scholarly journals Genetic and environmental risk for chronic pain and the contribution of risk variants for psychiatric disorders. Results from Generation Scotland: Scottish Family Health Study and UK Biobank

2016 ◽  
Author(s):  
Andrew M McIntosh ◽  
Lynsey S Hall ◽  
Yanni Zeng ◽  
Mark James Adams ◽  
Jude Gibson ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Environmental Risk ◽  
Genetic Factors ◽  
Family Health ◽  
Health Study ◽  
Shared Environment ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Generation Scotland ◽  
Genomic Risk

Background Chronic pain is highly prevalent worldwide and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with psychiatric illness, and major depressive disorder (MDD) in particular, is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the UK Biobank study. Methods Using family-based mixed-model analyses, we examined the contribution of genetics and environment to chronic pain using spouse, sibling and household groups as measures of shared environment. We then examined the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic risk architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. Results Chronic pain is a moderately heritable trait (narrow sense heritability = 38.4%) which is more likely to be concordant in spouses and partners (variance explained 18.7%). Chronic pain is positively correlated with depression (rho = 0.13, p = 2.72x10-68) and it shows a tendency to cluster within families for genetic reasons (genetic correlation rho = 0.51, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, predicted chronic pain in both GS:SFHS (maximum = 6.18x10-2, p = 4.3x10-4) and UK Biobank (maximum = 5.68 x 10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum = 6.62x10-2, p = 4.3x10-4) and UK Biobank (maximum = 2.56x10-2, p < 3x10-4). Conclusions Genetic factors and chronic pain in a partner or spouse contribute substantially to the risk of chronic pain in the general population. Chronic pain is genetically correlated with MDD, has a polygenic architecture and is predicted by polygenic risk of MDD.

scholarly journals Intelligence and neuroticism in relation to depression and psychological distress: evidence of interaction using data from Generation Scotland: Scottish Family Health Study and UK Biobank

2016 ◽  
Author(s):  
LB Navrady ◽  
SJ Ritchie ◽  
SWY Chan ◽  
DM Kerr ◽  
MJ Adams ◽  
...  
Keyword(s):  
Psychological Distress ◽  
Significant Interaction ◽  
Protective Factor ◽  
Short Form ◽  
Family Health ◽  
Population Based ◽  
Depressive Illness ◽  
Health Study ◽  
Uk Biobank ◽  
Generation Scotland

ABSTRACTBackgroundNeuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined.MethodsAssociations and interactions between neuroticism and general intelligence (g) on MDD and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, N=19,200) and UK Biobank (N=90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS.ResultsNeuroticism was associated with MDD and psychological distress in both samples. A significant interaction between neuroticism and g in predicting MDD status was found in UK Biobank (OR = 0.96, p < .01), suggesting that higher g ameliorated the adverse effects of neuroticism on the likelihood of having MDD. This interaction was not found in GS:SFHS. In both samples, higher neuroticism and lower intelligence were associated with increased psychological distress. A significant interaction was also found in both cohorts (GS:SFHS: ß = -0.05, p < .01; UK Biobank: ß = -0.02, p < .01), such that intelligence protected against the deleterious effect of neuroticism on psychological distress.ConclusionsFrom two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on risk for depressive illness and psychological distress.

1461-P: Cardiac Troponin T and Troponin I and Incident Diabetes in the General Population: Generation Scotland Scottish Family Health Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1461-P
Author(s):  
PAUL WELSH ◽  
DAVID PREISS ◽  
ARCHIE CAMPBELL ◽  
DAVID J. PORTEOUS ◽  
NICHOLAS L. MILLS ◽  
...  
Keyword(s):  
General Population ◽  
Cardiac Troponin ◽  
Troponin I ◽  
Troponin T ◽  
Family Health ◽  
Incident Diabetes ◽  
Health Study ◽  
Cardiac Troponin T ◽  
Generation Scotland

scholarly journals Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

2019 ◽  
Vol 3 ◽  
pp. 11 ◽  
Author(s):  
Toni-Kim Clarke ◽  
Yanni Zeng ◽  
Lauren Navrady ◽  
Charley Xia ◽  
Chris Haley ◽  
...  
Keyword(s):  
Risk Factors ◽  
Life Events ◽  
Stressful Life Events ◽  
Family Health ◽  
Stressful Life ◽  
Risk Scores ◽  
Health Study ◽  
Phenotypic Variance ◽  
Polygenic Risk ◽  
Genetic Overlap

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=1.9%, p=1.04 x 10-37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r2=0.3%, p=3 x 10-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (rG=0.33, S.E.=0.08 ) and neuroticism (rG=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

scholarly journals Molecular Genetic Risk for Psychosis Is Associated With Psychosis Risk Symptoms in a Population-Based UK Cohort: Findings From Generation Scotland

2020 ◽  
Vol 46 (5) ◽  
pp. 1045-1052
Author(s):  
Anna R Docherty ◽  
Andrey A Shabalin ◽  
Daniel E Adkins ◽  
Frank Mann ◽  
Robert F Krueger ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Molecular Genetic ◽  
Large Population ◽  
Genetic Data ◽  
Population Based ◽  
Health Study ◽  
Polygenic Risk ◽  
Generation Scotland ◽  
Common Genetic Variants ◽  
Psychosis Risk

Abstract Objective Subthreshold psychosis risk symptoms in the general population may be associated with molecular genetic risk for psychosis. This study sought to optimize the association of risk symptoms with genetic risk for psychosis in a large population-based cohort in the UK (N = 9104 individuals 18–65 years of age) by properly accounting for population stratification, factor structure, and sex. Methods The newly expanded Generation Scotland: Scottish Family Health Study includes 5391 females and 3713 males with age M [SD] = 45.2 [13] with both risk symptom data and genetic data. Subthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B) and calculation of polygenic risk for schizophrenia was based on 11 425 349 imputed common genetic variants passing quality control. Follow-up examination of other genetic risks included attention-deficit hyperactivity disorder (ADHD), autism, bipolar disorder, major depression, and neuroticism. Results Empirically derived symptom factor scores reflected interpersonal/negative symptoms and were positively associated with polygenic risk for schizophrenia. This signal was largely sex specific and limited to males. Across both sexes, scores were positively associated with neuroticism and major depressive disorder. Conclusions A data-driven phenotypic analysis enabled detection of association with genetic risk for schizophrenia in a population-based sample. Multiple polygenic risk signals and important sex differences suggest that genetic data may be useful in improving future phenotypic risk assessment.

536. Cognitive Performance in Major Depressive Disorder in Generation Scotland: The Scottish Family Health Study (GS:SFHS)

2017 ◽  
Vol 81 (10) ◽  
pp. S217
Author(s):  
Joeri Meijsen ◽  
Archie Campbell ◽  
Andrew McIntosh ◽  
David Porteous ◽  
Ian Deary ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Cognitive Performance ◽  
Family Health ◽  
Health Study ◽  
Major Depressive ◽  
Generation Scotland

scholarly journals Generation Scotland - Using Electronic Health Records for Research

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Archie Campbell ◽  
David Porteous
Keyword(s):  
Family Health ◽  
Health Study ◽  
Mortality Data ◽  
Generation Scotland ◽  
Scanned Images ◽  
Family Based ◽  
New Research ◽  
Lab Test ◽  
Longitudinal Dataset

Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based genetic epidemiology study of ~24,000 volunteers from ~7000 families recruited across Scotland between 2006 and 2011 with the capacity for follow-up through record linkage and re-contact. Broad consent was obtained for linkage to “medical records” for 98% of the cohort. Participants completed a questionnaire, provided samples, and underwent clinical assessment. The samples and data collected form a resource with consent for research on the genetics of health, becoming a longitudinal dataset by linkage to routine NHS hospital, maternity, lab test, prescribing, dentistry and mortality data. Researchers can use the linked datasets to test research hypotheses on a stratified population and target recruitment to new studies. We have established and validated EHR linkage, overcoming technical and governance issues in the process. We plan to collaborate with UK Biobank, creating a combined cohort of over 50,000 people in Scotland, and using the SHARE register to obtain new research samples from routine NHS tests. We will extend linkage to include primary care data and scanned images in the next year. The resources are available to academic and commercial researchers through a managed access process.

scholarly journals Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

2018 ◽  
Vol 3 ◽  
pp. 11 ◽  
Author(s):  
Toni-Kim Clarke ◽  
Yanni Zeng ◽  
Lauren Navrady ◽  
Charley Xia ◽  
Chris Haley ◽  
...  
Keyword(s):  
Risk Factors ◽  
Life Events ◽  
Stressful Life Events ◽  
Family Health ◽  
Stressful Life ◽  
Risk Scores ◽  
Health Study ◽  
Phenotypic Variance ◽  
Polygenic Risk ◽  
Genetic Overlap

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is correlated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively correlated with lifetime MDD status (β=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=1.9%, p=1.04 x 10-37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r2=0.3%, p=3 x 10-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (rG=0.33, S.E.=0.08 ) and neuroticism (rG=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

scholarly journals Cohort Profile: Stratifying Resilience and Depression Longitudinally (STRADL): a questionnaire follow-up of Generation Scotland: Scottish Family Health Study (GS:SFHS)

2017 ◽  
Vol 47 (1) ◽  
pp. 13-14g ◽  
Author(s):  
L B Navrady ◽  
M K Wolters ◽  
D J MacIntyre ◽  
T-K Clarke ◽  
A I Campbell ◽  
...  
Keyword(s):  
Family Health ◽  
Health Study ◽  
Generation Scotland

The structure of genetic and environmental risk factors for three measures of disordered eating

1999 ◽  
Vol 29 (4) ◽  
pp. 925-934 ◽  
Author(s):  
T. WADE ◽  
N. G. MARTIN ◽  
M. C. NEALE ◽  
M. TIGGEMANN ◽  
S. A. TRELOAR ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disordered Eating ◽  
Environmental Risk ◽  
Genetic Factors ◽  
Structured Interview ◽  
Environmental Risk Factors ◽  
Self Report ◽  
Shared Environment ◽  
Similar Degree ◽  
Psychiatric Interview

Background. The study explored the genetic and environmental risk factors for both the behaviours and attitudes characteristic of disordered eating.Methods. In three waves of data collection, information was collected from female twins regarding their eating and attitudes towards eating, weight and shape. The first assessment consisted of a self-report questionnaire (1988–9) with 1682 women. The second assessment consisted of a semi-structured psychiatric interview schedule (1992–3), completed by 1852 women, many of whom had completed Wave 1 assessment. The third assessment, with 325 women chosen from Waves 1 and 2 (1995–6), consisted of a semi-structured interview (the Eating Disorder Examination).Results. As only one twin pair was concordant for lifetime bulimia nervosa at Wave 3 assessment, ordinal measures of all assessments were used in a multivariate genetic analysis. Results indicated that additive genetic and non-shared environmental influences best explained variance in liability to disordered eating, with about 60% (95% CI 50–68) of the variance explained by genetic factors. Comparison with a model allowing for the effects of shared environment indicated genetic factors accounted for a similar degree of variance (59%, 95% CI 36–68).Conclusion. Liability to the development of the behaviours and attitudes characteristic of eating disorders is best explained by both environmental and genetic factors, with covariation between the three measures best explained by a single latent phenotype of disordered eating which has a heritability of 60%.

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