-08, R01 DK083756, U01 DK062432, U01 DK062432-07, U01 DK062432-08, U01 DK062432-09, U01 DK062432-10; Wellcome Trust: 083948/Z/07/Z, WT089120/Z/09/Z, WT091745/Z/10/Z

    Nature genetics 2011;43;3;246-52

  • Linkage and genome-wide association analysis of obesity-related phenotypes: association of weight with the MGAT1 gene.

    Johansson A, Marroni F, Hayward C, Franklin CS, Kirichenko AV, Jonasson I, Hicks AA, Vitart V, Isaacs A, Axenovich T, Campbell S, Floyd J, Hastie N, Knott S, Lauc G, Pichler I, Rotim K, Wild SH, Zorkoltseva IV, Wilson JF, Rudan I, Campbell H, Pattaro C, Pramstaller P, Oostra BA, Wright AF, van Duijn CM, Aulchenko YS, Gyllensten U and EUROSPAN Consortium

    Department of Genetics and Pathology, Rudbeck laboratory, Uppsala University, Uppsala, Sweden.

    As major risk-factors for diabetes and cardiovascular diseases, the genetic contribution to obesity-related traits has been of interest for decades. Recently, a limited number of common genetic variants, which have replicated in different populations, have been identified. One approach to increase the statistical power in genetic mapping studies is to focus on populations with increased levels of linkage disequilibrium (LD) and reduced genetic diversity. We have performed joint linkage and genome-wide association analyses for weight and BMI in 3,448 (linkage) and 3,925 (association) partly overlapping healthy individuals from five European populations. A total of four chromosomal regions (two for weight and two for BMI) showed suggestive linkage (lod >2.69) either in one of the populations or in the joint data. At the genome-wide level (nominal P < 1.6 x 10(-7), Bonferroni-adjusted P < 0.05) one single-nucleotide polymorphism (SNP) (rs12517906) (nominal P = 7.3 x 10(-8)) was associated with weight, whereas none with BMI. The SNP associated with weight is located close to MGAT1. The monoacylglycerol acyltransferase (MGAT) enzyme family is known to be involved in dietary fat absorption. There was no overlap between the linkage regions and the associated SNPs. Our results show that genetic effects influencing weight and BMI are shared across diverse European populations, even though some of these populations have experienced recent population bottlenecks and/or been affected by genetic drift. The analysis enabled us to identify a new candidate gene, MGAT1, associated with weight in women.

    Funded by: Chief Scientist Office: CZB/4/710; Medical Research Council

    Obesity (Silver Spring, Md.) 2010;18;4;803-8

  • Common variants in the JAZF1 gene associated with height identified by linkage and genome-wide association analysis.

    Johansson A, Marroni F, Hayward C, Franklin CS, Kirichenko AV, Jonasson I, Hicks AA, Vitart V, Isaacs A, Axenovich T, Campbell S, Dunlop MG, Floyd J, Hastie N, Hofman A, Knott S, Kolcic I, Pichler I, Polasek O, Rivadeneira F, Tenesa A, Uitterlinden AG, Wild SH, Zorkoltseva IV, Meitinger T, Wilson JF, Rudan I, Campbell H, Pattaro C, Pramstaller P, Oostra BA, Wright AF, van Duijn CM, Aulchenko YS, Gyllensten U and EUROSPAN Consortium

    Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, SE-751 85 Uppsala, Sweden.

    Genes for height have gained interest for decades, but only recently have candidate genes started to be identified. We have performed linkage analysis and genome-wide association for height in approximately 4000 individuals from five European populations. A total of five chromosomal regions showed suggestive linkage and in one of these regions, two SNPs (rs849140 and rs1635852) were associated with height (nominal P = 7.0 x 10(-8) and P = 9.6 x 10(-7), respectively). In total, five SNPs across the genome showed an association with height that reached the threshold of genome-wide significance (nominal P < 1.6 x 10(-7)). The association with height was replicated for two SNPs (rs1635852 and rs849140) using three independent studies (n = 31 077, n=1268 and n = 5746) with overall meta P-values of 9.4 x 10(-10) and 5.3 x 10(-8). These SNPs are located in the JAZF1 gene, which has recently been associated with type II diabetes, prostate and endometrial cancer. JAZF1 is a transcriptional repressor of NR2C2, which results in low IGF1 serum concentrations, perinatal and early postnatal hypoglycemia and growth retardation when knocked out in mice. Both the linkage and association analyses independently identified the JAZF1 region affecting human height. We have demonstrated, through replication in additional independent populations, the consistency of the effect of the JAZF1 SNPs on height. Since this gene also has a key function in the metabolism of growth, JAZF1 represents one of the strongest candidates influencing human height identified so far.

    Funded by: Cancer Research UK: C348/A3758, C348/A8896, C48/A6361; Chief Scientist Office: CZB/4/449, CZB/4/710, K/OPR/2/2/D333; Medical Research Council: G0000657-53203, MC_U127527180, MC_U127527198, MC_U127561128

    Human molecular genetics 2009;18;2;373-80

  • SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout.

    Vitart V, Rudan I, Hayward C, Gray NK, Floyd J, Palmer CN, Knott SA, Kolcic I, Polasek O, Graessler J, Wilson JF, Marinaki A, Riches PL, Shu X, Janicijevic B, Smolej-Narancic N, Gorgoni B, Morgan J, Campbell S, Biloglav Z, Barac-Lauc L, Pericic M, Klaric IM, Zgaga L, Skaric-Juric T, Wild SH, Richardson WA, Hohenstein P, Kimber CH, Tenesa A, Donnelly LA, Fairbanks LD, Aringer M, McKeigue PM, Ralston SH, Morris AD, Rudan P, Hastie ND, Campbell H and Wright AF

    MRC Human Genetics Unit, Western General Hospital, Edinburgh EH4 2XU, UK.

    Uric acid is the end product of purine metabolism in humans and great apes, which have lost hepatic uricase activity, leading to uniquely high serum uric acid concentrations (200-500 microM) compared with other mammals (3-120 microM). About 70% of daily urate disposal occurs via the kidneys, and in 5-25% of the human population, impaired renal excretion leads to hyperuricemia. About 10% of people with hyperuricemia develop gout, an inflammatory arthritis that results from deposition of monosodium urate crystals in the joint. We have identified genetic variants within a transporter gene, SLC2A9, that explain 1.7-5.3% of the variance in serum uric acid concentrations, following a genome-wide association scan in a Croatian population sample. SLC2A9 variants were also associated with low fractional excretion of uric acid and/or gout in UK, Croatian and German population samples. SLC2A9 is a known fructose transporter, and we now show that it has strong uric acid transport activity in Xenopus laevis oocytes.

    Funded by: Arthritis Research UK; Chief Scientist Office: CZB/4/710; Medical Research Council: G117/564, MC_PC_U127561128, MC_U127561111; Wellcome Trust

    Nature genetics 2008;40;4;437-42

Sean Ji

- PhD Student

EDUCATION

B. Sci. in Biotechnology, Yonsei University, Korea

M. Sci. in Biotechnology, Yonsei University, Korea

RESEARCH

Research Assistant, Network Biotechnology Lab, Yonsei University, Korea

Research Intern, Immune Cell Engineering Lab, Yonsei University, Korea

Research Intern, Structural Biology Lab, Yonsei University, Korea

Research

My PhD project is jointly supervised by Dr. Carl Anderson and Dr. Daniel Gaffney and focus on four related autoimmune diseases – Crohn’s disease (CD), ulcerative colitis (UC), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). The aim is to identify and functionally characterize risk variants associated to these diseases and improve the understanding of autoimmune diseases as a whole.

Jimmy Liu

- Research Associate

EDUCATION

Bachelor of Science (Genetics and Statistics), University of Queensland 2009

Bachelor of Economics, University of Queensland 2008

RESEARCH EXPERIENCE

Queensland Institute of Medical Research, Research Assistant, Genetics and Population Health, 2009-2010

Research

My PhD project focuses on the genetics of autoimmune diseases, in particular Crohn's disease, ulcerative colitis, primary biliary cirrhosis and primary sclerosing cholangitis. Using a combination of dense genotyping, fine mapping and next-generation sequencing technology, we hope to identify genetic variants that explain the underlying heritability of these individual diseases as well as jointly assessing comorbidity, and to develop more complete models of how genetic variation contributes to disease heritability and its application in risk prediction.

References

  • No association of candidate genes with cannabis use in a large sample of Australian twin families.

    Verweij KJ, Zietsch BP, Liu JZ, Medland SE, Lynskey MT, Madden PA, Agrawal A, Montgomery GW, Heath AC and Martin NG

    Queensland Statistical Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, Australia. karin.verweij@qimr.edu.au

    While there is solid evidence that cannabis use is heritable, attempts to identify genetic influences at the molecular level have yielded mixed results. Here, a large twin family sample (n = 7452) was used to test for association between 10 previously reported candidate genes and lifetime frequency of cannabis use using a gene-based association test. None of the candidate genes reached even nominal significance (P < 0.05). The lack of replication may point to our limited understanding of the neurobiology of cannabis involvement and also to potential publication bias and false-positive findings in previous studies.

    Funded by: NIAAA NIH HHS: AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, K05 AA017688, R01 AA013320, R01 AA013321; NIDA NIH HHS: DA12854, R01 DA012854; NIMH NIH HHS: MH66206

    Addiction biology 2012;17;3;687-90

  • Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned.

    Wray NR, Pergadia ML, Blackwood DH, Penninx BW, Gordon SD, Nyholt DR, Ripke S, MacIntyre DJ, McGhee KA, Maclean AW, Smit JH, Hottenga JJ, Willemsen G, Middeldorp CM, de Geus EJ, Lewis CM, McGuffin P, Hickie IB, van den Oord EJ, Liu JZ, Macgregor S, McEvoy BP, Byrne EM, Medland SE, Statham DJ, Henders AK, Heath AC, Montgomery GW, Martin NG, Boomsma DI, Madden PA and Sullivan PF

    Genetic Epidemiology, Molecular Epidemiology, Psychiatric Genetics and Queensland Statistical Genetics Laboratories, Queensland Institute of Medical Research, Brisbane, QLD, Australia. naomi.wray@qimr.edu.au

    Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10); and (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD.

    Funded by: Chief Scientist Office; Medical Research Council: G0701420; NIAAA NIH HHS: AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, K05 AA017688; NIDA NIH HHS: DA019951, DA12854, R01 DA012854; NIMH NIH HHS: MH059565, MH059571, MH059588, MH061675, MH067257, MH080403, MH59566, MH59586, MH59587, MH60870, MH66206, R01 MH059160, U01 MH060879; Wellcome Trust

    Molecular psychiatry 2012;17;1;36-48

  • Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3.

    Macgregor S, Montgomery GW, Liu JZ, Zhao ZZ, Henders AK, Stark M, Schmid H, Holland EA, Duffy DL, Zhang M, Painter JN, Nyholt DR, Maskiell JA, Jetann J, Ferguson M, Cust AE, Jenkins MA, Whiteman DC, Olsson H, Puig S, Bianchi-Scarrà G, Hansson J, Demenais F, Landi MT, Dębniak T, Mackie R, Azizi E, Bressac-de Paillerets B, Goldstein AM, Kanetsky PA, Gruis NA, Elder DE, Newton-Bishop JA, Bishop DT, Iles MM, Helsing P, Amos CI, Wei Q, Wang LE, Lee JE, Qureshi AA, Kefford RF, Giles GG, Armstrong BK, Aitken JF, Han J, Hopper JL, Trent JM, Brown KM, Martin NG, Mann GJ and Hayward NK

    Queensland Institute of Medical Research, Brisbane, Queensland, Australia. stuart.macgregor@qimr.edu.au

    We performed a genome-wide association study of melanoma in a discovery cohort of 2,168 Australian individuals with melanoma and 4,387 control individuals. In this discovery phase, we confirm several previously characterized melanoma-associated loci at MC1R, ASIP and MTAP-CDKN2A. We selected variants at nine loci for replication in three independent case-control studies (Europe: 2,804 subjects with melanoma, 7,618 control subjects; United States 1: 1,804 subjects with melanoma, 1,026 control subjects; United States 2: 585 subjects with melanoma, 6,500 control subjects). The combined meta-analysis of all case-control studies identified a new susceptibility locus at 1q21.3 (rs7412746, P = 9.0 × 10(-11), OR in combined replication cohorts of 0.89 (95% CI 0.85-0.95)). We also show evidence suggesting that melanoma associates with 1q42.12 (rs3219090, P = 9.3 × 10(-8)). The associated variants at the 1q21.3 locus span a region with ten genes, and plausible candidate genes for melanoma susceptibility include ARNT and SETDB1. Variants at the 1q21.3 locus do not seem to be associated with human pigmentation or measures of nevus density.

    Funded by: Cancer Research UK: C588/A4994; NCI NIH HHS: 2P50CA093459, CA055075, CA100264, CA109544, CA122838, CA133996, CA49449, CA83115, CA87969, CA88363, P30CA016672, R01 CA088363, R01 CA088363-10, R01CA133996; NHGRI NIH HHS: HG004446; PHS HHS: 268200782096C; Wellcome Trust: WT084766/Z/08/Z

    Nature genetics 2011;43;11;1114-8

  • Genome-wide association study identifies susceptibility loci for open angle glaucoma at TMCO1 and CDKN2B-AS1.

    Burdon KP, Macgregor S, Hewitt AW, Sharma S, Chidlow G, Mills RA, Danoy P, Casson R, Viswanathan AC, Liu JZ, Landers J, Henders AK, Wood J, Souzeau E, Crawford A, Leo P, Wang JJ, Rochtchina E, Nyholt DR, Martin NG, Montgomery GW, Mitchell P, Brown MA, Mackey DA and Craig JE

    Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia.

    We report a genome-wide association study for open-angle glaucoma (OAG) blindness using a discovery cohort of 590 individuals with severe visual field loss (cases) and 3,956 controls. We identified associated loci at TMCO1 (rs4656461[G] odds ratio (OR) = 1.68, P = 6.1 × 10(-10)) and CDKN2B-AS1 (rs4977756[A] OR = 1.50, P = 4.7 × 10(-9)). We replicated these associations in an independent cohort of cases with advanced OAG (rs4656461 P = 0.010; rs4977756 P = 0.042) and two additional cohorts of less severe OAG (rs4656461 combined discovery and replication P = 6.00 × 10(-14), OR = 1.51, 95% CI 1.35-1.68; rs4977756 combined P = 1.35 × 10(-14), OR = 1.39, 95% CI 1.28-1.51). We show retinal expression of genes at both loci in human ocular tissues. We also show that CDKN2A and CDKN2B are upregulated in the retina of a rat model of glaucoma.

    Funded by: PHS HHS: 2007-2010

    Nature genetics 2011;43;6;574-8

  • A versatile gene-based test for genome-wide association studies.

    Liu JZ, McRae AF, Nyholt DR, Medland SE, Wray NR, Brown KM, AMFS Investigators, Hayward NK, Montgomery GW, Visscher PM, Martin NG and Macgregor S

    Genetics and Population Health Division, Queensland Institute of Medical Research, Brisbane, Queensland 4006, Australia. jimmy.liu@uqconnect.edu.au

    We have derived a versatile gene-based test for genome-wide association studies (GWAS). Our approach, called VEGAS (versatile gene-based association study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. We show that for an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. We demonstrate proof-of-principle by using the gene-based test to replicate several genes known to be associated on the basis of results from a family-based GWAS for height in 11,536 individuals and a DNA-pooling-based GWAS for melanoma in approximately 1300 cases and controls. Our method has the potential to identify novel associated genes; provide a basis for selecting SNPs for replication; and be directly used in network (pathway) approaches that require per-gene association test statistics. We have implemented the approach in both an easy-to-use web interface, which only requires the uploading of markers with their association p-values, and a separate downloadable application.

    Funded by: NCI NIH HHS: CA083115, CA109544

    American journal of human genetics 2010;87;1;139-45

Tejas Shah

- Computational Biologist

I studied Mathematics and Computer Science at university and worked in the financial industry prior to joining Sanger.

Research

I'm a computational biologist in the Statistical Genetics group at the Sanger. I've been working on genotyping algorithms for microarrays, and have developed optiCall (http://www.sanger.ac.uk/resources/software/opticall/).

* quick link - http://q.sanger.ac.uk/statgen