Digging into the intrinsic capacity concept: Can it be applied to Alzheimer's disease?

Historically, aging research has largely centered on disease pathology rather than promoting healthy aging. The World Health Organization's (WHO) policy framework (2015-2030) underscores the significance of fostering the contributions of older individuals to their families, communities, and economies. The WHO has introduced the concept of intrinsic capacity (IC) as a key metric for healthy aging, encompassing five primary domains: locomotion, vitality, sensory, cognitive, and psychological. Past AD research, constrained by methodological limitations, has focused on single outcome measures, sidelining the complexity of the disease. Our current scientific milieu, however, is primed to adopt the IC concept. This is due to three critical considerations: (I) the decline in IC is linked to neurocognitive disorders, including AD, (II) cognition, a key component of IC, is deeply affected in AD, and (III) the cognitive decline associated with AD involves multiple factors and pathophysiological pathways. Our study explores the application of the IC concept to AD patients, offering a comprehensive model that could revolutionize the disease's diagnosis and prognosis. There is a dearth of information on the biological characteristics of IC, which are a result of complex interactions within biological systems. Employing a systems biology approach, integrating omics technologies, could aid in unraveling these interactions and understanding IC from a holistic viewpoint. This comprehensive analysis of IC could be leveraged in clinical settings, equipping healthcare providers to assess AD patients' health status more effectively and devise personalized therapeutic interventions in accordance with the precision medicine paradigm. We aimed to determine whether the IC concept could be extended from older individuals to patients with AD, thereby presenting a model that could significantly enhance the diagnosis and prognosis of this disease.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence.

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-ß and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

Systems Biology Methods for Alzheimer's Disease Research Toward Molecular Signatures, Subtypes, and Stages and Precision Medicine: Application in Cohort Studies and Trials.

Alzheimer's disease (AD) is a complex multifactorial disease, involving a combination of genomic, interactome, and environmental factors, with essential participation of (a) intrinsic genomic susceptibility and (b) a constant dynamic interplay between impaired pathways and central homeostatic networks of nerve cells. The proper investigation of the complexity of AD requires new holistic systems-level approaches, at both the experimental and computational level. Systems biology methods offer the potential to unveil new fundamental insights, basic mechanisms, and networks and their interplay. These may lead to the characterization of mechanism-based molecular signatures, and AD hallmarks at the earliest molecular and cellular levels (and beyond), for characterization of AD subtypes and stages, toward targeted interventions according to the evolving precision medicine paradigm. In this work, an update on advanced systems biology methods and strategies for holistic studies of multifactorial diseases-particularly AD-is presented. This includes next-generation genomics, neuroimaging and multi-omics methods, experimental and computational approaches, relevant disease models, and latest genome editing and single-cell technologies. Their progressive incorporation into basic research, cohort studies, and trials is beginning to provide novel insights into AD essential mechanisms, molecular signatures, and markers toward mechanism-based classification and staging, and tailored interventions. Selected methods which can be applied in cohort studies and trials, with the European Prevention of Alzheimer's Dementia (EPAD) project as a reference example, are presented and discussed.

Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic.

The last decade has seen a substantial increase in research focused on the identification of blood-based biomarkers that have utility in Alzheimer's disease (AD). Blood-based biomarkers have significant advantages of being time- and cost-efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood-based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public-private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.