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

2019· preprint· en· W2949586828 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWellcome Open Research · 2019
Typepreprint
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of Windsor
FundersBiotechnology and Biological Sciences Research CouncilChief Scientist Office, Scottish Government Health and Social Care DirectorateUniversity of EdinburghDr Mortimer and Theresa Sackler FoundationScottish GovernmentScottish Funding CouncilWellcome TrustMedical Research CouncilDirectorate for Biological SciencesCentre for Cognitive Ageing and Cognitive EpidemiologyWellcome
KeywordsNeuroticismDepression (economics)PsychologyEnvironmental stressClinical psychologyPersonalityEvolutionary biologyBiologySocial psychologyEconomics

Abstract

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<ns4:p> <ns4:bold>Background:</ns4:bold> 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. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> 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. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r <ns4:sup>2</ns4:sup> =1.1%, p=2.5 x 10 <ns4:sup>-25</ns4:sup> ) and neuroticism (β =0.13, r <ns4:sup>2</ns4:sup> =1.9%, p=1.04 x 10 <ns4:sup>-37</ns4:sup> ) 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 <ns4:sup>-4</ns4:sup> ). 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, r <ns4:sup>2</ns4:sup> =0.3%, p=3 x 10 <ns4:sup>-5</ns4:sup> ), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r <ns4:sub>G</ns4:sub> =0.33, S.E.=0.08 ) and neuroticism (r <ns4:sub>G</ns4:sub> =0.15, S.E.=0.07). </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> 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. </ns4:p>

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.349
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it