Genome-wide autozygosity is associated with lower general cognitive ability.

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Analysis of exome sequence in 604 trios for recessive genotypes in schizophrenia.

Genetic associations involving both rare and common alleles have been reported for schizophrenia but there have been no systematic scans for rare recessive genotypes using fully phased trio data. Here, we use exome sequencing in 604 schizophrenia proband-parent trios to investigate the role of recessive (homozygous or compound heterozygous) nonsynonymous genotypes in the disorder. The burden of recessive genotypes was not significantly increased in probands at either a genome-wide level or in any individual gene after adjustment for multiple testing. At a system level, probands had an excess of nonsynonymous compound heterozygous genotypes (minor allele frequency, MAF ⩽ 1%) in voltage-gated sodium channels (VGSCs; eight in probands and none in parents, P = 1.5 × 10(-)(4)). Previous findings of multiple de novo loss-of-function mutations in this gene family, particularly SCN2A, in autism and intellectual disability provide biological and genetic plausibility for this finding. Pointing further to the involvement of VGSCs in schizophrenia, we found that these genes were enriched for nonsynonymous mutations (MAF ⩽ 0.1%) in cases genotyped using an exome array, (5585 schizophrenia cases and 8103 controls), and that in the trios data, synaptic proteins interacting with VGSCs were also enriched for both compound heterozygosity (P = 0.018) and de novo mutations (P = 0.04). However, we were unable to replicate the specific association with compound heterozygosity at VGSCs in an independent sample of Taiwanese schizophrenia trios (N = 614). We conclude that recessive genotypes do not appear to make a substantial contribution to schizophrenia at a genome-wide level. Although multiple lines of evidence, including several from this study, suggest that rare mutations in VGSCs contribute to the disorder, in the absence of replication of the original findings regarding compound heterozygosity, this conclusion requires evaluation in a larger sample of trios.

Using linkage information to weight a genome-wide association of bipolar disorder.

Issues of multiple-testing and statistical significance in genomewide association studies (GWAS) have prompted statistical methods utilizing prior data to increase the power of association results. Using prior findings from genome-wide linkage studies on bipolar disorder (BPD), we employed a weighted false discovery approach (wFDR; [Roeder et al. 2006. Am J Hum Genet 78(2): 243­252]) to previously reported GWAS data drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Using this method, association signals are up or down-weighted given the linkage score in that genomic region. Although no SNPs in our sample reached genome-wide significance through the wFDR approach, the strongest single SNP result from the original GWAS results (rs4939921 in myosin VB) is strongly up-weighted as it occurs on a linkage peak of chromosome 18. We also identify regions on chromosome 9, 17, and 18 where modestly associated SNP clusters coincide with strong linkage scores, implicating them as possible candidate regions for further analysis. Moving forward, we believe the application of prior linkage information will be increasingly useful to future GWAS studies that incorporate rarer variants into their analysis.