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Background Parkinson’s disease (PD) is a neurodegenerative disorder, primarily characterized by motor impairments. Vitamin D has several regulatory functions in nerve cell survival and gene expression via its receptors. Although research has shown that vitamin D deficiency is prevalent among PD patients, the causal link to PD risk remains unclear. This study aims to investigate the causal relationship between vitamin D and PD using a bidirectional two-sample Mendelian randomization (MR) analysis method. Methods This study applied a bidirectional two-sample MR analysis to explore the causal link between vitamin D and PD. We selected statistically significant single nucleotide polymorphisms (SNPs) related to 25-hydroxyvitamin D (25(OH)D) as instrumental variables (IVs), ensuring no association with known confounders. The analysis used GWAS data from over 1.2 million Europeans across four major published datasets, elucidating the genetic correlation between vitamin D levels and PD. Results We identified 148 instrumental SNPs associated with 25(OH)D. After adjustment for confounding-related SNPs, 131 SNPs remained in the analysis. Data from three PD cohorts revealed no significant correlation between 25(OH)D levels and PD risk using the IVW method (Pcohort1 = 0.365, Pcohort2 = 0.525, Pcohort3 = 0.117). The reverse MR analysis indicated insufficient evidence of PD causing decreased vitamin D levels (P = 0.776). Conclusion This is the first study to use bidirectional MR across three PD cohorts to investigate the causal relationship between vitamin D and PD. The results indicate that vitamin D levels are not significantly causally related to PD risk at the genetic level. Therefore, future studies should exercise caution when investigating the relationship between vitamin D levels and PD risk. While no direct causal link exists between vitamin D levels and PD, this does not preclude the potential of vitamin D levels as a biomarker for PD diagnosis. Furthermore, larger-scale longitudinal studies are necessary to evaluate the diagnostic and predictive value of vitamin D levels in PD.
Background Parkinson’s disease (PD) is a neurodegenerative disorder, primarily characterized by motor impairments. Vitamin D has several regulatory functions in nerve cell survival and gene expression via its receptors. Although research has shown that vitamin D deficiency is prevalent among PD patients, the causal link to PD risk remains unclear. This study aims to investigate the causal relationship between vitamin D and PD using a bidirectional two-sample Mendelian randomization (MR) analysis method. Methods This study applied a bidirectional two-sample MR analysis to explore the causal link between vitamin D and PD. We selected statistically significant single nucleotide polymorphisms (SNPs) related to 25-hydroxyvitamin D (25(OH)D) as instrumental variables (IVs), ensuring no association with known confounders. The analysis used GWAS data from over 1.2 million Europeans across four major published datasets, elucidating the genetic correlation between vitamin D levels and PD. Results We identified 148 instrumental SNPs associated with 25(OH)D. After adjustment for confounding-related SNPs, 131 SNPs remained in the analysis. Data from three PD cohorts revealed no significant correlation between 25(OH)D levels and PD risk using the IVW method (Pcohort1 = 0.365, Pcohort2 = 0.525, Pcohort3 = 0.117). The reverse MR analysis indicated insufficient evidence of PD causing decreased vitamin D levels (P = 0.776). Conclusion This is the first study to use bidirectional MR across three PD cohorts to investigate the causal relationship between vitamin D and PD. The results indicate that vitamin D levels are not significantly causally related to PD risk at the genetic level. Therefore, future studies should exercise caution when investigating the relationship between vitamin D levels and PD risk. While no direct causal link exists between vitamin D levels and PD, this does not preclude the potential of vitamin D levels as a biomarker for PD diagnosis. Furthermore, larger-scale longitudinal studies are necessary to evaluate the diagnostic and predictive value of vitamin D levels in PD.
(1) Objective: To compare the effects of different exercise training for obese or overweight individuals’ executive function (EF) ; (2) Methods: Randomized controlled trials (RCTs) of exercise intervention in overweight or obese populations were included from PubMed, Web of Science, SPORTDiscus, MEDLINE, and CINAHL. The included articles in English should be published from January 2000 to February 2024. The Jadad scale with a total score of 7 was used to assess the quality of the literature. Using the random-effects model within the framework of frequency statistics in Stata 17.0 software for data synthesis; (3) Results: This NMA included 20 studies published between 2010 and 2023, encompassing a total of 1161 overweight or obese participants. The outcomes were inhibitory control, working memory(WM), cognitive flexibility(CF), and academic performance. Interventions were categorized into seven types: Control training(CT), Aerobic exercise(AE), resistance training(RT), Coordinated physical activity (CPA), Prolonged time of exercise(PTE), High-intensity interval training(HIIT), AE combines RT (mix mode, MIX). The surface under the cumulative ranking curve(SUCRA) results demonstrated the preferable effects of various interventions on EF improvement. Specifically, for CF accuracy, CPA (SUCRA = 99.6%) and PTE (SUCRA = 75.4%) were notable. For CF reaction time, CPA (SUCRA = 96.6%) and PTE (SUCRA = 78.2%) ranked highly. In terms of inhibitory accuracy, there were HIIT (SUCRA = 62.8%), RT (SUCRA = 57.7%), and PTE (SUCRA = 56.5%). As for inhibitory reaction time, there were CPA (SUCRA = 97.3%) and RT (SUCRA = 76.8%). Regarding WM accuracy, RT (SUCRA = 93.0%) ranked highly. For WM reaction time, CT (SUCRA = 62.1%) and AE (SUCRA = 60.1%) ranked highly. In terms of AP, AE (SUCRA = 92.9%) ranked highly. Through subgroup analysis based on age and intervention duration, we found AE exhibited a significant effect on interventions for the 0–17 age group (SMD = 0.60,95%CI = 0.19 ~ 1.01, P = 0.005), while in the intervention duration subgroup analysis, interventions lasting 8–16 weeks showed significant improvement in EFs (SMD = 0.53,95%CI = 0.00 ~ 1.05, P = 0.048). And there was a significant difference between one-time CPA intervention and CT (SMD = 1.12,95%CI = 0.45 ~ 1.80, P = 0.001). Additionally, PTE showed significant effects for children and adolescents aged 0–17 (SMD = 1.47,95%CI = 0.98 ~ 1.96, P < 0.001); (4) Conclusions: This research focuses on the impact of exercise on multiple outcome indicators of EFs in different obese or overweight populations. Due to the demand of children and adolescents for AP, AE is recommended. Considering the physiological characteristics of the elderly, PTE is most suitable for them and significantly improves their EFs. Lastly, considering the benefits of CF and inhibitory control in improving both health-related decision-making and adaptation to complex environments, CPA and PTE are identified as suitable intervention strategies.
Background Inflammation and nutritional markers have recently gained recognition for their roles in the fabrication of cognitive control centers demyelinating illnesses. Inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), and systemic inflammatory response index (SIRI), along with nutritional markers like albumin (ALB), hemoglobin (HB), and body mass index (BMI), may predict disease occurrence. However, their potential in evaluating diseases such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) remains unexplored. Methods We retrospectively evaluated 249 NMOSD patients, 244 MS patients, and 249 healthy controls (HC), calculating MLR, NLR, PLR, SII, and SIRI, and measuring ALB, HB, and BMI levels. Logistic regression and ROC curves were used to develop and validate models for diagnosing and differentiating MS and NMOSD. Further, 35 MS patients, 38 NMOSD patients, and 85 matched HC were recruited for validation, and marker changes were monitored over six months. Results Comparing MS and NMOSD groups with HC, MLR, NLR, SII, and SIRI were significantly greater, while ALB levels were lower (P<0.05). NMOSD patients exhibited higher MLR, NLR, SII, and SIRI, and lower HB and ALB levels contrasted with MS patients (P<0.05). These markers correlated negatively with total T lymphocytes and positively with C-reactive protein, the Expanded Disability Status Scale (EDSS), and MRI T2 lesion count. Following remission, NLR, SII, and SIRI decreased, while ALB increased over six months (P<0.05). Diagnostic models based on these markers showed AUCs of 0.840 (95% CI:0.806–0.875) for MS and 0.905 (95% CI:0.877–0.933) for NMOSD. Differential diagnosis between MS and NMOSD showed an AUC of 0.806 (95% CI: 0.750–0.863). Conclusion Inflammatory and nutritional markers are promising for assessing disease activity in MS and NMOSD. Diagnostic models based on these markers enhance the accuracy and clinical value of differentiating between the two conditions.
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