Liming Liang
Associate Professor

Liming Liang

Associate Professor of Statistical Genetics

Epidemiology

lliang@hsph.harvard.edu

Other Positions

Faculty Affiliate in the Department of Biostatistics

Biostatistics

Harvard T.H. Chan School of Public Health


Overview

Our group focuses on developing the computational and statistical tools required for understanding human genetic variation, with a particular focus on complex human disease. We are currently working on the following areas:

(1) Analysis of gene expression and methylation data, particular eQTL/meQTL mapping using both microarray and RNA-seq data, gene expression/methylation network estimation and its association with disease and trait of interest.

(2) New statistical approaches for the analysis of next-generation sequencing data. Ongoing projects include high depth sequencing on ~4000 breast cancer case-control subjects from multiple populations. The goals include fine mapping causal loci responsible for breast cancer risk and developing optimal design for next-generation sequencing studies.

(3) New statistical framework to maximize the utility of multiple related phenotypes and elucidate how genetic and epigenetic variants and their interaction with environmental factors involve in pathogenesis of complex diseases and traits.

(4) Statistical model to integrate genome-wide eQTL/meQTL data with genome-wide association studies.

We are currently part of several large genetic studies, including the 1000 Genomes Project (www.1000genomes.org), genome-wide association studies for type-2 diabetes and related phenotypes and biomarkers, childhood asthma, atopic dermatitis, colorectal cancer, melanoma, global gene expression and methylation.

I am still maintaining my research website at CSG at the University of Michigan.

Program Coordinator: Zachary Schwartz, zschwartz@hsph.harvard.edu


Bibliography

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

Chambers JC, Zhang W, Sehmi J, Li X, Wass MN, Van der Harst P, Holm H, Sanna S, Kavousi M, Baumeister SE, Coin LJ, Deng G, Gieger C, Heard-Costa NL, Hottenga JJ, Kühnel B, Kumar V, Lagou V, Liang L, Luan J, Vidal PM, Mateo Leach I, O'Reilly PF, Peden JF, Rahmioglu N, Soininen P, Speliotes EK, Yuan X, Thorleifsson G, Alizadeh BZ, Atwood LD, Borecki IB, Brown MJ, Charoen P, Cucca F, Das D, de Geus EJ, Dixon AL, Döring A, Ehret G, Eyjolfsson GI, Farrall M, Forouhi NG, Friedrich N, Goessling W, Gudbjartsson DF, Harris TB, Hartikainen AL, Heath S, Hirschfield GM, Hofman A, Homuth G, Hyppönen E, Janssen HL, Johnson T, Kangas AJ, Kema IP, Kühn JP, Lai S, Lathrop M, Lerch MM, Li Y, Liang TJ, Lin JP, Loos RJ, Martin NG, Moffatt MF, Montgomery GW, Munroe PB, Musunuru K, Nakamura Y, O'Donnell CJ, Olafsson I, Penninx BW, Pouta A, Prins BP, Prokopenko I, Puls R, Ruokonen A, Savolainen MJ, Schlessinger D, Schouten JN, Seedorf U, Sen-Chowdhry S, Siminovitch KA, Smit JH, Spector TD, Tan W, Teslovich TM, Tukiainen T, Uitterlinden AG, Van der Klauw MM, Vasan RS, Wallace C, Wallaschofski H, Wichmann HE, Willemsen G, Würtz P, Xu C, Yerges-Armstrong LM, Abecasis GR, Ahmadi KR, Boomsma DI, Caulfield M, Cookson WO, van Duijn CM, Froguel P, Matsuda K, McCarthy MI, Meisinger C, Mooser V, Pietiläinen KH, Schumann G, Snieder H, Sternberg MJ, Stolk RP, Thomas HC, Thorsteinsdottir U, Uda M, Waeber G, Wareham NJ, Waterworth DM, Watkins H, Whitfield JB, Witteman JC, Wolffenbuttel BH, Fox CS, Ala-Korpela M, Stefansson K, Vollenweider P, Völzke H, Schadt EE, Scott J, Järvelin MR, Elliott P, Kooner JS.

Nat Genet. 2011 Oct 16. 43(11):1131-8. PMID: 22001757


News

Program explores molecular underpinnings of chronic diseases

December 4, 2019—For many years, epidemiological data has shown a link between obesity and asthma. While researchers have long hypothesized that obesity increases the risk of asthma, why or how that risk is increased isn’t entirely clear. A…