Background: Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses.
Methods: A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF).
Results: The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF.
Conclusions: The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.
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http://dx.doi.org/10.1186/s12877-024-05039-5 | DOI Listing |
Planta
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School of Life Science and Technology, Wuhan Polytechnic University, Wuhan, 430023, China.
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Zhejiang Laboratory, Hangzhou 311100, Zhejiang, China.
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Department of Microbiology, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Kaiserslautern, Germany.
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Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Yahaba, Japan.
The polygenic score (PGS) holds promise for motivating preventive behavioral changes. However, no clinically validated standardization methodology currently exists. Here, we demonstrate the efficacy of a "reference-based" approach for standardization.
View Article and Find Full Text PDFEar Nose Throat J
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Department of Otolaryngology-Head & Neck Surgery (ORL-H&N), Prince Sultan Military Medical City (PSMMC), Riyadh, Saudi Arabia.
Etiological factors affecting outcomes of cochlear implants (Cis) are known; however, a direct comparison of efficacy based on lesion location is needed. We aimed to systematically examine the current evidence to compare the effectiveness of CIs in patients with presynaptic versus postsynaptic neuropathy. A comprehensive literature search was conducted across multiple databases, including MEDLINE (via PubMed), Embase, CENTRAL, Web of Science, Scopus, CINAHL, and PsycINFO.
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