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Background: Bipolar disorder (BPD) is a common and severe mental disorder. The involvement of genetic factors in the pathophysiology of BPD is well known. In the present study, we tested the association of several single-nucleotide polymorphisms (SNPs) within 3 strong candidate genes (CACNA1C, CHRNA7, and MAPK1) with BPD. These genes are involved in monoamine-related pathways, as well as in dendrite development, neuronal survival, synaptic plasticity, and memory/learning. Methods: One hundred and thirtytwo subjects diagnosed with BPD and 326 healthy controls of Korean ancestry were genotyped for 40 SNPs within CACNA1C, CHRNA17, and MAPK1. Distribution of alleles and block of haplotypes within each gene were compared in cases and controls. Interactions between variants in different loci were also tested. Results: Significant differences in the distribution of alleles between the cases and controls were detected for rs1016388 within CACNA1C, rs1514250, rs2337980, rs6494223, rs3826029 and rs4779565 within CHRNA7, and rs8136867 within MAPK1. Haplotype analyses also confirmed an involvement of variations within these genes in BPD. Finally, exploratory epistatic analyses demonstrated potential interactive effects, especially regarding variations in CACNA1C and CHRNA7. Limitations: Limited sample size and risk of false-positive findings. Discussion: Our data suggest a possible role of these 3 genes in BPD. Alterations of 1 or more common brain pathways (e.g., neurodevelopment and neuroplasticity, calcium signaling) may explain the obtained results. [ABSTRACT FROM AUTHOR]

Background: Translational research is needed to explore how people will respond to personal genetic susceptibility information related to common health conditions. Maximizing the rigor of this research will require that genetic test results be returned to study participants. Currently, there is no established method that guides the selection of genetic variants to be used in research with these objectives. Methods and Results: To address this question, we designed a process to identify gene variants and health conditions to be included in a prototype genetic test for use in a larger research effort, the Multiplex Initiative. The intention of this exploration was to facilitate research that generates individual genetic test results that are returned to study participants. Inclusion criteria were developed as part of a transdisciplinary and iterative process that considered the weight of evidential support for genetic association with common health conditions, the appropriateness of use in human subjects research, and the recommendations of expert peer reviewers. Conclusions: The selection process was designed to identify gene variants for the limited purpose of translational research and, therefore, should not be seen as producing a valid clinical test. However, this example of an applied selection process may provide guidance for researchers who are designing studies to evaluate the implications of genetic susceptibility testing through the return of personalized genetic information. As the rate of genomic discoveries increases, such research will be essential in steering the translation of this information towards the greatest public health benefit. Copyright © 2009 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Background: Nearly 21 million people in the United States, or 7% of the population, are estimated to have diabetes. The incidence and prevalence of diabetes differ by ethnicity; however, both type 1 diabetes (T1D) and type 2 diabetes (T2D) occur in all groups. The etiology of diabetes is multifactorial, involving both genetic and environmental factors. Advances in technology, leading to the identification of over a dozen candidate genes, have accelerated the search for genetic factors contributing to the risk of diabetes. To date, surprisingly little data exist to suggest there are common genetic pathways leading to development of T1D and T2D. These common forms of diabetes have complex genetic (and environmental) risk factors, making prediction and prevention difficult. Nonetheless, detection of diabetes susceptibility genes may facilitate identification of novel pathways that can serve as therapeutic targets and lead to disease prevention. Copyright © 2009 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]