Development, Application, and Results from a Precision-medicine Platform that Personalizes Multi-modal Treatment Plans for Mild Alzheimer’s Disease and At-risk Individuals

摘要

Introduction: Alzheimer’s Disease (AD) is a progressive neurodegenerative condition inwhich individuals exhibit memory loss, dementia, and impaired metabolism. Nearly all previoussingle-treatment studies to treat AD have failed, likely because it is a complex disease with multipleunderlying drivers contributing to risk, onset, and progression. Here, we explored the efficacy of amulti-therapy approach based on the disease risk factor status specific to individuals with AD diagnosisor concern.Methods: Novel software from uMETHOD Health was designed to execute a precision-medicinebasedapproach to develop personalized treatment recommendations with the goal of slowing or reversingbiologic drivers of AD. AD-associated inputs encompassed genomic data, bio-specimenmeasurements, imaging data (such as MRIs or PET scans), medical histories, medications, allergies,co-morbidities, relevant lifestyle factors, and results of neuropsychological testing. Algorithmswere then employed to prioritize physiologic and lifestyle states with the highest probabilityof contributing to disease status, and these priorities were incorporated into a personalized careplan, which was delivered to physicians and supported by health coaches to increase adherence.The sample included 40 subjects with Subjective Cognitive Decline patients (SCD), and Mild CognitiveImpairment Patients (MCI).Results: Software analysis was completed for 40 individuals. They remained on their treatmentplan for an average of 8.4 months, equal to 2.8 iterations of care plans. 80% of individuals overallshowed improved memory function scores or held steady, as measured by standardized cognitiveevaluations. Cognitive assessments showed significant improvement in the SCD group (CompositeP value .002, Executive P value .01), and the CNS-VS Executive domain showed significant resultsin the combined group as well (P value .01). There was also biomarker improvement over time observedfrom the blood panels. 8 out of 12 selected biomarkers showed slight, though statisticallynon-significant, improvement overall for symptomatic individuals, and 6 out of 12 for the overallpopulation. Only one biomarker, homocysteine, showed significant improvement, though (P values.03, .04, .002).Conclusions: Our analysis of these individuals lead to several interesting observations togethersuggesting that AD risk factors comprise a network of interlocking feedback loops that may bemodifiable. Our findings indicate previously unidentified connectivity between AD risk factors,suggesting that treatment regimens should be tailored to the individual and multi-modal to simultaneouslyreturn several risk factors to a normative state. If successfully performed, the possibility toslow progression of AD and possibly reverse aspects of cognitive decline may become achievable.