Biology subjects

Sarin, A.-P.

Publications and source records attributed to Sarin, A.-P..

3 recordsLinked to original sources

bioRxiv2019

Multivariate genome-wide association analysis of a cytokine network reveals variants with widespread immune, haematological and cardiometabolic pleiotropy

Cytokines are essential regulatory components of the immune system and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlie them, remain unknown. Here we aimed to identify and characterise genetic variants with pleiotropic effects on cytokines - to do this we performed a multivariate genome-wide association study on a correlation network of 11 circulating cytokines measured in 9,263 individuals. Meta-analysis identified a total of 8 loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. Bayesian colocalisation analysis revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins; on metabolic traits such as lipoprotein and lipid levels; on blood-cell related traits such as platelet count; and on disease traits such as coronary artery disease and type 2 diabetes.

genomics↗

bioRxiv2017

Haplotype sharing provides insights into fine-scale population history and disease in Finland

Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assemble a comprehensive view of recent population history ([≤]100 generations), the timespan during which most rare disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to geographically and linguistically adjacent countries with different population histories, including 16,060 Swedes, Estonians, Russians, and Hungarians. We find much more extensive sharing in Finns, with at least one [≥] 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from over 25,000 individuals, we find that while haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland share several-fold more of their genome in identity-by-descent (IBD) segments than individuals from southwest regions containing the major cities of Helsinki and Turku. We estimate recent effective population size changes over time across regions of Finland and find significant differences between the Early and Late Settlement Regions as expected; however, our results indicate more continuous gene flow than previously indicated as Finns migrated towards the northernmost Lapland region. Lastly, we show that haplotype sharing is locally enriched among pairs of individuals sharing rare alleles by an order of magnitude, especially among pairs sharing rare disease causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.

genetics↗

bioRxiv2016

The rate of false polymorphisms introduced when imputing genotypes from global imputation panels

Previous studies1,2 have shown that large multi-population imputation reference panels increases the number of well-imputed variants. However, to our knowledge, no previous studies have evaluated the rate of introduced variation in monomorphic sites of the study population when using imputation panels with admixed populations. In this study we evaluate the rate of false positive variants introduced by the imputation of Finnish genotype data using global reference panels (Haplotype Reference Consortium1; HRC, and the 1000Genomes project Phase I3; 1000G) and compare the results to a Finnish population-specific reference panel combining whole genome and exome sequenced samples. In sites that were monomorphic in our test set, we observed high false positive rates for the global reference panels (4.0% for 1000G and 2.6% for HRC) compared to the Finnish panel (0.26%). This rate was even higher (7.4%) when using a combination panel of 1000G and Finnish whole genome sequences with cross-panel imputation.

genetics↗