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GWS:is hypertension a special case

GWS:is hypertension a special case. Genome Scans in complex traits: is hypertension a special case? Anna F Dominiczak. Guilt by association- WTCCC.

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GWS:is hypertension a special case

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  1. GWS:is hypertension a special case Genome Scans in complex traits: is hypertension a special case?Anna F Dominiczak

  2. Guilt by association- WTCCC In a tour-de-force demonstration of feasibility, a consortium of 50 research teams used 500,000 genetic markers from each of 17,000 individuals to identify 24 genetic risk factors for 7 common human diseases Nature, 7 June 2007

  3. Genome-wide association scan • 2,000 individuals for each of the 7 major diseases • 3000 shared controls • 24 independent association signals identified at p<5x10-7 • Across all diseases-58 loci • (6 for HT) with p values between 10-5 and 5 x10-7

  4. Genome-wide scan for seven diseases P<1x10-5 Green WTCCC, Nature 7 June 2007

  5. The WTCCC & Risk • The overall increase in risk (1.2-1.5 times) conferred by the genetic risk factors identified is in agreement with those reported by others • However, these factors are unlikely to explain completely the clustering of any of the 7 diseases in families, and there are other genes (either many of small effect or rarer variants of genes) still to be identified

  6. GWA- WTCCC : Control groups • there were 2000 cases for each disease and 3000 common controls • there is a potential for misclassification bias as phenotyping is not available for the shared control group • it was estimated that if 5% of controls would meet the definition of cases, that loss of power is approx. the same as that due to reduction of sample size by 10% • however, hypertension might have had 30% not 5% misclassification bias..... • thus “hypercontrols” would have been more suitable than common controls.

  7. GWS & Hypertension • failure to detect a prominent association signal in the WTCCC cannot provide conclusive exclusion of any given gene Due to: • less than complete coverage of common variation genome-wide on the Affymetrix chip; • poor coverage (by design) of rare variants; • despite the sample size, relatively low power to detect variants with modest effects = OR < 1.2 • and specifically for hypertension – common controls without phenotypes

  8. WTCCC- Replication • WTCCC report is based on initial studies but “independent” groups have confirmed the involvement of all but one of these most significant regions • Some of the other identified regions with less statistically significant disease association are also likely to be true indicators of genetic risk  further evaluation needed • The WTCCC data are publicly available = resource to other groups /networks.

  9. WTCCC genome-wide association scan: What next? • The next step will be to study the exact nature of the disease-causing variants • Variations leading to common diseases are diverse, including coding and regulatory regions of genes • Thus the understanding of biological function of disease-risk-associated genomic regions will be challenging

  10. BRIGHT and drug response 2010 Sib Pairs Unresponsive to anti-HTN drug combinations 288 families ABCD A – ACEI/ARB B – Beta blockers C – CCB D - Diuretics AB CD 89 families 76 families

  11. 5 4 LOD 3 2 D2S2216 D2S391 D2S2368 D2S2333 D2S337 D2S286 1 ADD2 PLEK USP39 DOK1 FABP1 ANXA4 SLC4A5 FANCL RPS27A GPR75 USP34 RAB1A MTHFD2 PRSS25 PSME4 RHOQ NAT8 EPAS1 ATP6V1B1 CALM2 ARHGAP25 KCNK12 PRKCE ATP6V1E2 CALCINEURIN B cM 50 100 150 200 250 300 ADD2 = ß subunit of adducin SLC4A5 =sodium bicarbonate transporter Genome wide screen identifies new loci linked to response to antihypertensive treatment AB non-responders = ACEI & beta blockers Padmanabhan et al, Hypertension 2006;47:603

  12. Salt Sensitive Locus 4.84 BRIGHT AB only 2.7 LOD 1 Modified from Barkley et al. Hypertension 2004;43:477

  13. Ingenious strategy Malmo – All Swedish subjects Controls – Age >50 years BP <120/80 Not on antiHTN No prevalent CVD (MI,CVA) No incident CVD on follow-up until 2001 Cases – Hypertensive Age <60 years BP>160/100 550K Illumina BeadChip Hypercontrols Increase odds ratio Increase power Better LD coverage using HapMap2 InGenious HyperCare Investigators

  14. BHF Glasgow Cardiovascular Research Centre Human & Experimental Genomics Dr Christian Delles Dr S Padmanabhan Dr Lukas Zimmerli Dr Wai Kwong Lee Dr Martin McBride Dr Delyth Graham Dr Maria Moreno Dr John McClure Dr M Gaasenbeek Elisabeth Beattie Kirsten Gilday James Polke Caline Koh-Tan Carol Jenkins James McCulloch Deborah Clark Oxidative stress & Gene Transfer Prof Andrew Baker Dr Carlene Hamilton Dr Stuart Nicklin Dr Lorraine Work Dr William Miller Dr Angelika Kritz Dr Tracey Graham Dr Laura Denby Dr Alan Parker Katie Whyte Rachel Masson Nicola Britton Laura Graham Ruth Mackenzie Collaborators MRC BRIGHT Investigators WTCCC Wellcome CVS Functional Genomics EURATools Investigators InGenious HyperCare Investigators

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