Comparative Analysis of Lipid Profiles in AD Patients and Healthy Controls

Thesis Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and functional impairment, with mounting evidence suggesting a significant link between lipid metabolism alterations and disease pathology. Despite extensive research into AD biomarkers, the differential lipid profiles between AD patients and healthy controls remain inadequately characterized, limiting the development of lipid-based diagnostic and therapeutic strategies. This study aims to conduct a comprehensive comparative analysis of plasma lipid profiles in AD patients and age-matched healthy controls, thereby elucidating lipid alterations associated with AD and assessing their potential as diagnostic indicators. The specific objectives include (1) quantifying and comparing the levels of major lipid classes—including triglycerides, cholesterol esters, phospholipids, and sphingolipids—in plasma samples; (2) identifying lipid biomarkers significantly associated with AD status; and (3) exploring correlations between lipid profile alterations and clinical severity as measured by standardized cognitive assessments. The underlying hypothesis posits that distinct lipid signature patterns are present in AD patients relative to controls, potentially reflecting underlying metabolic dysregulation linked to neurodegeneration. A cross-sectional analytical research design was employed. The study population comprised 150 diagnosed AD patients and 150 cognitively healthy controls, all aged between 60 and 85 years, recruited from neurology outpatient clinics and community health centers. Participants were selected via stratified random sampling to ensure demographic and clinical comparability across groups. Blood samples were collected following standardized procedures, with plasma separated and stored at -80°C pending analysis. Lipid profiling was performed using advanced lipidomics techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS), enabling precise quantification of individual lipid species. Additional biochemical parameters, such as apolipoprotein E genotype, were also determined to explore genetic influences on lipid variations. Validity and reliability of lipid measurements were ensured through calibration with known standards and replication of assays. Data analysis involved descriptive statistics to summarize lipid levels, and inferential statistics—including multivariate analysis of variance (MANOVA), logistic regression, and principal component analysis—to identify lipid patterns associated with AD. The analytical framework was grounded in the lipid dysregulation theory of neurodegeneration, positing that disturbed lipid homeostasis contributes to amyloid plaque formation, neuroinflammation, and neuronal death. Expected findings include significant differences in the concentrations of certain lipid species—particularly ceramides and sphingomyelins—between AD patients and controls, with AD patients exhibiting elevated levels indicative of associated neurotoxic pathways. Findings are anticipated to reveal lipid profile patterns correlating with disease severity, supporting the premise of lipid alterations as potential biomarkers for early detection and progression monitoring. These results will contribute to the expanding body of knowledge on lipid metabolism in AD, providing insights into pathophysiological mechanisms and facilitating the identification of lipid-related therapeutic targets. In conclusion, the study will demonstrate that specific lipid alterations are characteristic of AD, underscoring their diagnostic and prognostic relevance. It is recommended that future research focus on longitudinal assessments of lipid profiles to establish causal relationships and evaluate the efficacy of lipid-modulating interventions. Additionally, integrating lipidomic profiling into routine clinical practice could enhance early detection and personalized treatment strategies. This research thus advances understanding of lipid metabolism's role in AD and proposes a foundation for innovative biomarker development in neurodegenerative disease management.