We are 5!
Dr. Manju Mamtani
Peer-reviewed research papers: 78
Presentations at International meetings: 6
Book chapters: 2
Computer Programs: 1
Diabetes – I am especially interested in the pathophysiology and genetic epidemiology of Type 2 Diabetes. During my volunteering at TBRI, I was given access to the excellent data on the San Antonio Family Heart Study (SAFHS) that focuses on 1,400 members of more than 40 large Mexican American families in San Antonio. The SAFHS aims to quantify the relative contributions of genetic and environmental factors to the risk of developing cardiovascular diseases and metabolic syndrome. During this time I have contributed to seven different papers that deal with anthropometric and lipidomic risk factors of existing and future development of type 2 diabetes. These papers have been published in high impact journals like Diabetologia, Hypertension, Lipid Research, Lipids in Health and Disease, etc. My interest in this field springs from conducting a case-control study in India in 2004 as a part of my dissertation and publishing a highly cited paper (Mamtani and Kulkarni, Archives of Medical Research, 2005) that dealt with the specific association of waist circumference with the risk of type 2 diabetes. Currently, I oversee an Indian study in the Sindhi ethnic group which is investigating the genetic bases of T2D in an Indian context.
Genetics - I have successfully conducted genotyping studies on several single nucleotide polymorphisms (SNPs) using the restriction fragment length polymorphism (RFLP) as well as the Taqman Allelic discrimination approaches. I have also genotyped 57 microsatellite markers using the ABI Prism system in relation to important contributory genes in autoimmune diseases. Further, I have conducted genotyping of the copy number variations in two immunity-related genes (CCL3L1 and FCGR3B) using Taqman assays. I am also well versed with techniques like DNA isolation and Gel electrophoresis. Also, I have extensive experience in the research related to the most intensively scrutinized genetic disease – β thalassemia.
Biostatistics – I have conducted complex statistical analyses like generalized estimating equations for panel data, multivariate and polynomial logistic regression analyses, Kaplan-Meier survival plots, multivariate Cox proportional hazards modeling and correlation analyses using the STATA software. Recently, I have also helped analyze highly complex epigenetic data on the CpG methylation sites from HIV patients with differing phenotypes. During my volunteering at TBRI, I have also worked with the popular SOLAR software used for analyses of pedigree data.
Epidemiology – I received my training in MBBS (equivalent to the MD degree in the USA) and MD (Preventive and Social medicine, equivalent to the MPH degree in the USA). During the latter training, I was introduced to and involved in the principles and practices of Epidemiology. As a part of practicum requirement for my MPH equivalent course, I conducted a case-control study on the risk factors of Type 2 Diabetes (referred to above). In my research at UTHSCSA, I employed these epidemiological principles effectively. For example, I used techniques and methods such as case-control studies, cross-sectional studies and cohort studies from the several study cohorts available for analysis.
Infectious Diseases – I have substantial interest and experience in epidemiological and clinical research studies involving infectious diseases. Specifically, I have worked extensively in the field of tuberculosis since it is a high-prevalence scourge globally but especially in India. I have conducted clinical as well as genetic studies in tuberculosis that dealt with the CCR5/CCL3L1 association with tuberculosis, use of interferon-gamma assays (Quantiferon®) for screening of latent and active tuberculosis and clinical trial of high dose INH for treatment of MDR tuberculosis. I also have substantial experience in the research of childhood diarrheas that includes a clinical trial of zinc supplementation in acute diarrhea, meta-analyses of the therapeutic and preventive use of zinc supplementation, organism-specific effectiveness of zinc supplementation (specifically in relation to E. coli, Klebsiella and rotavirus) and invited review article on the roles of zinc supplementation in the pathophysiology of diarrhea. Lastly, I have also worked on multicenter studies (APPIS) in which we tested the effectiveness of a novel nomogram in predicting early mortality in cases of severe pneumonia and the use of radiography to predict and risk-stratify adverse outcomes in severe pneumonia.
Autoimmune Diseases – I have been intricately involved with the research on Autoimmune Diseases like Systemic Lupus Erythematosus (SLE), Sjogren's syndrome and Rheumatoid Arthritis. I have participated in studies on the host-genetic aspects of these diseases with an emphasis on the potential influence of the chemokine-chemokine receptor nexus (especially CCR5 and CCL3L1) in the pathogenesis of these diseases. My work relates to the understanding that there exist common genetic variants for diseases of similar disposition (the "common variant/multiple disease" hypothesis). The spectrum of my involvement in research on autoimmune diseases extends from generation of biologically viable and plausible hypotheses, conducting genotyping studies, conducting biostatistical analyses and writing high-impact manuscripts for publication in reputed, peer-reviewed journals. In the lab, I had access to highly informative cohorts from Colombia, Ohio and San Antonio and have conducted detailed analyses of these cohorts which have thus far culminated into several research papers. In addition, I have been working on three infectious diseases with heavy immunological underpinnings - Kawasaki disease (KD), tuberculosis and HIV-AIDS. I have also collaborated with Dr. Jane Burns and her team from University of California at San Diego who is a world-renowned expert in the field of Kawasaki disease.
Dr. Hemant Kulkarni
Peer-reviewed research papers: 136
Presentations at International meetings: 12
Book chapters: 3
Computer programs: 10
Statistical Genetics – I worked as Staff Scientist II at the Texas Biomedical Research Institute for over three years. During this time, I worked closely with the world-renowned expert in statistical genetics, Dr. John Blangero. I have gained extensive experience in the field of family studies, studies of the genome, lipidome, methylome and transcriptome. I have several publications relating to my work in this area in peer-reviewed, high impact factor journals. I have developed a new method to quantify the lipidomic distance between individuals for use under the variance components framework (Kulkarni et al. J Lipd Res 2014). I am currently working on several aspects of the genetics of type 2 diabetes and obesity in Mexican Americans.
Biostatistics – I have conducted biostatistical analyses in innumerable research projects that I have been involved with. My specific areas of interest are as follows:
Non-linear dynamics of biological phenomena: Specifically, I have worked with fuzzy logic and have published on the potential use of fuzzy logic in making surgical decisions in trauma patients. This work has been lauded by experts in the field (as detailed in the Invited Commentary written by Dr. T Buchman:”Fuzzy logic, clear reasoning”, Surgery 2000 127(3): 257).
Survival analyses: I have expertise in conducting the survival analyses as reflected by my publications. For the past 8 years that I have worked at UTHSCSA, I have done extensive survival analyses that include the use of Kaplan-Meier survival plots, log rank and Wilcoxon tests, Cox proportional hazards modeling, and modeling and interpretation of Schoenfeld residuals.
I have conducted several meta-analyses on topics of clinical importance. My five papers dealing with meta-analysis have been published and one paper is currently in review. I have also served on the Expert Panel of AHRQ's recent systematic review on use of thrombectomy devices in STEMI and non-STEMI patients.
Mathematical modeling: I have conducted mathematical modeling of the biological datasets.
My work on Markov modeling of the predicted change in the distribution of gene copy number in populations of different ethnic background has already been published (Gonzalez et al, Science 2005;307:1434-1440.)
The second aspect of my mathematical modeling work was published in PLoS One and deals with the prediction of how the and genotypes may strongly influence the HIV epidemic trajectories in closed populations and the estimates of HIV vaccine efficacy.
A third area of the mathematical modeling work I have done includes the use of non-linear generalized estimating equations technique to population level dynamics of the CD4+ T cell counts that are dictated by host genotypes and how these population–level dynamics capture the response to highly active antiretroviral therapy (Ahuja et al, Nat Med 2008; 14(4):413-20)
Another feature of the mathematical modeling work that I was involved in deals with the development of a novel surrogate marker for HIV disease course – cumulative CD4 count (cCD4). The development and validity of this parameter has been published (Dolan et al. Nat Immunol 2007 Dec;8(12):1324-1336)
My work on the risk stratification of HIV-infected subjects based on the CCL3L1 and CCR5 genotypes was published in PLoS One.
I have worked on large publicly available datasets of gene expression microarrays for disease status classification in the field of cancers. I have also conducted genome-wide association studies for SNPs and methylomes.
Cost-effectiveness studies: I have conducted interesting cost-effectiveness analyses related to the utility of screening programs for type 2 diabetes with a special emphasis on the role of plasma lipidomics in diabetes screening. My contributions to the series on the costs and outcomes of PCI in the United States is a reflection of my deep interest in cost-effectiveness studies.
I have expertise in – both flat-field and relational databases – of highly complex and dense genetic datasets and have contributed to genetic epidemiology of several genes that are associated with HIV/AIDS including CCR5, CCL3L1, CCL4L1, DARC, ApoE, MBL-2 and MCP-1. I have written several task-dedicated scripts in Visual Basic that have helped accomplish complex data management tasks in the Microsoft Access and Microsoft Excel environment.
I have worked in collaboration with , Dr. Partho Sengupta, Professor of Cardiology at Mt. Sinai Hospital, NY on several advanced aspects of cardiac imaging. These projects included the use of sophisticated statistical analyses including hierarchical clustering, biomarker analyses and incremental diagnostic indices.
Data Science – Keeping pace with the increasing awareness and demand of advanced data science techniques, I have also mastered and successfully worked with my clients. For example, I have recently completed a high-dimensional data analysis using Machine Learning (ML) algorithms to assess the value of signal-processed surface ECG to predict diastolic dysfunction. The ML techniques used in this project included a wide array comprising discriminant analyses, neural networks, component-wise boosting, random forests, and support vector machines. I have substantial experience of working in the R environment for these analyses.
Epidemiology – I have been trained as a Clinical Epidemiologist in the Robertson-Wood-Johnson program for Clinical Epidemiology at the University of North Carolina at Chapel Hill, NC, USA in 1997. The coursework comprised of detailed description and hands-on exercises in quantitative and qualitative aspects of descriptive, analytical and interventional epidemiology.
Big data analyses – Through my involvement with genome- and epigenome-level datasets, I go introduced to and then passionate about big data analyses and combining this with various machine learning techniques. In collaboration with Dr. Partho Sengupta, Chief, Section of Cardiology, West Virginia University, Morgantown, WV and the Heart Test Labs (Westlake, Texas) I have conducted some very interesting analyses of the highly sensitive, wavelet-transformed EKGs and their association with relaxation abnormalities. I have mastered several ML techniques including neural networks and random forests which I have used in my soon-to-be-published analyses of the above-mentioned data.