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Missing heritability

Etty Kruzel-Davila, Walter G Wasser, Karl Skorecki
Common DNA sequence variants rarely have a high-risk association with a common disease. When such associations do occur, evolutionary forces must be sought, such as in the association of apolipoprotein L1 (APOL1) gene risk variants with nondiabetic kidney diseases in populations of African ancestry. The variants originated in West Africa and provided pathogenic resistance in the heterozygous state that led to high allele frequencies owing to an adaptive evolutionary selective sweep. However, the homozygous state is disadvantageous and is associated with a markedly increased risk of a spectrum of kidney diseases encompassing hypertension-attributed kidney disease, focal segmental glomerulosclerosis, human immunodeficiency virus nephropathy, sickle cell nephropathy, and progressive lupus nephritis...
November 2017: Seminars in Nephrology
Jing Huang, Yulun Liu, Steve Vitale, Trevor M Penning, Alexander S Whitehead, Ian A Blair, Anil Vachani, Margie L Clapper, Joshua E Muscat, Philip Lazarus, Paul Scheet, Jason H Moore, Yong Chen
Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis...
November 7, 2017: Genetic Epidemiology
R R Mota, P Mayeres, C Bastin, G Glorieux, C Bertozzi, S Vanderick, H Hammami, F G Colinet, N Gengler
The segregation of the causal mutation () in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing adapted genetic evaluations might overcome this situation through efficient selection. However, the heterogeneity of dpBB populations at the locus implies separating the major gene and other polygenic effects in complex modeling. The use of mixed inheritance models may be an interesting option because they simultaneously assume both influences...
October 2017: Journal of Animal Science
Sergi Sayols-Baixeras, Isaac Subirana, Alba Fernández-Sanlés, Mariano Sentí, Carla Lluís-Ganella, Jaume Marrugat, Roberto Elosua
Obesity is associated with increased risk of several diseases and has become epidemic. Obesity is highly heritable but the genetic variants identified by genome-wide association studies explain only limited variability. Epigenetics could contribute to explain the missing variability. The study aim was to discover differential methylation patterns related to obesity. We designed an epigenome-wide association study with a discovery phase in a subsample of 641 REGICOR study participants, validated by analysis of 2,515 participants in the Framingham Offspring Study...
November 3, 2017: Epigenetics: Official Journal of the DNA Methylation Society
Elena Szefer, Donghuan Lu, Farouk Nathoo, Mirza Faisal Beg, Jinko Graham
Using publicly-available data from the Alzheimer's Disease Neuroimaging Initiative, we investigate the joint association between single-nucleotide polymorphisms (SNPs) in previously established linkage regions for Alzheimer's disease (AD) and rates of decline in brain structure. In an initial, discovery stage of analysis, we applied a weighted RV test to assess the association between 75,845 SNPs in the Alzgene linkage regions and rates of change in structural MRI measurements for 56 brain regions affected by AD, in 632 subjects...
November 1, 2017: Statistical Applications in Genetics and Molecular Biology
Bruno Sauce, Louis D Matzel
Intelligence can have an extremely high heritability, but also be malleable; a paradox that has been the source of continuous controversy. Here we attempt to clarify the issue, and advance a frequently overlooked solution to the paradox: Intelligence is a trait with unusual properties that create a large reservoir of hidden gene-environment (GE) networks, allowing for the contribution of high genetic and environmental influences on individual differences in IQ. GE interplay is difficult to specify with current methods, and is underestimated in standard metrics of heritability (thus inflating estimates of "genetic" effects)...
October 30, 2017: Psychological Bulletin
Alexandra J Mayhew, David Meyre
The goal of this review article is to provide a conceptual based summary of how heritability estimates for complex traits such as obesity are determined and to explore the future directions of research in the heritability field. The target audience are researchers who use heritability data rather than those conducting heritability studies. The article provides an introduction to key concepts critical to understanding heritability studies including: i) definitions of heritability: broad sense versus narrow sense heritability; ii) how data for heritability studies are collected: twin, adoption, family and population-based studies; and iii) analytical techniques: path analysis, structural equations and mixed or regressive models of complex segregation analysis...
August 2017: Current Genomics
Yafang Li, Xiangjun Xiao, Younghun Han, Olga Gorlova, David Qian, Natasha Leighl, Jakob S Johansen, Matt Barnett, Chu Chen, Gary Goodman, Angela Cox, Fiona Taylor, Penella Woll, H-Erich Wichmann, Judith Manz, Thomas Muley, Angela Risch, Albert Rosenberger, Susanne M Arnold, Eric B Haura, Ciprian Bolca, Ivana Holcatova, Vladimir Janout, Milica Kontic, Jolanta Lissowska, Anush Mukeria, Simona Ognjanovic, Tadeusz M Orlowski, Ghislaine Scelo, Beata Swiatkowska, David Zaridze, Per Bakke, Vidar Skaug, Shanbeh Zienolddiny, Eric J Duell, Lesley M Butler, Richard Houlston, María Soler Artigas, Kjell Grankvist, Mikael Johansson, Frances A Shepherd, Michael W Marcus, Hans Brunnström, Jonas Manjer, Olle Melander, David C Muller, Kim Overvad, Antonia Trichopoulou, Rosario Tumino, Geoffrey Liu, Stig E Bojesen, Xifeng Wu, Loic Le Marchand, Demetrios Albanes, Heike Bickeböller, Melinda C Aldrich, William S Bush, Adonina Tardon, Gad Rennert, M Dawn Teare, John K Field, Lambertus A Kiemeney, Philip Lazarus, Aage Haugen, Stephen Lam, Matthew B Schabath, Angeline S Andrew, Pier Alberto Bertazzi, Angela C Pesatori, David C Christiani, Neil Caporaso, Mattias Johansson, James D McKay, Paul Brennan, Rayjean J Hung, Christopher I Amos
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between SNPs and smoking status (never vs ever smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13,336 NSCLC cases. Candidate SNPs with p-value less than 0...
October 20, 2017: Carcinogenesis
Robert L Baker, Wen Fung Leong, Nan An, Marcus T Brock, Matthew J Rubin, Stephen Welch, Cynthia Weinig
We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits...
October 20, 2017: TAG. Theoretical and Applied Genetics. Theoretische und Angewandte Genetik
Baishali Bandyopadhyay, Veda Chanda, Yupeng Wang
Thousands of genome-wide association studies (GWAS) have been conducted to identify the genetic variants associated with complex disorders. However, only a small proportion of phenotypic variances can be explained by the reported variants. Moreover, many GWAS failed to identify genetic variants associated with disorders displaying hereditary features. The "missing heritability" problem can be partly explained by rare variants. We simulated a causality scenario that gestational ages, a quantitative trait that can distinguish preterm (<37 weeks) and term births, were significantly correlated with the rare variant aggregations at 1000 single-nucleotide polymorphism loci...
2017: Bioinformatics and Biology Insights
Ilja M Nolte, Joeri A Jansweijer, Hariette Riese, Folkert W Asselbergs, Pim van der Harst, Timothy D Spector, Yigal M Pinto, Harold Snieder, Yalda Jamshidi
Twin studies have found that ~50% of variance in electrocardiogram (ECG) traits can be explained by genetic factors. However, genetic variants identified through genome-wide association studies explain less than 10% of the total trait variability. Some have argued that the equal environment assumption for the classical twin model might be invalid, resulting in inflated narrow-sense heritability (h 2) estimates, thus explaining part of the 'missing h 2'. Genomic relatedness restricted maximum likelihood (GREML) estimation overcomes this issue...
October 17, 2017: Twin Research and Human Genetics: the Official Journal of the International Society for Twin Studies
Hui-Min Liu, Jing-Yang He, Qiang Zhang, Wan-Qiang Lv, Xin Xia, Chang-Qing Sun, Wei-Dong Zhang, Hong-Wen Deng
Genome-wide association studies (GWAS) have been shown to have the potential of explaining more of the "missing heritability" of complex human phenotypes by improving statistical approaches. Here, we applied a genetic-pleiotropy-informed conditional false discovery rate (cFDR) to capture additional polygenic effects associated with estimated glomerular filtration rate (creatinine) (eGFRcrea) and type 2 diabetes (T2D). The cFDR analysis improves the identification of pleiotropic variants by incorporating potentially shared genetic mechanisms between two related traits...
October 16, 2017: Molecular Genetics and Genomics: MGG
Brian J Morris
No abstract text is available yet for this article.
October 2017: Circulation. Cardiovascular Genetics
Ellen S Ovenden, Nathaniel W McGregor, Robin A Emsley, Louise Warnich
Antipsychotic response in schizophrenia is a complex, multifactorial trait influenced by pharmacogenetic factors. With genetic studies thus far providing little biological insight or clinical utility, the field of pharmacoepigenomics has emerged to tackle the so-called "missing heritability" of drug response in disease. Research on psychiatric disorders has only recently started to assess the link between epigenetic alterations and treatment outcomes. DNA methylation, the best characterised epigenetic mechanism to date, is discussed here in the context of schizophrenia and antipsychotic treatment outcomes...
October 7, 2017: Progress in Neuro-psychopharmacology & Biological Psychiatry
Bertrand Jordan
Recently, a systematic (but limited) search for rare variants implicated in adult height, a highly polygenic trait, has uncovered a number of new variants for which the effect size is inversely correlated with the minor allele frequency. This opens interesting perspectives on the genetic architecture of complex traits and on the vexing problem of "missing heritability".
June 2017: Médecine Sciences: M/S
Chia-Wei Chen, Hsin-Chou Yang
Combining statistical significances (P-values) from a set of single-locus association tests in genome-wide association studies is a proof-of-principle method for identifying disease-associated genomic segments, functional genes and biological pathways. We review P-value combinations for genome-wide association studies and introduce an integrated analysis tool, Omnibus P-value Association Tests (OPATs), which provides popular analysis methods of P-value combinations. The software OPATs programmed in R and R graphical user interface features a user-friendly interface...
July 10, 2017: Briefings in Bioinformatics
Weiwei Ouyang, Xiaofeng Zhu, Huaizhen Qin
Genome-wide association studies have identified many common genetic variants which are associated with certain diseases. The identified common variants, however, explain only a small portion of the heritability of a complex disease phenotype. The missing heritability motivated researchers to test the hypothesis that rare variants influence common diseases. Next-generation sequencing technologies have made the studies of rare variants practicable. Quite a few statistical tests have been developed for exploiting the cumulative effect of a set of rare variants on a phenotype...
2017: Methods in Molecular Biology
Shan-Shan Dong, Yan Guo, Shi Yao, Yi-Xiao Chen, Mo-Nan He, Yu-Jie Zhang, Xiao-Feng Chen, Jia-Bin Chen, Tie-Lin Yang
Genome-wide association studies (GWASs) are an effective strategy to identify susceptibility loci for human complex diseases. However, missing heritability is still a big problem. Most GWASs single-nucleotide polymorphisms (SNPs) are located in noncoding regions, which has been considered to be the unexplored territory of the genome. Recently, data from the Encyclopedia of DNA Elements (ENCODE) and Roadmap Epigenomics projects have shown that many GWASs SNPs in the noncoding regions fall within regulatory elements...
August 16, 2017: Briefings in Bioinformatics
Mohamad Saad, Ellen M Wijsman
Genome-wide association studies have been an important approach used to localize trait loci, with primary focus on common variants. The multiple rare variant-common disease hypothesis may explain the missing heritability remaining after accounting for identified common variants. Advances of sequencing technologies with their decreasing costs, coupled with methodological advances in the context of association studies in large samples, now make the study of rare variants at a genome-wide scale feasible. The resurgence of family-based association designs because of their advantage in studying rare variants has also stimulated more methods development, mainly based on linear mixed models (LMMs)...
August 31, 2017: Briefings in Bioinformatics
Jinzhuang Dou, Baoluo Sun, Xueling Sim, Jason D Hughes, Dermot F Reilly, E Shyong Tai, Jianjun Liu, Chaolong Wang
Knowledge of biological relatedness between samples is important for many genetic studies. In large-scale human genetic association studies, the estimated kinship is used to remove cryptic relatedness, control for family structure, and estimate trait heritability. However, estimation of kinship is challenging for sparse sequencing data, such as those from off-target regions in target sequencing studies, where genotypes are largely uncertain or missing. Existing methods often assume accurate genotypes at a large number of markers across the genome...
September 2017: PLoS Genetics
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