The ultimate goal of biomedical research is to identify the underlying causes of human disease. Traditional approaches for identify disease-associated genes either track multiple DNA markers through large disease-affected family pedigrees, or perform large-scale genome-wide searches for loci that are differentiated between cases and controls. Despite the success of these approaches for simple disorders, identification of genetic risk factors in complex non-Mendelian diseases such as bipolar disorder remains challenging. We examined old genetics studies of human diseases and serendipitously noticed that genetic recombination appears to occur at different rates between cases and controls in the regions containing disease genes; this effect was seen in simple genetic diseases such as Huntington's disease and myotonic dystrophy, as well as in several complex diseases such as major psychosis, breast cancer, and diabetes. If real, such an effect would point to unknown biology associated with disease. Following this observation, we have developed a strategy for the systematic investigation of this phenomenon. Our hypothesis is that recombination shows localized difference at disease-associated loci in affected individuals compared to controls. As such, the main goal of this project is to map large numbers of the recombination events occurring in males affected with bipolar disorder via high throughput single cell sequencing of sperm, and compare this to the maps from unaffected subjects. The project may uncover indicators of diseases that have previously been overlooked, and therefore provide new insight into disease biology.
Although there is general agreement that bipolar disorder is a heritable disease, identification of genetic risk factors has been slow, despite significant research efforts. In this project, we suggest an innovative strategy for detection of subtle molecular changes in the genome, which may increase the risk of developing bipolar disorder. For this, we will investigate how chromosomes interact during the formation of germ cells and identify regions that appear to behave abnormally. Identification of such regions could provide new insight into the origins of psychiatric disease.
