Associations Between Social Network Characteristics and Brain Structure Among Older Adults.

INTRODUCTION: Social connectedness is associated with slower cognitive decline among older adults. Recent research suggests that distinct aspects of social networks may have differential effects on cognitive resilience, but few studies analyze brain structure. METHODS: This study includes 117 cognitively impaired and 59 unimpaired older adults. The effects of social network characteristics (bridging/bonding) on brain regions of interests were analyzed using linear regressions and voxel-wise multiple linear regressions of gray matter density. RESULTS: Increased social bridging was associated with greater bilateral amygdala volume and insular thickness, and left frontal lobe thickness, putamen, and thalamic volumes. Increased social bonding was associated with greater bilateral medial orbitofrontal and caudal anterior cingulate thickness, as well as right frontal lobe thickness, putamen, and amygdala volumes. DISCUSSION: The associations between social connectedness and brain structure vary depending on the types of social enrichment accessible through social networks, suggesting that psychosocial interventions could mitigate neurodegeneration. HIGHLIGHTS: Distinct forms of social capital are uniquely linked to gray matter density (GMD). Bridging is associated with preserved GMD in limbic system structures. Bonding is associated with preserved GMD in frontal lobe regions. Bridging is associated with increased brain reserve in sensory processing regions. Bonding is associated with increased brain reserve in regions of stress modulation.

Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes.

BACKGROUND: Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. OBJECTIVE: The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. METHODS: Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. RESULTS: Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. CONCLUSIONS: Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression.

BACKGROUND: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies. METHODS: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed. RESULTS: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression. DISCUSSION: The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.

Sex and APOE ε4 carrier effects on atrophy, amyloid PET, and tau PET burden in early-onset Alzheimer's disease.

INTRODUCTION: We used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early-onset Alzheimer's disease (EOAD). METHODS: We included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non-Alzheimer's disease (EOnonAD) participants from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel-wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden. RESULTS: EOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non-carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non-carriers also had greater gray matter atrophy than female ε4 carriers. DISCUSSION: The effects of sex and APOE ε4 must be considered when studying these populations. HIGHLIGHTS: Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE Îµ4) carrier status on neuroimaging biomarkers among early-onset Alzheimer's disease (EOAD), early-onset non-AD (EOnonAD), and cognitively normal (CN) participants. Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex. The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts.

Baseline neuropsychiatric symptoms and psychotropic medication use midway through data collection of the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort.

INTRODUCTION: We examined neuropsychiatric symptoms (NPS) and psychotropic medication use in a large sample of individuals with early-onset Alzheimer's disease (EOAD; onset 40-64 years) at the midway point of data collection for the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). METHODS: Baseline NPS (Neuropsychiatric Inventory - Questionnaire; Geriatric Depression Scale) and psychotropic medication use from 282 participants enrolled in LEADS were compared across diagnostic groups - amyloid-positive EOAD (n = 212) and amyloid negative early-onset non-Alzheimer's disease (EOnonAD; n = 70). RESULTS: Affective behaviors were the most common NPS in EOAD at similar frequencies to EOnonAD. Tension and impulse control behaviors were more common in EOnonAD. A minority of participants were using psychotropic medications, and use was higher in EOnonAD. DISCUSSION: Overall NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants. Future research will investigate moderators and etiological drivers of NPS, and NPS differences in EOAD versus late-onset AD.

APOE ε4 is associated with earlier symptom onset in LOAD but later symptom onset in EOAD.

BACKGROUND: We studied the effect of apolipoprotein E (APOE) ε4 status and sex on age of symptom onset (AO) in early- (EO) and late- (LO) onset Alzheimer's disease (AD). METHOD: A total of 998 EOAD and 2562 LOAD participants from the National Alzheimer's Coordinating Center (NACC) were included. We used analysis of variance to examine AO differences between sexes and APOE genotypes and the effect of APOE ε4, sex, and their interaction on AO in EOAD and LOAD, separately. RESULTS: APOE ε4 carriers in LOAD had younger AO and in EOAD had older AO. Female EOAD APOE ε4 carriers had older AO compared to non-carriers (P < 0.0001). There was no difference for males. Both male and female LOAD APOE ε4 carriers had younger AO relative to non-carriers (P < 0.0001). CONCLUSION: The observed earlier AO in EOAD APOE ε4 non-carriers relative to carriers, particularly in females, suggests the presence of additional AD risk variants.

APOE ε4 carrier status and sex differentiate rates of cognitive decline in early- and late-onset Alzheimer's disease.

BACKGROUND: We studied the effect of apolipoprotein E (APOE) ε4 status and sex on rates of cognitive decline in early- (EO) and late- (LO) onset Alzheimer's disease (AD). METHOD: We ran mixed-effects models with longitudinal cognitive measures as dependent variables, and sex, APOE ε4 carrier status, and interaction terms as predictor variables in 998 EOAD and 2562 LOAD participants from the National Alzheimer's Coordinating Center. RESULTS: APOE ε4 carriers showed accelerated cognitive decline relative to non-carriers in both EOAD and LOAD, although the patterns of specific cognitive domains that were affected differed. Female participants showed accelerated cognitive decline relative to male participants in EOAD only. The effect of APOE ε4 was greater in EOAD for executive functioning (p < 0.0001) and greater in LOAD for language (p < 0.0001). CONCLUSION: We found APOE ε4 effects on cognitive decline in both EOAD and LOAD and female sex in EOAD only. The specific patterns and magnitude of decline are distinct between the two disease variants. HIGHLIGHTS: Apolipoprotein E (APOE) ε4 carrier status and sex differentiate rates of cognitive decline in early-onset (EO) and late-onset (LO) Alzheimer's disease (AD). APOE ε4 in EOAD accelerated decline in memory, executive, and processing speed domains. Female sex in EOAD accelerated decline in language, memory, and global cognition. The effect of APOE ε4 was stronger for language in LOAD and for executive function in EOAD. Sex effects on language and executive function decline differed between EOAD and LOAD.

Predicting the Emergence of Major Neurocognitive Disorder Within Three Months After a Stroke.

Background: Neurocognitive disorder (NCD) is common after stroke, with major NCD appearing in about 10% of survivors of a first-ever stroke. We aimed to classify clinical- and imaging factors related to rapid development of major NCD 3 months after a stroke, so as to examine the optimal composition of factors for predicting rapid development of the disorder. We hypothesized that the prediction would mainly be driven by neurodegenerative as opposed to vascular brain changes. Methods: Stroke survivors from five Norwegian hospitals were included from the "Norwegian COgnitive Impairment After STroke" (Nor-COAST) study. A support vector machine (SVM) classifier was trained to distinguish between patients who developed major NCD 3 months after the stroke and those who did not. Potential predictor factors were based on previous literature and included both vascular and neurodegenerative factors from clinical and structural magnetic resonance imaging findings. Cortical thickness was obtained via FreeSurfer segmentations, and volumes of white matter hyperintensities (WMH) and stroke lesions were semi-automatically gathered using FSL BIANCA and ITK-SNAP, respectively. The predictive value of the classifier was measured, compared between classifier models and cross-validated. Results: Findings from 227 stroke survivors [age = 71.7 (11.3), males = (56.4%), stroke severity NIHSS = 3.8 (4.8)] were included. The best predictive accuracy (AUC = 0.876) was achieved by an SVM classifier with 19 features. The model with the fewest number of features that achieved statistically comparable accuracy (AUC = 0.850) was the 8-feature model. These features ranked by their weighting were; stroke lesion volume, WMH volume, left occipital and temporal cortical thickness, right cingulate cortical thickness, stroke severity (NIHSS), antiplatelet medication intake, and education. Conclusion: The rapid (<3 months) development of major NCD after stroke is possible to predict with an 87.6% accuracy and seems dependent on both neurodegenerative and vascular factors, as well as aspects of the stroke itself. In contrast to previous literature, we also found that vascular changes are more important than neurodegenerative ones. Although possible to predict with relatively high accuracy, our findings indicate that the development of rapid onset post-stroke NCD may be more complex than earlier suggested.