Evidence map›Paper›PMID 42566603›Full record

ArticleMedicine2026

Causal association between cataract and psychiatric disorders: A bidirectional 2-sample Mendelian randomization study.

Xiaoling Su, Guoqiang Tian

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiaoling SuDepartment of Psychiatry, Shengzhou Traditional Chinese Medicine Hospital, Shengzhou, Zhejiang, China.
Guoqiang TianDepartment of Psychiatry, Seventh People's Hospital of Shaoxing, Shaoxing, Zhejiang, China.ORCID 0009-0007-4406-3272

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to investigate the genetic causality between cataract (senile and other types) and psychiatric disorders using Mendelian randomization (MR). We performed a bidirectional 2-sample MR analysis using genome-wide association studies summary data. Primary analysis employed inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses included Cochran Q, MR-pleiotropy residual sum and outlier, MR-Egger intercept, and leave-one-out tests to assess heterogeneity and pleiotropy. Forward MR analysis revealed a suggestive causal effect of other cataract on anxiety (inverse-variance weighted odds ratio [OR] = 0.99, 95% confidence interval: 0.98-1.00, P = .043), though unsupported by other methods. MR-Egger and weighted median suggested potential associations between other cataract and bipolar disorder (P < .05). No significant links were found between senile cataract and psychiatric disorders. Reverse MR analysis showed no consistent causal effects, except for anxiety disorder on other cataract (MR-Egger OR = 8.04, P = .040; weighted median OR = 2.99, P = .047). Sensitivity analyses confirmed robustness despite heterogeneity. This study provides evidence of a potential causal relationship between other cataract and anxiety, though findings were method-dependent. No significant associations were observed for senile cataract or most psychiatric disorders.

Indexed as

CataractMendelian Randomization AnalysisMental DisordersAnxiety DisordersBipolar DisorderCausalityGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single Nucleotidecataractcausal associationgenetic analysesMendelian randomizationpsychiatric disorders

Identifiers

PMID42566603
PMCPMC13456826

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.