scholarly journals Self-Reported Symptoms of COVID-19, Including Symptoms Most Predictive of SARS-CoV-2 Infection, Are Heritable

2020 ◽  
Vol 23 (6) ◽  
pp. 316-321
Author(s):  
Frances M. K. Williams ◽  
Maxim B. Freidin ◽  
Massimo Mangino ◽  
Simon Couvreur ◽  
Alessia Visconti ◽  
...  
Keyword(s):  
Social Deprivation ◽  
Association Studies ◽  
Clinical Manifestations ◽  
Twin Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Host Genotype ◽  
Susceptibility To Infection ◽  
Genome Wide ◽  
True Infection

AbstractSusceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

4. What are the contributions of environments and genes to intelligence differences?

2020 ◽  
pp. 50-69
Author(s):  
Ian J. Deary
Keyword(s):  
Association Studies ◽  
Twin Studies ◽  
Identical Twins ◽  
New Method ◽  
Genome Wide Association ◽  
Shared Environment ◽  
Genome Wide Association Studies ◽  
Genetic Inheritance ◽  
Genome Wide ◽  
Shared Environments

‘What are the contributions of environments and genes to intelligence differences?’ asks whether genetic inheritance and the environments people experience affect intelligence differences. Researchers use two main resources to answer this question: twins and samples of DNA. Studies of identical and non-identical twins are used to show the contributions of genes, shared environment, and non-shared environment to people’s differences in traits. Twin studies tell us that by adulthood, about two-thirds of intelligence differences are caused by how people vary in their genetic inheritance, and that both shared and non-shared environments make significant contributions to intelligence differences. The introduction of genome-wide association studies in 2011 has provided a new method of estimating the heritability of intelligence.

scholarly journals Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

2020 ◽  
Author(s):  
Siwen Deng ◽  
Daniel Caddell ◽  
Jinliang Yang ◽  
Lindsay Dahlen ◽  
Lorenzo Washington ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Population Level ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Host Genotype ◽  
Rhizosphere Microbiome ◽  
Genome Wide ◽  
Sorghum Genotypes

AbstractHost genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to host genotype, and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.

scholarly journals Genome wide association study reveals plant loci controlling heritability of the rhizosphere microbiome

2021 ◽  
Author(s):  
Siwen Deng ◽  
Daniel F. Caddell ◽  
Gen Xu ◽  
Lindsay Dahlen ◽  
Lorenzo Washington ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Population Level ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Host Genotype ◽  
Rhizosphere Microbiome ◽  
Genome Wide ◽  
Sorghum Genotypes

AbstractHost genetics has recently been shown to be a driver of plant microbiome composition. However, identifying the underlying genetic loci controlling microbial selection remains challenging. Genome-wide association studies (GWAS) represent a potentially powerful, unbiased method to identify microbes sensitive to the host genotype and to connect them with the genetic loci that influence their colonization. Here, we conducted a population-level microbiome analysis of the rhizospheres of 200 sorghum genotypes. Using 16S rRNA amplicon sequencing, we identify rhizosphere-associated bacteria exhibiting heritable associations with plant genotype, and identify significant overlap between these lineages and heritable taxa recently identified in maize. Furthermore, we demonstrate that GWAS can identify host loci that correlate with the abundance of specific subsets of the rhizosphere microbiome. Finally, we demonstrate that these results can be used to predict rhizosphere microbiome structure for an independent panel of sorghum genotypes based solely on knowledge of host genotypic information.

scholarly journals Twin studies, genome-wide association studies and myopia genetics

2018 ◽  
Vol 2 ◽  
pp. 69-69 ◽  
Author(s):  
Katie M. Williams ◽  
Pirro Hysi ◽  
Christopher J. Hammond
Keyword(s):  
Association Studies ◽  
Twin Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations

2016 ◽  
Author(s):  
E. L. Duncan ◽  
L. M. Thornton ◽  
A. Hinney ◽  
M. J. Daly ◽  
P. F. Sullivan ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genetic Correlations ◽  
Twin Studies ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
High Morbidity ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractAnorexia nervosa (AN) is a serious eating disorder characterized by restriction of energy intake relative to requirements, resulting in abnormally low body weight. It has a lifetime prevalence of approximately 1%, disproportionately affects females1,2, and has no well replicated evidence of effective pharmacological or psychological treatments despite high morbidity and mortality2. Twin studies support a genetic basis for the observed aggregation of AN in families3, with heritability estimates of 48%-74%4. Although initial genome-wide association studies (GWASs) were underpowered5,6, evidence suggested that signals for AN would be detected with increased power5. We present a GWAS of 3,495 AN cases and 10,982 controls with one genome-wide significant locus (index variant rs4622308, p=4.3x10−9) in a region (chr12:56,372,585-56,482,185) which includes six genes. The SNP-chip heritability of AN from these data is 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability stems from common genetic variation. Using these GWAS results, we also find significant positive genetic correlations with schizophrenia, neuroticism, educational attainment, and HDL cholesterol, and significant negative genetic correlations with body mass, insulin, glucose, and lipid phenotypes. Our results support the reconceptualization of AN as a disorder with both psychiatric and metabolic components.

scholarly journals Germline burden of rare damaging variants negatively affects human healthspan and lifespan

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Anastasia V Shindyapina ◽  
Aleksandr A Zenin ◽  
Andrei E Tarkhov ◽  
Didac Santesmasses ◽  
Peter O Fedichev ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Aging Process ◽  
Rare Variants ◽  
Association Studies ◽  
Twin Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Mortality And Morbidity ◽  
Human Lifespan ◽  
Genome Wide

Heritability of human lifespan is 23–33% as evident from twin studies. Genome-wide association studies explored this question by linking particular alleles to lifespan traits. However, genetic variants identified so far can explain only a small fraction of lifespan heritability in humans. Here, we report that the burden of rarest protein-truncating variants (PTVs) in two large cohorts is negatively associated with human healthspan and lifespan, accounting for 0.4 and 1.3 years of their variability, respectively. In addition, longer-living individuals possess both fewer rarest PTVs and less damaging PTVs. We further estimated that somatic accumulation of PTVs accounts for only a small fraction of mortality and morbidity acceleration and hence is unlikely to be causal in aging. We conclude that rare damaging mutations, both inherited and accumulated throughout life, contribute to the aging process, and that burden of ultra-rare variants in combination with common alleles better explain apparent heritability of human lifespan.

Genetics and pain in childhood

2021 ◽  
pp. 79-86
Author(s):  
Jeffrey S. Mogil
Keyword(s):  
Candidate Gene ◽  
Association Studies ◽  
Single Gene ◽  
Gene Mutations ◽  
Twin Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Pediatric Pain ◽  
Genome Wide ◽  
Pediatric Populations

Genomic and other “omic” approaches are now routinely applied to the study of pain. Some of these investigations have utilized pediatric populations. This review describes what is currently known about the heritability of pain in children (from twin studies), genes relevant to pain in children (from single-gene mutations, candidate gene, and genome-wide association studies), and the application of newer techniques, such as epigenomics, to pediatric pain.

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