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Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

ABSTRACT: Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers' previous expectations for definition of a comorbid subset and leads to smaller data sets, with a concomitant attrition in power. An alternative is to test for dependence between genetic sharing and covariates across the entire data set. This approach offers the advantage of exploiting the full data set and could be widely applied to complex-trait genome scans. However, existing maximum-likelihood methods can be prohibitively computationally expensive, especially since permutation is often required to determine significance. We developed a less computationally intensive score test and applied it to biometric and biochemical covariate data, from 2,044 sibling pairs with severe hypertension, collected by the British Genetics of Hypertension (BRIGHT) study. We found genomewide-significant evidence for linkage with hypertension and several related covariates. The strongest signals were with leaner-body-mass measures on chromosome 20q (maximum LOD = 4.24) and with parameters of renal function on chromosome 5p (maximum LOD = 3.71). After correction for the multiple traits and genetic locations studied, our global genomewide P value was .046. This is the first identity-by-descent regression analysis of hypertension to our knowledge, and it demonstrates the value of this approach for the incorporation of additional phenotypic information in genetic studies of complex traits.

SUBMITTER: Wallace C

PROVIDER: S-EPMC1559504 | biostudies-literature | 2006 Aug

REPOSITORIES: biostudies-literature

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Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

Wallace Chris C Xue Ming-Zhan MZ Newhouse Stephen J SJ Marcano Ana Carolina B AC Onipinla Abiodun K AK Burke Beverley B Gungadoo Johannie J Dobson Richard J RJ Brown Morris M Connell John M JM Dominiczak Anna A Lathrop G Mark GM Webster John J Farrall Martin M Mein Charles C Samani Nilesh J NJ Caulfield Mark J MJ Clayton David G DG Munroe Patricia B PB

American journal of human genetics 20060619 2

Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers' previous expectations for definition of a como ...[more]

PMID: 16826522

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Project description:Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package "clusterProfiler." SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (P fdr < 0.10), including rs1707302 (1p34.1, OR = 0.93, 95% CI: 0.90-0.97, P = 7.60 × 10-4), rs2516448 (6p21.33, OR = 1.07, 95% CI: 1.03-1.11, P = 1.00 × 10-3), rs3869062 (6p22.1, OR = 0.91, 95% CI: 0.86-0.96, P = 7.10 × 10-4), rs174549 (11q12.2, OR = 0.90, 95% CI: 0.87-0.94, P = 1.00 × 10-7), rs7193541 (16q23.1, OR = 0.93, 95% CI: 0.90-0.96, P = 1.20 × 10-4), and rs8064454 (17q12, OR = 1.07, 95% CI: 1.03-1.11, P = 4.30 × 10-4). The eQTL analysis and functional annotation suggested that these variants might modify lung cancer susceptibility through regulating the expression of related genes. Pathway enrichment analysis showed that genes modulated by these variants play important roles in cancer carcinogenesis. Our findings demonstrate the pleiotropic associations between non-lung cancer susceptibility loci and lung cancer risk, providing important insights into the shared mechanisms of carcinogenesis across cancers.

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Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

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Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

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