Genomic epidemiology in large cosmopolitan populations
As genetic data becomes increasingly available through genomic sequencing efforts, so does the potential. Dr. Van Hout has conducted genetic epidemiology and population genetics based analyses using whole exome sequencing (WES) in some of the largest studies in the world, including over 150,000 participants with electronic health records from North-Central Pennsylvania, USA1-3. Dr. Van Hout lead the first evaluation of exome sequencing in 50,000 participants with WES from the UK Biobank project4. His experience in these projects crosses many phases of analysis; organizing and quality control of phenotype data, summary and quality control of genomic data, modeling and genome wide association testing of single variants and gene burden tests, evaluation of the robustness of statistical methods, and interpretation of statistical results.
UK Biobank phenotypes and genomic data are publicly available to researchers with research plans who request access. UK Biobank currently contains exome sequence, genotype chip and imputed genome sequence for 500,000 individuals, as well as electronic health records, questionnaire data, and a number of standardized biometric and biochemical measures.
Statistical and population genetics of founder and isolate populations
Over the last 15 years, Dr. Van Hout’s interests in human genetics have included statistical genomics approaches to understand disease etiology and demography in founder and isolate populations, in particular the Old Order Amish. Academic and industry/academic collaborations have resulted in novel gene discovery for risk factors of cardiovascular disease (CVD)5, epidemiologically relevant risk factors for CVD6, and population genomics aspects of special populations, including the Old Order Amish7 and indigenous American populations8,9.
An up to date list of publications is available here.
References
1. Gusarova V, O’Dushlaine C, Teslovich TM, Benotti PN, Mirshahi T, Gottesman O, Van Hout CV, et al., Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes. Nature Communications. 2018 June 13. PMID: 29899519
2. Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, O’Dushlaine C, Van Hout CV, et al,. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science. 2016 Dec 23;354(6319). PMID: 28008009
3. Dewey FE, Gusarova V, O’Dushlaine C, Gottesman O, Trejos J, Hunt C, Van Hout CV, et al. Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease. New England Journal of Medicine. 2016 Mar 24;374(12):1123-33. PMID: 26933753
4. Van Hout CV, et al., Exome sequencing in 50,000 participants in the UK Biobank. Nature. 2020 Oct;586(7831):749-756. PMID: 33087929 F1000Prime recommended paper
5. Montasser M*, Van Hout CV*, et al., A missense variant in B4GALT1 reduces low-density lipoprotein cholesterol and fibrinogen. Science. 2021 Dec 3;374(6572):1221-1227. PMID: 34855475
6. Montasser ME, Douglas JA, Roy-Gagnon MH, Van Hout CV, et al., Distribution and Determinants of Salt Sensitivity in a Relatively Healthy Adult Population. Journal of Clinical Hypertension. 2011, Nov;13(11):795-800. PMID: 22051423
7. Van Hout CV*, Levin AM*, Rampersaud E, Shen H, O’Connell J, Mitchell BD, Shuldiner AR, Douglas JA. Extent and Distribution of Linkage Disequilibrium in the Old Order Amish. Genetic Epidemiology. 2010, Feb;34(2):146-150. PMID: 19697356
8. Kim HI, Gosalia N, Ye B, Regeneron Genetics Center, Köroğlu C, Hanson RL, Hsueh WC, Knowler WC, Baier LJ, Bogardus C, Shuldiner AR, Van Hout CV. Characterization of exome variants and their metabolic impact in 6,716 American Indians from Southwest US. American Journal of Human Genetics, 2020 July 7. PMID: 32640185
9. Hanson RL, Van Hout CV, Hseuh WC, Shuldiner AR, Kobes S, Sinha M, Baier LJ, Regeneron Genetics Center, Knowler WC. Assessment of the Potential Role of Natural Selection in Type 2 Diabetes and Related Traits Across Human Continental Ancestry Groups: Comparison of Phenotypic with Genotypic Distance. Diabetologia, 2020 December 7. PMID: 32886191