Our lab develops and utilizes statistical genetics, computational biology, and population genetics-based approaches to understand the biological underpinnings and evolutionary history of human traits and complex disease.
Population Genetics, Statistical Genetics, Bioinformatics, Computational Biology, Statistics, Systems Biology, Metabolic Disorder, Type-2 Diabetes, Coronary Heart Disease, non-Alcoholic Fatty Liver Disease, Obesity, Myocardial Infarction, Cholesterol Levels, Natural Selection, Demography, Genome-wide Association Study (GWAS), Next-Generation Sequencing, Mendelian randomization.
The central aim in my lab is to understand the genetic, biological, and evolutionary basis of metabolic and cardiovascular phenotypes in human populations. To build this understanding, the lab constructs computational and statistical tools grounded in principles of population biology and quantitative genetics. These tools are then applied to genetic data collected across thousands of whole human genomes.
My research has answered population genetic questions about recent demographic and selective events in human populations, and work to develop new statistics to identify selective pressures is ongoing. Recent work in the lab has focused on statistical models which capture variability in the rate of mutation in the human genome.
I have an active interest in mapping risk alleles for common diseases, particularly type-2 diabetes and coronary heart disease, but perhaps more importantly, to identify the causal variant, gene, and mechanism that influences risk to these diseases from existing non-coding associations identified by genome-wide association studies.
I continue to utilize the framework of Mendelian Randomization
, to perform causal inference studies between genetically-heritable biomarkers and complex diseases. Work in the lab is toward applications, but also development of novel methodologies.
In the coming years, the lab activities will focus on several key areas of interest, which includes:
- Developing statistical models to capture variability in the rate of mutation in human genomes, with application to identifying de novo
mutations and rare variation related to human disease
- Computational methods and functional characterization of the causal variants and genes related to non-coding associations for type 2 diabetes and heart disease
- Developing informational and statistical tools which interrogate human genetic association data together with other sources of 'omics data to construct credibly actionable information on pathways responsible for disease susceptibility
- Population genetic methods to identify loci in the human genome which are targets of natural selective pressures, and to further identify the causal variants and genes responsible
- Performing large-scale genomic studies using data from the Million Veteran Program, a large (>1M) multi-ethnic cohort enriched for cardiometabolic disease.
For the 2020-2021 academic year, my lab has openings for computational post-doctoral positions. Please see the following site
for further details on how to apply.
The lab also has a number of potential graduate student rotation projects available for the 2020-2021 academic year. Ideal students will have a strong background in computational sciences, and projects will be built around human genetic data, bioinformatic applications, statistical genetic analysis, epidemiology, and/or population and systems biology. Please contact me if you are interested.
Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, Hindy G, Hólm H, Ding EL, Johnson T, Schunkert H, Samani NJ, Clarke R, Hopewell JC, Thompson JF, Li M, Thorleifsson G, Newton-Cheh C, Musunuru K, Pirruccello JP, Saleheen D, Chen L, Stewart AF, Schillert A, Thorsteinsdottir U, Thorgeirsson G, Anand S, Engert JC, Morgan T, Spertus J, Stoll M, Berger K, Martinelli N, Girelli D, McKeown PP, Patterson CC, Epstein SE, Devaney J, Burnett MS, Mooser V, Ripatti S, Surakka I, Nieminen MS, Sinisalo J, Lokki ML, Perola M, Havulinna A, de Faire U, Gigante B, Ingelsson E, Zeller T, Wild P, de Bakker PI, Klungel OH, Maitland-van der Zee AH, Peters BJ, de Boer A, Grobbee DE, Kamphuisen PW, Deneer VH, Elbers CC, Onland-Moret NC, Hofker MH, Wijmenga C, Verschuren WM, Boer JM, van der Schouw YT, Rasheed A, Frossard P, Demissie S, Willer C, Do R, Ordovas JM, Abecasis GR, Boehnke M, Mohlke KL, Daly MJ, Guiducci C, Burtt NP, Surti A, Gonzalez E, Purcell S, Gabriel S, Marrugat J, Peden J, Erdmann J, Diemert P, Willenborg C, König IR, Fischer M, Hengstenberg C, Ziegler A, Buysschaert I, Lambrechts D, Van de Werf F, Fox KA, El Mokhtari NE, Rubin D, Schrezenmeir J, Schreiber S, Schäfer A, Danesh J, Blankenberg S, Roberts R, McPherson R, Watkins H, Hall AS, Overvad K, Rimm E, Boerwinkle E, Tybjaerg-Hansen A, Cupples LA, Reilly MP, Melander O, Mannucci PM, Ardissino D, Siscovick D, Elosua R, Stefansson K, O'Donnell CJ, Salomaa V, Rader DJ, Peltonen L, Schwartz SM, Altshuler D, Kathiresan S. : Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. The Lancet 380(9841): 572-580, Aug 2012 Notes: Leading Author Contribution: I led all aspects of the work as the first author.
Aggarwala V and Voight BF: An expanded sequence context model broadly explains variability in polymorphism levels across the human genome. Nature Genetics 48(4): 349–355, Apr 2016 Notes: Senior Author Contribution: I contributed to all aspects of the work as the senior author.
Babb PL, Lahens NF, Correa-Garhwal SM, Nicholson DN, Kim EJ, Hogenesch JB, Kuntner M, Higgins L, Hayashi CY, Agnarsson I, Voight BF.: The Nephila clavipes genome highlights the diversity of spider silk genes and their complex expression. Nature Genetics 49(6): 895-903, June 2017 Notes: Senior Author Contribution: I contributed to all aspects of the work as the senior author.
Siewert KM and Voight BF: Detecting Long-term Balancing Selection using Allele Frequency Correlation. Mol. Biol. Evol 34(11), Nov 2017 Notes: Senior Author Contribution: I contributed to all aspects of the work as the senior author.
Voight BF*, Kudaravalli S*, Wen X, Pritchard JK: A map of recent positive selection in the human genome. PLoS Biology 4(3): e72, Mar 2006 Notes: Leading Co-Author Contribution: I contributed jointly to lead all aspects of the work as a co-first author.
Aikens RC, Zhao W, Saleheen D, Reilly MP, Epstein SE, Tikkanen E, Salomaa V, Voight BF.: Systolic Blood Pressure and Risk of Type 2 Diabetes: a Mendelian Randomization Study. Diabetes 66(2): 543-550, Feb 2017 Notes: Senior Author Contribution: I contributed to all aspects of the work as the senior author.
Keenan T, Zhao W, Rasheed A, Ho WK, Malik R, Felix JF, Young R, Shah N, Samuel M, Sheikh N, Mucksavage ML, Shah O, Li J, Morley M, Laser A, Mallick NH, Zaman KS, Ishaq M, Rasheed SZ, Memon FU, Ahmed F, Hanif B, Lakhani MS, Fahim M, Ishaq M, Shardha NK, Ahmed N, Mahmood K, Iqbal W, Akhtar S, Raheel R, O'Donnell CJ, Hengstenberg C, März W, Kathiresan S, Samani N, Goel A, Hopewell JC, Chambers J, Cheng YC, Sharma P, Yang Q, Rosand J, Boncoraglio GB, Kazmi SU, Hakonarson H, Köttgen A, Kalogeropoulos A, Frossard P, Kamal A, Dichgans M, Cappola T, Reilly MP, Danesh J, Rader DJ, Voight BF*, Saleheen D*.: Causal Assessment of Serum Urate Levels in Cardiometabolic Diseases Through a Mendelian Randomization Study. J Am Coll Cardiol 67(4): 407-16, Feb 2016 Notes: Senior Co-Author Contribution: I contributed to all aspects of the work as co-senior author.
Aggarwala V, Ganguly A, Voight BF: De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm. BMC Genomics 18(1): 155, Feb 2017 Notes: Senior Author Contribution: I contributed to all aspects of the work as the senior author.
Voight BF*, Scott LJ*, Steinthorsdottir V*, Morris AP*, Dina C*, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Bengtsson Boström K, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI; MAGIC investigators; GIANT Consortium.: Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nature Genetics 42(7): 579-89, Jul 2010 Notes: Leading Co-Author Contribution: I contributed jointly to lead all aspects of the work as a co-first author.
Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research, Saxena R, Voight BF, Lyssenko V, Burtt NP, de Bakker PI, Chen H, Roix JJ, Kathiresan S, Hirschhorn JN, Daly MJ, Hughes TE, Groop L, Altshuler D, Almgren P, Florez JC, Meyer J, Ardlie K, Bengtsson Boström K, Isomaa B, Lettre G, Lindblad U, Lyon HN, Melander O, Newton-Cheh C, Nilsson P, Orho-Melander M, Råstam L, Speliotes EK, Taskinen MR, Tuomi T, Guiducci C, Berglund A, Carlson J, Gianniny L, Hackett R, Hall L, Holmkvist J, Laurila E, Sjögren M, Sterner M, Surti A, Svensson M, Svensson M, Tewhey R, Blumenstiel B, Parkin M, Defelice M, Barry R, Brodeur W, Camarata J, Chia N, Fava M, Gibbons J, Handsaker B, Healy C, Nguyen K, Gates C, Sougnez C, Gage D, Nizzari M, Gabriel SB, Chirn GW, Ma Q, Parikh H, Richardson D, Ricke D, Purcell S: Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science (New York, N.Y.) 316(5829): 1331-6, Jun 2007 Notes: Middle-Author Contribution: I provided data sets, analysis, contributed text, and helped revised the manuscript.
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Last updated: 06/28/2021
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