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Sharon Lutz

Assistant Professor

Dr. Sharon Lutz is an Assistant Professor in the Department of Population Medicine with a secondary appointment in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. Dr. Lutz received her MA in Mathematics from the University of Colorado at Boulder and her MA and PhD in Biostatistics from Harvard University. She completed her postdoctoral fellowship at the Institute for Genomic Mathematics at the University of Bonn, Germany and the Department of Biostatistics at Harvard T.H. Chan School of Public Health. 

Dr. Lutz's research interests include the theory and application of statistical methods for genetic and genomics. These methods are used to determine and understand the path from gene to disease and the role of the environment and sex using causal inference, mediation analysis, Mendelian randomization, machine learning, deep learning, and computational statistics. Dr. Lutz’s methodological contributions include the development of approaches for pleiotropy, ascertainment bias, direct and indirect genetic effects, gene by environment/sex interactions, and approaches to combine data. Dr. Lutz is the principal investigator of a NIMH R01 focused on developing methods to detect sex effects in genetic association studies of depression for common variants and polygenic effects. 

In addition, Dr. Lutz has either led or collaborated on several applications of statistical genetics and genomics methods for depression, COPD, asthma, cigarette smoking, alcohol use, mental health, maternal health, or related traits. Dr. Lutz has also served as the site PI for a NIMH R01 to develop new methods to test for a genetic association with mental health phenotypes in family-based studies.

 

Focus Areas
  • Genomics / Precision Medicine

Publications

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. (Pubmed Abstract)

Authors
Chen F, Wang X, Jang SK, Quach BC, Weissenkampen JD, Khunsriraksakul C, Yang L, Sauteraud R, Albert CM, Allred NDD, Arnett DK, Ashley-Koch AE, Barnes KC, Barr RG, Becker DM, Bielak LF, Bis JC, Blangero J, Boorgula MP, Chasman DI, Chavan S, Chen YI, Chuang LM, Correa A, Curran JE, David SP, Fuentes LL, Deka R, Duggirala R, Faul JD, Garrett ME, Gharib SA, Guo X, Hall ME, Hawley NL, He J, Hobbs BD, Hokanson JE, Hsiung CA, Hwang SJ, Hyde TM, Irvin MR, Jaffe AE, Johnson EO, Kaplan R, Kardia SLR, Kaufman JD, Kelly TN, Kleinman JE, Kooperberg C, Lee IT, Levy D, Lutz SM, Manichaikul AW, Martin LW, Marx O, McGarvey ST, Minster RL, Moll M, Moussa KA, Naseri T, North KE, Oelsner EC, Peralta JM, Peyser PA, Psaty BM, Rafaels N, Raffield LM, Reupena MS, Rich SS, Rotter JI, Schwartz DA, Shadyab AH, Sheu WH, Sims M, Smith JA, Sun X, Taylor KD, Telen MJ, Watson H, Weeks DE, Weir DR, Yanek LR, Young KA, Young KL, Zhao W, Hancock DB, Jiang B, Vrieze S, Liu DJ
Abbreviation
Nat Genet
Publication Date
2023-01-26
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