Skip to Content
SBMI Horizontal Logo
image of Han Chen, PhD

Han Chen, PhD

Associate Professor
Joint appointment with the School of Public Health


 


Contact

Han.Chen.2@uth.tmc.edu | 713-500-9958



Han Chen, Ph.D. became an assistant professor at the UTHealth Houston on December 1, 2016. Chen holds a joint appointment with McWilliams School of Biomedical Informatics at UTHealth Houston and UTHealth’s School of Public Health. Before joining UTHealth, Chen was a postdoctoral research fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. Prior to that, Chen received his B.S. in biological sciences from Tsinghua University in 2007, M.A. in statistics from Columbia University in 2009, and Ph.D. in biostatistics from Boston University School of Public Health in 2013.

Chen’s research interests mainly focus on statistical genetics and genomics, including computational methods for analyzing large-scale sequencing data, parametric and semiparametric statistical models for correlated data analysis, rare genetic variant association analysis, meta-analysis, gene-environment interactions, with applications to complex disease genetics. His current research projects include: 1) Computationally efficient statistical association tests to account for population structure and relatedness in large-scale multi-ethnic sequencing studies; 2) Gene-environment and gene-treatment interaction tests for epidemiological and pharmacogenomic studies; and 3) Genetic epidemiological studies on complex heritable human diseases, such as obstructive sleep apnea. In 2015, Chen received an NIH Pathway to Independence Award (K99/R00) from the National Heart, Lung, and Blood Institute.

“Precision medicine research involves multi-disciplinary collaboration between bioinformaticians, biostatisticians, epidemiologists and physicians.” Chen said, “With the advance of technology, we are generating and collecting huge amount of data every day. I am excited about the development of statistical methods and computational tools that can be applied to big data research. Together, we can better understand, treat and prevent complex diseases and improve human health.”



Education


  • PhD, Biostatistics, 2013, Boston University
  • MA, Statistics, 2009, Columbia University
  • BS, Biological Sciences, 2007, Tsinghua University

Areas of Expertise


  • Statistical genetics and genomics
  • Correlated data analysis
  • High-dimensional sparse data analysis
  • Statistical computing
  • Meta-analysis
  • Survival analysis
  • Gene-environment interaction
  • Genetic epidemiology
  • Complex heritable human diseases

Staff Support


Susan Rojas | 713-500-3654

Publications

Book Chapters

[1] Chen H, Dupuis J. Rare Variant Association Analysis: Beyond Collapsing Approaches (Chapter 11, pages 149-167). In “Assessing Rare Variation in Complex Traits: Design and Analysis of Genetic Studies”, edited by Zeggini E, Morris A. Springer, New York 2015 (ISBN 978-1-4939-2823-1).

Peer-Reviewed Journal Publications

[1] Strawbridge RJ, Dupuis J, Prokopenko I, Barker A, Ahlqvist E, Rybin D, Petrie JR, Travers ME, Bouatia-Naji N, Dimas AS, Nica A, Wheeler E, Chen H et al. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes 2011, 60 (10): 2624-2634.

[2] Chen H*, Hendricks AE*, Cheng Y, Cupples AL, Dupuis J, Liu CT. Comparison of statistical approaches to rare variant analysis for quantitative traits. BMC Proceedings 2011, 5 (S9): S113.

* Equal contribution

[3] Scott RA, Chu AY, Grarup N, Manning AK, Hivert MF, Shungin D, Tönjes A, Yesupriya A, Barnes D, Bouatia-Naji N, Glazer NL, Jackson AU, Kutalik Z, Lagou V, Marek D, Rasmussen-Torvik LJ, Stringham HM, Tanaka T, Aadahl M, Arking DE, Bergmann S, Boerwinkle E, Bonnycastle LL, Bornstein SR, Brunner E, Bumpstead SJ, Brage S, Carlson OD, Chen H et al. No interactions between previously associated 2-hour glucose gene variants and physical activity or BMI on 2-hour glucose levels. Diabetes 2012, 61 (5): 1291-1296.

[4] Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, Rybin D, Liu CT, Bielak LF, Prokopenko I et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nature Genetics 2012, 44 (6): 659-669.

[5] Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè AV, Steinthorsdottir V, Strawbridge RJ, Khan H, Grallert H, Mahajan A, Prokopenko I, Kang HM, Dina C, Esko T, Fraser RM, Kanoni S, Kumar A, Lagou V, Langenberg C, Luan J, Lindgren CM, Müller-Nurasyid M, Pechlivanis S, Rayner NW, Scott LJ, Wiltshire S, Yengo L, Kinnunen L, Rossin EJ, Raychaudhuri S, Johnson AD, Dimas AS, Loos RJ, Vedantam S, Chen H et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nature Genetics 2012, 44 (9): 981-990.

[6] Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, Mägi R, Strawbridge RJ, Rehnberg E, Gustafsson S, Kanoni S, Rasmussen-Torvik LJ, Yengo L, Lecoeur C, Shungin D, Sanna S, Sidore C, Johnson PC, Jukema JW, Johnson T, Mahajan A, Verweij N, Thorleifsson G, Hottenga JJ, Shah S, Smith AV, Sennblad B, Gieger C, Salo P, Perola M, Timpson NJ, Evans DM, Pourcain BS, Wu Y, Andrews JS, Hui J, Bielak LF, Zhao W, Horikoshi M, Navarro P, Isaacs A, O'Connell JR, Stirrups K, Vitart V, Hayward C, Esko T, Mihailov E, Fraser RM, Fall T, Voight BF, Raychaudhuri S, Chen H et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nature Genetics 2012, 44 (9): 991-1005.

[7] Chen H, Manning AK, Dupuis J. A method of moments estimator for random effect multivariate meta-analysis. Biometrics 2012, 68 (4): 1278-1284.

[8] Chen H, Meigs JB, Dupuis J. Sequence kernel association test for quantitative traits in family samples. Genetic Epidemiology 2013, 37 (2): 196-204.

[9] DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Consortium, Mahajan A, Go MJ, Zhang W, Below JE, Gaulton KJ, Ferreira T, Horikoshi M, Johnson AD, Ng MC, Prokopenko I, Saleheen D, Wang X, Zeggini E, Abecasis GR, Adair LS, Almgren P, Atalay M, Aung T, Baldassarre D, Balkau B, Bao Y, Barnett AH, Barroso I, Basit A, Been LF, Beilby J, Bell GI, Benediktsson R, Bergman RN, Boehm BO, Boerwinkle E, Bonnycastle LL, Burtt N, Cai Q, Campbell H, Carey J, Cauchi S, Caulfield M, Chan JC, Chang LC, Chang TJ, Chang YC, Charpentier G, Chen CH, Chen H et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nature Genetics 2014, 46 (3): 234-244.

[10] Chen H, Lumley T, Brody J, Heard-Costa NL, Fox CS, Cupples LA, Dupuis J. Sequence kernel association test for survival traits. Genetic Epidemiology 2014, 38 (3): 191-197.

[11] Chen H, Choi SH, Hong J, Lu C, Milton JN, Allard C, Lacey SM, Lin H, Dupuis J. Rare genetic variant analysis on blood pressure in related samples. BMC Proceedings 2014, 8 (S1): S35.

[12] Lin H, Wang M, Brody JA, Bis JC, Dupuis J, Lumley T, McKnight B, Rice K, Sitlani CM, Reid JG, Bressler J, Liu X, Davis BC, Johnson AD, O’Donnell CJ, Kovar CL, Dinh H, Wu Y, Newsham I, Chen H et al. Strategies to design and analyze targeted sequencing data: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) targeted sequencing study. Circulation: Cardiovascular Genetics 2014, 7 (3): 335-343.

[13] Chen H, Meigs JB, Dupuis J. Incorporating gene-environment interaction in testing for association with rare genetic variants. Human Heredity 2014, 78 (2): 81-90.

[14] Chen H*, Malzahn D*, Balliu B, Li C, Bailey JN. Testing genetic association with rare and common variants in family data. Genetic Epidemiology 2014, 38 (S1): S37-S43.

* Equal contribution

[15] Gaulton KJ, Ferreira T, Lee Y, Raimondo A, Mägi R, Reschen ME, Mahajan A, Locke A, William Rayner N, Robertson N, Scott RA, Prokopenko I, Scott LJ, Green T, Sparso T, Thuillier D, Yengo L, Grallert H, Wahl S, Frånberg M, Strawbridge RJ, Kestler J, Chheda H, Eisele L, Gustafsson S, Steinthorsdottir V, Thorleifsson G, Qi L, Karssen LC, van Leeuwen EM, Willems SM, Li M, Chen H et al. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci. Nature Genetics 2015, 47 (12): 1415-1425.

[16] Lin X, Lee S, Wu MC, Wang C, Chen H, Li Z, Lin X. Test for rare variants by environment interactions in sequencing association studies. Biometrics 2016, 72 (1): 156-164.

[17] Chen H*, Wang C*, Conomos MP, Stilp AM, Li Z, Sofer T, Szpiro AA, Chen W, Brehm JM, Celedón JC, Redline S, Papanicolaou GJ, Thornton TA, Laurie CC, Rice K, Lin X. Control for population structure and relatedness for binary traits in genetic association studies via logistic mixed models. The American Journal of Human Genetics 2016, 98 (4): 653-666.

* Equal contribution

[18] Hobbs BD, Parker MM, Chen H, Lao T, Hardin M, Qiao D, Hawrylkiewicz I, Sliwinski P, Yim JJ, Kim WJ et al. Exome array analysis identifies a common variant in IL27 associated with chronic obstructive pulmonary disease. The American Journal of Respiratory and Critical Care Medicine 2016, 194 (1): 48-57.

[19] Liang J, Cade BE, Wang H, Chen H, Gleason KJ, Larkin EK, Saxena R, Lin X, Redline S, Zhu X. Comparison of heritability estimation and linkage analysis for multiple traits using principal component analyses. Genetic Epidemiology 2016, 40 (3): 222-232.

[20] Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, Ma C, Fontanillas P, Moutsianas L, McCarthy DJ, Rivas MA, Perry JRB, Sim X, Blackwell TW, Robertson NR, Rayner NW, Cingolani P, Locke AE, Fernandez Tajes J, Highland HM, Dupuis J, Chines PS, Lindgren CM, Hartl C, Jackson AU, Chen H et al. The genetic architecture of type 2 diabetes. Nature 2016, 536 (7614): 41-47.

[21] Horikoshi M, Pasquali L, Wiltshire S, Huyghe JR, Mahajan A, Asimit JL, Ferreira T, Locke AE, Robertson NR, Wang X, Sim X, Fujita H, Hara K, Young R, Zhang W, Choi S, Chen H et al. Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms. Human Molecular Genetics 2016, 25 (10): 2070-2081.

[22] Cade BE, Chen H, Stilp AM, Gleason KJ, Sofer T, Ancoli-Israel S, Arens R, Bell GI, Below JE, Bjonnes AC et al. Genetic associations with obstructive sleep apnea traits in Hispanic/Latino Americans. The American Journal of Respiratory and Critical Care Medicine 2016, 194 (7): 886-897.

[23] Walford GA, Gustafsson S, Rybin D, Stan?áková A, Chen H, Liu CT, Hong J, Jensen RA, Rice K, Morris AP et al. Genome-wide association study of the modified Stumvoll insulin sensitivity index identifies BCL2 and FAM19A2 as novel insulin sensitivity loci. Diabetes 2016, 65 (10): 3200-3211.

[24] Liu C, Kraja AT, Smith JA, Brody JA, Franceschini N, Bis JC, Rice K, Morrison AC, Lu Y, Weiss S, Guo X, Palmas W, Martin LW, Chen YDI, Surendran P, Drenos F, Cook JP, Auer PL, Chu AY, Tsosie KS, Zhao W, Jakobsdóttir J, Lin LA, Stafford JM, Amin N, Mei H, Yao J, Voorman A, Larson MG, Grove ML, Smith AV, Hwang SJ, Chen H et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nature Genetics 2016, 48 (10): 1162-1170.

[25] Wang H, Cade BE, Chen H, Gleason KJ, Saxena R, Feng T, Larkin EK, Ramachandran VS, Lin H, Patel SR et al. Variants in Angiopoietin-2 (ANGPT2) contribute to variation in Nocturnal Oxyhemoglobin Saturation Level. Human Molecular Genetics 2016, Oct 18 [Epub ahead of print].