Sarcopenia-related Traits, Body Mass Index and Ovarian Cancer Risk
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Sarcopenia-related Traits, Body Mass Index and Ovarian Cancer Risk

Announcing a new article publication for BIO Integration journal.  This study was aimed at exploring the causal relationships of four sarcopenia-related traits (appendicular lean mass, usual walking pace, right hand grip strength, and levels of moderate to vigorous physical activity) with body mass index (BMI) and ovarian cancer risk, by using univariable and multivariable Mendelian randomization (MR) methods.

Univariable and multivariable MR was performed to estimate causal relationships among sarcopenia-related traits, BMI, and ovarian cancer risk, in aggregated genome-wide association study (GWAS) data from the UK Biobank. Genetic variants associated with each variable (P < 5 × 10−8) were identified as instrumental variables. Three methods—inverse variance weighted (IVW) analysis, weighted median analysis, and MR-Egger regression—were used.

Univariable MR analyses revealed positive causal effects of high appendicular lean mass (P = 0.02) and high BMI (P = 0.001) on ovarian cancer occurrence. In contrast, a genetically predicted faster usual walking pace was associated with lower risk of ovarian cancer (P = 0.03). No evidence was found supporting roles of right hand grip strength and levels of moderate to vigorous physical activity in ovarian cancer development (P = 0.56 and P = 0.22, respectively). In multivariable MR analyses, the association between a genetically predicted faster usual walking pace and lower ovarian cancer risk remained significant (P = 0.047).

This study highlights a role of slower usual walking pace in the development of ovarian cancer. Further studies are required to validate our findings and understand the underlying mechanisms.

https://www.scienceopen.com/hosted-document?doi=10.15212/bioi-2023-0020

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ISSN 2712-0074

eISSN 2712-0082

Manli Wu, Jiahao Chen and Xiaohong Kuang et al. Sarcopenia-related Traits, Body Mass Index and Ovarian Cancer Risk: Investigation of Causal Relationships Through Multivariable Mendelian Randomization Analyses. BIOI. 2024. Vol. 5(1). DOI: 10.15212/bioi-2023-0020