Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study

2018 ◽  
Author(s):  
Yunpeng Wu ◽  
Ge Li ◽  
Hong Cheng ◽  
Lanweng Han ◽  
Junling Fu ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Lifestyle Factors

Lifestyle factors and genetic variants on two biological age measures: evidence from 94,443 Taiwan Biobank participants

2021 ◽  
Author(s):  
Wan-Yu Lin
Keyword(s):  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Lifestyle Factors ◽  
Biological Age ◽  
Biological Aging ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome ◽  
The Uk

Abstract Background Biological age (BA) can be estimated by phenotypes and is useful for predicting lifespan and healthspan. Levine et al. proposed a PhenoAge and a BioAge to measure BA. Although there have been studies investigating the genetic predisposition to BA acceleration in Europeans, little has been known regarding this topic in Asians. Methods I here estimated PhenoAgeAccel (age-adjusted PhenoAge) and BioAgeAccel (age-adjusted BioAge) of 94,443 Taiwan Biobank (TWB) participants, wherein 25,460 TWB1 subjects formed a discovery cohort and 68,983 TWB2 individuals constructed a replication cohort. Lifestyle factors and genetic variants associated with PhenoAgeAccel and BioAgeAccel were investigated through regression analysis and a genome-wide association study (GWAS). Results A unit (kg/m 2) increase of BMI was associated with a 0.177-year PhenoAgeAccel (95% C.I. = 0.163~0.191, p = 6.0×) and 0.171-year BioAgeAccel (95% C.I. = 0.165~0.177, p = 0). Smokers on average had a 1.134-year PhenoAgeAccel (95% C.I. = 0.966~1.303, p = 1.3×) compared with non-smokers. Drinkers on average had a 0.640-year PhenoAgeAccel (95% C.I. = 0.433~0.847, p = 1.3×) and 0.193-year BioAgeAccel (95% C.I. = 0.107~0.279, p = 1.1×) relative to non-drinkers. A total of 11 and 4 single-nucleotide polymorphisms (SNPs) were associated with PhenoAgeAccel and BioAgeAccel (p<5× in both TWB1 and TWB2), respectively. Conclusions A PhenoAgeAccel-associated SNP (rs1260326 in GCKR) and two BioAgeAccel-associated SNPs (rs7412 in APOE; rs16998073 near FGF5) were consistent with the finding from the UK Biobank. The lifestyle analysis shows that prevention from obesity, cigarette smoking, and alcohol consumption is associated with a slower rate of biological aging.

scholarly journals Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunpeng Wu ◽  
Ling Zhong ◽  
Ge Li ◽  
Lanwen Han ◽  
Junling Fu ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Pubertal Development ◽  
Lifestyle Factors ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Exercise Frequency ◽  
Cross Sectional ◽  
Individual Snps ◽  
Diet Score

BackgroundHypoadiponectinemia has been associated with various cardiometabolic disease states. Previous studies in adults have shown that adiponectin levels were regulated by specific genetic and behavioral or lifestyle factors. However, little is known about the influence of these factors on adiponectin levels in children, particularly as mitigated by pubertal development.MethodsWe performed a cross-sectional analysis of data from 3,402 children aged 6-18 years from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. Pubertal progress was classified as prepubertal, midpuberty, and postpuberty. Six relevant single nucleotide polymorphisms (SNPs) were selected from previous genome-wide association studies of adiponectin in East Asians. Individual SNPs and two weighted genetic predisposition scores, as well as their interactions with 14 lifestyle factors, were analyzed to investigate their influence on adiponectin levels across puberty. The effect of these factors on adiponectin was analyzed using general linear models adjusted for age, sex, and BMI.ResultsAfter adjustment for age, sex, and BMI, the associations between adiponectin levels and diet items, and diet score were significant at prepuberty or postpuberty, while the effect of exercise on adiponectin levels was more prominent at mid- and postpuberty. Walking to school was found to be associated with increased adiponectin levels throughout puberty. Meanwhile, the effect of WDR11-FGFR2-rs3943077 was stronger at midpuberty (P = 0.002), and ADIPOQ-rs6773957 was more effective at postpuberty (P = 0.005), while CDH13-rs4783244 showed the strongest association with adiponectin levels at all pubertal stages (all P < 3.24 × 10-15). We further found that effects of diet score (Pinteraction = 0.022) and exercise (Pinteraction = 0.049) were stronger in children with higher genetic risk of hypoadiponectinemia, while higher diet score and exercise frequency attenuated the differences in adiponectin levels among children with different genetic risks.ConclusionsOur study confirmed puberty modulates the associations between adiponectin, and genetic variants, lifestyle factors, and gene-by-lifestyle interactions. These findings provide new insight into puberty-specific lifestyle suggestions, especially in genetically susceptible individuals.

scholarly journals Interactions between genetic variants of folate metabolism genes and lifestyle affect plasma homocysteine concentrations in the Boston Puerto Rican population

2011 ◽  
Vol 14 (10) ◽  
pp. 1805-1812 ◽  
Author(s):  
Tao Huang ◽  
Katherine L Tucker ◽  
Yu-Chi Lee ◽  
Jimmy W Crott ◽  
Laurence D Parnell ◽  
...  
Keyword(s):  
Physical Activity ◽  
Puerto Rican ◽  
Genetic Polymorphisms ◽  
Genetic Variants ◽  
Pyridoxal Phosphate ◽  
Smoking Status ◽  
Plasma Concentrations ◽  
Lifestyle Factors ◽  
Plasma Homocysteine ◽  
Folate Metabolism

AbstractObjectiveTo investigate genetic and lifestyle factors and their interactions on plasma homocysteine (Hcy) concentrations in the Boston Puerto Rican population.DesignCross-sectional study. Plasma concentrations of Hcy, folate, vitamin B12and pyridoxal phosphate were measured, and genetic polymorphisms were determined. Data on lifestyle factors were collected in interviews.SettingA population survey of health and nutritional measures.SubjectsA total of 994 Puerto Rican men and women residing in the Boston metropolitan area.ResultsSmoking status was positively associated with plasma Hcy. Genetic polymorphismsMTHFR677C→T,FOLH11561C→T,FOLH1rs647370 andPCFT928A→G interacted significantly with smoking for Hcy.MTHFR1298A→C (P= 0·040) andPCFT928A→G (P= 0·002) displayed significant interactions with alcohol intake in determining plasma Hcy. Subjects withPCFT928GGgenotype had significantly higher plasma Hcy concentrations compared with carriers of theAallele (AA+AG;P= 0·030) among non-drinking subjects. When consuming alcohol,GGsubjects had lower plasma Hcy levels compared withAA+AGsubjects. Physical activity interacted significantly withMTR2756A→G in determining plasma Hcy (Pfor interaction = 0·002). Smoking interacted with physical activity for plasma Hcy (Pfor interaction = 0·023).ConclusionsSmoking and drinking were associated plasma Hcy concentrations. Genetic variants involved in folate metabolism further modify the effects of lifestyle on plasma Hcy.

scholarly journals Modifiable lifestyle factors and severe COVID-19 risk: a Mendelian randomisation study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Shuai Li ◽  
Xinyang Hua
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Association Studies ◽  
Lifestyle Factors ◽  
Mendelian Randomisation ◽  
Severe Illness ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk

Abstract Background Lifestyle factors including obesity and smoking are suggested to be correlated with increased risk of COVID-19 severe illness or related death. However, whether these relationships are causal is not well known; neither for the relationships between COVID-19 severe illness and other common lifestyle factors, such as physical activity and alcohol consumption. Methods Genome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, physical activity and alcohol consumption identified by large-scale genome-wide association studies (GWAS) of up to 941,280 individuals were selected as instrumental variables. Summary statistics of the genetic variants on severe illness of COVID-19 were obtained from GWAS analyses of up to 6492 cases and 1,012,809 controls. Two-sample Mendelian randomisation analyses were conducted. Results Both per-standard deviation (SD) increase in genetically predicted BMI and lifetime smoking were associated with about two-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P < 0.05). Per-SD increase in genetically predicted physical activity was associated with decreased risks of severe respiratory COVID-19 (odds ratio [OR] = 0.19; 95% confidence interval [CI], 0.05, 0.74; P = 0.02), but not with COVID-19 hospitalization (OR = 0.44; 95% CI 0.18, 1.07; P = 0.07). No evidence of association was found for genetically predicted alcohol consumption. Similar results were found across robust Mendelian randomisation methods. Conclusions Evidence is found that BMI and smoking causally increase and physical activity might causally decrease the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

scholarly journals Modifiable lifestyle factors and severe COVID-19 risk: Evidence from Mendelian randomization analysis

2020 ◽  
Author(s):  
Shuai Li
Keyword(s):  
Physical Activity ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Lifestyle Factors ◽  
Severe Illness ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk

AbstractBackgroundLifestyle factors including obesity and smoking are suggested to be related to increased risk of COVID-19 severe illness or related death. However, little is known about whether these relationships are causal, or the relationships between COVID-19 severe illness and other lifestyle factors, such as alcohol consumption and physical activity.MethodsGenome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, alcohol consumption and physical activity identified by large-scale genome-wide association studies (GWAS) were selected as instrumental variables. GWAS summary statistics of these genetic variants for relevant lifestyle factors and severe illness of COVID-19 were obtained. Two-sample Mendelian randomization (MR) analyses were conducted.ResultsBoth genetically predicted BMI and lifetime smoking were associated with about 2-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P<0.05). Genetically predicted physical activity was associated with about 5-fold (95% confidence interval [CI], 1.4, 20.3; P=0.02) decreased risk of severe respiratory COVID-19, but not with COVID-19 hospitalization, though the majority of the 95% CI did not include one. No evidence of association was found for genetically predicted alcohol consumption, but associations were found when using pleiotropy robust methods.ConclusionEvidence is found that BMI and smoking causally increase and physical activity causally decreases the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

scholarly journals Multi-omics insights into the biological mechanisms underlying gene-by-lifestyle interactions with smoking and alcohol consumption detected by genome-wide trans-ancestry meta-analysis

2021 ◽  
Author(s):  
Timothy D Majarian ◽  
Amy R Bentley ◽  
Vincent Laville ◽  
Michael R Brown ◽  
Daniel I Chasman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Pressure ◽  
Alcohol Consumption ◽  
Genetic Variants ◽  
Blood Lipids ◽  
Epigenetic Modification ◽  
Smoking Behavior ◽  
Lifestyle Factors ◽  
Biological Mechanisms ◽  
Genome Wide

Gene-lifestyle interaction analyses have identified genetic variants whose effect on cardiovascular risk-raising traits is modified by alcohol consumption and smoking behavior. The biological mechanisms of these interactions remain largely unknown, but may involve epigenetic modification linked to perturbation of gene expression. Diverse, individual-level datasets including genotypes, methylation and gene expression conditional on lifestyle factors, are ideally suited to study this hypothesis, yet are often unavailable for large numbers of individuals. Summary-level data, such as effect sizes of genetic variants on a phenotype, present an opportunity for multi-omic study of the biological mechanisms underlying gene-lifestyle interactions. We propose a method that unifies disparate, publicly available summary datasets to build mechanistic hypotheses in models of smoking behavior and alcohol consumption with blood lipid levels and blood pressure measures. Of 897 observed genetic interactions, discovered through genome-wide analysis in diverse multi-ethnic cohorts, 48 were identified with lifestyle-related differentially methylated sites within close proximity and linked to target genes. Smoking behavior and blood lipids account for 37 and 28 of these signals respectively. Five genes also showed differential expression conditional on lifestyle factors within these loci with mechanisms supported in the literature. Our analysis demonstrates the utility of summary data in characterizing observed gene-lifestyle interactions and prioritizes genetic loci for experimental follow up related to blood lipids, blood pressure, and cigarette smoking. We show concordance between multiple trait- or exposure-related associations from diverse assays, driving hypothesis generation for better understanding gene-lifestyle interactions.

Sign in / Sign up

Export Citation Format

Share Document