Archive Page - Genetics of complex traits in humans

Panos is Professor of Cardiovascular Genomics at the William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University London. Before becoming an Honorary Faculty member, Panos led the Genetics of complex traits in humans group at the Wellcome Trust Sanger Institute from 1994 to 2013, investigating both the extent of sequence variation in human populations and the functional consequences of specific variants in their contribution to complex traits including common disease and response to external stimuli, for example drugs. In particular, his team focused on the genetic predisposition of traits affecting coronary artery disease and myocardial infarction.

Panos was one of the founding members of the Human Genetics groups at the Wellcome Trust Sanger Institute when he joined as a group leader to help build the genetic maps for the Human Genome Project. His team made contributions first to the Human Genome Project by assembling the sequence map of chromosomes 10 & 20 and then to the International HapMap project by building SNP maps for quarter of the genome in four populations. His current research interests and work can be found on the Queen Mary University London website.

[Genome Research Limited]

Background

The availability of resources like the HapMap with over 4 million mapped variants coupled with advances in array technology have enabled the conduct of large-scale association studies to identify disease genes. We have set up a high-throughput facility for genotyping and expression analysis undertaking genetic studies of common diseases such as type 2 diabetes, cardiovascular, obesity and malaria as well as pharmacogenetic studies of the anticoagulant drug warfarin.

Whole genome association studies in large, well-phenotyped collections are finding disease genes; we have reported several new loci as part of the Wellcome Trust Case Control Consortium. Population samples of healthy individuals on which multiple phenotypic measurements have been collected offer a unique resource to map quantitative traits. In that context gene expression can also be analysed providing a further link between genotype and measured trait. Research interests evolve around both the technical and analytical optimisation of such studies as well as the deployment of molecular tools to further characterise the genomic regions resulting from them; identification of the actual causative variant requires functional analysis.

The challenge in understanding the basis of complex traits includes finding the environmental factors and how they interact with the genetic factors.

Research

The Wellcome Trust Case Control Consortium

The Wellcome Trust Case Control Consortium (WTCCC) was formed in 2004 with the aim to explore the utility, design, execution and analysis of genome-wide association (GWA) studies. It comprises over 50 UK research groups working on the genetics of common human diseases, and collectively covering the fields of clinical, genotyping, informatics and statistical analysis.

The Consortium has undertaken three experiments so far:

1. GWA studies of 2000 cases and 3000 shared controls for seven complex human diseases of major public health importance: bipolar disorder (BD), coronary artery disease (CAD), Crohns disease (CD), hypertension (HT), rheumatoid arthritis (RA), type 1 diabetes (T1D), and type 2 diabetes (T2D).

2. A GWA study for tuberculosis in 1500 cases and 1500 controls, sampled from The Gambia.

3. An association study of 1500 common controls with 1000 cases for each of breast cancer, multiple sclerosis, ankylosing spondylitis, and autoimmune thyroid disease, all typed at around 15,000 mainly non-synonymous SNPs.

By simultaneously studying seven diseases with differing aetiologies, we hoped to develop insights, not only into the specific genetic contributions to each of the diseases, but also into differences in allelic architecture across the diseases. A further major aim was to address important methodological issues of relevance to all GWA studies, such as quality control, design and analysis. In addition to our main association results, we address several of these issues below, including the choice of controls for genetic studies, the extent of population structure within the UK, sample sizes necessary to detect genetic effects of varying sizes, and improvements in genotype calling algorithms and analytical methods.

Scan of an individuals DNA with an array harbouring a genome wide set of 550,000 tag SNP markers (Illumina).

Scan of an individuals DNA with an array harbouring a genome wide set of 550,000 tag SNP markers (Illumina).

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Genotyping

Genetic studies in both haploid and diploid organisms rely heavily on our ability to interrogate accurately polymorphic sites in the genome (single base positions or sequence segments in the genome that occur in two or more alleles in the population). Bi-allelic markers such as Single Nucleotide Polymorphisms (SNPs) and small insertion deletions (INDELS) have largely replaced microsatellites as they are amenable to automation and high level of multiplexing.

We set up a high-throughput facility with the aim to identify and implement a combination of robust genotyping platforms to undertake large-scale genetic analysis. In addition to accuracy, we select platforms on the basis of throughput, cost efficiency, and DNA consumption. The latter is very important in studies with irreplaceable clinical samples available in finite quantities. Research activities focus on issues surrounding sample quality and optimisation of calling algorithms, both of paramount importance since the advent of genome-wide genotyping based on array technology developed by Affymetrix and Illumina. Disease association studies aim to identify variants with differences in frequency between cases and controls which are often small. Thus any bias in genotype calling introduced by either DNA quality and / or the calling algorithm used can lead to false positive associations. Our informatics team is developing tools for automating data handling and quality control as well as data storage and visualisation.

Our Facility runs multiple genotyping platforms including Illumina (Golden Gate and Infinium assays), Affymetrix (Gene Chip), Sequenom (iPLEX and homogeneous mass extend assays) and Taqman (ABI). We have made substantial contributions to major international projects such as those undertaken by The SNP Consortium and the HapMap consortium.

Genotyping quality control

This document outlines aspects of the process and quality control implemented in the genotyping pipeline. Many details are given, but it should be noted that these may vary depending on the nature of each project.

Selected publications

  • The DNA sequence and comparative analysis of human chromosome 10.

    Deloukas P, Earthrowl ME, Grafham DV, Rubenfield M, French L, Steward CA, Sims SK, Jones MC, Searle S, Scott C, Howe K, Hunt SE, Andrews TD, Gilbert JG, Swarbreck D, Ashurst JL, Taylor A, Battles J, Bird CP, Ainscough R, Almeida JP, Ashwell RI, Ambrose KD, Babbage AK, Bagguley CL, Bailey J, Banerjee R, Bates K, Beasley H, Bray-Allen S, Brown AJ, Brown JY, Burford DC, Burrill W, Burton J, Cahill P, Camire D, Carter NP, Chapman JC, Clark SY, Clarke G, Clee CM, Clegg S, Corby N, Coulson A, Dhami P, Dutta I, Dunn M, Faulkner L, Frankish A, Frankland JA, Garner P, Garnett J, Gribble S, Griffiths C, Grocock R, Gustafson E, Hammond S, Harley JL, Hart E, Heath PD, Ho TP, Hopkins B, Horne J, Howden PJ, Huckle E, Hynds C, Johnson C, Johnson D, Kana A, Kay M, Kimberley AM, Kershaw JK, Kokkinaki M, Laird GK, Lawlor S, Lee HM, Leongamornlert DA, Laird G, Lloyd C, Lloyd DM, Loveland J, Lovell J, McLaren S, McLay KE, McMurray A, Mashreghi-Mohammadi M, Matthews L, Milne S, Nickerson T, Nguyen M, Overton-Larty E, Palmer SA, Pearce AV, Peck AI, Pelan S, Phillimore B, Porter K, Rice CM, Rogosin A, Ross MT, Sarafidou T, Sehra HK, Shownkeen R, Skuce CD, Smith M, Standring L, Sycamore N, Tester J, Thorpe A, Torcasso W, Tracey A, Tromans A, Tsolas J, Wall M, Walsh J, Wang H, Weinstock K, West AP, Willey DL, Whitehead SL, Wilming L, Wray PW, Young L, Chen Y, Lovering RC, Moschonas NK, Siebert R, Fechtel K, Bentley D, Durbin R, Hubbard T, Doucette-Stamm L, Beck S, Smith DR and Rogers J

    Nature 2004;429;6990;375-81

  • The DNA sequence and comparative analysis of human chromosome 20.

    Deloukas P, Matthews LH, Ashurst J, Burton J, Gilbert JG, Jones M, Stavrides G, Almeida JP, Babbage AK, Bagguley CL, Bailey J, Barlow KF, Bates KN, Beard LM, Beare DM, Beasley OP, Bird CP, Blakey SE, Bridgeman AM, Brown AJ, Buck D, Burrill W, Butler AP, Carder C, Carter NP, Chapman JC, Clamp M, Clark G, Clark LN, Clark SY, Clee CM, Clegg S, Cobley VE, Collier RE, Connor R, Corby NR, Coulson A, Coville GJ, Deadman R, Dhami P, Dunn M, Ellington AG, Frankland JA, Fraser A, French L, Garner P, Grafham DV, Griffiths C, Griffiths MN, Gwilliam R, Hall RE, Hammond S, Harley JL, Heath PD, Ho S, Holden JL, Howden PJ, Huckle E, Hunt AR, Hunt SE, Jekosch K, Johnson CM, Johnson D, Kay MP, Kimberley AM, King A, Knights A, Laird GK, Lawlor S, Lehvaslaiho MH, Leversha M, Lloyd C, Lloyd DM, Lovell JD, Marsh VL, Martin SL, McConnachie LJ, McLay K, McMurray AA, Milne S, Mistry D, Moore MJ, Mullikin JC, Nickerson T, Oliver K, Parker A, Patel R, Pearce TA, Peck AI, Phillimore BJ, Prathalingam SR, Plumb RW, Ramsay H, Rice CM, Ross MT, Scott CE, Sehra HK, Shownkeen R, Sims S, Skuce CD, Smith ML, Soderlund C, Steward CA, Sulston JE, Swann M, Sycamore N, Taylor R, Tee L, Thomas DW, Thorpe A, Tracey A, Tromans AC, Vaudin M, Wall M, Wallis JM, Whitehead SL, Whittaker P, Willey DL, Williams L, Williams SA, Wilming L, Wray PW, Hubbard T, Durbin RM, Bentley DR, Beck S and Rogers J

    Nature 2001;414;6866;865-71

Team

Team members

Stephane Bourgeois

sb20@sanger.ac.uk unknown

I started by studying fundamental physics at Universite Denis Diderot, Paris 7, before moving to Montreal, Canada, for my MSc and PhD in molecular biology at Universite de Montreal. I was working at the Sainte-Justine Hospital in Professor Damian Labuda laboratory, focusing on population genetics. My work there revolved around the peopling of the Americas.

In 2008 I moved to Cambridge to start my post-doc with Dr Deloukas.

Research

My current research focuses on Pharmacogenetics, which aims at the elucidation of the genetic causes of Adverse Drug Reactions (ADRs). I have worked on Carbamazepine (anti-epiletic), as well as Warfarin (anti-coagulant), Nevirapine (HIV drug), ACE inhibitors (anti-hypertensive) and Non-Steroidal Anti-Inflammatory Drugs (NSAIDs, like aspirin and ibuprofen).

References

  • An X-linked haplotype of Neandertal origin is present among all non-African populations.

    Yotova V, Lefebvre JF, Moreau C, Gbeha E, Hovhannesyan K, Bourgeois S, Bédarida S, Azevedo L, Amorim A, Sarkisian T, Avogbe PH, Chabi N, Dicko MH, Kou' Santa Amouzou ES, Sanni A, Roberts-Thomson J, Boettcher B, Scott RJ and Labuda D

    Research Center, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada.

    Recent work on the Neandertal genome has raised the possibility of admixture between Neandertals and the expanding population of Homo sapiens who left Africa between 80 and 50 Kya (thousand years ago) to colonize the rest of the world. Here, we provide evidence of a notable presence (9% overall) of a Neandertal-derived X chromosome segment among all contemporary human populations outside Africa. Our analysis of 6,092 X-chromosomes from all inhabited continents supports earlier contentions that a mosaic of lineages of different time depths and different geographic provenance could have contributed to the genetic constitution of modern humans. It indicates a very early admixture between expanding African migrants and Neandertals prior to or very early on the route of the out-of-Africa expansion that led to the successful colonization of the planet.

    Funded by: Canadian Institutes of Health Research: IGI-94494, MOP-67150

    Molecular biology and evolution 2011;28;7;1957-62

  • HLA-A*3101 and carbamazepine-induced hypersensitivity reactions in Europeans.

    McCormack M, Alfirevic A, Bourgeois S, Farrell JJ, Kasperavičiūtė D, Carrington M, Sills GJ, Marson T, Jia X, de Bakker PI, Chinthapalli K, Molokhia M, Johnson MR, O'Connor GD, Chaila E, Alhusaini S, Shianna KV, Radtke RA, Heinzen EL, Walley N, Pandolfo M, Pichler W, Park BK, Depondt C, Sisodiya SM, Goldstein DB, Deloukas P, Delanty N, Cavalleri GL and Pirmohamed M

    Molecular and Cellular Therapeutics, the Royal College of Surgeons in Ireland, Dublin, Ireland.

    Background: Carbamazepine causes various forms of hypersensitivity reactions, ranging from maculopapular exanthema to severe blistering reactions. The HLA-B*1502 allele has been shown to be strongly correlated with carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS-TEN) in the Han Chinese and other Asian populations but not in European populations.

    Methods: We performed a genomewide association study of samples obtained from 22 subjects with carbamazepine-induced hypersensitivity syndrome, 43 subjects with carbamazepine-induced maculopapular exanthema, and 3987 control subjects, all of European descent. We tested for an association between disease and HLA alleles through proxy single-nucleotide polymorphisms and imputation, confirming associations by high-resolution sequence-based HLA typing. We replicated the associations in samples from 145 subjects with carbamazepine-induced hypersensitivity reactions.

    Results: The HLA-A*3101 allele, which has a prevalence of 2 to 5% in Northern European populations, was significantly associated with the hypersensitivity syndrome (P=3.5×10(-8)). An independent genomewide association study of samples from subjects with maculopapular exanthema also showed an association with the HLA-A*3101 allele (P=1.1×10(-6)). Follow-up genotyping confirmed the variant as a risk factor for the hypersensitivity syndrome (odds ratio, 12.41; 95% confidence interval [CI], 1.27 to 121.03), maculopapular exanthema (odds ratio, 8.33; 95% CI, 3.59 to 19.36), and SJS-TEN (odds ratio, 25.93; 95% CI, 4.93 to 116.18).

    Conclusions: The presence of the HLA-A*3101 allele was associated with carbamazepine-induced hypersensitivity reactions among subjects of Northern European ancestry. The presence of the allele increased the risk from 5.0% to 26.0%, whereas its absence reduced the risk from 5.0% to 3.8%. (Funded by the U.K. Department of Health and others.).

    Funded by: Department of Health; Medical Research Council: G0400126; PHS HHS: HHS-N261200800001E, HHSN261200800001E; Wellcome Trust: 084730

    The New England journal of medicine 2011;364;12;1134-43

  • X-chromosome lineages and the settlement of the Americas.

    Bourgeois S, Yotova V, Wang S, Bourtoumieu S, Moreau C, Michalski R, Moisan JP, Hill K, Hurtado AM, Ruiz-Linares A and Labuda D

    Centre de Recherche de l'Hôpital Sainte-Justine, Montréal, QC H3T 1C5, Canada.

    Most genetic studies on the origins of Native Americans have examined data from mtDNA and Y-chromosome DNA. To complement these studies and to broaden our understanding of the origin of Native American populations, we present an analysis of 1,873 X-chromosomes representing Native American (n = 438) and other continental populations (n = 1,435). We genotyped 36 polymorphic sites, forming an informative haplotype within an 8-kb DNA segment spanning exon 44 of the dystrophin gene. The data reveal continuity from a common Eurasian ancestry between Europeans, Siberians, and Native Americans. However, the loss of two haplotypes frequent in Eurasia (18.8 and 7%) and the rise in frequency of a third haplotype rare elsewhere, indicate a major population bottleneck in the peopling of the Americas. Although genetic drift appears to have played a greater role in the genetic differentiation of Native Americans than in the latitudinally distributed Eurasians, we also observe a signal of a differentiated ancestry of southern and northern populations that cannot be simply explained by the serial southward dilution of genetic diversity. It is possible that the distribution of X-chromosome lineages reflects the genetic structure of the population of Beringia, itself issued from founder effects and a source of subsequent southern colonization(s).

    Funded by: Canadian Institutes of Health Research: MOP-67150

    American journal of physical anthropology 2009;140;3;417-28

  • A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose.

    Takeuchi F, McGinnis R, Bourgeois S, Barnes C, Eriksson N, Soranzo N, Whittaker P, Ranganath V, Kumanduri V, McLaren W, Holm L, Lindh J, Rane A, Wadelius M and Deloukas P

    Wellcome Trust Sanger Institute, Hinxton, UK.

    We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5 x 10(-7)) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that approximately 30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another approximately 12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10(-78)) at SNPs clustering near VKORC1 and the second lowest p-values (p<10(-31)) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p = 8.3 x 10(-10)) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.

    Funded by: Wellcome Trust

    PLoS genetics 2009;5;3;e1000433

  • Dynamic allele-specific oligonucleotide hybridization on solid support.

    Bourgeois S and Labuda D

    Centre de Recherche de l'Hôpital Sainte-Justine, Centre de Cancérologie Charles Bruneau, Montréal, Que., Canada H3T 1C5.

    Analytical biochemistry 2004;324;2;309-11

Dirk Paul

- PhD Student

Until October 2012, I was on a Marie Curie PhD fellowship at the Wellcome Trust Sanger Institute and the University of Cambridge. I previously graduated with a BSc and MSc in Life Science from the University of Konstanz, Germany. During my studies at university, I participated in the National University of Singapore Exchange Programme. I worked on complex diseases, such as cirrhosis at the Biopolis in Singapore, and asthma at Boehringer Ingelheim. For my Master's thesis, I worked on the development of a novel approach to targeted high-throughput DNA sequencing at the Wellcome Trust Centre for Human Genetics in Oxford.

Research

My research interests are focused on the functional follow-up of genome-wide association study signals. I apply experimental as well as computational approaches to aid the identification of functional variants underlying association signals for haematological traits and coronary artery disease.

References

  • Maps of open chromatin highlight cell type-restricted patterns of regulatory sequence variation at hematological trait loci.

    Paul DS, Albers CA, Rendon A, Voss K, Stephens J, HaemGen Consortium, van der Harst P, Chambers JC, Soranzo N, Ouwehand WH and Deloukas P

    Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, United Kingdom. d.paul@ucl.ac.uk

    Nearly three-quarters of the 143 genetic signals associated with platelet and erythrocyte phenotypes identified by meta-analyses of genome-wide association (GWA) studies are located at non-protein-coding regions. Here, we assessed the role of candidate regulatory variants associated with cell type-restricted, closely related hematological quantitative traits in biologically relevant hematopoietic cell types. We used formaldehyde-assisted isolation of regulatory elements followed by next-generation sequencing (FAIRE-seq) to map regions of open chromatin in three primary human blood cells of the myeloid lineage. In the precursors of platelets and erythrocytes, as well as in monocytes, we found that open chromatin signatures reflect the corresponding hematopoietic lineages of the studied cell types and associate with the cell type-specific gene expression patterns. Dependent on their signal strength, open chromatin regions showed correlation with promoter and enhancer histone marks, distance to the transcription start site, and ontology classes of nearby genes. Cell type-restricted regions of open chromatin were enriched in sequence variants associated with hematological indices. The majority (63.6%) of such candidate functional variants at platelet quantitative trait loci (QTLs) coincided with binding sites of five transcription factors key in regulating megakaryopoiesis. We experimentally tested 13 candidate regulatory variants at 10 platelet QTLs and found that 10 (76.9%) affected protein binding, suggesting that this is a frequent mechanism by which regulatory variants influence quantitative trait levels. Our findings demonstrate that combining large-scale GWA data with open chromatin profiles of relevant cell types can be a powerful means of dissecting the genetic architecture of closely related quantitative traits.

    Funded by: British Heart Foundation: RG/09/12/28096; Wellcome Trust: 097117, 098051

    Genome research 2013;23;7;1130-41

  • Seventy-five genetic loci influencing the human red blood cell.

    van der Harst P, Zhang W, Mateo Leach I, Rendon A, Verweij N, Sehmi J, Paul DS, Elling U, Allayee H, Li X, Radhakrishnan A, Tan ST, Voss K, Weichenberger CX, Albers CA, Al-Hussani A, Asselbergs FW, Ciullo M, Danjou F, Dina C, Esko T, Evans DM, Franke L, Gögele M, Hartiala J, Hersch M, Holm H, Hottenga JJ, Kanoni S, Kleber ME, Lagou V, Langenberg C, Lopez LM, Lyytikäinen LP, Melander O, Murgia F, Nolte IM, O'Reilly PF, Padmanabhan S, Parsa A, Pirastu N, Porcu E, Portas L, Prokopenko I, Ried JS, Shin SY, Tang CS, Teumer A, Traglia M, Ulivi S, Westra HJ, Yang J, Zhao JH, Anni F, Abdellaoui A, Attwood A, Balkau B, Bandinelli S, Bastardot F, Benyamin B, Boehm BO, Cookson WO, Das D, de Bakker PI, de Boer RA, de Geus EJ, de Moor MH, Dimitriou M, Domingues FS, Döring A, Engström G, Eyjolfsson GI, Ferrucci L, Fischer K, Galanello R, Garner SF, Genser B, Gibson QD, Girotto G, Gudbjartsson DF, Harris SE, Hartikainen AL, Hastie CE, Hedblad B, Illig T, Jolley J, Kähönen M, Kema IP, Kemp JP, Liang L, Lloyd-Jones H, Loos RJ, Meacham S, Medland SE, Meisinger C, Memari Y, Mihailov E, Miller K, Moffatt MF, Nauck M, Novatchkova M, Nutile T, Olafsson I, Onundarson PT, Parracciani D, Penninx BW, Perseu L, Piga A, Pistis G, Pouta A, Puc U, Raitakari O, Ring SM, Robino A, Ruggiero D, Ruokonen A, Saint-Pierre A, Sala C, Salumets A, Sambrook J, Schepers H, Schmidt CO, Silljé HH, Sladek R, Smit JH, Starr JM, Stephens J, Sulem P, Tanaka T, Thorsteinsdottir U, Tragante V, van Gilst WH, van Pelt LJ, van Veldhuisen DJ, Völker U, Whitfield JB, Willemsen G, Winkelmann BR, Wirnsberger G, Algra A, Cucca F, d'Adamo AP, Danesh J, Deary IJ, Dominiczak AF, Elliott P, Fortina P, Froguel P, Gasparini P, Greinacher A, Hazen SL, Jarvelin MR, Khaw KT, Lehtimäki T, Maerz W, Martin NG, Metspalu A, Mitchell BD, Montgomery GW, Moore C, Navis G, Pirastu M, Pramstaller PP, Ramirez-Solis R, Schadt E, Scott J, Shuldiner AR, Smith GD, Smith JG, Snieder H, Sorice R, Spector TD, Stefansson K, Stumvoll M, Tang WH, Toniolo D, Tönjes A, Visscher PM, Vollenweider P, Wareham NJ, Wolffenbuttel BH, Boomsma DI, Beckmann JS, Dedoussis GV, Deloukas P, Ferreira MA, Sanna S, Uda M, Hicks AA, Penninger JM, Gieger C, Kooner JS, Ouwehand WH, Soranzo N and Chambers JC

    Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands. p.van.der.harst@umcg.nl

    Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

    Funded by: British Heart Foundation: RG/08/014/24067; Cancer Research UK: 14136; Chief Scientist Office: CZB/4/505, ETM/55; Medical Research Council: G0600705, G0700704, G0801056, G1000143, G9815508, MC_U106179471, MC_U106188470; NCATS NIH HHS: UL1 TR000439; NCI NIH HHS: R01 CA165001; NCRR NIH HHS: K12 RR023250, U54 RR020278, UL1 RR025005; NHGRI NIH HHS: T32 HG002536, U01 HG004402; NHLBI NIH HHS: HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C, P01 HL076491, P01 HL098055, P20 HL113452, R01 HL059367, R01 HL086694, R01 HL087641, R01 HL087679, R01 HL088119, R01 HL103866, R01 HL103931, U01 HL072515, U01 HL084756; NIA NIH HHS: N01AG12109, R01 AG018728; NICHD NIH HHS: R01 HD042157; NIDA NIH HHS: HHSN271201100005C; NIDDK NIH HHS: P30 DK072488; NIGMS NIH HHS: R01 GM053275, U01 GM074518; NIMH NIH HHS: R01 MH081802, RL1 MH083268, U24 MH068457; NLM NIH HHS: R01 LM010098; Wellcome Trust: 092731, 097117

    Nature 2012;492;7429;369-75

  • A GWAS sequence variant for platelet volume marks an alternative DNM3 promoter in megakaryocytes near a MEIS1 binding site.

    Nürnberg ST, Rendon A, Smethurst PA, Paul DS, Voss K, Thon JN, Lloyd-Jones H, Sambrook JG, Tijssen MR, HaemGen Consortium, Italiano JE, Deloukas P, Gottgens B, Soranzo N and Ouwehand WH

    Department of Haematology, University of Cambridge and National Health Service Blood and Transplant, Cambridge, United Kingdom.

    We recently identified 68 genomic loci where common sequence variants are associated with platelet count and volume. Platelets are formed in the bone marrow by megakaryocytes, which are derived from hematopoietic stem cells by a process mainly controlled by transcription factors. The homeobox transcription factor MEIS1 is uniquely transcribed in megakaryocytes and not in the other lineage-committed blood cells. By ChIP-seq, we show that 5 of the 68 loci pinpoint a MEIS1 binding event within a group of 252 MK-overexpressed genes. In one such locus in DNM3, regulating platelet volume, the MEIS1 binding site falls within a region acting as an alternative promoter that is solely used in megakaryocytes, where allelic variation dictates different levels of a shorter transcript. The importance of dynamin activity to the latter stages of thrombopoiesis was confirmed by the observation that the inhibitor Dynasore reduced murine proplatelet for-mation in vitro.

    Funded by: British Heart Foundation: RG/09/12/28096; Medical Research Council: G0800784, G1000143; NHLBI NIH HHS: HL68130; Wellcome Trust: WT-084183/2/07/2

    Blood 2012;120;24;4859-68

  • Compound inheritance of a low-frequency regulatory SNP and a rare null mutation in exon-junction complex subunit RBM8A causes TAR syndrome.

    Albers CA, Paul DS, Schulze H, Freson K, Stephens JC, Smethurst PA, Jolley JD, Cvejic A, Kostadima M, Bertone P, Breuning MH, Debili N, Deloukas P, Favier R, Fiedler J, Hobbs CM, Huang N, Hurles ME, Kiddle G, Krapels I, Nurden P, Ruivenkamp CA, Sambrook JG, Smith K, Stemple DL, Strauss G, Thys C, van Geet C, Newbury-Ecob R, Ouwehand WH and Ghevaert C

    Department of Haematology, University of Cambridge, Cambridge, UK. caa@sanger.ac.uk

    The exon-junction complex (EJC) performs essential RNA processing tasks. Here, we describe the first human disorder, thrombocytopenia with absent radii (TAR), caused by deficiency in one of the four EJC subunits. Compound inheritance of a rare null allele and one of two low-frequency SNPs in the regulatory regions of RBM8A, encoding the Y14 subunit of EJC, causes TAR. We found that this inheritance mechanism explained 53 of 55 cases (P < 5 × 10(-228)) of the rare congenital malformation syndrome. Of the 53 cases with this inheritance pattern, 51 carried a submicroscopic deletion of 1q21.1 that has previously been associated with TAR, and two carried a truncation or frameshift null mutation in RBM8A. We show that the two regulatory SNPs result in diminished RBM8A transcription in vitro and that Y14 expression is reduced in platelets from individuals with TAR. Our data implicate Y14 insufficiency and, presumably, an EJC defect as the cause of TAR syndrome.

    Funded by: British Heart Foundation: FS/09/039, FS/09/039/27788, RG/09/012/28096, RG/09/12/28096; Wellcome Trust: 082597, 084183, WT-082597/Z/07/Z, WT-084183/2/07/2, WT091310

    Nature genetics 2012;44;4;435-9, S1-2

  • Maps of open chromatin guide the functional follow-up of genome-wide association signals: application to hematological traits.

    Paul DS, Nisbet JP, Yang TP, Meacham S, Rendon A, Hautaviita K, Tallila J, White J, Tijssen MR, Sivapalaratnam S, Basart H, Trip MD, Cardiogenics Consortium, MuTHER Consortium, Göttgens B, Soranzo N, Ouwehand WH and Deloukas P

    Wellcome Trust Sanger Institute, Hinxton, United Kingdom. dp5@sanger.ac.uk

    Turning genetic discoveries identified in genome-wide association (GWA) studies into biological mechanisms is an important challenge in human genetics. Many GWA signals map outside exons, suggesting that the associated variants may lie within regulatory regions. We applied the formaldehyde-assisted isolation of regulatory elements (FAIRE) method in a megakaryocytic and an erythroblastoid cell line to map active regulatory elements at known loci associated with hematological quantitative traits, coronary artery disease, and myocardial infarction. We showed that the two cell types exhibit distinct patterns of open chromatin and that cell-specific open chromatin can guide the finding of functional variants. We identified an open chromatin region at chromosome 7q22.3 in megakaryocytes but not erythroblasts, which harbors the common non-coding sequence variant rs342293 known to be associated with platelet volume and function. Resequencing of this open chromatin region in 643 individuals provided strong evidence that rs342293 is the only putative causative variant in this region. We demonstrated that the C- and G-alleles differentially bind the transcription factor EVI1 affecting PIK3CG gene expression in platelets and macrophages. A protein-protein interaction network including up- and down-regulated genes in Pik3cg knockout mice indicated that PIK3CG is associated with gene pathways with an established role in platelet membrane biogenesis and thrombus formation. Thus, rs342293 is the functional common variant at this locus; to the best of our knowledge this is the first such variant to be elucidated among the known platelet quantitative trait loci (QTLs). Our data suggested a molecular mechanism by which a non-coding GWA index SNP modulates platelet phenotype.

    Funded by: British Heart Foundation: RG/09/12/28096; Medical Research Council: G0800784, G0900339, MC_U105260799; Wellcome Trust: 081917/Z/07/Z, 091746/Z/10/Z

    PLoS genetics 2011;7;6;e1002139

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