Ischemic stroke and sarcopenia have an asymmetric bidirectional relationship based on a two-sample Mendelian randomization study

 Sarcopenia has been discussed as a stroke problem for a long time, I'd have you all fired for not solving it!

The whole goal of stroke research is to solve stroke, not just describe the problems from stroke. You'll want stroke solved before you become

the 1 in 4 per WHO that has a stroke.

sarcopenia (16 posts to March 2016)

Ischemic stroke and sarcopenia have an asymmetric bidirectional relationship based on a two-sample Mendelian randomization study

Fan-Qiao Meng¹Yu Zhang²Xiao-Xin Bai¹Fan-Li Kong^3*Feng-E Li^4,5*

• ¹Department of Postgraduate, School of Clinical Medicine, Beihua University, Jilin, China
• ²Department of Pediatrics, The First Hospital of Jilin University, Changchun, China
• ³Department of Pathophysiology, School of Basic Medicine, Beihua University, Jilin, China
• ⁴Department of Neurology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
• ⁵Department of Neurology, The Affiliated Hospital of Beihua University, Jilin, China

Background: We investigated the potential relationship between age-related conditions, particularly sarcopenia and ischemic stroke (IS), through a two-sample Mendelian randomization (MR) study.

Methods: We conducted a two-sample bidirectional MR study to investigate the relationship between sarcopenia and stroke. Genetic instruments for sarcopenia were derived from the UK Biobank, while data on IS and its subtypes were obtained from the MEGASTROKE consortium. Inverse variance weighting (IVW) served as the primary analytical method. Additionally, heterogeneity and pleiotropy were assessed to ensure the robustness of the findings.

Results: The analysis indicates a negative correlation between appendicular lean mass (ALM) and small vessel stroke (SVS; OR = 0.790, 95% CI: 0.703–0.888, p < 0.001), a positive correlation with cardioembolic stroke (CES; OR = 1.165, 95% CI: 1.058–1.284, p = 0.002), and no causal relationship with any ischemic stroke (AIS) or large artery stroke (LAS). Additionally, SVS is negatively associated with right-hand grip strength (OR = 0.639, 95% CI: 0.437–0.934, p = 0.021), while AIS, LAS, and CES do not exhibit a causal relationship with grip strength. Furthermore, no causal relationship was identified between left-hand grip strength, usual walking pace, and IS or its subtypes. MR analysis reveals only a negative association between CES and usual walking pace (OR = 0.989, 95% CI: 0.980–0.998, p = 0.013), with no associations found between other IS subtypes and sarcopenia-related traits.

Conclusion: This study demonstrates that a reduction in ALM and right-hand grip strength is associated with SVS, whereas decreased ALM may serve as a protective factor against CES. Conversely, our analysis suggests that CES can impact walking speed. Overall, these findings provide valuable insights into the prevention and treatment of these conditions.(But you did nothing to address those needs! Stroke research should solve stroke problems; NOT JUST DESCRIBE THEM!)

1 Introduction

Stroke is the second leading cause of death and disability globally (1). In China, the incidence of stroke is rising each year, making it the leading cause of mortality (2, 3). According to a 2019 study, common risk factors for stroke include hypertension, high body mass index (BMI), elevated fasting glucose, air pollution, and smoking (4). However, given the increasing incidence of stroke, it is crucial to explore additional risk factors. Sarcopenia, which has been identified as influencing the incidence and outcomes of stroke, has primarily been studied through observational data (5–8). These observational studies are often subject to confounding factors, complicating the establishment of accurate causal relationships. While the impact of sarcopenia on stroke risk has been explored, most studies have focused on the overall risk of stroke without analyzing specific stroke subtypes. Additionally, several studies have reported a relatively high incidence of sarcopenia following a stroke (9–11), which can adversely affect patient recovery and quality of life. Despite this, the relationship between stroke subtypes and sarcopenia has been largely overlooked, with limited research addressing this area. To fill this gap, we employed the Mendelian randomization (MR) method to investigate the causal relationship between sarcopenia and the risk of various stroke subtypes, providing new insights for clinical prevention and intervention strategies.

Sarcopenia was first introduced in the late 1980s by Rosenberg. The term is derived from Greek, with “sarx” meaning flesh and “penia” meaning loss (12). As the global population ages, sarcopenia has emerged as a significant health concern, with an estimated 500 million people projected to be affected by 2050 (13). Sarcopenia is associated with an increased risk of falls, fractures, disability, weakness, and mortality (14). According to the European Working Group on Sarcopenia in Older People (EWGSOP), sarcopenia is defined by a decline in both muscle mass and function (15). In 2018, the EWGSOP2 updated the diagnostic criteria, proposing a stepwise approach. Initially, muscle strength is assessed, typically through grip strength measurement, with reduced grip strength suggesting possible sarcopenia. Next, appendicular lean mass (ALM) is evaluated using dual-energy X-ray absorptiometry, bioelectrical impedance analysis, computed tomography, or magnetic resonance imaging, with a diagnosis confirmed by decreased muscle mass and quantity. Finally, low physical capacity is used to assess the severity of sarcopenia, with commonly used indicators including gait speed and a timed 400-meter walk; reduced performance on these tests indicates severe sarcopenia (16). Consequently, we selected three variables to evaluate the onset and progression of sarcopenia: ALM, grip strength, and walking pace.

MR is a method used to infer causal relationships between an exposure and an outcome, grounded in Mendel’s Second Law. This approach reduces confounding bias and addresses the limitations inherent in traditional observational studies. By selecting single nucleotide polymorphisms (SNPs) associated with the exposure as instrumental variables (IVs), genetic variation is utilized to derive robust causal inferences between exposure factors and outcomes (17). In this study, we employed a two-sample MR analysis to evaluate the causal relationship between sarcopenia and IS.

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