Evidence map›Paper›PMID 41612910›Full record

ArticleBrain and behavior2026

Decoding Causal Associations Between Neuropsychiatric Disorders and Rotator Cuff Tendinopathy: A Two-Sample Mendelian Randomization Study.

Weizhe Zhang, Ming Chen, Haozhang Huang, Puyi Sheng

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Article in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Weizhe ZhangDepartment of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.
Ming ChenGuangdong Mental Health Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou City, Guangdong Province, China.
Haozhang HuangDepartment of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou City, Guangdong Province, China.
Puyi ShengDepartment of Joint Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou City, Guangdong Province, China.

Funding

China Postdoctoral Science Foundation 2022M723653
6 · The paper itself

Abstract

backgroundRotator cuff tendinopathy (RCT) is a major contributor to over 30 million surgeries which are conducted to treat shoulder overuse injuries worldwide annually. Accumulating evidence indicates that neuropsychiatric disorders (ND) share pathogenic pathways with tendinopathy. However, unclarified causal relationships between these two disease spectra undermine the individualized design of treatment strategies benefiting patients with ND while minimizing the RCT risk. We aimed to unveil whether ND were genetically associated with increased RCT occurrence by conducting a two-sample Mendelian randomization (MR) algorithm.

methodsGenome-wide association studies (GWAS) data of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), and RCT patients of European ancestry were retrieved for bidirectional two-sample Mendelian randomization (MR) analyses to establish causal relationships among these eight main types of ND and RCT. To detect false positive findings, MR-Egger, weighted median and causal analysis using summary effect estimates (CAUSE) were employed as sensitivity tests. Body shape, lifestyle, and socioeconomic parameters were adjusted as mediators in multivariable MR to validate the robustness of the results.

resultsUnivariable MR revealed that genetic predisposition to ADHD (odds ratio [OR] 1.14, 95% confidence interval [CI] 1.05-1.24, p = 0.001) and PTSD (OR 2.23, 95% CI 1.75-2.84, p < 0.001) significantly increased the RCT risk. MDD showed a similar association (OR 1.21, 95% CI 1.06-1.38, p = 0.004), which was attenuated after confounder adjustment (p = 0.78). Multivariable MR confirmed ADHD (OR 1.09, 95% CI 1.01-1.18, p = 0.02) and PTSD (OR 2.00, 95% CI 1.41-2.82, p < 0.001) as robust causal factors for RCT after adjusting for anthropometric, lifestyle, physical activity, and socioeconomic confounders.

conclusionOur study sheds new light on the need for early screening, targeted overuse injury prevention, and specialized clinical interventions to alleviate the RCT burden in ADHD and PTSD populations.

Indexed as

Mental DisordersTendinopathyAttention Deficit Disorder with HyperactivityGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideRotator Cuff

Identifiers

PMID41612910
PMCPMC12856381

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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 Socratic graph.