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Gerome Breen

Publications and source records attributed to Gerome Breen.

3 recordsLinked to original sources

Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection

Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide such insight. We report the largest single cohort genome-wide association study of schizophrenia (11,260 cases and 24,542 controls) and through meta-analysis with existing data we identify 50 novel GWAS loci. Using gene-wide association statistics we implicate an additional set of 22 novel associations that map onto a single gene. We show for the first time that the common variant association signal is highly enriched among genes that are intolerant to loss of function mutations and that variants in these genes persist in the population despite the low fecundity associated with the disorder through the process of background selection. Associations point to novel areas of biology (e.g. metabotropic GABA-B signalling and acetyl cholinesterase), reinforce those implicated in earlier GWAS studies (e.g. calcium channel function), converge with earlier rare variants studies (e.g. NRXN1, GABAergic signalling), identify novel overlaps with autism (e.g. RBFOX1, FOXP1, FOXG1), and support early controversial candidate gene hypotheses (e.g. ERBB4 implicating neuregulin signalling). We also demonstrate the involvement of six independent central nervous system functional gene sets in schizophrenia pathophysiology. These findings provide novel insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation intolerant genes and suggest a mechanism by which common risk variants are maintained in the population.

Genomics

Rare loss-of-function variants in KMT2F are associated with schizophrenia and developmental disorders

Schizophrenia is a common, debilitating psychiatric disorder with a substantial genetic component. By analysing the whole-exome sequences of 4,264 schizophrenia cases, 9,343 controls, and 1,077 parent-proband trios, we identified a genome-wide significant association between rare loss-of-function (LoF) variants in KMT2F and risk for schizophrenia. In this dataset, we observed three de novo LoF mutations, seven LoF variants in cases, and none in controls (P = 3.3x10-9). To search for LoF variants in KMT2F in individuals without a known neuropsychiatric diagnosis, we examined the exomes of 45,376 individuals in the ExAC database and found only two heterozygous LoF variants, showing that KMT2F is significantly depleted of LoF variants in the general population. Seven of the ten individuals with schizophrenia carrying KMT2F LoF variants also had varying degrees of learning difficulties. We further identified four KMT2F LoF carriers among 4,281 children with diverse, severe, undiagnosed developmental disorders, and two additional carriers in an independent sample of 5,720 Finnish exomes, both with notable neuropsychiatric phenotypes. Together, our observations show that LoF variants in KMT2F cause a range of neurodevelopmental disorders, including schizophrenia. Combined with previous common variant evidence, we more generally implicate epigenetic dysregulation, specifically in the histone H3K4 methylation pathway, as an important mechanism in the pathogenesis of schizophrenia.

Genomics

FORGE: multivariate calculation of gene-wide p-values from Genome-Wide Association Studies Authors and Affiliations

Genome-wide association studies (GWAS) have proven a valuable tool to explore the genetic basis of many traits. However, many GWAS lack statistical power and the commonly used single-point analysis method needs to be complemented to enhance power and interpretation. Multivariate region or gene-wide association are an alternative, allowing for identification of disease genes in a manner more robust to allelic heterogeneity. Gene-based association also facilitates systems biology analyses by generating a single p-value per gene. We have designed and implemented FORGE, a software suite which implements a range of methods for the combination of p-values for the individual genetic variants within a gene or genomic region. The software can be used with summary statistics (marker ids and p-values) and accepts as input the result file formats of commonly used genetic association software. When applied to a study of Crohns disease susceptibility, it identified all genes found by single SNP analysis and additional genes identified by large independent metaanalysis. FORGE p-values on gene-set analyses highlighted association with the Jak-STAT and cytokine signalling pathways, both previously associated with CD. We highlight the softwares main features, its future development directions and provide a comparison with alternative available software tools. FORGE can be freely accessed at https://github.com/inti/FORGE.

Genetics