Evidence map›Paper›PMID 33407157›Full record

ArticleBMC medical research methodology2021

Improved selection of participants in genetic longevity studies: family scores revisited.

Mar Rodríguez-Girondo, Niels van den Berg, Michel H Hof, Marian Beekman, Eline Slagboom

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Article in BMC medical research methodology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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3 · Its place in the literature

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4 citing papers in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Mar Rodríguez-GirondoDepartment of Biomedical Data Sciences, section of Medical Statistics, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands. m.rodriguez_girondo@lumc.nl.ORCID 0000-0003-0414-870X
Niels van den BergDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands.
Michel H HofDepartment of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands.
Marian BeekmanDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands.
Eline SlagboomDepartment of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands.

Funding

Ministerio de Economía, Industria y Competitividad, Gobierno de España MTM2017-89422-P
6 · The paper itself

Abstract

backgroundAlthough human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data.

methodsWe discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN).

resultsEmpirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score .

conclusionsModel-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.

Indexed as

Family CharacteristicsLongevityBiasComputer SimulationHumansNetherlandsFamily history scoreFamily sizeLongevityMixed effects modelling

Identifiers

PMID33407157
PMCPMC7789146

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