Mychaleckyj, Josyf (Joe) C.
Professor, Public Health Sciences
PO Box 800717
Statistical analysis applied to complex disease genetics; Genetics and genomics of diabetic complications and kidney disease
During the last 15 years biology has come of age as an information-based science, in some ways playing catch-up to other quantitative disciplines. Data generation has become easier, cheaper, and faster yielding exponential increases in sizes of data sets and databases. The relative explosion during recent years coincides with the rise of the internet, burgeoning and novel biomedical engineering and biophysics methods and assays, and increasing public awareness and interest in contemporary biomedical research. The sequencing of the Human Genome presaged this and validated the concept of large-scale highly collaborative biological science projects, familiar to physicists in particle discovery or astrophysics research. It is clear that biology requires similarly inter-disciplinary teams.
Our work focuses on the application of statistical, bioinformatic, and genomic methods to synthesize and make sense of the large data sets emerging from human genetic susceptibility mapping projects. Genome-wide association, massively parallel sequencing, and microarray gene expression experiments provide the raw data for our highly collaborative work and this provides many avenues for research encompassing genetic epidemiology, application of new statistical methods, and multi-dimensional data integration.
Our complex disease genetics specialty is diabetes and diabetic nephropathy. Projects have included mapping and cloning susceptibility genes for type 1, type 2, and MODY diabetes, diabetic nephropathy, and end stage kidney disease, but has also included other interesting work in diverse areas such as malnutrition, prostate cancer, stem cells, host-pathogen interactions, and mouse pheromone memory.
Some of our current projects include:
Statistical and bioinformatic analysis collaboration with the Joslin Diabetes Center to study the genetic factors that influence onset and progression of diabetic nephropathy in type 1 diabetes
Analysis center for the MESA SHARe (Multi-ethnic Study of Atherosclerosis SNP Health Association Resource) project. High throughput analysis, annotation, and distribution of results from candidate wide (CWAS) and genome wide (GWAS) analysis of 1000s of quantitative and qualitative traits related to subclinical atherosclerosis and other complex phenotypes.
Mal-ED Network for Malnutrition and Enteric Disease: Bill and Melinda Gates Foundation funded project to understand the interaction of genetic and infectious disease risk factors in malnutrition and enteric disease based on molecular genetic and genomic risk profiles.
Vitamin Intervention for Stroke Prevention (VISP): Analysis of genetic risk factors underlying ischemic and recurrent stroke, and stroke-associated biomarkers.