Identification of rare variants for hypertension with incorporation of linkage information

Abstract

We conducted linkage analysis using the genome-wide association study data on chromosome 3, and then assessed association between hypertension and rare variants of genes located in the regions showing evidence of linkage. The rare variants were collapsed if their minor allele frequencies were less than or equal to the thresholds: 0.01, 0.03, or 0.05. In the collapsing process, they were either unweighted or weighted by the nonparametric linkage log of odds scores in 2 different schemes: exponential weighting and cumulative weighting. Logistic regression models using the generalized estimating equations approach were used to assess association between the collapsed rare variants and hypertension adjusting for age and gender. Evidence of association from the weighted and unweighted collapsing schemes with minor allele frequencies ≤0.01, after accounting for multiple testing, was found for genes DOCK3 (p = 0.0090), ARMC8 (p = 1.29E-5), KCNAB1 (p = 5.8E-4), and MYRIP (p = 5.79E-6). DOCK3 and MYRIP are newly discovered. Incorporating linkage scores as weights was found to help identify rare causal variants with a large effect size.

Challenges of Linkage Analysis in the Era of Whole‐Genome Sequencing

“…Chiu et al [] analyzed hypertension as a dichotomous trait and, rather than focusing on a single family or using all families equally, chose a weighting scheme that incorporated linkage information into subsequent association tests for rare variants. Using linkage analysis of hypertension, they identified 13 intervals with a LOD score greater than 4.0 for which genes within 1‐LOD support intervals were then found.…”

“…For example, combining over pedigrees yielded stronger linkage and association signals compared to conducting pedigree‐specific tests [Bull et al., ]; however, Stewart et al [] showed that restricting analysis to a single family and using conservation information can also lead to a high‐quality gene target, one with a high probability of linkage and linkage disequilibrium, in a highly conserved region located in a biologically reasonable candidate gene for the trait under study. In contrast, Chiu et al [] did not restrict their analysis to a subset of families in a discrete manner but rather used LOD scores to create a weighted score for each individual for collapsing rare variants. Hence a family's contribution to the test for association was directly determined by the extent to which they contributed to the linkage signal.…”

“…Contributors focusing on simulated data used either all markers provided [Szymczak et al., ] or sequence variants in MAP4 [Bull et al., ; Szymczak et al., ], depending on the goals of their study. However, investigators using the SAFS data restricted their analyses to chromosome 3, as suggested by the GAW18 organizers, with the restriction being primarily a result of computational challenges and time constraints [Chen et al., ; Chiu et al., ; Stewart et al., ]. Genotype data were further restricted for linkage analysis to either genome‐wide association markers only, sequence variants, or a smaller subset to further reduce linkage disequilibrium between markers, with markers with higher minor allele frequency (MAF) selected because they would be more informative for linkage.…”

“…One of the variants is located in a highly conserved intron of a lipid receptor, OSBPL10, and is part of a 4-SNP haplotype that appears in one other family (pedigree 4) that provided some evidence of linkage at this locus as well (maximum posterior probability of linkage = 7%). Chiu et al [2014] analyzed hypertension as a dichotomous trait and, rather than focusing on a single family or using all families equally, chose a weighting scheme that incorporated linkage information into subsequent association tests for rare variants. Using linkage analysis of hypertension, they identified 13 intervals with a LOD score greater than 4.0 for which genes within 1-LOD support intervals were then found.…”

Deletion of Kvβ1.1 subunit leads to electrical and haemodynamic changes causing cardiac hypertrophy in female murine hearts

“…In 2008, a patient who suffered sudden cardiac death demonstrated a deletion in KCNAB1 (Banerjee et al 2008). In addition, recent genomic studies identified KCNAB1 as a gene of interest for genetic association with blood pressure (BP) and a causal variant in humans with hypertension (Chiu et al 2014; McCarthy et al 2014). …”