Evidence map›Paper›PMID 38324978›Full record

ArticleSocial science & medicine (1982)2024

Genetic influences on depression and selection into adverse life experiences.

Tamkinat Rauf, Jeremy Freese

Open access · greenAbstract read
In one paragraph

Article in Social science & medicine (1982), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Tamkinat RaufDepartment of Sociology, University of Wisconsin-Madison, USA. Electronic address: trauf@wisc.edu.
Jeremy FreeseDepartment of Sociology, Stanford University, USA. Electronic address: jfreese@stanford.edu.
Stanford University · USUniversity of Wisconsin–Madison · US

Funding

Wave IV Data CollectionP01HD031921 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HARRIS, KATHLEEN MULLAN · 1994 to 2020
$86.1M
Wisconsin longitudinal study: Initial lifetime's impact on Alzheimer's disease and related disorders (WLS-ILIAD)R01AG060737 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sanjay Asthana, Michal Engelman · 2018 to 2026
$56.8M
National Longitudinal Study of Adolescent to Adult Health (Add Health): Wave VII Core ProjectU01AG071448 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBERT A HUMMER · 2021 to 2026
$40.2M
WISCONSIN LONGITUDINAL STUDY--SIBLING INTERVIEWS (1)R01AG009775 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI HERD, PAMELA · 1991 to 2012
$23.4M
National Longitudinal Study of Adolescent to Adult Health (Add Health): Wave VI Cognition and Early Risk Factors for Dementia ProjectU01AG071450 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI AIELLO, ALLISON E, HUMMER, ROBERT A · 2021 to 2025
$16.2M
Aging Together: Brothers and Sisters of the Wisconsin Longitudinal StudyR01AG033285 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI HERD, PAMELA, WARREN, JOHN ROBERT · 2009 to 2013
$11.8M
POPULATION, LIFE COURSE, AND AGINGT32AG000129 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1986 to 2026
$6.0M
Add Health: A Genotype and Phenotype Resource for the Global Scientific CommunityR01HD073342 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HARRIS, KATHLEEN MULLAN · 2012 to 2016
$3.6M
NIA NIH HHS R01 AG009775NIA NIH HHS R01 AG033285NIA NIH HHS R01 AG060737NIA NIH HHS T32 AG000129NIA NIH HHS U01 AG071448NIA NIH HHS U01 AG071450NICHD NIH HHS P01 HD031921NICHD NIH HHS R01 HD073342
6 · The paper itself

Abstract

Genome-wide association studies find that a large number of genetic variants jointly influence the risk of depression, which is summarized by polygenic indices (PGIs) of depressive symptoms and major depression. But PGIs by design remain agnostic about the causal mechanisms linking genes to depression. Meanwhile, the role of adverse life experiences in shaping depression risk is well-documented, including via gene-environment correlation. Building on theoretical work on dynamic and contingent genetic selection, we suggest that genetic influences may lead to differential selection into negative life experiences, forging gene-environment correlations that manifest in various permutations of depressive behaviors and environmental adversities. We also examine the extent to which apparent genetic influences may reflect spurious associations due to factors such as indirect genetic effects. Using data from two large surveys of middle-aged and older US adults, we investigate to what extent a PGI of depression predicts the risk of 27 different adversities. Further, to glean insights about the kinds of processes that might lead to gene-environment correlation, we augment these analyses with data from an original preregistered survey to measure cultural understandings of the behavioral dependence of various adversities. We find that the PGI predicts the risk of majority of adversities, net of class background and prior depression, and that the selection risk is greater for adversities typically perceived as being dependent on peoples' own behaviors. Taken together, our findings suggest that the PGI of depression largely picks up the risk of behaviorally-influenced adversities, but to a lesser degree also captures other environmental influences. The results invite further exploration into the behavioral and interactional processes that lie along the pathways intervening between genetic differences and wellbeing.

Indexed as

DepressionMajor Depressive DisorderAdultAgedGenome-Wide Association StudyHumansLife Change EventsMiddle AgedSurveys and Questionnaires

Identifiers

PMID38324978
PMCPMC12284870
OpenAlexW4391483028

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.