Comparison of Genotypic and Phenotypic Correlations: Cheverud’s Conjecture in Humans

Sodini, Sebastian M.; Kemper, Kathryn E.; Wray, Naomi R.; Trzaskowski, Maciej

doi:10.1101/291062

Cited by 10 publications

(11 citation statements)

References 34 publications

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“…Given that under the “Cheverud’s Conjecture” 20,21 genetic correlations can be used as proxies of phenotypic correlations, we can use the genetic correlations obtained from LDscore regression for the GWAS of Y*, X* and λ to fit (3) using GenomicSEM 22 .…”

Section: Proposed Correction Methods and Implementation In Genomicsemmentioning

confidence: 99%

Genetic analyses identify widespread sex-differential participation bias

Pirastu

Cordioli

Nandakumar

et al. 2020

Preprint

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48Genetic association results are often interpreted with the assumption that study participation 49 does not affect downstream analyses. Understanding the genetic basis of this participation bias 50 is challenging as it requires the genotypes of unseen individuals. However, we demonstrate that 51 it is possible to estimate comparative biases by performing GWAS contrasting one subgroup 52 versus another. For example, we show that sex exhibits autosomal heritability in the presence of 53 sex-differential participation bias. By performing a GWAS of sex in ~3.3 million males and 54 females, we identify over 150 autosomal loci significantly associated with sex and highlight 55 complex traits underpinning differences in study participation between sexes. For example, the 56 body mass index (BMI) increasing allele at the FTO locus was observed at higher frequency in 57 males compared to females (OR 1.02 [1.02-1.03], P=4.4x10 -36 ). Finally, we demonstrate how 58 these biases can potentially lead to incorrect inferences in downstream analyses and propose a 59 conceptual framework for addressing such biases. Our findings highlight a new challenge that 60 genetic studies may face as sample sizes continue to grow. 61 62 63 64 65 66Individuals who enroll in research studies or purchase direct-to-consumer genetic tests are often 67 not representative of the general population 1,2,3 . 68For example, the UK Biobank study invited ~9 million individuals and achieved an overall 69 participation rate of 5.45% 4 . These enrolled individuals clearly demonstrated a "healthy 70 volunteer bias", with lower rates of obesity, smoking and fewer self-reported health conditions 71 than the sampling frame 4 . Achieving accurate representation of the sampling population in any 72 study is challenging. Examples do exist, however, such as the iPSYCH study which enrolled a 73 random sample of the population, based on DNA extracted from a nationwide collection of 74 neonatal dried blood spots 5 . The benefits of achieving such representativeness have long been 75 discussed 6,7,8,9 , with many arguing that unrepresentative samples can bias prevalence estimates 76 but do not necessarily create substantial biases on exposure-disease associations 10,11 . 77Purposely non-representative study designs can also be valuable, for example case-control 78 studies seeking to enrich cases with non-genetic risk factors can maximize power to detect 79 genetic effects 12 . 80 81Recent studies have highlighted that genetic factors are associated with aspects of study 82 engagement 13,14,15 . For example, individuals with high genetic risk for schizophrenia enrolled in 83 a study are less likely to complete health questionnaires, attend clinical assessments and 84 continue participation in longitudinal studies than those with lower genetic risk 13,16 . It remains 85 unclear to what extent genetic factors influence initial study participation, or what the 86 downstream consequences of such bias are, though there are prior attempts to quantify the bias 87 with simul...

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Section: Proposed Correction Methods and Implementation In Genomicsemmentioning

confidence: 99%

Genetic analyses identify widespread sex-differential participation bias

Pirastu

Cordioli

Nandakumar

et al. 2020

Preprint

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“…Therefore, the recent H. sapiens pooled within-population P matrices for the occipital and frontal bones were used as proxies for H. erectus. H. sapiens was chosen because it is the closest extant phylogenetic match for H. erectus [49,52,80] and the human P matrix is a good estimate of its G matrix [81][82][83]. In total, 145 recent H. sapiens from three populations with n ∼ 50 each were used to calculate the pooled within-population covariance matrices that were used as proxies for H. erectus in testing Prediction 3 (electronic supplementary material, table S3).…”

Section: (C) Predictionmentioning

confidence: 99%

Reconstructing cranial evolution in an extinct hominin

Baab

2021

Proc. R. Soc. B.

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Homo erectus is the first hominin species with a truly cosmopolitan distribution and resembles recent humans in its broad spatial distribution. The microevolutionary events associated with dispersal and local adaptation may have produced similar population structure in both species. Understanding the evolutionary population dynamics of H. erectus has larger implications for the emergence of later Homo lineages in the Middle Pleistocene. Quantitative genetics models provide a means of interrogating aspects of long-standing H. erectus population history narratives. For the current study, cranial fossils were sorted into six major palaeodemes from sites across Africa and Asia spanning 1.8–0.1 Ma. Three-dimensional shape data from the occipital and frontal bones were used to compare intraspecific variation and test evolutionary hypotheses. Results indicate that H. erectus had higher individual and group variation than Homo sapiens , probably reflecting different levels of genetic diversity and population history in these spatially disperse species. This study also revealed distinct evolutionary histories for frontal and occipital bone shape in H. erectus , with a larger role for natural selection in the former. One scenario consistent with these findings is climate-driven facial adaptation in H. erectus , which is reflected in the frontal bone through integration with the orbits.

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“…The concept of morphological integration encompasses the pattern and the amount of correlation between different morphological traits (the socalled variables), which is detected by the analysis of correlation coe cient matrices 23 . Recently, Sodini et al supported the correlation between the morphological traits and the genetic and phenotypic features 24 . We have found that the correlation among the landmarks set within a single linear module (i.e.…”

Section: Discussionmentioning

confidence: 97%

Radial symmetry molding skull roundness: a human fetal MR study

Serrao

Corte

Triulzi

et al. 2021

Preprint

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The aim of this study consists in evaluating the morphological integration and molding shape of the human fetal craniofacial complex development on MR sagittal images. The sella point has been used as a reference point to build eleven dimensional parameters encompassing the craniofacial complex. Data and measurements obtained were statistically analyzed by PCA. The designed rays were significantly correlated, normally distributed and characterized by linearity over the overall fetal development. These findings showed that the craniofacial units are clustering together, whereas craniobasal and craniopharyngeal traits are spread. The data analysis supported the efficacy of specific morphological traits to evaluate differences emerging during the modeling growth processes. Skull modeling seems to be characterized by a rotational symmetry around the sella as inertial point. We firstly present the intriguing hypothesis through which the skull development grows along a dihedral angle symmetry made of a both rotational and reflection vector.

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Comparison of Genotypic and Phenotypic Correlations: Cheverud’s Conjecture in Humans

Cited by 10 publications

References 34 publications

Genetic analyses identify widespread sex-differential participation bias

Genetic analyses identify widespread sex-differential participation bias

Reconstructing cranial evolution in an extinct hominin

Radial symmetry molding skull roundness: a human fetal MR study

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