Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms

Abstract

Because of the high costs associated with ascertainment of families most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. While microsatellite markers spaced every 10 centimorgans typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carry out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 SNPs. Of the ~1100 families, 972 were informative for further analyses and mean information content was 0.86 after pruning for LD. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with Bipolar II disorder (BPII) and 702 subjects with Recurrent Major Depression. Three affection status models were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus Recurrent Major Depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (Nonparametric Pairs Lod 3.4 for rs1046943 at 119 cM) and 9q21 (Nonparametric Pairs Lod 3.4 for rs722642 at 78 cM) using only BPI and SA, BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis we observed 59 parametric lods of 2 or greater, many of which are likely to be close to maximum possible scores. While some linkage findings may be false positives the results could help prioritize the search for rare variants using whole exome or genome sequencing.