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Biology subjects

Joseph K Pickrell

Publications and source records attributed to Joseph K Pickrell.

2 recordsLinked to original sources

Cell-type specific open chromatin profiling in human postmortem brain infers functional roles for non-coding schizophrenia loci

To better understand the role of cis regulatory elements in neuropsychiatric disorders we applied ATAC-seq to neuronal and non-neuronal nuclei isolated from frozen postmortem human brain. Most of the identified open chromatin regions (OCRs) are differentially accessible between neurons and non-neurons, and show enrichment with known cell type markers, promoters and enhancers. Relative to those of non-neurons, neuronal OCRs are more evolutionarily conserved and are enriched in distal regulatory elements. Our data reveals sex differences in chromatin accessibility and identifies novel OCRs that escape X chromosome inactivation, with implications for intellectual disability. Transcription factor footprinting analysis identifies differences in the regulome between neuronal and non-neuronal cells and ascribes putative functional roles to 16 non-coding schizophrenia risk variants. These results represent the first analysis of cell-type-specific OCRs and TF binding sites in postmortem human brain and further our understanding of the regulome and the impact of neuropsychiatric disease-associated genetic risk variants.

Genomics

Case-control association mapping without cases

The case-control association study is a powerful method for identifying genetic variants that influence disease risk. However, the collection of cases can be time-consuming and expensive; if a disease occurs late in life or is rapidly lethal, it may be more practical to identify family members of cases. Here, we show that replacing cases with their first-degree relatives enables genome-wide association studies by proxy (GWAX). In randomly-ascertained cohorts, this approach enables previously infeasible studies of diseases that are absent (or nearly absent) in the cohort. As an illustration, we performed GWAX of 12 common diseases in 116,196 individuals from the UK Biobank. By combining these results with published GWAS summary statistics in a meta-analysis, we replicated established risk loci and identified 17 newly associated risk loci: four in Alzheimers disease, eight in coronary artery disease, and five in type 2 diabetes. In addition to informing disease biology, our results demonstrate the utility of association mapping using family history of disease as a phenotype to be mapped. We anticipate that this approach will prove useful in future genetic studies of complex traits in large population cohorts.

Genetics