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INTRODUCTION: Multi-domain intervention for Alzheimer’s disease (AD) risk reduction is an emerging therapeutic paradigm. METHODS: Patients were prescribed individually-tailored interventions (education/pharmacologic/non-pharmacologic) and rated on compliance. Normal cognition/subjective cognitive decline/preclinical-AD were classified as Prevention. Mild cognitive impairment due to AD/mild-AD were classified as Early Treatment. Change from baseline to 18-months on the modified-Alzheimer’s Prevention Cognitive Composite (primary outcome) was compared against matched historical control cohorts. Cognitive aging composite (CogAging), AD/cardiovascular risk-scales, and serum biomarkers were secondary outcomes. RESULTS: 174 were assigned interventions (age 25–86). Higher-compliance Prevention improved more than both historical cohorts (P=.0012,P

ADHD and the specific learning disorders of dyslexia and dyscalculia form a class of neurodevelopmental disorders which are often undiagnosed in childhood, especially for adults born before these disorders were recognized. Recent research has revealed that the symptoms of these disorders can persist across the lifespan and cause substantial disabilities in work, school, and personal life. Moreover, these disorders may influence how neurodegenerative disease symptoms and pathology begin and spread. Despite the proliferation of diagnostic instruments for assessing ADHD and learning disorder during childhood, however, availability of validated modalities for the adult population is significantly limited. This is a critical research gap given the considerable adult disease burden (up to 6% of the population), the differences between adult and pediatric presentation, and the fact that the most promising treatments for neurodegenerative diseases will be initiated in minimally symptomatic adults. In this review, we describe the available self-report scales, neuropsychological tests, and structural imaging and genetic biomarkers that may allow accurate identification of adults with ADHD, dyslexia, and dyscalculia. Discussion of these instruments may provide clinicians with a set of tools to reduce cognitive disability in educational, occupational, and medical populations.

Alzheimer's disease (AD) is a major source of morbidity and mortality, with the disease burden expected to rise as the population ages. No disease-modifying agent is currently available, but recent research suggests that nutritional and lifestyle modifications can delay or prevent the onset of AD. However, preventive nutritional interventions are not universally applicable and depend on the clinical profile of the individual patient. This article reviews existing nutritional modalities for AD prevention that act through improvement of insulin resistance, correction of dyslipidemia, and reduction of oxidative stress, and discusses how they may be modified on the basis of individual biomarkers, genetics, and behavior. In addition, we report preliminary results of clinical application of these personalized interventions at the first AD prevention clinic in the United States. The use of these personalized interventions represents an important application of precision medicine techniques for the prevention of AD that can be adopted by clinicians across disciplines.

Alzheimer's disease (AD) is a neurodegenerative dementia that affects nearly 50 million people worldwide and is a major source of morbidity, mortality, and healthcare expenditure. While there have been many attempts to develop disease-modifying therapies for late-onset AD, none have so far shown efficacy in humans. However, the long latency between the initial neuronal changes and onset of symptoms, the ability to identify patients at risk based on family history and genetic markers, and the emergence of AD biomarkers for preclinical disease suggests that early risk-reducing interventions may be able to decrease the incidence of, delay or prevent AD. In this review, we discuss six mechanisms-dysregulation of glucose metabolism, inflammation, oxidative stress, trophic factor release, amyloid burden, and calcium toxicity-involved in AD pathogenesis that offer promising targets for risk-reducing interventions. In addition, we offer a blueprint for a multi-modality AD risk reduction program that can be clinically implemented with the current state of knowledge. Focused risk reduction aimed at particular pathological factors may transform AD to a preventable disorder in select cases.

Like virtually all age-related chronic diseases, late-onset Alzheimer's disease (AD) develops over an extended preclinical period and is associated with modifiable lifestyle and environmental factors. We hypothesize that multimodal interventions that address many risk factors simultaneously and are individually tailored to patients may help reduce AD risk. We describe a novel clinical methodology used to evaluate and treat patients at two Alzheimer's Prevention Clinics. The framework applies evidence-based principles of clinical precision medicine to tailor individualized recommendations, follow patients longitudinally to continually refine the interventions, and evaluate N-of-1 effectiveness (trial registered at ClinicalTrials.gov NCT03687710). Prior preliminary results suggest that the clinical practice of AD risk reduction is feasible, with measurable improvements in cognition and biomarkers of AD risk. We propose using these early findings as a foundation to evaluate the comparative effectiveness of personalized risk management within an international network of clinician researchers in a cohort study possibly leading to a randomized controlled trial.

Background: As adult brain structure is primarily established in early life, genetic and environmental exposures in infancy and childhood influence the risk for Alzheimer disease (AD). In this systematic review, we identified several early life risk factors and discussed the evidence and underlying mechanism for each. Summary: Early risk factors for AD may alter brain anatomy, causing vulnerability to AD-related dementia later in life. In the perinatal period, both genes and learning disabilities have been associated with the development of distinct AD phenotypes. During early childhood, education and intellect, as well as body growth, may predispose to AD through alterations in cognitive and brain reserve, though the specific mediators of neural injury are disputed. Childhood socioeconomic status (SES) may predispose to AD by influencing adult SES and cognition. Association of these risk factors with underlying AD pathology (rather than just clinical diagnosis) has not been sufficiently examined. Key Messages: Factors that impede or alter brain growth during early life could render certain brain regions or networks selectively vulnerable to the onset, accumulation or spread of AD-related pathology during later life. Careful life-course epidemiology could provide clues as to why the brain systematically degenerates during AD.

Background Neurodevelopmental learning and attentional disorders (NLAD) such as dyslexia, dyscalculia and attention deficit hyperactivity disorder (ADHD) affect at least 6% of the adult population or more. They are associated with atypical cognitive patterns in early and adult life. The cognitive patterns of affected individuals in late life have never been described. One main challenge is detecting individuals in clinical settings during which mild cognitive changes could be confounding the clinical presentation. This is a critical research gap because these conditions interact, across the life course, with an individual’s risk for dementia. Also, learning disabilities which present in childhood pose persistent cognitive differences in areas involving executive function, reading and math. Clinicians lack tools to detect undiagnosed neurodevelopmental in adults with memory disorders. The majority of patients presenting at memory clinics today come from a generation during which NLAD were not yet clinically recognized. In this study, we hypothesized that a self-report scale can detect NLAD in a memory clinic population. Methods We developed a self-report, retrospective childhood cognitive questionnaire including key attributes adapted from prior validated measures. 233 participants were included in the primary analysis. Results Confirmatory Factor Analysis resulted in a best-fit model with six labelled factors (Math, Language, Attention, Working Memory, Sequential Processing, and Executive Function) and 15 total question items. The model demonstrated unidimensionality, reliability, convergent validity, discriminant validity, and predictive validity. Using 1.5 standard deviations as the cut-off, subjects were categorized into: Normal (n = 169), Language (n = 10), Math (n = 12), Attention (n = 10) or Other/Mixed (n = 32). Conclusion A self-report measure can be a useful tool to elicit childhood cognitive susceptibilities in various domains that could represent NLAD among patients in a memory clinic setting, even in the presence of mild cognitive impairment.