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Pinpointing culprit causal variants along signal peaks of genomewide association studies (GWAS) is challenging. To overcome confounding effects of multiple independent variants at such a locus and narrow the interval for causal allele capture, we developed an approach that maps local shared haplotypes harboring a putative causal variant. We demonstrate our method in an extreme isolate founder population, the pacific Island of Kosrae. We analyzed plasma plant sterol (PPS) levels, a surrogate measure of cholesterol absorption from the intestine, where previous studies have implicated 2p2i mutations in the ATP binding cassette subfamily G members 5 or 8 (ABCG5 or ABCG8) genes. We have previously reported that 11.1% of the islanders are carriers of a frameshift ABCG8 mutation increasing PPS levels in carriers by 50%. GWAS adjusted for this mutation revealed genomewide significant signals along 11 Mb around it. To fine-map this signal, we detected pairwise identity-by-descent haplotypes using our tool GERMLINE and implemented a clustering algorithm to identify haplotypes shared across multiple samples with their unique shared boundaries. A single 526-kb haplotype mapped strongly to PPS levels, dramatically refining the mapped interval. This haplotype spans the ABCG5/ABCG8 genes, is carried by 1.8% of the islanders, and results in a striking 100% increase of PPS in carriers. Resequencing of ABCG5 in these carriers found a D450H missense mutation along the associated haplotype. These findings exemplify the power of haplotype analysis for mapping mutations in isolated populations and specifically for dissecting effects of multiple variants of the same locus. [ABSTRACT FROM AUTHOR]

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10⁻⁸).

Unlabelled: Background- Variation in LDL-cholesterol (LDL-C) among individuals is a complex genetic trait involving multiple genes and gene-environment interactions., Methods and Results: In a genome-wide association study (GWAS) to identify genetic variants influencing LDL-C in an isolated population from Kosrae, we observed associations for SNPs in the gene encoding 3hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) reductase (HMGCR). Three of these SNPs (rs7703051, rs12654264, and rs3846663) met the statistical threshold of genome-wide significance when combined with data from the Diabetes Genetics Initiative GWAS. We followed up the association results and identified a functional SNP in intron13 (rs3846662), which was in linkage disequilibrium with the SNPs of genome-wide significance and affected alternative splicing of HMGCR mRNA. In vitro studies in human lymphoblastoid cells demonstrated that homozygosity for the rs3846662 minor allele was associated with up to 2.2-fold lower expression of alternatively spliced HMGCR mRNA lacking exon13, and minigene transfection assays confirmed that allele status at rs3846662 directly modulated alternative splicing of HMGCR exon13 (42.9+/-3.9 versus 63.7+/-1.0%Deltaexon13/total HMGCR mRNA, P=0.02). Further, the alternative splice variant could not restore HMGCR activity when expressed in HMGCR deficient UT-2 cells., Conclusions: We identified variants in HMGCR that are associated with LDL-C across populations and affect alternative splicing of HMGCR exon13.