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...

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Published in:Twin Research & Human Genetics Vol. 24; no. 2; pp. 103 - 110
Main Authors: 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.
Format: research Journal Article
Published: Cambridge University Press Apr2021
Online Access:View this record in EBSCOhost
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      jtl: Twin Research & Human Genetics
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      dt: Apr2021
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      pub: Cambridge University Press
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        10.1017/thg.2021.18
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        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
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