Evidence map›Paper›PMID 37735503›Full record

SynthesisMolecular psychiatry2023

Loneliness and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies.

David A Sbarra, Ferris A Ramadan, Karmel W Choi, Jorien L Treur, Daniel F Levey, Robyn E Wootton, Murray B Stein, Joel Gelernter, Yann C Klimentidis

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Molecular psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
16.0field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 58 citations in OpenAlex.

  1. Article
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  6. Social Networks and Loneliness in the Blackfeet American Indian Community.International journal of behavioral medicine · 2026
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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

9 authors at 6 institutions in 4 countries.

David A SbarraDepartment of Psychology, University of Arizona, Tucson, AZ, USA. sbarra@email.arizona.edu.ORCID 0000-0001-6727-6552
Ferris A RamadanDepartment of Epidemiology and Biostatistics, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.
Karmel W ChoiDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA.
Jorien L TreurDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
Daniel F LeveyVA Connecticut Healthcare System, Psychiatry Service, West Haven, CT, USA.ORCID 0000-0001-8431-9569
Robyn E WoottonSchool of Psychological Science, University of Bristol, Bristol, UK.ORCID 0000-0003-3961-3202
Murray B SteinVA San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA.ORCID 0000-0001-9564-2871
Joel GelernterVA Connecticut Healthcare System, Psychiatry Service, West Haven, CT, USA.ORCID 0000-0002-4067-1859
Yann C KlimentidisDepartment of Epidemiology and Biostatistics, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.
University of Arizona · USYale University · USAmsterdam University Medical Centers · NLHarvard University · USUniversity of Bristol · GBUniversity of California San Diego · US

Funding

Genetically Informed Studies of Social Connectedness and HealthR01AG078361 · NIA · UNIVERSITY OF ARIZONA · PI DAVID A SBARRA · 2022 to 2026
$5.6M
Integrating Health Records, Genomic, and Social Data to Stratify Adolescent Depression RiskK08MH127413 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI CHOI, KARMEL · 2021 to 2025
$987k
NIA NIH HHS R01 AG078361NIMH NIH HHS K08 MH127413U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) K08MH127413U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01AG078361-01
6 · The paper itself

Abstract

Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world's population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.

Indexed as

Genome-Wide Association StudyMajor Depressive DisorderDepressionHumansLonelinessMendelian Randomization AnalysisProspective Studies

Identifiers

PMID37735503
PMCPMC11406447
OpenAlexW4386932378

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.