This study investigates the multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) through a data-driven analysis of over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The analysis reveals that vascular dysregulation is an early pathological event in LOAD progression, followed by amyloid-β (Aβ) deposition, metabolic dysfunction, functional impairment, and grey matter atrophy. Cognitive decline is noticeable from the initial stages of LOAD, suggesting early memory deficits associated with primary disease factors. High abnormality levels are observed for specific proteins related to vascular system integrity. The study highlights the importance of vascular dysregulation in LOAD and suggests potential early biomarkers for preventive therapeutic interventions. The proposed multifactorial data-driven analysis (MFDDA) approach could be applied to other neurodegenerative disorders to improve understanding and develop effective therapeutic strategies.This study investigates the multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) through a data-driven analysis of over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The analysis reveals that vascular dysregulation is an early pathological event in LOAD progression, followed by amyloid-β (Aβ) deposition, metabolic dysfunction, functional impairment, and grey matter atrophy. Cognitive decline is noticeable from the initial stages of LOAD, suggesting early memory deficits associated with primary disease factors. High abnormality levels are observed for specific proteins related to vascular system integrity. The study highlights the importance of vascular dysregulation in LOAD and suggests potential early biomarkers for preventive therapeutic interventions. The proposed multifactorial data-driven analysis (MFDDA) approach could be applied to other neurodegenerative disorders to improve understanding and develop effective therapeutic strategies.