Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure.
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...
| Published in: | Twin Research & Human Genetics Vol. 24; no. 2; pp. 103 - 110 |
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| Main Authors: | , , , , , , , , , , |
| Format: | research Journal Article |
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Cambridge University Press
Apr2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151214656&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151214656 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18324274 DZR jtl: Twin Research & Human Genetics issn: 18324274 maglogo: N pubinfo: dt: Apr2021 vid: 24 iid: 2 pid: 15979 pub: Cambridge University Press artinfo: ui: 151214656 151214656 NLM34213412 151214656 10.1017/thg.2021.18 NLM34213412 151214656 ppf: 103 ppct: 7 formats: tig: atl: Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure. aug: au: de Zeeuw, Eveline L. Voort, Lykle Schoonhoven, Ruurd Nivard, Michel G. Emery, Thomas Hottenga, Jouke-Jan Willemsen, Gonneke A. H. M. Dykstra, Pearl A. Zarrabi, Narges Kartopawiro, John D. Boomsma, Dorret I. affil: Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands sug: subj: Health Care Costs Sequence Analysis Prospective Studies Genotype Polymorphism, Genetic Human Comparative Studies Multicenter Studies Evaluation Research Validation Studies Social Readjustment Rating Scale ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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