P.046 Expression of the adult ADHD-associated gene ADGRL3 is dysregulated by genetic risk variants and environmental risk factors

BackgroundThe Temperance Boards in Sweden registered individuals for three reasons: public drunkenness, driving under the influence of alcohol and committing a crime in connection with alcohol. We wanted to ascertain whether these three forms of alcohol-related problems result from similar or different genetic and environmental risk factors.MethodWe conducted a trivariate twin analysis of these three causes of registration in all male-female twin pairs of known zygosity born in Sweden, 1926–1949 (n=5177 twin pairs).ResultsPrevalences of registration for public drunkenness, drink-driving and alcohol-related crime were, respectively, 9.0, 3.6 and 4.0%. The best-fitting model had one general genetic and one general familial – environmental factor with specific genetic risk factors for drink-driving and specific familial – environmental risk factors for alcohol-related crime.ConclusionsThe three causes for alcohol registration in Sweden largely reflect the same genetic and environmental risk factors. Estimated heritabilities were similar for the three forms of registration. However, specific genetic risk factors exist for drink-driving and specific familial – environmental risk factors for alcohol-related crime. Genetic factors are somewhat less important and familial –environmental factors more important for public drunkenness than for drink-driving and alcohol related crime.

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The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

Twin Research and Human Genetics ◽

10.1375/twin.14.6.516 ◽

2011 ◽

Vol 14 (6) ◽

pp. 516-523 ◽

Cited By ~ 19

Author(s):

Kenneth S. Kendler ◽

John M. Myers ◽

Corey L. M. Keyes

Keyword(s):

Risk Factors ◽

Environmental Risk ◽

Genetic Risk ◽

Genetic Risk Factors ◽

Environmental Risk Factors ◽

Mental Wellbeing ◽

Negatively Associated ◽

Externalizing Psychopathology ◽

Internalizing Psychopathology ◽

The Relationship

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed withthe Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing.

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Genetic and environmental risk factors in males for self-report externalizing traits in mid-adolescence and criminal behavior through young adulthood

Psychological Medicine ◽

10.1017/s003329171300007x ◽

2013 ◽

Vol 43 (10) ◽

pp. 2161-2168 ◽

Cited By ~ 8

Author(s):

K. S. Kendler ◽

C. J. Patrick ◽

H. Larsson ◽

C. O. Gardner ◽

P. Lichtenstein

Keyword(s):

Risk Factors ◽

Environmental Factors ◽

Environmental Risk ◽

Genetic Risk ◽

Criminal Behavior ◽

Environmental Risk Factors ◽

Environmental Risks ◽

The Self ◽

Self Report ◽

Equation Modeling

BackgroundExternalizing traits or behaviors are typically assessed by self-report scales or criminal records. Few genetically informative studies have used both methods to determine whether they assess the same genetic or environmental risk factors.MethodWe examined 442 male Swedish twin pairs with self-reported externalizing behaviors at age 16–17 years [externalizing traits (EXT), self-reported delinquency (SRD), impulsivity (IMP), grandiosity (GRD) and callousness (CLS)] and criminal behavior (CB) from the National Suspect Registry from age 13 to 25 years. Multivariate structural equation modeling was conducted with Mx.ResultsThe best-fit model contained one genetic, one shared environmental and two non-shared environmental common factors, and variable specific genetic and non-shared environmental factors. The risk for CB was influenced substantially by both genetic (a2 = 0.48) and familial–environmental factors (c2 = 0.22). About one-third of the genetic risk for CB but all of the shared environmental risk was indexed by the self-report measures. The degree to which the individual measures reflected genetic versus familial–environmental risks for CB varied widely. GRD and CLS were correlated with CB mainly through common genetic risk factors. SRD and CB covaried largely because of shared familial–environmental factors. For EXT and IMP, observed correlations with CB resulted in about equal parts from shared genetic and shared familial–environmental factors.ConclusionsIn adolescence, measures of grandiose and callous temperament best tap the genetic liability to CB. Measures of antisocial behaviors better index familial–environmental risks for CB. A substantial proportion of the genetic risk to CB was not well reflected in any of the self-report measures.

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Interactions of established risk factors and a GWAS-based genetic risk score on the risk of venous thromboembolism

Thrombosis and Haemostasis ◽

10.1160/th16-02-0172 ◽

2016 ◽

Vol 116 (10) ◽

pp. 705-713 ◽

Cited By ~ 6

Author(s):

Marta Crous-Bou ◽

Immaculata De Vivo ◽

Carlos A. Camargo ◽

Raphaëlle Varraso ◽

Francine Grodstein ◽

...

Keyword(s):

Risk Factors ◽

Venous Thromboembolism ◽

Risk Score ◽

Environmental Risk ◽

Genetic Risk ◽

Genetic Risk Score ◽

Environmental Risk Factors ◽

Health Study ◽

Targeted Prevention ◽

Genome Wide

SummaryMultiple genetic and environmental risk factors contribute to venous thromboembolism (VTE) risk. Understanding how genes and environmental risk factors interact may provide key insight into the pathophysiology of VTE and may identify opportunities for targeted prevention and treatment. It was our aim to examine the main effects and the potential effect-modification between single nucleotide polymorphisms (SNPs) at established loci and lifestyle risk factors for VTE. We performed a nested case-control study using data on 1,040 incident VTE cases and 16,936 controls from the Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-up Study cohorts, who gave blood, were selected as participants in a previous genome-wide association study (GWAS), and completed a biennial questionnaire at time of blood draw. We selected SNPs that were associated with VTE risk in previous GWAS studies. A genetic risk score (GRS) was constructed to evaluate the combined effect of the 16 SNPs that have reached genome-wide significance in previous GWAS of VTE. Interactions between SNPs and VTE risk factors (BMI and smoking) were also assessed. We found a significant association between our GRS and VTE risk. The risk of VTE among individuals in the highest GRS tertile was 2.02 times that of individuals in the lowest GRS tertile (p-trend = 9.69x10-19). The OR was 1.52 (p=1.03x10-8) for participants in the highest GRS tertile compared to those in the medium GRS tertile. However, while BMI and smoking were associated with VTE, and their effects were additive to each other we did not observe any significant multiplicative gene-environment interactions.Supplementary Material to this article is available online at www.thrombosis-online.com.

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Continuity of genetic and environmental influences on clinically assessed major depression from ages 18 to 45

Psychological Medicine ◽

10.1017/s0033291718003550 ◽

2018 ◽

Vol 49 (15) ◽

pp. 2582-2590

Author(s):

Fartein Ask Torvik ◽

Kristin Gustavson ◽

Eivind Ystrom ◽

Tom H. Rosenström ◽

Nathan Gillespie ◽

...

Keyword(s):

Risk Factors ◽

Environmental Risk ◽

Genetic Risk ◽

Longitudinal Design ◽

Environmental Influences ◽

Environmental Risk Factors ◽

Shared Environment ◽

Term Stability ◽

Long Term Stability

AbstractBackgroundStudies on the stability of genetic risk for depression have relied on self-reported symptoms rather than diagnoses and/or short follow-up time. Our aim is to determine to what degree genetic and environmental influences on clinically assessed major depressive disorder (MDD) are stable between age 18 and 45.MethodsA population-based sample of 11 727 twins (6875 women) born between 1967 and 1991 was followed from 2006 to 2015 in health registry data from primary care that included diagnoses provided by treating physicians. Individuals with schizophrenia or bipolar disorder (n = 163) were excluded. We modelled genetic and environmental risk factors for MDD in an accelerated longitudinal design.ResultsThe best-fitting model indicated that genetic influences on MDD were completely stable from ages 18 to 45 and explained 38% of the variance. At each age, the environmental risk of MDD was determined by the risk at the preceding observation, plus new environmental risk, with an environmental correlation of +0.60 over 2 years. The model indicated no effects of shared environment and no environmental effects stable throughout the observational period. All long-term stability was therefore explained by genetic factors.ConclusionsDifferent processes unfolded in the genetic and environmental risk for MDD. The genetic component is stable from later adolescence to middle adulthood and accounted for nearly all long-term stability. Therefore, molecular genetic studies can use age-heterogenous samples when investigating genetic risk variants of MDD. Environmental risk factors were stable over a short span of years with associations rapidly decreasing and no evidence of permanent environmental scarring.

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Environmental Risk Factors for Schizophrenia and Bipolar Disorder and Their Relationship to Genetic Risk: Current Knowledge and Future Directions

Frontiers in Genetics ◽

10.3389/fgene.2021.686666 ◽

2021 ◽

Vol 12 ◽

Author(s):

Natassia Robinson ◽

Sarah E. Bergen

Keyword(s):

Risk Factors ◽

Bipolar Disorder ◽

Environmental Factors ◽

Environmental Risk ◽

Genetic Risk ◽

Childhood Adversity ◽

Environmental Exposures ◽

Genetic Risk Factors ◽

Environmental Risk Factors ◽

Early Gene

Schizophrenia (SZ) and bipolar disorder (BD) are severe psychiatric disorders which result from complex interplay between genetic and environmental factors. It is well-established that they are highly heritable disorders, and considerable progress has been made identifying their shared and distinct genetic risk factors. However, the 15–40% of risk that is derived from environmental sources is less definitively known. Environmental factors that have been repeatedly investigated and often associated with SZ include: obstetric complications, infections, winter or spring birth, migration, urban living, childhood adversity, and cannabis use. There is evidence that childhood adversity and some types of infections are also associated with BD. Evidence for other risk factors in BD is weaker due to fewer studies and often smaller sample sizes. Relatively few environmental exposures have ever been examined for SZ or BD, and additional ones likely remain to be discovered. A complete picture of how genetic and environmental risk factors confer risk for these disorders requires an understanding of how they interact. Early gene-by-environment interaction studies for both SZ and BD often involved candidate genes and were underpowered. Larger samples with genome-wide data and polygenic risk scores now offer enhanced prospects to reveal genetic interactions with environmental exposures that contribute to risk for these disorders. Overall, although some environmental risk factors have been identified for SZ, few have been for BD, and the extent to which these account for the total risk from environmental sources remains unknown. For both disorders, interactions between genetic and environmental risk factors are also not well understood and merit further investigation. Questions remain regarding the mechanisms by which risk factors exert their effects, and the ways in which environmental factors differ by sex. Concurrent investigations of environmental and genetic risk factors in SZ and BD are needed as we work toward a more comprehensive understanding of the ways in which these disorders arise.

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NRN1 and CAT Gene Polymorphisms, Complex Noise, and Lifestyles Interactively Affect the Risk of Noise-Induced Hearing Loss

10.21203/rs.3.rs-93355/v1 ◽

2020 ◽

Author(s):

Shuang-yan LIU ◽

Jia-Rui XIN ◽

Zheng LI ◽

Song LEI ◽

Ying-Qi CHEN ◽

...

Keyword(s):

Risk Factors ◽

Physical Exercise ◽

Environmental Risk ◽

Genetic Risk ◽

Gene Polymorphisms ◽

Noise Exposure ◽

Sedentary Lifestyle ◽

Environmental Risk Factors ◽

Working Pressure ◽

Noise Metrics

Abstract Background: Multiple genetic and environmental factors influence the severity of NIHL. However, few studies have reported interactions among such factors in modulating the risk of NIHL. This study aimed to assess for interactions among gene polymorphisms, noise metrics, and lifestyles on the risk of NIHL.Methods: A case-control study was conducted using 307 patients with NIHL and 307 matched healthy individuals from five manufacturing industries. General demographic data, lifestyle details, and noise exposure levels were recorded. The kompetitive allele-specific polymerase chain reaction (KASP) was used to analyze the genotypes of 18 single nucleotide polymorphisms (SNPs). The generalized multifactor dimensionality reduction (GMDR) method was used to examine the effects of all possible interactions. Results: The proportion of people with complex noise exposure, high CNE, high adj-CNE, smoking, propensity to watch loud videos, or sedentary lifestyle was significantly greater in the NIHL group than in the healthy group (P < 0.05). The GMDR model demonstrated a relevant interaction between NRN1 rs3805789 and CAT rs7943316. Subjects with the SNP pair of NRN1 rs3805789-CC and CAT rs7943316-AT, NRN1 rs3805789-CT and CAT rs7943316-AA, NRN1 rs3805789-CT and CAT rs7943316-TT, NRN1 rs3805789-CT/TT and CAT rs7943316-AA, or NRN1 rs3805789-CC and CAT rs7943316-AT/TT had higher risks of NIHL than those with NRN1 rs3805789-CC and CAT rs7943316-AA (P < 0.05). There was an interaction among NRN1 rs3805789, CAT rs7943316, and kurtosis. Subjects exposed to complex noise and carrying both NRN1 rs3805789-CT and CAT rs7943316-TT or NRN1 rs3805789-CT/TT and CAT rs7943316-AA had higher risks of NIHL than those exposed to steady noise and carrying both NRN1 rs3805789-CC and CAT rs7943316-AA (P < 0.05). The best six‐locus model involving NRN1 rs3805789, CAT rs7943316, smoking, video volume, physical exercise, and working pressure for the risk of NIHL was found to be the interaction (P = 0.0010). An interaction was also found among smoking, video volume, physical exercise, working pressure, and kurtosis (P = 0.0107).Conclusions: Complex noise, high CNE, high adj-CNE, smoking, high video volume, and sedentary lifestyle are environmental risk factors for NIHL. Concurrence of NRN1 rs3805789 and CAT rs7943316 constitutes a genetic risk factor for NIHL. Complex noise exposure significantly increases the risk of NIHL in subjects with a high genetic risk score. Interactions between genes and lifestyle as well as noise metrics and lifestyle affect the risk of NIHL. These results provide a theoretical basis for screening genetic and environmental risk factors to prevent NIHL.

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Gene-Environment Interactions in Multiple Sclerosis

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000001007 ◽

2021 ◽

Vol 8 (4) ◽

pp. e1007

Author(s):

Benjamin Meir Jacobs ◽

Alastair J. Noyce ◽

Jonathan Bestwick ◽

Daniel Belete ◽

Gavin Giovannoni ◽

...

Keyword(s):

Risk Factors ◽

Multiple Sclerosis ◽

Childhood Obesity ◽

Environmental Risk ◽

Genetic Risk ◽

Environmental Risk Factors ◽

Age At Menarche ◽

Targeted Prevention ◽

Uk Biobank ◽

Polygenic Risk

ObjectiveWe sought to determine whether genetic risk modifies the effect of environmental risk factors for multiple sclerosis (MS). To test this hypothesis, we tested for statistical interaction between polygenic risk scores (PRS) capturing genetic susceptibility to MS and environmental risk factors for MS in UK Biobank.MethodsPeople with MS were identified within UK Biobank using ICD-10–coded MS or self-report. Associations between environmental risk factors and MS risk were quantified with a case-control design using multivariable logistic regression. PRS were derived using the clumping-and-thresholding approach with external weights from the largest genome-wide association study of MS. Separate scores were created including major histocompatibility complex (MHC) (PRSMHC) and excluding (PRSnon-MHC) the MHC locus. The best-performing PRS were identified in 30% of the cohort and validated in the remaining 70%. Interaction between environmental and genetic risk factors was quantified using the attributable proportion due to interaction (AP) and multiplicative interaction.ResultsData were available for 2,250 people with MS and 486,000 controls. Childhood obesity, earlier age at menarche, and smoking were associated with MS. The optimal PRS were strongly associated with MS in the validation cohort (PRSMHC: Nagelkerke's pseudo-R2 0.033, p = 3.92 × 10−111; PRSnon-MHC: Nagelkerke's pseudo-R2 0.013, p = 3.73 × 10−43). There was strong evidence of interaction between polygenic risk for MS and childhood obesity (PRSMHC: AP = 0.17, 95% CI 0.06–0.25, p = 0.004; PRSnon-MHC: AP = 0.17, 95% CI 0.06–0.27, p = 0.006).ConclusionsThis study provides novel evidence for an interaction between childhood obesity and a high burden of autosomal genetic risk. These findings may have significant implications for our understanding of MS biology and inform targeted prevention strategies.

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Self-Control As a Moderator for Environmental Risk Factors

PsycEXTRA Dataset ◽

10.1037/e609212010-001 ◽

2010 ◽

Author(s):

Thomas A. Wills ◽

Pallav Pokhrel ◽

Frederick X. Gibbons ◽

James D. Sargent ◽

Mike Stoolmiller

Keyword(s):

Risk Factors ◽

Environmental Risk ◽

Environmental Risk Factors ◽

Self Control

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