Genetic nurturing, missing heritability, and causal analysis in genetic statistics.
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ABSTRACT:
SUBMITTER: Shen H
PROVIDER: S-EPMC7568332 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Human genetics has been haunted by the mystery of "missing heritability" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator--that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating "phantom heritability." Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.
| S-EPMC3268279 | biostudies-other
Project description:Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
| S-EPMC9985486 | biostudies-literature
Project description:The purpose of this study was to detect the missing heritability of patients with KIF11-related retinopathy and to describe their clinical and genetic characteristics. We enrolled 10 individuals from 7 unrelated families harboring a pathogenic monoallelic variant in KIF11. All subjects underwent ophthalmic assessment and extraocular phenotype evaluations, as well as comprehensive molecular genetic analyses using next-generation sequencing. Minigene assays were performed to observe the effects of one novel deep intron variant (DIV) and one novel synonymous variant on pre-mRNA splicing. We detected 6 novel different disease-causing variants of KIF11 in the seven pedigrees. Co-segregation analysis and ultra-deep sequencing results indicated that 5 variants arose de novo in 5 families (71%). Functional validation revealed that the synonymous variant leads to an exon skip, while the DIV causes a pseudoexon (PE) inclusion. The patients presented with high variations in their phenotype, and two families exhibited incomplete penetrance. Ocular manifestations and characteristic facial features were observed in all patients, as well as microcephaly in seven patients, intellectual disability in five patients, and lymphedema in one patient. The key retinal features for KIF11-related retinopathy were retinal folds, tractional retinal detachment, and chorioretinal dysplasia. All seven probands had more severe visual detects than other affected family members. Our findings widen the genetic spectrum of KIF11 variants. DIV explained rare unresolved cases with KIF11-related retinopathy. The patients displayed a variable phenotype expressivity and incomplete penetrance, indicating the importance of genetic analysis for patients with KIF11-related retinopathy.
| S-EPMC9858922 | biostudies-literature
Project description:The etiologies underlying variation in adult cognitive performance and cognitive aging have enjoyed much attention in the literature, but much of that attention has focused on broad factors, principally general cognitive ability. The current review provides meta-analyses of age trends in heritability of specific cognitive abilities and considers the profile of genetic and environmental factors contributing to cognitive aging to address the 'missing heritability' issue. Our findings, based upon evaluating 27 reports in the literature, indicate that verbal ability demonstrated declining heritability, after about age 60, as did spatial ability and perceptual speed more modestly. Trends for general memory, working memory, and spatial ability generally indicated stability, or small increases in heritability in mid-life. Equivocal results were found for executive function. A second meta-analysis then considered the gap between twin-based versus SNP-based heritability derived from population-based GWAS studies. Specifically, we considered twin correlation ratios to agnostically re-evaluate biometrical models across age and by cognitive domain. Results modestly suggest that nonadditive genetic variance may become increasingly important with age, especially for verbal ability. If so, this would support arguments that lower SNP-based heritability estimates result in part from uncaptured non-additive influences (e.g., dominance, gene-gene interactions), and possibly gene-environment (GE) correlations. Moreover, consistent with longitudinal twin studies of aging, as rearing environment becomes a distal factor, increasing genetic variance may result in part from nonadditive genetic influences or possible GE correlations. Sensitivity to life course dynamics is crucial to understanding etiological contributions to adult cognitive performance and cognitive aging.
| S-EPMC5289922 | biostudies-literature
Project description:While novel statistical methods quantifying the shared heritability of traits and diseases between ancestral distinct populations have been recently proposed, a thorough evaluation of these approaches under differing circumstances remain elusive. Brown et al.2016 proposed the method Popcorn to estimate the shared heritability, i.e. genetic correlation, using only summary statistics. Here, we evaluate Popcorn under several parameters and circumstances: sample size, number of SNPs, sample size of external reference panel, various population pairs, inappropriate external reference panel, and admixed population involved. Our results determined the minimum sample size of the external reference panel, summary statistics, and number of SNPs required to accurately estimate both the genetic correlation and heritability. Moreover, the number of individuals and SNPs required to produce accurate and stable estimates was directly proportional with heritability in Popcorn. Misrepresentation of the reference panel overestimated the genetic correlation by 20% and heritability by 60%. Lastly, applying Popcorn to homogeneous (EUR) and admixed (ASW) populations underestimated the genetic correlation by 15%. Although statistical approaches estimating the shared heritability between ancestral populations will provide novel etiologic insight, caution is required ensuring results are based on the appropriate sample size, number of SNPs, and the generalizability of the reference panel to the discovery populations.
| S-EPMC8550643 | biostudies-literature
Project description:PurposeTo identify the missing heritability of patients with Wolfram syndrome 1 (WFS1) in a Chinese cohort and to report their clinical and genetic features.MethodsWe recruited 24 unrelated patients with suspected WFS1 who carried at least one variant in WFS1. All patients underwent ophthalmic examinations and comprehensive molecular genetic analyses, including Sanger-DNA sequencing of WFS1 and next-generation sequencing of the whole WFS1 sequence.ResultsWe identified 38 distinct pathogenic variants of WFS1 in the 24 probands, comprising 23 patients with biallelic variants and one patient with a monoallelic variant. Sanger-DNA sequencing of WFS1 initially detected 35 variants, and subsequent whole genome sequencing revealed three missing variants: one novel deep intronic variant (DIV), one copy number variant (CNV), and one variant in the promoter region. Minigene assays showed that the DIV activated cryptic splice sites, leading to the insertion of pseudoexons. Optic atrophy was observed in all patients, and diabetes mellitus (DM) was revealed in 21 patients (91.3%), hearing loss in nine patients (39.1%), renal tract abnormalities in nine patients (39.1%), and diabetes insipidus in five patients (21.7%). The mean onset age for DM was significantly younger in the patients with biallelic null variants than in the patients with biallelic missense variants.ConclusionsOur results extend the pathogenic variant spectrum of WFS1. DIVs and CNVs explained rare unresolved Chinese cases with WFS1. The patients showed a wide and variable clinical spectrum, supporting the importance of genetic analysis for patients with atypical WFS1.
| S-EPMC9482318 | biostudies-literature
Project description:We propose a novel approach to analyze genomic data that incorporates haplotype information for detecting rare variants within a regional heritability mapping framework. The performance of our approach was tested in a simulation study based on human genotypes. The phenotypes were simulated by generating regional variance using either SNP(s) or haplotype(s). Regional genomic relationship matrices, constructed with either a SNP-based or a haplotype-based estimator, were employed to estimate the regional variance. The results from the study show that haplotype heritability mapping captures the regional effect, with its relative performance decreasing with increasing analysis window size. The SNP-based regional mapping approach often misses the effect of causal haplotype(s); however, it has a greater power to detect simulated SNP-based-variants. Heritability estimates suggest that the haplotype heritability mapping estimates the simulated regional heritability accurately for all phenotypes and analysis windows. However, the SNP-based analysis overestimates the regional heritability and performs less well than our haplotype-based approach for the simulated rare haplotype-based-variant. We conclude that haplotype heritability mapping is a useful tool to capture the effect of rare variants, and explain a proportion of the missing heritability.
| S-EPMC5862984 | biostudies-literature
Project description:Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.
| S-EPMC7242266 | biostudies-literature
Project description:Next-generation sequencing has led to many complex-trait rare-variant (RV) association studies. Although single-variant association analysis can be performed, it is grossly underpowered. Therefore, researchers have developed many RV association tests that aggregate multiple variant sites across a genetic region (e.g., gene), and test for the association between the trait and the aggregated genotype. After these aggregate tests detect an association, it is only possible to estimate the average genetic effect for a group of RVs. As a result of the "winner's curse," such an estimate can be biased. Although for common variants one can obtain unbiased estimates of genetic parameters by analyzing a replication sample, for RVs it is desirable to obtain unbiased genetic estimates for the study where the association is identified. This is because there can be substantial heterogeneity of RV sites and frequencies even among closely related populations. In order to obtain an unbiased estimate for aggregated RV analysis, we developed bootstrap-sample-split algorithms to reduce the bias of the winner's curse. The unbiased estimates are greatly important for understanding the population-specific contribution of RVs to the heritability of complex traits. We also demonstrate both theoretically and via simulations that for aggregate RV analysis the genetic variance for a gene or region will always be underestimated, sometimes substantially, because of the presence of noncausal variants or because of the presence of causal variants with effects of different magnitudes or directions. Therefore, even if RVs play a major role in the complex-trait etiologies, a portion of the heritability will remain missing, and the contribution of RVs to the complex-trait etiologies will be underestimated.
| S-EPMC3484659 | biostudies-literature
Project description:For human complex traits, non-additive genetic variation has been invoked to explain "missing heritability," but its discovery is often neglected in genome-wide association studies. Here we propose a method of using SNP data to partition and estimate the proportion of phenotypic variance attributed to additive and dominance genetic variation at all SNPs (hSNP(2) and δSNP(2)) in unrelated individuals based on an orthogonal model where the estimate of hSNP(2) is independent of that of δSNP(2). With this method, we analyzed 79 quantitative traits in 6,715 unrelated European Americans. The estimate of δSNP(2) averaged across all the 79 quantitative traits was 0.03, approximately a fifth of that for additive variation (average hSNP(2) = 0.15). There were a few traits that showed substantial estimates of δSNP(2), none of which were replicated in a larger sample of 11,965 individuals. We further performed genome-wide association analyses of the 79 quantitative traits and detected SNPs with genome-wide significant dominance effects only at the ABO locus for factor VIII and von Willebrand factor. All these results suggest that dominance variation at common SNPs explains only a small fraction of phenotypic variation for human complex traits and contributes little to the missing narrow-sense heritability problem.
| S-EPMC4375616 | biostudies-literature