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Published on: July 24, 2013
Visual impairment and frailty: insights from genetic correlation and Mendelian randomization
Zhen Deng1,2, Yangziding Bu2, Tianshu Hou1
1Chengdu Integrated Traditional Chinese Medicine and Western Medicine Hospital, Chengdu, China.
Introduction:
Visual impairment (VI) is associated with frailty in observational studies, but whether this relationship is causal remains uncertain. This study aimed to investigate the genetic correlation and causal associations between genetically predicted VI and frailty using Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC).
Material And Methods:
Genome-wide association studies provided summary data for VI subtypes (glaucoma, cataracts, diabetic retinopathy, age-related macular degeneration, hypermetropia, myopia) and frailty measures (frailty index (FI) and fried frailty score (FFS)). LDSC was used to estimate genetic correlations, and MR was conducted using inverse-variance weighted (IVW) as the primary method, supplemented by MR-Egger and weighted median. Sensitivity analyses, including radial MR, Cochran's Q test, MR-Egger intercept, and MR-PRESSO, were used to assess pleiotropy and heterogeneity.
Results:
Significant genetic correlations were found between VI, cataracts, age-related macular degeneration, and frailty. Suggestive correlations were identified between myopia and FI. MR analysis showed increased FI and FFS risks with other cataracts (FI: p = 0.0324; FFS: p = 0.027) and diabetic retinopathy (FI: p < 0.001; FFS: p = 0.0119). Visual disturbances were associated with increased FI risk (p = 0.0101), while age-related macular degeneration elevated FFS risk (p = 0.0251). Reverse analysis revealed that frailty also increased susceptibility to VI. No causal relationships were found for other eye diseases, and analyses showed no evidence of pleiotropy or heterogeneity.
Conclusions:
This study highlights significant genetic associations and bidirectional causal relationships between VI and frailty. Future research should include multiethnic populations and larger datasets to further explore these mechanisms.
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