Quantifying longitudinal cognitive resilience to Alzheimer's disease and other neuropathologies

Single-cell multiregion dissection of Alzheimer's disease

Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.

Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

BACKGROUND

Leveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.

METHODS

We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women).

RESULTS

The favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline.

CONCLUSION

These findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.

Alzheimer's therapeutic development: shifting neurodegeneration to neuroregeneration

Alzheimer's disease (AD), similar to AD-related dementias, is characterized by impaired/lost neuronal structures and functions due to a long progression of neurodegeneration. Derailed endogenous signal pathways and disease processes have critical roles in neurodegeneration and are pharmacological targets in inducing neuroregeneration. Pharmacologically switching/shifting the brain status from neurodegeneration to neuroregeneration is emerging as a new therapeutic concept, one that is not only achievable, but also essential for effective therapy for AD. The results of the pharmacological-induced shift from neurodegeneration to neuroregeneration are twofold: arresting cognitive deterioration (and directing the brain toward cognitive recovery) in established AD, and preventing neurodegeneration through building up cognitive resilience in patients with preclinical or probable AD. In this review, we discuss these new developments in AD pharmacology and relevant clinical trials.

Changes in Body Mass Index and Incident Mild Cognitive Impairment Among African American Older Adults

BACKGROUND

Previous research suggests a decline in body mass index (BMI) among older adults is associated with negative health outcomes, including mild cognitive impairment (MCI) and incident dementia. However, no studies have examined the effects of education or developing MCI on BMI trajectories over time. The purpose of this investigation was to characterize trajectories of change in BMI among older adults who develop MCI.

METHODS

Participants were from the Minority Aging Research Study (MARS), a longitudinal cohort study of cognitive decline and Alzheimer's disease in older African Americans living in the greater Chicago, Illinois, area. The study included annual clinical evaluations of cognitive status, as well as measurements of height and weight for BMI calculation. Older African American participants without cognitive impairment at baseline were included in the present analysis (N = 436, 78% women, mean baseline age = 72 [SD = 5.7], mean education = 15 [SD = 3.5]).

RESULTS

In piecewise linear mixed-effects models that included a random intercept and 2 random slopes, BMI declined over time (B = -0.20, SE = 0.02, p < .001), with a faster decline after MCI diagnosis (additional decline, B = -0.15, SE = 0.06, p = .019). Older age was associated with lower baseline BMI (B = -0.19, SE = 0.05, p < .001), as was higher education (B = -0.34, SE = 0.09, p < .001). Further, higher education was associated with a slower decline in BMI before MCI (B = 0.02, SE = 0.006, p = .001), but a faster decline after MCI (B = -0.06, SE = 0.022, p = .003).

CONCLUSIONS

These results suggest an accelerated decline in BMI following an MCI diagnosis, with higher education related to an even faster BMI decline.

Estimating dementia risk in an African American population using the DCTclock

The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Americans are twice as likely to develop dementia than other ethnic populations. Traditional cognitive screening solutions lack the sensitivity to independently identify individuals at risk for cognitive decline. The DCTclock is a 3-min AI-enabled adaptation of the well-established clock drawing test. The DCTclock can estimate dementia risk for both general cognitive impairment and the presence of AD pathology. Here we performed a retrospective analysis to assess the performance of the DCTclock to estimate future conversion to ADRD in African American participants from the Rush Alzheimer's Disease Research Center Minority Aging Research Study (MARS) and African American Clinical Core (AACORE). We assessed baseline DCTclock scores in 646 participants (baseline median age = 78.0 ± 6.4, median years of education = 14.0 ± 3.2, 78% female) and found significantly lower baseline DCTclock scores in those who received a dementia diagnosis within 3 years. We also found that 16.4% of participants with a baseline DCTclock score less than 60 were significantly more likely to develop dementia in 5 years vs. those with the highest DCTclock scores (75-100). This research demonstrates the DCTclock's ability to estimate the 5-year risk of developing dementia in an African American population. Early detection of elevated dementia risk using the DCTclock could provide patients, caregivers, and clinicians opportunities to plan and intervene early to improve cognitive health trajectories. Early detection of dementia risk can also enhance participant selection in clinical trials while reducing screening costs.

Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer's disease pathology

Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood. To address this, we generated a single-cell transcriptomic atlas of the aged human prefrontal cortex covering 2.3 million cells from postmortem human brain samples of 427 individuals with varying degrees of AD pathology and cognitive impairment. Our analyses identified AD-pathology-associated alterations shared between excitatory neuron subtypes, revealed a coordinated increase of the cohesin complex and DNA damage response factors in excitatory neurons and in oligodendrocytes, and uncovered genes and pathways associated with high cognitive function, dementia, and resilience to AD pathology. Furthermore, we identified selectively vulnerable somatostatin inhibitory neuron subtypes depleted in AD, discovered two distinct groups of inhibitory neurons that were more abundant in individuals with preserved high cognitive function late in life, and uncovered a link between inhibitory neurons and resilience to AD pathology.

Associations Between Loneliness and Cognitive Resilience to Neuropathology in Older Adults

OBJECTIVES

Loneliness in the aging population is associated with decreased cognitive function and increased neuropathology; less is understood about the association of loneliness and cognitive resilience (CR), defined as the discordance between a person's actual and expected cognition given their neuropathology. Here we assess the effect of loneliness and change in loneliness on CR at end of life and across older adulthood.

METHODS

Data were combined from 2 longitudinal studies of older adults. CR proximate to death (CRlast_level) and across time (CRslope) was obtained by independently regressing global cognition and change in cognition onto multiple neuropathology indicators and extracting the resulting residuals. We used a series of simple linear regression models to assess the effect of loneliness level and change on CRlast_level and CRslope.

RESULTS

Higher baseline loneliness was associated with lower CRlast_level (β = -0.11, 95% confidence interval [95% CI; -0.18, -0.04], p < .01); higher baseline loneliness and increasing loneliness over time was associated with lower CRslope (β = -0.13, 95% CI [-0.22, -0.05], p < .01 and β = -0.12, 95% CI [-0.20, -0.04], p < .01, respectively). Results were robust to covariate inclusion and independent of objective social isolation.

DISCUSSION

Higher and increasing loneliness was associated with lower CR in the face of neuropathology. These results suggest that some individuals are less resilient to the accumulation of neuropathology than others, and experiencing high/increasing loneliness is a key factor putting some at risk. Interventions aimed at optimizing cognitive function across older adults should include loneliness reduction as a potential area of focus.