Department of Internal Medicine, Section of Molecular Medicine
Wake Forest School of Medicine
Sobha Puppala, Ph.D.
Center for Precision Medicine
Nutrition Research Center (NRC) Building, G-55, Medical Center Blvd, Winston-Salem, NC 27157
Education and Training
B.Sc., Botany, Zoology, Chemistry (1981)
M.A., Anthropology (1983)
Ph.D., Biological Anthropology (2001)
Postdoc, Epidemiology and Biostatistics (2001-2003 )
Postdoc, Genetics, (2003-2009)
Dr. V. S. Krishna College, Waltair, AP, India
Andhra University, Waltair, AP, India
University of Kansas, Lawrence, KS
Case Western Reserve University, Cleveland, OH
Southwest Foundation for Biomedical Research, San Antonio, TX
Staff Scientist I, Texas Biomedical Research Institute, San Antonio, TX (2010-2017)
Tools and Methods
Pedsys and SOLAR
Computer Assisted Stereology Toolbox (CAST) 2.0 system (CAST) to quantify lipid content in liver using stereoscopy.
Weighted gene co-expression network analysis (WGCNA)
Ingenuity Pathway Analysis software
Partek Genomics Suite
Dr. Puppala received training in anthropology, genetic epidemiology and statistical genetics. She currently studies the genetic basis of complex diseases and their phenotypes. For over a decade, Dr. Puppala has been working in genetic epidemiology and statistical genetics, and most of her research effort has been focused on detecting genes that play a role in our genetic susceptibility to diseases such as type 2 diabetes, obesity, and the metabolic syndrome. Dr. Puppala conducted large data set analyses from extended Mexican American families as part of the San Antonio Family Diabetes/Gallbladder Study. Here, she identified genes responsible for susceptibility to gallbladder disease, hypertension and diabetic kidney disease-related traits. The latter is of particular importance as it is the most common cause of end-stage renal disease. Dr. Puppala also performed several analyses to data to identify genes and functional variants that contribute to the variation in type 2 diabetes-related traits in Mexican American populations. More recently, she started to analyze data on the primate fetal response to maternal obesity. She conducts her studies as part of the research group led by Dr. Laura Cox.
Inside the Lab
Genetic linkage analyses: As part of genetic epidemiologic investigation, we identified major susceptibility genes for gallbladder disease for the first time in Mexican American families, (San Antonio Family Diabetes/Gallbladder Study) located on Chromosome 1. We performed a genome-wide linkage analysis and found evidence for a major susceptibility gene that differentially influences glomerular filtration rate, which is used to assess the progression of renal disease. Our studies also identified major genes for systolic blood pressure in the Veterans Administration Genetic Epidemiology Study of Mexican Americans.
Genetic association analyses: We conducted several genetic association analyses to identify and characterize the genetic variants that contribute to the variation in type 2 diabetes related traits in Mexican American populations.
Metabolic risk factors in Mexican American (MA) children: We looked at cardiometabolic risk factors in children and adolescents without type 2 diabetes, to examine the genetic basis of metabolic syndrome, the genetic basis for correlations between the number of metabolic syndrome components and measures of obesity, insulin resistance, inflammation and physical fitness; and the clustering of MS-related risk factors as influenced by common genetic factors. This study, part of the Mexican American children and adolescents in the San Antonio Family Assessment of Metabolic Risk Indicators in Youth study (SAFARI), also identified a major susceptibility locus influencing preterm birth and metabolites as novel biomarkers for childhood obesity-related traits in Mexican-American children.
Type 2 diabetes gene discovery studies. As collaborators in the type 2 diabetes susceptibility gene discovery project, part of the San Antonio Mexican American Family Studies, we analyzed data to identify genes and functional variants that influence complex disease phenotypes in human sequence data