scholarly journals Evaluating the genetic effects of sex hormone on the development of mental traits: a polygenic score analysis and genome-wide genetic interaction analysis in the UK Biobank cohort

2020 ◽  
Author(s):  
Xiao Liang ◽  
ShiQiang Cheng ◽  
Jing Ye ◽  
XiaoMeng Chu ◽  
Yan Wen ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Fluid Intelligence ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Genetic Effects ◽  
Sex Hormone ◽  
Uk Biobank ◽  
Genome Wide ◽  
Study Results ◽  
The Uk

Abstract Objective: To evaluate the genetic effects of sex hormone on the development of mental traits.Methods: The SNPs significantly associated with sex hormone traits were driven from a two-stage genome-wide association study (GWAS). Four sex hormone were selected in this study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk scores (PRS) of sex hormone traits were calculated from individual-level genotype data of the UK Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, genome-wide genetic interaction study (GWGIS) was performed to detect novel candidate genes interacting with the sex hormone on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0.Results: We observed positive associations between SHBG and the frequency of alcohol consumption (b=0.01, p=3.84×10–11) in males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b=0.01, p=1,96×10–8), fluid intelligence (b=0.01, p=1.90×10–2) and the frequency of smoking (b=0.01, p=1.77×10–2) in males. Moreover, SHBG was associated with the frequency of alcohol consumption (b=0.01, p=2.60×10–3), fluid intelligence (b=0.01, p=4.25×10–2) and anxiety (b=-0.01, p=3.79×10–2) in females. Finally, GWGIS identified one significant loci, Tenascin R (TNR) (rs34633780, p=3.45×10–8) interacting with total testosterone for fluid intelligence.Conclusion: Our study results support the genetic effects of sex hormone on the development of intelligence and the frequency of alcohol consumption.

scholarly journals Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and genome-wide genetic interaction analysis in UK Biobank cohort

2020 ◽  
Author(s):  
Xiao Liang ◽  
ShiQiang Cheng ◽  
Jing Ye ◽  
XiaoMeng Chu ◽  
Yan Wen ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Fluid Intelligence ◽  
Genetic Interaction ◽  
Genetic Effects ◽  
Sex Hormone ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Middle Aged ◽  
Genome Wide ◽  
Middle Aged Adults

Abstract Objective: To evaluate the genetic effects of sex hormone traits on the development of mental traits in middle-aged adults.Methods: The SNPs associated with sex hormone traits were derived from a two-stage genome-wide association study (GWAS). Four sex hormone traits were selected in the current study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk score (PRS) of sex hormone traits were calculated from individual-level genotype data of the United Kingdom (UK) Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, genome-wide genetic interaction study (GWGIS) was performed to detect novel candidate genes interacting with the sex hormone traits on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0.Results: We observed positive association between SHBG and the frequency of alcohol consumption (b=0.0101, p=3.84×10–11) in middle-aged males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b=0.0128, p=1,96×10–8), fluid intelligence (b=0.0084, p=1.90×10–2) and the frequency of smoking (b=0.0054, p=1.77×10–2) in middle-aged males. Moreover, SHBG was associated with the frequency of alcohol consumption (b=0.0067, p=2.60×10–3), fluid intelligence (b=0.0067, p=4.25×10–2) and anxiety (b=-0.0071, p=3.79×10–2) in middle-aged females. Finally, GWGIS identified one significant loci, Tenascin R (TNR) (rs34633780, p=3.45×10–8) interacting with total testosterone for fluid intelligence.Conclusion: Our study results support the genetic effects of sex hormone traits on the development of intelligence and the frequency of alcohol consumption in middle-aged adults in UK.

scholarly journals Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and genome-wide genetic interaction analysis in UK Biobank cohort

2020 ◽  
Author(s):  
Xiao Liang ◽  
ShiQiang Cheng ◽  
Jing Ye ◽  
XiaoMeng Chu ◽  
Yan Wen ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Fluid Intelligence ◽  
Genetic Interaction ◽  
Genetic Effects ◽  
Sex Hormone ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Middle Aged ◽  
Genome Wide ◽  
Middle Aged Adults

Abstract Objective: To evaluate the genetic effects of sex hormone traits on the development of mental traits in middle-aged adults.Methods: The SNPs associated with sex hormone traits were derived from a two-stage genome-wide association study (GWAS). Four sex hormone traits were selected in the current study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk score (PRS) of sex hormone traits were calculated from individual-level genotype data of the United Kingdom (UK) Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, genome-wide genetic interaction study (GWGIS) was performed to detect novel candidate genes interacting with the sex hormone traits on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0.Results: We observed positive association between SHBG and the frequency of alcohol consumption (b=0.0101, p=3.84×10–11) in middle-aged males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b=0.0128, p=1,96×10–8) in middle-aged males. Moreover, SHBG was associated with the frequency of alcohol consumption (b=0.0067, p=2.60×10–3) in middle-aged females. Finally, GWGIS identified one significant loci, Tenascin R (TNR) (rs34633780, p=3.45×10–8) interacting with total testosterone for fluid intelligence.Conclusion: Our study results support the genetic effects of sex hormone traits on the development of intelligence and the frequency of alcohol consumption in middle-aged adults in UK.

scholarly journals Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and gene-environment-wide interaction study in UK Biobank cohort

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao Liang ◽  
ShiQiang Cheng ◽  
Jing Ye ◽  
XiaoMeng Chu ◽  
Yan Wen ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Fluid Intelligence ◽  
Genetic Effects ◽  
Sex Hormone ◽  
Uk Biobank ◽  
Interaction Study ◽  
Middle Aged ◽  
Bioavailable Testosterone ◽  
Gene Environment ◽  
Middle Aged Adults

Abstract Objective To evaluate the genetic effects of sex hormone traits on the development of mental traits in middle-aged adults. Methods The SNPs associated with sex hormone traits were derived from a two-stage genome-wide association study (GWAS). Four sex hormone traits were selected in the current study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk score (PRS) of sex hormone traits were calculated from individual-level genotype data of the United Kingdom (UK) Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, gene-environment-wide interaction study (GEWIS) was performed to detect novel candidate genes interacting with the sex hormone traits on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0. Results We observed positive association between SHBG and the frequency of alcohol consumption (b = 0.0101, p = 3.84 × 10–11) in middle-aged males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b = 0.0128, p = 1.96 × 10–8) in middle-aged males. Moreover, bioavailable testosterone was associated with the fluid intelligence (b = − 0.0136, p = 5.74 × 10–5) in middle-aged females. Finally, GEWIS identified one significant loci, Tenascin R (TNR) (rs34633780, p = 3.45 × 10–8) interacting with total testosterone for fluid intelligence. Conclusion Our study results support the genetic effects of sex hormone traits on the development of intelligence and the frequency of alcohol consumption in middle-aged adults in UK.

scholarly journals Dietary Habit Is Associated with Depression and Intelligence: An Observational and Genome-Wide Environmental Interaction Analysis in the UK Biobank Cohort

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1150
Author(s):  
Bolun Cheng ◽  
Xiaomeng Chu ◽  
Xuena Yang ◽  
Yan Wen ◽  
Yumeng Jia ◽  
...  
Keyword(s):  
Mental Health ◽  
Fluid Intelligence ◽  
Dietary Habits ◽  
Interaction Analysis ◽  
Dietary Habit ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Study Results ◽  
The Individual ◽  
The Uk

Dietary habits have considerable impact on brain development and mental health. Despite long-standing interest in the association of dietary habits with mental health, few population-based studies of dietary habits have assessed depression and fluid intelligence. Our aim is to investigate the association of dietary habits with depression and fluid intelligence. In total, 814 independent loci were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habit-related traits. The individual genotype data were obtained from the UK Biobank cohort. Regression analyses were then conducted to evaluate the association of dietary habits with depression and fluid intelligence, respectively. PLINK 2.0 was utilized to detect the single nucleotide polymorphism (SNP) × dietary habit interaction effect on the risks of depression and fluid intelligence. We detected 22 common dietary habit-related traits shared by depression and fluid intelligence, such as red wine glasses per month, and overall alcohol intake. For interaction analysis, we detected that OLFM1 interacted with champagne/white wine in depression, while SYNPO2 interacted with coffee type in fluid intelligence. Our study results provide novel useful information for understanding how eating habits affect the fluid intelligence and depression.

scholarly journals Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and gene-environment-wide interaction study in UK Biobank cohort

2020 ◽  
Author(s):  
Xiao Liang ◽  
ShiQiang Cheng ◽  
Jing Ye ◽  
XiaoMeng Chu ◽  
Yan Wen ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Fluid Intelligence ◽  
Genetic Effects ◽  
Sex Hormone ◽  
Uk Biobank ◽  
Interaction Study ◽  
Middle Aged ◽  
Bioavailable Testosterone ◽  
Gene Environment ◽  
Middle Aged Adults

Abstract Objective: To evaluate the genetic effects of sex hormone traits on the development of mental traits in middle-aged adults.Methods: The SNPs associated with sex hormone traits were derived from a two-stage genome-wide association study (GWAS). Four sex hormone traits were selected in the current study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk score (PRS) of sex hormone traits were calculated from individual-level genotype data of the United Kingdom (UK) Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, gene-environment-wide interaction study (GEWIS) was performed to detect novel candidate genes interacting with the sex hormone traits on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0.Results: We observed positive association between SHBG and the frequency of alcohol consumption (b=0.0101, p=3.84×10–11) in middle-aged males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b=0.0128, p=1,96×10–8) in middle-aged males. Moreover, bioavailable testosterone was associated with the fluid intelligence (b=-0.0136, p=5.74×10-5) in middle-aged females. Finally, GEWIS identified one significant loci, Tenascin R (TNR) (rs34633780, p=3.45×10–8) interacting with total testosterone for fluid intelligence.Conclusion: Our study results support the genetic effects of sex hormone traits on the development of intelligence and the frequency of alcohol consumption in middle-aged adults in UK.

scholarly journals Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Angli Xue ◽  
Longda Jiang ◽  
Zhihong Zhu ◽  
Naomi R. Wray ◽  
Peter M. Visscher ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Longitudinal Changes ◽  
Genome Wide ◽  
The Uk ◽  
Almost All ◽  
Cardiovascular Traits

AbstractGenome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.

scholarly journals Large-Scale, Genome-Wide Gene-Diet Interaction Testing for HbA1c Using Derived Dietary Patterns in the UK Biobank

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1280-1280
Author(s):  
Kenneth Westerman ◽  
Ye Chen ◽  
Han Chen ◽  
Jose Florez ◽  
Joanne Cole ◽  
...  
Keyword(s):  
Principal Components ◽  
Dietary Patterns ◽  
Genetic Variants ◽  
Interaction Analysis ◽  
European Ancestry ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Gene Level ◽  
The Uk

Abstract Objectives Gene-diet interaction analysis can inform the development of precision nutrition for diabetes by uncovering genetic variants whose effects on glycemic traits vary across dietary behaviors. However, due to noise in dietary datasets and the low statistical power inherent in interaction analysis, there is a lack of confident, well-replicated gene-diet interactions for glycemic traits. Emerging computationally-efficient software tools have made it feasible to conduct well-powered, genome-wide interaction analysis in hundreds of thousands of individuals. Here, our objective was to conduct a genome-wide gene-diet interaction analysis for glycated hemoglobin (HbA1c; a measure of hyperglycemia), leveraging the large sample size of the UK Biobank cohort and data-driven dietary patterns to discover genetic variants whose effect is modulated by diet. Methods Food frequency questionnaires were previously used to derive empirical dietary patterns using principal components analysis (FFQ-PCs) in the UK Biobank. FFQ-PCs were used in genome-wide interaction analysis for HbA1c levels in unrelated, non-diabetic individuals of European ancestry (N = 331,610), adjusting for age, sex, and 10 genetic principal components. P-values were calculated for both the interaction (P-int) and a joint test (significance of the variant-HbA1c association combining the main and interaction effects) and the MAGMA tool was used to calculate gene-level enrichment statistics. Results Preliminary results from the first two FFQ-PCs confirmed known genetic loci for HbA1c using the joint test, such as at G6PC2 and GCK. Though no interaction tests reached genome-wide significance, suggestive signals (P-int < 1e-5) emerged at the variant level (including one near TPSD1, which codes for a tryptase and has been linked to red blood cell traits) and the gene level (such as for GTF3C2, which has previously been shown to interact with sleep in impacting lipid traits). Conclusions We have conducted the largest genome-wide study of gene-diet interactions for glycemic traits to-date and identified regions in the genome whose effect on HbA1c may be modulated by dietary intake, suggesting that this approach has the potential to reveal new insights into the genetics of glycemic traits and inform individualized dietary guidelines for diabetes prevention and management. Funding Sources NHLBI.

scholarly journals Familial influences on Neuroticism and Education in the UK Biobank

2019 ◽  
Author(s):  
R. Cheesman ◽  
J. Coleman ◽  
C. Rayner ◽  
K.L. Purves ◽  
G. Morneau-Vaillancourt ◽  
...  
Keyword(s):  
Environmental Influence ◽  
Heritability Estimate ◽  
Genetic Effects ◽  
Uk Biobank ◽  
Multiple Sources ◽  
Genome Wide ◽  
Familial Influences ◽  
Couple Similarity ◽  
Family Based ◽  
The Uk

AbstractGenome-wide studies often exclude family members, even though they are a valuable source of information. We identified parent-offspring pairs, siblings and couples in the UK Biobank and implemented a family-based DNA-derived heritability method to capture additional genetic effects and multiple sources of environmental influence on neuroticism and years of education. Compared to estimates from unrelated individuals, heritability increased from 10% to 27% and from 19% to 57% for neuroticism and education respectively by including family-based genetic effects. We detected no family environmental influences on neuroticism, but years of education was substantially influenced by couple similarity (38%). Overall, our genetic and environmental estimates closely replicate previous findings from an independent sample, but more research is required to dissect contributions to the additional heritability, particularly rare and structural genetic effects and residual environmental confounding. The latter is especially relevant for years of education, a highly socially-contingent variable, for which our heritability estimate is at the upper end of twin estimates in the literature. Family-based genetic effects narrow the gap between twin and DNA-based heritability methods, and could be harnessed to improve polygenic prediction.

scholarly journals Genome-wide environmental interaction analysis identifies dietary habit related risk loci for depression and intelligence in UK Biobank

2020 ◽  
Author(s):  
Bolun Cheng ◽  
Xiaomeng Chu ◽  
Yan Wen ◽  
Yumeng Jia ◽  
Chujun Liang ◽  
...  
Keyword(s):  
Dietary Habits ◽  
Interaction Analysis ◽  
Significant Snps ◽  
Dietary Habit ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Study Results ◽  
The Individual

Abstract Background Dietary habits have considerable impact on brain development and mental health. Our aim is to explore the possible association of dietary habits with depression and intelligence. Methods A total of 814 independent loci from a genome-wide association study (GWAS) of dietary habits were utilized to calculate the individual polygenic risk score (PRS) for 143 dietary habits related traits. The individual genotype data were obtained from UK Biobank cohort. Regression analyses were then conducted to evaluate the possible association of dietary habits with depression (including 153,549 subjects) and intelligence (including 160,121 subjects), respectively. Using dietary habits related PRSs as covariates, PLINK 2.0 was utilized to detect the SNP × dietary habit interaction effect on the risks of depression and intelligence, respectively. Results We detected 32 and 41 candidate dietary habits related traits for depression and intelligence, respectively, such as never eat sugar vs. no sugar restrictions (P = 1.09 × 10− 2) for depression, and coffee type: decaffeinated vs. any other (P = 8.77 × 10− 3) for intelligence. We also detected 22 common dietary habits related traits shared by depression and intelligence, such as red wine glasses per month (Pdepression = 8.75 × 10− 3, Pintelligence = 3.35 × 10− 19), and overall alcohol intake (Pdepression = 3.60 × 10− 2, Pintelligence = 8.31 × 10− 8). Interaction analysis of depression detected OLFM1 with 9 significant SNPs interacted with champagne/white wine glasses per month. Interaction analysis of intelligence detected SYNPO2 with 3 significant SNPs interacted with coffee type: decaffeinated vs. any other. Conclusions Our study results provide novel useful information for understanding how eating habits affecting the intelligence and the risk of depression.

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