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Evidence of inbreeding depression on human height.

ABSTRACT: Stature is a classical and highly heritable complex trait, with 80%-90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (?(2) = 83.89, df = 1; p = 5.2 × 10(-20)). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.

SUBMITTER: McQuillan R

PROVIDER: S-EPMC3400549 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Evidence of inbreeding depression on human height.

McQuillan Ruth R Eklund Niina N Pirastu Nicola N Kuningas Maris M McEvoy Brian P BP Esko Tõnu T Corre Tanguy T Davies Gail G Kaakinen Marika M Lyytikäinen Leo-Pekka LP Kristiansson Kati K Havulinna Aki S AS Gögele Martin M Vitart Veronique V Tenesa Albert A Aulchenko Yurii Y Hayward Caroline C Johansson Asa A Boban Mladen M Ulivi Sheila S Robino Antonietta A Boraska Vesna V Igl Wilmar W Wild Sarah H SH Zgaga Lina L Amin Najaf N Theodoratou Evropi E Polašek Ozren O Girotto Giorgia G Lopez Lorna M LM Sala Cinzia C Lahti Jari J Laatikainen Tiina T Prokopenko Inga I Kals Mart M Viikari Jorma J Yang Jian J Pouta Anneli A Estrada Karol K Hofman Albert A Freimer Nelson N Martin Nicholas G NG Kähönen Mika M Milani Lili L Heliövaara Markku M Vartiainen Erkki E Räikkönen Katri K Masciullo Corrado C Starr John M JM Hicks Andrew A AA Esposito Laura L Kolčić Ivana I Farrington Susan M SM Oostra Ben B Zemunik Tatijana T Campbell Harry H Kirin Mirna M Pehlic Marina M Faletra Flavio F Porteous David D Pistis Giorgio G Widén Elisabeth E Salomaa Veikko V Koskinen Seppo S Fischer Krista K Lehtimäki Terho T Heath Andrew A McCarthy Mark I MI Rivadeneira Fernando F Montgomery Grant W GW Tiemeier Henning H Hartikainen Anna-Liisa AL Madden Pamela A F PA d'Adamo Pio P Hastie Nicholas D ND Gyllensten Ulf U Wright Alan F AF van Duijn Cornelia M CM Dunlop Malcolm M Rudan Igor I Gasparini Paolo P Pramstaller Peter P PP Deary Ian J IJ Toniolo Daniela D Eriksson Johan G JG Jula Antti A Raitakari Olli T OT Metspalu Andres A Perola Markus M Järvelin Marjo-Riitta MR Uitterlinden André A Visscher Peter M PM Wilson James F JF

PLoS genetics 20120719 7

Stature is a classical and highly heritable complex trait, with 80%-90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different pop ...[more]

PMID: 22829771

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Project description:BackgroundThe availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (FLH1 and FLH2), VanRaden (FVR1 and FVR2), Yang and colleagues (FYA1 and FYA2), marker homozygosity (FHOM), runs of homozygosity (FROH) and estimates based on pedigree (FPED) in comparison with estimates obtained from IBD measures (FIBD).ResultsIf the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with FIBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with FIBD is generally obtained by FLH1 and the best estimator of ΔID is FYA2. The estimators FVR2 and FLH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with FIBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (FHOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (FROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (FPED) show a lower correlation with FIBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.ConclusionsWhen base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with FIBD and provide good estimates of ΔID. When base population allele frequencies are unknown, FLH1 is the marker frequency-based estimator that is most correlated with FIBD, and FYA2 provides the most accurate estimates of ΔID. Estimates from FROH are also very precise in most scenarios. The estimators FVR2 and FLH2 have the poorest performances.

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Evidence of inbreeding depression on human height.

Publications

Evidence of inbreeding depression on human height.

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