Dementias Platform UK: Bringing genetics into life

Leonenko, Ganna ORCID: https://orcid.org/0000-0001-8025-661X, Bauermeister, Sarah, Ghanti, Dipanwita, Stevenson-Hoare, Joshua, Simmonds, Emily, Brookes, Keeley, Morgan, Kevin, Chaturvedi, Nishi, Elliot, Paul, Sudlow, Cathie, Thomas, Alan, Wareham, Nicholas, Gallacher, John and Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483 2024. Dementias Platform UK: Bringing genetics into life. Alzheimer's & Dementia: The Journal of the Alzheimer's Association 20 (5) , pp. 3281-3289. 10.1002/alz.13782

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview

Abstract

Background: DPUK is a data repository bringing together a wide range of population and clinical cohorts from the UK, Europe and South Korea. It enables data discovery, variable selection, and data access for multi-modal, multi-cohort analysis in a shared and secure environment. Neurodegenerative dementias are group of diseases with highly heterogeneous pathology and with an overlapping genetic component that is poorly understood. Combing genetic data from different studies is important due to the increase in power this provides, but this presents an additional challenge due to differences in genotyping arrays and lack of overlapping variants. Method: We have curated and harmonized genome-wide data from 6 studies (Brains for Dementia Research, EPIC Norfolk, Generation Scotland, Airwave-chip 1, Airwave-chip 2, MRC National Survey of Health Development (NSHD)) within the DPUK platform. We created a pipeline that performs rigorous quality-control (QC) analysis and imputes genetic variance with the 1000 Genome reference panel using the minimac algorithm. Further, standard pruning and thresholding Polygenic Risk Score (PRS) have been generated with 5 summary statistics related to neurodegenerative diseases (clinical AD, clinical/proxy AD, FTD, ALS, PD) for all 6 studies separately and for the combined dataset. Result: Research-ready imputed genetic data that have undergone QC and the PRS, based upon the latest neurodegenerative GWAS, are available for the 6 cohorts separately, and for the combined dataset of 60,670 individuals. Conclusion: Preparing multiple datasets to a common standard for research-readiness increases scientific opportunity and allows the wider research community to access and process data at scale and pace.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Publisher:	Wiley Open Access
ISSN:	1552-5260
Date of First Compliant Deposit:	30 January 2024
Date of Acceptance:	29 January 2024
Last Modified:	10 Jun 2024 11:11
URI:	https://orca.cardiff.ac.uk/id/eprint/165917

Actions (repository staff only)

Edit Item