The aging global population has led to dementia emerging as a significant public health concern. According to the World Health Organization (WHO), the global prevalence of dementia was approximately 47 million in 2015, and it is projected to exceed 75 million by 2030. Dementia significantly impacts both the physical and mental well-being of individuals, diminishes their quality of life, and imposes substantial pressure and financial strain on society and families. It is noteworthy that Alzheimer’s disease (AD) stands as the most prevalent neurodegenerative form of dementia.
Numerous empirical studies have investigated the potential contributions of immune inflammation, mitochondrial dysfunction, genetic heredity, gut microbiota abnormalities, and cerebrovascular dysfunction to the pathogenesis of AD. However, the exact etiology of AD remains unclear. Current pharmacological treatments for AD focus on symptom management without altering the disease progression. Consequently, non-pharmacological interventions are being investigated to ameliorate symptoms and associated dysfunctions in AD.
Dietary interventions have emerged as a key area of research aimed at potentially slowing the onset and progression of AD. Specifically, the Mediterranean diet has been associated with a reduced risk of AD development, while a pro-inflammatory diet has been linked to an increased risk of AD. It is important to note that observational studies cannot establish direct causation, and a consensus on the influence of dietary habits on AD is lacking. Large-scale population-based studies are needed to provide genetic evidence supporting the potential impact of dietary interventions in reducing AD risk. Recognizing the potential benefits of dietary interventions for AD patients is clinically significant and requires further investigation in this area.
Mendelian randomization (MR) analysis is a statistical technique that employs genetic variants as instrumental variables to explore causal relationships between exposure factors and outcomes. This method effectively utilizes results from genome-wide association studies (GWAS) to investigate the causal link between exposures and outcomes using genetic variants as instrumental variables (IVs).