UNASSIGNED: At first, we used the dataset of the genome-wide association studies studying vitamin D and cognitive performance to conduct Mendelian randomization analysis. Subsequently, we employed linear regression and smooth curve fitting methods to assess the relationship using the National Health and Nutrition Examination Survey data. Finally, we investigated other predictive features of cognitive performance utilizing a machine learning model.
UNASSIGNED: We found that a 1-unit increase in vitamin D is associated with a 6.51% reduction (P < .001) in the risk of cognitive decline. The correlation between vitamin D and cognitive performance is nonlinear, with the inflection point at 79.9 nmol/L (left: β = 0.043, P < .001; right: β = -0.007, P = .420). In machine learning, the top 5 predictors are vitamin D, weight, height, age, and body mass index.
UNASSIGNED: There is a causal relationship between vitamin D and cognitive performance. 79.9 nmol/L could be the optimal dose for vitamin D supplementation in the elderly. Further consideration of other factors in vitamin D interventions is necessary.
■首先,我们使用研究维生素D和认知能力的全基因组关联研究的数据集进行孟德尔随机化分析.随后,我们采用线性回归和平滑曲线拟合方法,利用国家健康和营养调查数据评估两者的关系.最后,我们利用机器学习模型研究了认知表现的其他预测特征。
■我们发现,维生素D增加1个单位与认知能力下降的风险降低6.51%(P<.001)有关。维生素D与认知能力之间的相关性是非线性的,拐点为79.9nmol/L(左:β=0.043,P<.001;右:β=-0.007,P=.420)。在机器学习中,前5个预测因子是维生素D,体重,高度,年龄,和体重指数。
■维生素D与认知能力之间存在因果关系。79.9nmol/L是老年人补充维生素D的最佳剂量。需要进一步考虑维生素D干预中的其他因素。