Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment

Proceedings of the National Academy of Sciences · 2023 · 116 citations

• Psychology
• Audiology
• Neuroscience

= 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.

The complementary utility of cognitive testing and the medication management ability assessment in older adults.

Neuropsychology · 2022 · 8 citations

• Psychology
• Clinical psychology
• Psychiatry

OBJECTIVE: Older adults are susceptible to cognitive declines that may limit independence. Though neuropsychologists opine about risk of functional decline, the degree to which cognitive testing and in-office simulations approximate everyday behavior is unclear. We assessed the complementary utility of cognitive testing and the face-valid Medication Management Ability Assessment (MMAA) to predict medication management among older adults. METHOD: groups. Logistic regression assessed which cognitive domains independently predicted group status. The incremental value of the MMAA was assessed, holding uniquely associated cognitive test scores constant. RESULTS: Those receiving assistance with medication management performed worse across all neurocognitive domains and the MMAA compared with independent counterparts. EF was the only unique cognitive predictor of medication management status. When modeled alone, EF and MMAA performance correctly classified 79.5% and 80.8% of cases, respectively. When modeled together, both were independently associated with medication management status and correctly classified 83.3% of cases. CONCLUSIONS: EF uniquely predicted medication management status beyond other cognitive domains. The MMAA provided complementary predictive utility. Concurrent interpretation of executive functioning and MMAA performance is advised when assessing older adults suspected of medication mismanagement. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

Translational Psychiatry · 2021 · 65 citations

• Oncology
• Psychology
• Internal medicine

F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal β-amyloid in neocortical regions but prompt cognitive decline by interacting with β-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer's disease could be illustrated with biomarker measurement under NIA-AA framework. Clinical-neuroimaging-neuropathological studies in other cohorts are needed to validate these findings.

Plasma phosphorylated-tau181 as a predictive biomarker for Alzheimer’s amyloid, tau and FDG PET status

Translational Psychiatry · 2021 · 68 citations

• Medicine
• Pathology
• Oncology

Plasma phosphorylated-tau181 (p-tau181) showed the potential for Alzheimer's diagnosis and prognosis, but its role in detecting cerebral pathologies is unclear. We aimed to evaluate whether it could serve as a marker for Alzheimer's pathology in the brain. A total of 1189 participants with plasma p-tau181 and PET data of amyloid, tau or FDG PET were included from ADNI. Cross-sectional relationships of plasma p-tau181 with PET biomarkers were tested. Longitudinally, we further investigated whether different p-tau181 levels at baseline predicted different progression of Alzheimer's pathological changes in the brain. We found plasma p-tau181 significantly correlated with brain amyloid (Spearman ρ = 0.45, P < 0.0001), tau (0.25, P = 0.0003), and FDG PET uptakes (-0.37, P < 0.0001), and increased along the Alzheimer's continuum. Individually, plasma p-tau181 could detect abnormal amyloid, tau pathologies and hypometabolism in the brain, similar with or even better than clinical indicators. The diagnostic accuracy of plasma p-tau181 elevated significantly when combined with clinical information (AUC = 0.814 for amyloid PET, 0.773 for tau PET, and 0.708 for FDG PET). Relationships of plasma p-tau181 with brain pathologies were partly or entirely mediated by the corresponding CSF biomarkers. Besides, individuals with abnormal plasma p-tau181 level (>18.85 pg/ml) at baseline had a higher risk of pathological progression in brain amyloid (HR: 2.32, 95%CI 1.32-4.08) and FDG PET (3.21, 95%CI 2.06-5.01) status. Plasma p-tau181 may be a sensitive screening test for detecting brain pathologies, and serve as a predictive biomarker for Alzheimer's pathophysiology.

Spread of pathological tau proteins through communicating neurons in human Alzheimer’s disease

Nature Communications · 2020 · 532 citations

• Neuroscience
• Biology
• Psychology

Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

Anticholinergic/Sedative Drug Burden and Subjective Cognitive Decline in Older Adults at Risk of Alzheimer’s Disease

The Journals of Gerontology Series A · 2020 · 27 citations

• Medicine
• Psychiatry
• Internal medicine

BACKGROUND: Anticholinergic/sedative drug use, measured by the Drug Burden Index (DBI), has been linked to cognitive impairment in older adults. Subjective cognitive decline (SCD) may be among the first symptoms patients with Alzheimer's disease (AD) experience. We examined whether DBI values are associated with SCD in older adults at risk of AD. We hypothesized that increased DBI would be associated with greater SCD at older ages. METHOD: Two-hundred-six community-dwelling, English-speaking adults (age = 65 ± 9 years) at risk of AD (42% apolipoprotein ε4 carriers; 78% with AD family history) were administered a single question to ascertain SCD: "Do you feel like your memory is becoming worse?" Response options were "No"; "Yes, but this does not worry me"; and "Yes, this worries me." DBI values were derived from self-reported medication regimens using older adult dosing recommendations. Adjusting for relevant covariates (comorbidities and polypharmacy), we examined independent effects of age and DBI on SCD, as well as the moderating effect of age on the DBI-SCD association at mean ± 1 SD of age. RESULTS: Both SCD and anticholinergic/sedative drug burden were prevalent. Greater drug burden was predictive of SCD severity, but age alone was not. A significant DBI*Age interaction emerged with greater drug burden corresponding to more severe SCD among individuals age 65 and older. CONCLUSION: Anticholinergic/sedative drug exposure was associated with greater SCD in adults 65 and older at risk for AD. Longitudinal research is needed to understand if this relationship is a pre-clinical marker of neurodegenerative disease and predictive of future cognitive decline.

Functional brain architecture is associated with the rate of tau accumulation in Alzheimer’s disease

Nature Communications · 2020 · 338 citations

• Neuroscience
• Medicine
• Biology

In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology

Scientific Reports · 2020 · 133 citations

• Computer Science
• Machine Learning
• Artificial Intelligence

Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer's disease (AD), a complex progressive disease, as a model because the well-established evidence provides a "gold-standard" causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the "gold standard" graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.