Evidence map›Paper›PMID 38394117›Full record

ArticlePloS one2024

Effect of weight on depression using multiple genetic instruments.

Jutta Viinikainen, Petri Böckerman, Barton Willage, Marko Elovainio, Jaana T Kari, Terho Lehtimäki, Jaakko Pehkonen, Niina Pitkänen, Olli Raitakari

Open access · goldAbstract read
In one paragraph

Article in PloS one, 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
3.3field-weighted citation impact, top 9% 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, 6 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

9 authors at 6 institutions in 3 countries.

Jutta ViinikainenJyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.ORCID 0000-0002-4252-3147
Petri BöckermanJyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.
Barton WillageDepartment of Economics, University of Colorado-Denver, Denver, Colorado, United States of America.
Marko ElovainioDepartment of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
Jaana T KariJyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.ORCID 0000-0001-5205-7031
Terho LehtimäkiDepartment of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Jaakko PehkonenJyväskylä University School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland.
Niina PitkänenResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
Olli RaitakariResearch Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
University of Jyväskylä · FIUniversity of Turku · FIIZA - Institute of Labor Economics · DETampere University · FIUniversity of Denver · USUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A striking global health development over the past few decades has been the increasing prevalence of overweight and obesity. At the same time, depression has become increasingly common in almost all high-income countries. We investigated whether body weight, measured by body mass index (BMI), has a causal effect on depression symptoms in Finland. Using data drawn from the Cardiovascular Risk in Young Finns Study (N = 1,523, mean age 41.9, SD 5), we used linear regression to establish the relationship between BMI and depression symptoms measured by 21-item Beck's Depression Inventory. To identify causal relationships, we used the Mendelian randomization (MR) method with weighted sums of genetic markers (single nucleotide polymorphisms, SNPs) as instruments for BMI. We employ instruments (polygenic risk scores, PGSs) with varying number of SNPs that are associated with BMI to evaluate the sensitivity of our results to instrument strength. Based on linear regressions, higher BMI was associated with a higher prevalence of depression symptoms among females (b = 0.238, p = 0.000) and males (b = 0.117, p = 0.019). However, the MR results imply that the positive link applies only to females (b = 0.302, p = 0.007) but not to males (b = -0.070, p = 0.520). Poor instrument strength may explain why many previous studies that have utilized genetic instruments have been unable to identify a statistically significant link between BMI and depression-related traits. Although the number of genetic markers in the instrument had only a minor effect on the point estimates, the standard errors were much smaller when more powerful instruments were employed.

Indexed as

DepressionObesityAdultBody Mass IndexFemaleGenetic MarkersGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMiddle AgedOverweightPolymorphism, Single NucleotideGenetic Markers

Identifiers

PMID38394117
PMCPMC10889664
OpenAlexW4392125045

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.