Rajeev Ayyagari
Lana Dinic
David Fardo
Jesse Hsu
Kihwa Kang, Ph.D.
Clifford Meyer, Ph.D.
Edward Ruiz-Narvaez
Jeremy Stuart, D.Sc.
Kelvin Tsai, M.D.
Sara Vallerie
Katy Wellen
Hongying Zhong
Rajeev Ayyagari is a 2nd year predoctoral student in the Department of Biostatistics. He has a unique background in both biostatistics (BSc and MS degrees at Indian Statistical Institute) and computer science (MS degree from University of Maryland). His efforts have been largely focused on computational aspects of statistics (data mining and statistical learning theory) and during his MS degree, he designed efficient algorithms for data mining problems and computationally intensive statistical applications. Recognizing that he wished to pursue research in an academic setting, he applied to our program with the "desire to be at the center of progress in this interdisciplinary effort, rather than contribute from the edges."
Lana Dinic: Entering 1st year HSPH predoctoral student in the Biological Sciences in Public Health (BPH) program. Lana has a BS degree in Life Sciences from Mt. Holyoke College. She applied to our program “motivated by a passion for making meaningful contributions to knowledge that will address problems in human disease”. In particular, her interests lie in reducing the impact of infectious disease on global health, and she is seeking to develop expertise in the area of molecular biology of pathogenic organisms.
David Fardo: Predoctoral student, PhD candidate in the Department of Biostatistics. David examined the effects of differing phenotype characterizations on the power to detect a disease susceptibility locus / phenotype association. Specifically, his project used R-based simulations of trios (simulated genotype and phenotype of one offspring and genotypes of both parents) to compare the power of family based association tests (FBATs) when using a continuous trait against different rules of dichotomizing the trait. These simulations were carried out using a progression of reasonable assumptions regarding heritability, allele frequency and sample size in order to gauge how the different dichotomizations affect power in varying situations.
Jessie Hsu: First year predoctoral student in the Department of Biostatistics. She has combined training with a BS degree from the University of Washington as a double major in biochemistry and statistics. Her research experience as a Howard Hughes Medical Institute Research Intern at the Fred Hutchinson Cancer Research Center in Seattle was her inspiration for pursuing a PhD in biostatistics. She studied nucleotide diversity in human olfactory genes with an aim to quantify genetic variation and to describe selective pressures underlying allelic diversity. This background in computational biology fit well with the training the Roadmap program seeks to provide. Jesse’s ultimate goal is to be a "biostatistician at a research institution …[to] engage in collaborative research with scientists and doctors."
Kihwa Kang, Ph.D. (Food Microbiology and Toxicology, University of Wisconsin-Madison): Postdoctoral fellow co-mentored by Drs. Chih-Hao Lee and Frank Hu at Harvard School of Public Health. Hypertriglyceridemia is frequently associated with obesity and metabolic diseases including insulin resistance. Based on the findings that nuclear receptor PPAR delta senses dietary lipids and regulates fat catabolism, the hypothesis behind Kihwa's project is that PPARd is a key regulator of metabolic homeostasis and insulin sensitivity. Her project examines the effect of receptor deletion on glucose and lipid metabolism as well as on insulin signaling using mouse models. As nuclear receptors control biological processes through transcriptional regulation, she seeks to identify target genes of PPAR in critical metabolic pathways to dissect the molecular mechanism by which PPAR regulates metabolism. After establishing the role of PPAR in metabolic homeostasis and insulin sensitivity, she will test gene-diet interactions by examining whether PPAR delta polymorphisms modify the effects of dietary fatty acids and carbohydrates on risk of developing obesity, the metabolic syndrome, and type 2 diabetes. A large cohort study led by Dr. Frank Hu lends itself to this interdisciplinary investigation.
Clifford Meyer, Ph.D. (Chemical Engineering, Princeton University): Postdoctoral fellow co-mentored by Drs. Shirley Liu and Myles Brown at DFCI. Their joint research project was on chromatin immunoprecipitation (ChIP) tiling arrays and the development of analysis software that is reliable, easy-to-use and capable of representing important features of the data and their relation to the genome. Cliff's particular interests reside in normalization of raw data, data filtering, ChIP-enriched region location and the identification of binding sites and features of the genome such as protein coding sequences and motifs.
Edward Ruiz-Navaerez: HSPH predoctoral student, 3rd year DSc candidate in the Departments of Epidemiology and Nutrition. Apolipoprotein CIII (apoCIII) and AV (apoAV) regulate triglyceride metabolism in opposite ways. Also, several studies have shown that naturally occurring sequence variation in both APOC3 and APOA5 genes affects plasma triglyceride levels, but evidence for an association with risk of coronary heart disease (CHD) is scarce. Edward's work involved analysis of single nucleotide polymorphisms (SNPs) in the APOC3 and APOA5 genes to determine whether haplotypes defined by these genetic variants are associated with the risk of nonfatal myocardial infarction (MI) in the Costa Rican population. He also examined whether haplotypes interact with non-genetic factors (for example, diet) on the determination of MI risk or plasma lipid concentrations.
Jeremy Stuart, D.Sc. (Cancer Cell Biology, Harvard School of Public Health): Post-doctoral fellow co-mentored by Drs. Zhi-min Yuan and Gokhan Hotamisligil. One of the most over-looked aspects of obesity-associated disorders is the predisposition to tumors. Jeremy tested the hypothesis that adipose tissue produces factors that modulate the growth of tumor cells and contribute to the cancer risk associated with weight gain. To address this question, he studied the interaction between adipocytes and tumor cells in vitro using a 3D cell culture approach. The ultimate goal being to identify adipocyte derived factors regulating tumor growth in vitro.
Kelvin Tsai, M.D.: HSPH graduate of the BPH program. Kelvin employed heterotypic coculture models to study the interactions between mammary stromal fibroblasts and epithelial cells. This model system explores the effects of low-level stress and cell premature senescence on breast morphogenesis and carcinogenesis. His work led to a first author paper published in Cancer Research.
Sara Vallerie: HSPH predoctoral student, BPH program. Sara's projects focused on elucidating the roles of JNK1 and JNK3 in the metabolic syndrome. JNK1 and JNK2 have already been shown to be key players in obesity-associated disease. Using molecular and cellular biology, physiological, and biochemical techniques, Sara explored their roles in metabolic disease. Sara was recently awarded an individual NRSA to support her efforts.
Katy Wellen: HSPH graduate of the BPH program. Katy's project focused on understanding the metabolic role of a poorly understood protein called Stamp2. Found primarily in adipocytes and regulated by both nutritional and inflammatory stimuli, this protein may represent a point of intersection for metabolic and inflammatory pathways. Katy used both cell culture and mouse models to investigate the role of Stamp2 in adipocyte function and whole body energy metabolism. She has several manuscripts pending publication from her studies.
Hongying Zhong, Ph.D. (Chemistry, University of Alberta): Postdoctoral fellow associated with Proteomics Core in a joint research project led by Drs. Dieter Wolf, Alexander Ivanov, Gokhan Hotamisligil, Frank Sacks, Louise Ryan and Eric Rimm. This combined research effort focused on identifying biomarkers for metabolic disease, including diabetes and coronary heart disease, using plasma proteomics. Hongying's role in this team-directed effort was to devise standardized plasma sample preparation affording sensitivity, reproducibility and throughput. Mouse models of metabolic disease were used to develop and test this technology.