Safe linkage of cohort and population-based register data in a genomewide association study on health care expenditure

Eveline L. De Zeeuw, Lykle Voort, Ruurd Schoonhoven, Michel G. Nivard, Thomas Emery, Jouke Jan Hottenga, Gonneke A.H.M. Willemsen, Pearl A. Dykstra, Narges Zarrabi, John D. Kartopawiro, Dorret I. Boomsma*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.

Original languageEnglish
Pages (from-to)103-109
Number of pages7
JournalTwin Research and Human Genetics
Volume24
Issue number2
DOIs
Publication statusPublished - Apr 2021

Bibliographical note

Financial support
We gratefully acknowledge the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI; NWO: NRGWI.obrug.2018.008); ‘Netherlands Twin Register Repository: Researching the interplay between genome and environment’ (NWO: 480-15-001/674); KNAW Academy Professor Award (PAH/6635) and ‘Genetics as a research tool: A natural experiment to elucidate the causal effects of social mobility on health’ (ZonMw: 531003014).

Publisher Copyright:
© 2021 Twin Research and Human Genetics. All rights reserved.

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