Statistical examination of shared loci in neuropsychiatric diseases using genome-wide association study summary statistics

Author:

Spargo Thomas P123ORCID,Gilchrist Lachlan145,Hunt Guy P256,Dobson Richard JB2378,Proitsi Petroula1ORCID,Al-Chalabi Ammar19ORCID,Pain Oliver1ORCID,Iacoangeli Alfredo123

Affiliation:

1. Maurice Wohl Clinical Neuroscience Institute, King’s College London, Department of Basic and Clinical Neuroscience

2. Department of Biostatistics and Health Informatics, King’s College London

3. NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and King’s College London

4. Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London

5. Perron Institute for Neurological and Translational Science

6. Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University

7. Institute of Health Informatics, University College London

8. NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust

9. King’s College Hospital

Abstract

Continued methodological advances have enabled numerous statistical approaches for the analysis of summary statistics from genome-wide association studies. Genetic correlation analysis within specific regions enables a new strategy for identifying pleiotropy. Genomic regions with significant ‘local’ genetic correlations can be investigated further using state-of-the-art methodologies for statistical fine-mapping and variant colocalisation. We explored the utility of a genome-wide local genetic correlation analysis approach for identifying genetic overlaps between the candidate neuropsychiatric disorders, Alzheimer’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, and schizophrenia. The correlation analysis identified several associations between traits, the majority of which were loci in the human leukocyte antigen (HLA) region. Colocalisation analysis suggested that disease-implicated variants in these loci often differ between traits and, in one locus, indicated a shared causal variant between amyotrophic lateral sclerosis and Alzheimer’s disease. Our study identified candidate loci that might play a role in multiple neuropsychiatric diseases and suggested the role of distinct mechanisms across diseases despite shared loci. The fine-mapping and colocalisation analysis protocol designed for this study has been implemented in a flexible analysis pipeline that produces HTML reports and is available at: https://github.com/ThomasPSpargo/COLOC-reporter.

Publisher

eLife Sciences Publications, Ltd

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