Introduction There is an urgent need to develop effective interventional treatments for people with Alzheimer's disease (AD). AD results from a complex multi‐decade interplay of multiple interacting dysfunctional biological systems that have not yet been fully elucidated. Epidemiological studies have linked several modifiable lifestyle factors with increased incidence for AD. Because monotherapies have failed to prevent or ameliorate AD, interventional studies should deploy multiple, targeted interventions that address the dysfunctional systems that give rise to AD. Methods This randomized controlled trial (RCT) will examine the efficacy of a 12‐month personalized, multimodal, lifestyle intervention in 60 mild cognitive impairment (MCI) and early stage AD patients (aged 50+, amyloid positivity). Both groups receive data‐driven, lifestyle recommendations designed to target multiple systemic pathways implicated in AD. One group receives these personalized recommendations without coaching. The other group receives personalized recommendations with health coaching, dietary counseling, exercise training, cognitive stimulation, and nutritional supplements. We collect clinical, proteomic, metabolomic, neuroimaging, and genetic data to fuel systems‐biology analyses. We will examine effects on cognition and hippocampal volume. The overarching goal of the study is to longitudinally track biological systems implicated in AD to reveal the dynamics between these systems during the intervention to understand differences in treatment response. Results We have developed and implemented a protocol for a personalized, multimodal intervention program for early AD patients. We began enrollment in September 2019; we have enrolled a third of our target (20 of 60) with a 95% retention and 86% compliance rate. Discussion This study presents a paradigm shift in designing multimodal, lifestyle interventions to reduce cognitive decline, and how to elucidate the biological systems being targeted. Analytical efforts to explain mechanistic or causal underpinnings of individual trajectories and the interplay between multi‐omic variables will inform the design of future hypotheses and development of effective precision medicine trials.
Background: Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention. Objective: We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox ® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader ® by Brainreader). Methods: Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n = 161) and quantitative vMRI (n = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models. Results: The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87). Conclusion: This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia.
Background: Strength and mobility are essential for activities of daily living. With aging, weaker handgrip strength, mobility, and asymmetry predict poorer cognition. We therefore sought to quantify the relationship between handgrip metrics and volumes quantified on brain magnetic resonance imaging (MRI). Objective: To model the relationships between handgrip strength, mobility, and MRI volumetry. Methods: We selected 38 participants with Alzheimer’s disease dementia: biomarker evidence of amyloidosis and impaired cognition. Handgrip strength on dominant and non-dominant hands was measured with a hand dynamometer. Handgrip asymmetry was calculated. Two-minute walk test (2MWT) mobility evaluation was combined with handgrip strength to identify non-frail versus frail persons. Brain MRI volumes were quantified with Neuroreader. Multiple regression adjusting for age, sex, education, handedness, body mass index, and head size modeled handgrip strength, asymmetry and 2MWT with brain volumes. We modeled non-frail versus frail status relationships with brain structures by analysis of covariance. Results: Higher non-dominant handgrip strength was associated with larger volumes in the hippocampus (p = 0.02). Dominant handgrip strength was related to higher frontal lobe volumes (p = 0.02). Higher 2MWT scores were associated with larger hippocampal (p = 0.04), frontal (p = 0.01), temporal (p = 0.03), parietal (p = 0.009), and occipital lobe (p = 0.005) volumes. Frailty was associated with reduced frontal, temporal, and parietal lobe volumes. Conclusion: Greater handgrip strength and mobility were related to larger hippocampal and lobar brain volumes. Interventions focused on improving handgrip strength and mobility may seek to include quantified brain volumes on MR imaging as endpoints.
BackgroundHandgrip strength is important for performing activities of daily living[1]. In older adults, weaker handgrip strength and asymmetry are associated with poorer cognition. o better understand mechanisms, we sought to quantify the relationship between handgrip strength and regional volumes quantified on brain MR imaging.MethodWe selected 32 participants (mean age=70.8±7.3 [range 57‐89] years, 53.1% female, 90.6% right‐handed, mean body mass index BMI=23.9±4.1) from the Pacific Brain Health Center at Providence St. John’s Health Center, with Alzheimer dementia biomarker evidence of amyloidosis[2]. Mean Montreal Cognitive Assessment score for all participants was 21.3±3.8 points. Handgrip strength on dominant and non‐dominant hands was measured using the NIH Motor Toolbox[3] as part of a cognitive fitness assessment using a hydraulic hand dynamometer. The resulting scores included handgrip strength and percentile comparisons to normative data. Asymmetry scores were calculated. Regional brain volumes, including lobar structures and the hippocampus, were measured from T1‐weighted MR images using Neuroreader[4]. Partial correlations (rp), adjusting for age, sex, BMI and total intracranial volume modeled handgrip strength, asymmetry, and brain volumes with a significance threshold of p<0.05.ResultIn the dominant hand, higher handgrip strength scores and percentiles were associated with larger volumes in the left frontal lobe (rp=+0.51, p=0.007; rp =+0.47, p=0.01) and right parietal lobe (rp=+0.40, p=0.03; rp=+0.39, p=0.04). In the non‐dominant hand, higher handgrip strength score and percentiles were associated with smaller total cerebral spinal fluid (CSF) volume (rp =‐0.55, p=0.004; rp =‐0.52, p =0.006) and larger volumes within the left hippocampus (rp=+0.45, p=0.01; rp=+.43, p=0.02), right hippocampus (rp=+0.47, p=0.01; rp=+0.43, p=0.02), and right parietal lobe (rp=+0.39, p=0.04; rp=+0.44, p=0.02). Handgrip strength asymmetry was inversely related to right hippocampal volume (rp=‐0.58, p=0.002) and positively correlated to CSF volume (rp=+0.39, p=0.04).ConclusionGreater handgrip strength was related to larger regional brain volumes. A higher number of brain regions were related to the non‐dominant hand. Asymmetry was associated with lower right hippocampal volume and higher CSF volume. Interventions focused on improving handgrip strength may seek to include quantified brain volumes on MR imaging as endpoints.
BackgroundPersonalized multi‐modal interventions for Alzheimer dementia hold promise to slow progression of symptoms yet related quantitative neuroimaging biomarkers have not been investigated[1,2].MethodWe selected 16 participants (mean age 68.6±5.9 [range 57‐77] years, 50% female) from the Pacific Brain Health Center at Providence St. John’s Health Center, with biomarker evidence of Alzheimer dementia amyloidosis. All participants received data‐supported clinical recommendations (DSCR), [3–7] which included a modified SHIELD program[8] recommending a low carbohydrate diet. DSCRs were personalized based on clinical evaluations and laboratory values and closely overseen by a dementia specialist (DM, CW). T1‐weighted MR images were acquired at baseline and with a 1‐year average follow up. Total gray and white matter, hippocampal, lateral ventricle, temporal, parietal, occipital and frontal lobe volumes were quantified using Neuroreader[9]. Global cognition was tested using the Montreal Cognitive Assessment (MoCA). Paired t‐tests were done for these metrics.ResultChanges in hippocampal volumes (t=+1.6, p=0.11), temporal (t=+0.03, p=0.97) and frontal lobes (t=‐0.63, p=0.53) were not significant. There was a marginally significant decline in the parietal lobes (t=+2.1, p=.048) and statistically significant increased lateral ventricles (t=‐4.9, p<0.01). White matter volume declined significantly (t=‐2.8, p=0.01) while gray matter did not change significantly (t=+1.2, p=0.21). Table 1 shows annualized percent changes for these regions. These changes were attenuated compared to literature values for the following regions: gray matter at ‐2%/year [10], hippocampus at ‐3.5%/year [11], temporal lobes at ‐3.23%/year, parietal lobes at ‐3.62%/year and frontal lobes at ‐2.88%/year [12]. Total gray matter and frontal lobe volumes showed increased average annualized changes at +1.97%/year and +0.87%/year respectively. Over the same time period as the brain‐volume trajectory measurements, there was an average decline in MoCA (‐1.5 from 22.06±4.1 to 20.56±6.1, p=0.06) that trended towards but was not statistically significant.ConclusionRegional volume loss, while present, was moderated compared to literature derived rates. Increased ventricular volumes appear driven by white matter volume loss. These preliminary data suggest that efforts to track and report on clinical outcomes in settings providing close medical management and multimodal lifestyle recommendations may be a worthwhile step towards validating research findings.
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