comparative linkage meta-analysis reveals regionally-distinct, disparate genetic architectures application to bipolar disorder and schizophrenia比较连锁分析揭示了regionally-distinct,不同的遗传体系结构应用于双相情感障碍和精神分裂症.pdfVIP

Comparative Linkage Meta-Analysis Reveals Regionally- Distinct, Disparate Genetic Architectures: Application to Bipolar Disorder and Schizophrenia 1 2 3 Brady Tang , Tricia Thornton-Wells , Kathleen D. Askland * 1 Biostatistics Graduate Program, Brown University, Providence, Rhode Island, United States of America, 2 Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America, 3 Department of Psychiatry and Human Behavior, Butler Hospital, The Warren Alpert School of Medicine of Brown University, Providence, Rhode Island, United States of America Abstract New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ’’missing heritability.’’ However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP- based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (,1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves a