Longitudinal Cognitive Trajectories Research Articles

Cognitive subtypes in youth at clinical high risk for psychosis.

Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories. Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters. Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones. Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.

Low testosterone levels relate to poorer cognitive function in women in an APOE-ε4-dependant manner

BackgroundPast research suggests that low testosterone levels relate to poorer cognitive function and higher Alzheimer’s disease (AD) risk; however, these findings are inconsistent and are mostly derived from male samples, despite similar age-related testosterone decline in females. Both animal and human studies demonstrate that testosterone’s effects on brain health may be moderated by apolipoprotein E ε4 allele (APOE-ε4) carrier status, which may explain some previous inconsistencies. We examined how testosterone relates to cognitive function in older women versus men across healthy aging and the AD continuum and the moderating role of APOE-ε4 genotype.MethodsFive hundred and sixty one participants aged 55–90 (155 cognitively normal (CN), 294 mild cognitive impairment (MCI), 112 AD dementia) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), who had baseline cognitive and plasma testosterone data, as measured by the Rules Based Medicine Human DiscoveryMAP Panel were included. There were 213 females and 348 males (self-reported sex assigned at birth), and 52% of the overall sample were APOE-ε4 carriers. We tested the relationship of plasma testosterone levels and its interaction with APOE-ε4 status on clinical diagnostic group (CN vs. MCI vs. AD), global, and domain-specific cognitive performance using ANOVAs and linear regression models in sex-stratified samples. Cognitive domains included verbal memory, executive function, processing speed, and language.ResultsWe did not observe a significant difference in testosterone levels between clinical diagnostic groups in either sex, regrardless of APOE-ε4 status. Across clinical diagnostic group, we found a significant testosterone by APOE-ε4 interaction in females, such that lower testosterone levels related to worse global cognition, processing speed, and verbal memory in APOE-ε4 carriers only. We did not find that testosterone, nor its interaction with APOE-ε4, related to cognitive outcomes in males.ConclusionsFindings suggest that low testosterone levels in older female APOE-ε4 carriers across the aging-MCI-AD continuum may have deleterious, domain-specific effects on cognitive performance. Although future studies including additional sex hormones and longitudinal cognitive trajectories are needed, our results highlight the importance of including both sexes and considering APOE-ε4 carrier status when examining testosterone’s role in cognitive health.

Revealing the heterogeneity of plasma protein and cognitive decline trajectory among Mild Cognitive Impairment patients by clustering of brain atrophy features

Alzheimer's disease (AD) is suggested to be a heterogeneous disorder, but limited studies explore the heterogeneity of the Mild Cognitive Impairment (MCI) stage. This study aimed to tackle such problems using the CIMLR (Cancer Integration via Multikernel Learning) algorithm to cluster brain structural features extracted from T1-weighted Magnetic Resonance Images of MCI patients from Alzheimer's Disease Neuroimaging Initiative. The demographic and cognitive results, characteristics of brain structural features, plasma biomarkers, and longitudinal cognitive trajectory were analyzed for each cluster. The CIMLR clustering analysis revealed four distinct clusters. Cluster 1 is the oldest group but has had mild atrophy and moderate progression with elevated Tumor Necrosis Factor Receptor 2 level; and low Brain-Derived Neurotrophic Factor and CD40 Ligand levels. Cluster 2 showed the highest risk for aggressive MCI progression, with abnormal Leptin, Adiponectin, and Creatine kinase-MB values. Cluster 3 exhibited a low level of Monokine Induced by Gamma Interferon and mild atrophy that shared similar patterns with Cluster 1. Cluster 4 represented the healthiest group during longitudinal tracking, with the mildest Parahippocampal atrophy, which was found to be positively correlated with cognitive impairment and amino acid levels. The longitudinal analyses showed the potential of Hepatocyte Growth Factor as a marker for slow cognitive impairment; Cortisol and Neurofilament Light Polypeptide as prognosis markers for aggressive MCI progression. These findings may lay out new suggestions for further research contributing to the accurate diagnosis and precision medicine for dementia and AD.

Longitudinal Cognitive Trajectories in Older Adults with Restless Legs Syndrome or Willis-Ekbom Disease.

Background: Restless legs syndrome/Willis-Ekbom disease (RLS/WED) has occasionally but not consistently been associated with cognitive and most notably language and executive impairment. The present study was conducted to investigate the cognitive trajectories of older individuals with RLS/WED. Methods: Participants were drawn from the randomly selected, older (>64 years), population-based HELIAD cohort. Individuals without dementia and with available neuropsychological evaluations at baseline and follow-up were considered for potential eligibility. A comprehensive assessment examining five principal components of cognition (memory, visuo-spatial ability, attention, executive function, and language) was administered to the participants. Generalized estimating equation analyses were used to examine the unadjusted and adjusted (for critical factors and covariates) effects of RLS/WED on cognition over time. Results: A total of 1003 predominantly female (59.5%), older (72.9 ± 4.9 years) participants with follow-up evaluations after a mean of 3.09 ± 0.85 years and without dementia at baseline and follow-up were included in the present study. Among them, 81 were diagnosed with RLS/WED at baseline. Global cognition, memory, attention, and executive and visuo-perceptual skills did not differ between those with and without RLS/WED. However, the RLS/WED group performed worse on language at baseline by a standard deviation of 0.249, while demonstrating a mitigated language decline over time, by a standard deviation of 0.063. The unadjusted models yielded similar results. Conclusions: Our findings were indicative of a baseline language disadvantage among older individuals with RLS/WED, but the initial discrepancy tends to dissolve over time.

Single‐cell Transcriptomes Reveal Cell‐type Specific Roles of VEGF Family Genes in the Pathogenesis of Alzheimer’s Disease

AbstractBackgroundThe role of the vascular endothelial growth factors (VEGFs) in the pathogenesis of Alzheimer’s disease (AD) has been recently described, including notable changes along the VEGFB/FLT1 signaling pathway. Yet, cell‐specific alterations are not well characterized. To disentangle VEGFs’ cell‐specific effect on AD‐related traits, we performed association analyses of mRNA expression from 10 VEGF genes with cognitive performance and AD pathology in eight brain cell types using a large single nucleus RNA sequencing dataset from human brain.MethodThis project utilized recently published single‐cell transcriptomes derived from dorsolateral prefrontal cortex tissues of 424 donors collected at Rush Alzheimer’s Disease Center. Processed single cell RNA sequencing data were acquired from AD Knowledge Portal (syn2580853). Mean age at death was 89 years, 68% were females, and 37% were AD cases. Negative binomial lognormal mixed models implemented in the NEBULA R package were used to detect differential expression between AD cases and cognitively normal controls, and to analyze the associations with immunohistochemical amyloid and tangles, and finally to assess cross‐sectional and longitudinal global cognitive scores. Correction for multiple comparisons was completed using the false discovery rate procedure (Pfdr<0.05).ResultPrefrontal cortical FLT1 expression was upregulated in AD participants compared to cognitively normal controls in both endothelial (endo) and microglial (micro) cells. Higher micro‐FLT1, endo‐FLT4, and oligodendrocyte (oligo) VEGFB expression was associated with greater β‐amyloid burden in AD samples, whereas higher VEGFB expression in inhibitory neurons was associated with lower β‐amyloid burden. Higher expression of micro‐FLT1 and oligo‐VEGFB associated with worse cognitive trajectories. Higher micro‐ and endo‐ expression of FLT1 associated with lower cognition scores at the last clinic visit before death. Lastly, higher astrocyte‐expressed NRP1 was associated with lower tangle burden.ConclusionConsistent with our previously reported bulk tissue results, prefrontal cortical expression of FLT1 and FLT4 were associated with global cognition, longitudinal cognitive trajectories, and AD neuropathology, and these associations appear to be limited to endothelial and microglial cells. In contrast, VEGFB expression seems to have opposite effects on amyloid burden depending on the cell types, suggesting its more dynamic role in AD physiopathology.

Individual bioenergetic capacity as a potential source of resilience to Alzheimer’s disease

AbstractBackgroundBrain glucose hypometabolism is among the earliest pathogenic changes in Alzheimer’s disease (AD). This metabolic dysfunction points to the personal bioenergetic capacity, defined as the ability to maintain energy homeostasis under all circumstances including deregulated glucose uptake, as a potential source of resilience to the disease. Fasting blood acylcarnitine profiles are a central readout for this capacity in the absence of dietary glucose and capture the activity and efficiency of glucose‐independent routes of mitochondrial energy metabolism.MethodWe used fasting serum acylcarnitine profiles of 1,531 participants (465 with normal cognition, 762 with mild cognitive impairment, and 304 with clinical AD) from the AD Neuroimaging Initiative to perform unsupervised subgroup identification using hierarchical clustering. Identified subgroups were investigated for differences in A/T/N biomarker profiles and cognitive status. The contributions of genetic and potentially modifiable factors defining the subgroups were quantified using analysis of explained variance. The influence of the strongest determining factors on longitudinal cognitive trajectories was estimated using linear mixed‐effects models and gene‐by‐environment interaction analysis.ResultWe found several bioenergetically distinct subgroups with significant differences in AD biomarker profiles and cognitive function. The strongest genetic contribution to this bioenergetic endophenotype seems to be specifically linked to succinylcarnitine metabolism and significantly modulates the rate of future cognitive decline. In contrast, potentially modifiable sustainment of beta‐oxidation efficiency seems to decelerate bioenergetic aging, thus creating a bioenergetic reserve that delays progression of cognitive decline. Using gene‐by‐environment interaction analysis, we demonstrate that this molecular framework identifies a subgroup of individuals that is likely to benefit significantly from personalized therapeutic, dietary or lifestyle interventions tailored to increase resilience against bioenergetic disturbances in AD.ConclusionOur study reports on a set of genetic and metabolic markers that define bioenergetically distinct subgroups with significant differences on the AD biomarker and cognitive level. Longitudinal data suggest that targeting the modifiable fraction of this endophenotype might be a promising strategy to slow down disease progression in individuals with specific allelic configurations.

Prognostic prediction of the longitudinal cognitive trajectory of amyloid‐positive patients with mild dementia

AbstractBackgroundPrediction of longitudinal cognitive decline for patients with mild dementia using baseline characteristics will be useful for designing optimal clinical trials and real‐world patient monitoring. This can be accomplished via machine‐learning models using baseline clinical characteristics. Adding plasma pTau181 and brain region volumes may improve the predictions.MethodThe training cohort (TC) included 905 amyloid‐positive (A+) patients with mild dementia from two clinical trials. The validation cohort (VC) included 230 A+ patients from another clinical trial. Over 85% of these patients had MCI. The longitudinal cognitive decline was defined by the change from baseline in CDR‐SB at months 3, 6, 9, 12, 15, and 18. Plasma pTau181 was measured using Simoa assay in a subset of 159 patients in TC.Structural brain network (SBN) modules and hubs were derived using 207 regional volumetric MRI measures in TC via an algorithm from genomics called “multiscale embedded gene co‐expression network analysis”. A signature for predicting longitudinal cognitive trajectory for each patient was first derived using baseline cognitive assessments and demographics within TC via the Stochastic Gradient Boosting algorithm. The added value of SBNs and plasma pTau181 was then evaluated within this framework. Prediction performance was evaluated in VC via the correlation between predicted versus observed cognitive trajectory.ResultPredictions of the longitudinal cognitive trajectory using baseline cognitive assessments achieved 43.4% and 42.5% correlation with observed values at months 12 and 18 respectively. Key baseline cognitive function predictors were ADAS‐Cog‐14, CDR‐SB, and sub‐scores such as ideational praxis and word recall.Adding baseline SBNs significantly improved the correlation between predicted versus observed cognitive trajectory to 46.3% and 49.7% at months 12 and 18 respectively (p<0.05). Key baseline SBN predictors were middle and inferior temporal, inferior parietal, and superior frontal cortex, along with a module comprising the entorhinal cortex and temporal pole. Adding baseline plasma pTau181 to cognitive assessments yielded similar improvements, but adding both pTau181 and SBNs did not improve the predictions further.ConclusionLongitudinal cognitive decline of A+ patients with mild dementia can be predicted using baseline cognitive assessments. Adding specific structural brain networks or plasma pTau181 significantly improves the predictions.

Estimating a clinically normal individual’s position along a preclinical Alzheimer’s disease continuum using cognitive and amyloid trajectories

AbstractBackgroundOptimizing longitudinal cognitive and biomarker trajectories can distill multiple observations from one individual into a single metric. Relative to other individuals, this metric can represent an individual’s distance from an anchor‐point based on their rate and non‐linearity of change. We have recently developed a cognitive time (c‐time) based on the cognitive trajectories of clinically normal older adults. We examined the association between c‐time and a previously published ‘time‐to‐Aβ+ threshold’ and how these metrics align with demographics and other biomarkers.MethodWe identified 135 clinically normal older adults from the Harvard Aging Brain Study (Agemean:73years(±5.9); Female:61%) with ≥3 neuropsychological assessments and PiB‐PET, ≥1 Flortaucipir‐PET, ≥2 volumetric MRI, and diagnostic follow up. We defined c‐time using iterative non‐linear least‐squares optimization to define a curvilinear function that described the group‐level Preclinical Alzheimer Cognitive Composite (PACC) trajectory (Fig1D). Each participant’s PACC trajectory was subsequently located on the curve using the same optimization framework (Fig1E). We identified the anchor‐point of cognitive decline (c‐time) using piecewise linear mixed‐effects models. Time‐to‐Aβ+ was calculated using the published sampled iterative local approximation (SILA; Fig1A) algorithm with the anchor‐point indicating Aβ+ threshold (Fig1B). We examined associations between c‐time and time‐to‐Aβ+ using linear regression. Individuals were subsequently placed into groups depending on their position relative to the anchor‐point on each axis, as well as the line‐of‐best‐fit (Fig2). We compared the groups on demographics, and both cross‐sectional and longitudinal indices of medial temporal (MTL) Flortaucipir‐PET (entorhinal, parahippocampal, amygdala) and ICV‐adjusted hippocampal volume.ResultC‐time and time‐to‐Aβ+ were significantly associated (r = 0.42,p<0.001). Only one participant (who progressed to MCI/dementia) was post‐c‐time and remained pre‐time‐to‐Aβ+, supporting the notion that time‐to‐Aβ+ occurs prior to cognitive inflection. Individuals post‐c‐time and post‐time‐to‐Aβ+ (Group 1) were more likely to be APOEε4 carriers, progressors to MCI/dementia, have significantly higher baseline MTL tau and lower hippocampal volume, and faster hippocampal atrophy (Fig3). Group 2 (post‐time‐to‐Aβ+/pre‐c‐time) were more likely APOEε4 carriers. Notably, no age or other effects were apparent between groups.ConclusionOptimizing longitudinal cognitive and biomarker data to estimate a preclinical disease continuum can provide unique, and potentially age‐independent, information about the distance an individual might be from disease‐relevant events.

Decline in cognitive trajectories in the neuropathological spectrum of Lewy Body disease

AbstractBackgroundPathological Lewy body disease (LBD) may commonly present clinically as Parkinson’s disease dementia (PDD), Dementia with Lewy bodies (DLB) or Alzheimer’s disease dementia (ADD). Neuropathological definitions also include a group in which ADD is present, but the postmortem Lewy pathology does not meet threshold density and distribution levels for the neuropathological diagnosis of DLB (ADLB). Little is known about the cognitive profiles of patients with ADLB and despite common underlying pathology, studies delineating neuropsychological profiles in LBD are fraught with inconsistencies. We characterized the longitudinal cognitive trajectories defined by neuropsychological profiles in cases along the pathological spectrum of LBD.MethodCases from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with a cognitive diagnosis of dementia at death and who at minimum, had two neuropsychological evaluations were included. Final neuropathological diagnosis was determined as LBD (neocortical or limbic LB ± AD), ADLB, and AD pathology only. LBD cases were categorized by their cognitive clinical syndromes as PDD and DLB. Global cognition was evaluated using MMSE. Neuropsychological domains of Memory, Executive function, language, attention, and visuospatial were evaluated. Mixed linear methods were used to predict longitudinal change for a given baseline MMSE.Result287 participants and 1874 participant‐years of data were included in this study. LBD (n = 115), and ADLB (52) groups were predominantly male, while AD (n = 114) group was primarily female. Baseline MMSE was similar across all pathologic groups. Linear mixed modelling methods showed faster decrease in memory domain scores (decreasing 0.22 units/year – 0.42 units/year faster, p = 0.01) in ADLB group compared to other groups. Significantly faster decline was noted in LBD and ADLB group in clock drawing (p<0.001), fluency scores (declining 1.02 unit/year faster p<0.001) compared to AD group. There was no difference between PDD and DLB clinical subgroups.ConclusionIn autopsy confirmed cases, ADLB had an accelerated trajectory of decline in memory tasks, while AD, and LBD appeared to have similar trajectories. In contrast, all groups with Lewy bodies progressed faster and showed accelerated decline compared to AD in measures of frontal‐subcortical functions. These results may inform antemortem classification of patients and diagnostic accuracy in these groups.

Determinants of successful cognitive aging over 15 years: a population‐based study

AbstractBackgroundAlthough aging is related to loss in cognitive function, some individuals maintain high levels of cognitive performance also in late life. However, studies mapping longitudinal cognitive trajectories are scarce and little is known about the factors that may promote successful cognitive aging (SCA). We sought to identify predictors of SCA, based on latent profiles derived from interindividual differences in rate of change across several cognitive domains.MethodWe followed 1,966 individuals from the Swedish National Study on Aging and Care in Kungsholmen (SNAC‐K) over 15 years (mean baseline age = 71.6 years; 62.9% female). Participants were free from dementia at baseline and had undergone at least two cognitive assessments during follow‐up. Cognition was assessed with a comprehensive battery, including tests of semantic memory, episodic recall and recognition, letter and verbal fluency, and executive function. We estimated level and change within each of the cognitive domains with linear mixed effect models, based on which we classified participants into successful, normal, or decline groups. These groups were used to derive profiles of overall cognitive change trajectories, through latent class analysis. We then investigated demographic, health, lifestyle, and genetic predictors of profile membership.ResultWe obtained three latent cognitive profiles. 31.6% of the sample was classified as successful, 50.6% as normal, and 17.8% as decliner. In multi‐adjusted multinomial logistic regression analysis, membership in the successful profile was predicted by female sex, higher education, and a faster walking speed (ps < 0.003). Current smoking, feelings of loneliness, and carrying the Apolipoprotein ԑ4‐allele were associated with a lower likelihood of being classified as successful (ps < 0.037). Higher age, diagnosis of diabetes or depression, and being an ԑ4‐carrier increased the likelihood of being classified into the decline profile (ps < 0.026).ConclusionWe identified several demographic, lifestyle, health, and genetic factors of SCA. Of note, these factors were different from those that predicted accelerated cognitive decline. Although some cognitive loss may be an inevitable part of aging, our results suggest certain modifiable factors (i.e. smoking and quality of social interactions) to be related to maintained cognitive function in older age.

Associations between blood‐based biomarkers and cognitive decline among participants at risk of Alzheimer’s disease: the Memento cohort

AbstractBackgroundBlood‐based biomarkers for Alzheimer’s disease (AD) pathology and neurodegeneration are promising biomarkers due to their lower cost, accessibility, and minimally invasive nature. Higher levels of AD blood‐based biomarkers have been shown to be associated with the risk of AD and cognitive decline. Yet, the specific cognitive domains involved need to be further investigated. We thus aimed at estimating the association between levels of baseline AD blood‐based biomarkers with cognitive trajectories over 5 years of follow‐up across different domains in a large clinical based cohort.MethodWe selected the 2060 dementia‐free individuals aged 60 years and older included in the Memento study, a French nationwide cohort, following patients from 28 memory clinics with either isolated cognitive complaints or mild cognitive impairment. Amyloid‐β 40 and 42, P‐tau181, and Neurofilament Light Chain (NfL) concentrations were measured at baseline using Simoa HD‐X analyzer. Global cognition, episodic memory, semantic memory, and executive functioning were assessed every year up to 5 years using the Mini Mental State Examination, the Free and Cued Reminding test, the Animal fluency test, and the Trail Making Test B respectively. Linear mixed models adjusted for sex, education level, APOE‐ε4 status, and practice effect, with age as time scale and quadratic slopes were performed to examine how AD blood‐based biomarkers relate to longitudinal cognitive trajectories by domain.ResultMean age was 72.8 years, 62% were women, 28% were APOE‐ε4 carriers, and 58% had a Clinical Dementia Rating score of 0.5. Higher baseline plasma P‐tau181 was associated with significantly faster nonlinear cognitive decline in all four cognitive domains (p<0.001). On the opposite, baseline plasma Aβ42/40 ratio and NfL were not associated with cognitive decline whatever the domain. Associations between AD blood‐based biomarkers and faster cognitive decline were not modified by APOE‐ε4, sex, nor education level (p value for interaction > 0.05).ConclusionIn a memory clinic population, plasma P‐tau181 is a marker of future cognitive decline. This marker is a good candidate for additional studies assessing biomarkers relevant for the identification of individuals who may benefit from treatment early in the disease course.

Screening strategies and dynamic risk prediction models for Alzheimer's disease

BackgroundCharacterizing the progression from Mild cognitive impairment (MCI) to Alzheimer's disease (AD) is essential for early AD prevention and targeted intervention. Our goal was to construct precise screening schemes for individuals with different risk of AD and to establish prognosis models for them. MethodsWe constructed a retrospective cohort by reviewing individuals with baseline diagnosis of MCI and at least one follow-up visits between November 2005 and May 2021. They were stratified into high-risk and low-risk groups with longitudinal cognitive trajectory. Then, we established a screening framework and obtained optimal screening strategies for two risk groups. Cox and random survival forest (RSF) models were developed for dynamic prognosis prediction. ResultsIn terms of screening strategies, the combination of Clinical Dementia Rating Sum of Boxes (CDRSB) and hippocampus volume was recommended for the high-risk MCI group, while the combination of Alzheimer's Disease Assessment Scale Cognitive 13 items (ADAS13) and FAQ was recommended for low-risk MCI group. The concordance index (C-index) of the Cox model for the high-risk group was 0.844 (95% CI: 0.815–0.873) and adjustments for demographic information and APOE ε4. The RSF model incorporating longitudinal ADAS13, FAQ, and demographic information and APOE ε4 performed for the low-risk group. ConclusionThis precise screening scheme will optimize allocation of medical resources and reduce the economic burden on individuals with low risk of MCI. Moreover, dynamic prognosis models may be helpful for early identification of individuals at risk and clinical decisions, which will promote the secondary prevention of AD.

Relationship of APOE genotypes and level of cognitive reserve to cognitive trajectories among cognitively normal individuals

AbstractBackgroundPrior findings indicate that both genetic factors and indices of cognitive reserve (CR) influence risk of cognitive decline, with APOE4 genetic status increasing risk, and APOE2 genetic status and higher CR indices decreasing risk. However, it remains unclear whether these genetic and lifestyle variables interact to influence long‐term cognitive trajectories. This study examined whether these variables modify baseline cognitive scores and longitudinal cognitive trajectories in N = 1819 participants who were cognitively normal at baseline and included in the Preclinical AD Consortium (PAC).MethodPAC datasets include harmonized data from five longitudinal cohort studies: ACS, AIBL, BIOCARD, BLSA, and WRAP. Longitudinal cognitive performance was measured by harmonized factor scores for global cognition, memory, and executive function (M follow‐up = 9.8y; Table 1). APOE genotypes were coded with separate indicator variables for APOE2 (n = 233) and APOE4 (n = 581), with APOE3/3 (n = 1005) as the reference group. A CR index was calculated by combining years of education and literacy scores.ResultIn longitudinal mixed effect models, using time since baseline as the timescale (Table 2), higher CR index scores were associated with better baseline cognitive performance for all cognitive factor scores, but not with rate of change in cognition over time. In contrast, APOE4 genotype was associated with more negative rates of cognitive change. For the global and memory scores, there were also 3‐way CR index x APOE4 x time interactions, indicating the negative effect of APOE4 genotype on global and memory score change was attenuated among individuals with higher CR index scores (Figure 1). When the models were re‐run with the term for APOE4 genetic status reflecting the number of APOE4 alleles (i.e., 0, 1, 2; Table 3), the patterns of results were similar, except the 3‐way CR index x APOE4 x time interaction for global cognition was only marginal (p = 0.06).ConclusionHigher CR proxy scores are associated with higher levels of cognitive performance, whereas APOE4 genetic status is associated with greater rates of cognitive decline. Higher levels of CR may attenuate APOE4‐related declines in global cognition and memory, but level of CR and APOE4 have largely independent effects on executive function.

Sex Differences in Longitudinal Trajectories of Cognitive Aging in Zaragoza, Spain

ObjectivesThe objective of this study was to document the longitudinal trajectories of cognitive aging in a sample of cognitively healthy subjects of 55 years or older. The following differences between men and women were hypothesized: 1) in the cognitive loss through aging, 2) in the distinct trajectories identified; and 3) in the predictors associated with the identified trajectories. Design and settingA 4-wave, population-based study in Zaragoza, Spain (1994–2006). ParticipantsA total of 2,403 individuals aged 55+ years, cognitively healthy at baseline. MeasurementsAll participants had at least three measurements with the Mini-Mental State Examination (MMSE). Validated Spanish versions of international instruments were used for assessment. Random effects linear panel regression model for analyzing differences by sex in MMSE scores through aging were performed, and growth mixture models (GMM) applied independently for each sex for modeling the longitudinal cognitive trajectories. ResultsWomen showed lower mean MMSE scores in all phases and significantly higher loss in the MMSE from phases 2 to 3 and 3 to 4. The best fitting age-adjusted model of the cognitive trajectories was a 4-class GMM in men and a 3-class in women. Education was a predictor of cognitive trajectories in both men and women. Dependence on iADLs and alcohol status were predictors only for men, and depression and diabetes only for women. ConclusionsThe identified differences by sex in cognitive trajectories and their associated factors suggest that men and women may require a different strategy when addressing cognitive aging.

The regulatory roles of socio-economic status, social and intellectual activity in the relationship between alcohol consumption and cognitive decline trajectory in middle-aged and elderly Chinese: A prospective cohort study.

To determine the relationship between alcohol consumption and cognitive decline, and to further explore the potential regulatory role of education, socio-economic status (SES), and social or intellectual activity in this relationship. 6197 participants aged 45-75years with four repeated measures data from 2011 to 2018 were included. A mixed-effect model was used to explore the relationship between alcohol consumption and the rate of change in cognitive decline, a latent class growth mixed model (LCGMM) was applied to determine the potential trajectory of cognitive decline, and finally, the mediating and moderating analyses were used to determine the regulatory effect of all four variables on the relationship between alcohol consumption and potential trajectory. Compared to never-drinkers, moderate alcohol consumption was a protective factor for overall cognitive function (β=0.13, 95% CI: 0.04-0.20, p<0.001), but there was no statistical correlation with the decline rate of cognitive function. And this protective effect was no longer significant after additional adjustments for education, SES, social and intellectual activity. The LCGMM model divided participants into two trajectories, a high-level-to-decline group including 79.75% of participants (quadratic: β [SE]: -0.90 [0.07], p<0.001), and a low-level-to-decline group including 20.25% participants (linear: β [SE]: -3.05 [0.49], p<0.001). With the latter as the reference, SES played a reverse regulation role in the harmful effect of heavy drinking on cognitive trajectories (odd ratio [OR]=0.46, 95% CI: 0.23-0.93, p<0.05). Social and intellectual activities played a negative mediating role in the harmful effect of alcohol consumption on cognitive trajectories (light: OR=0.96, p<0.001; moderate: OR=0.96, p<0.001; heavy: OR=0.97, p<0.01). Alcohol itself has no protective effect on the decline of longitudinal cognitive trajectory. But the regulatory effect of SES, social and intellectual activities slows down the harm of alcohol consumption on the decline of cognitive function. The data used in this study are from publicly available databases. They are retrospective cohort studies without any intervention. Therefore, no clinical trial registration has been conducted.

Lifetime Traumatic Brain Injury and Cognitive Domain Deficits in Late Life: The PROTECT-TBI Cohort Study.

Traumatic brain injury (TBI) causes cognitive impairment but it remains contested regarding which cognitive domains are most affected. Further, moderate-severe TBI is known to be deleterious, but studies of mild TBI (mTBI) show a greater mix of negative and positive findings. This study examines the longer-term cognitive effects of TBI severity and number of mTBIs in later life. We examined a subset (n = 15,764) of the PROTECT study, a cohort assessing risk factors for cognitive decline (ages between 50 and 90 years). Participants completed cognitive assessments annually for 4 years. Cognitive tests were grouped using a principal components analysis (PCA) into working memory, episodic memory, attention, processing speed, and executive function. Lifetime TBI severity and number were retrospectively recalled by participants using the Brain Injury Screening Questionnaire (BISQ). Linear mixed models (LMMs) examined the effect of severity of head injury (non-TBI head strike, mTBI, and moderate-severe TBI) and number of mTBI at baseline and over time. mTBI was considered as a continuous and categorical variable (groups: 0 mTBI, 1 mTBI, 2 mTBIs, 3 mTBIs, and 4+ mTBIs). Of the participants 5725 (36.3%) reported at least one mTBI and 510 (3.2%) at least one moderate-severe TBI, whereas 3711 (23.5%) had suffered at worst a non-TBI head strike and 5818 (32.9%) reported no head injuries. The participants had suffered their last reported head injury an average (standard deviation, SD) of 29.6 (20.0) years prior to the study. Regarding outcomes, there was no worsening in longitudinal cognitive trajectories over the study duration but at baseline there were significant cognitive deficits associated with TBI. At baseline, compared with those without head injury, individuals reporting at least one moderate-severe TBI had significantly poorer attention (B = -0.163, p < 0.001), executive scores (B = -0.151, p = 0.004), and processing speed (B = -0.075, p = 0.033). Those who had suffered at least a single mTBI also demonstrated significantly poorer attention scores at baseline compared with the no head injury group (B = -0.052, p = 0.001). Compared with those with no mTBI, those in the 3 mTBI group manifested poorer baseline executive function (B = -0.149, p = 0.025) and attention scores (B = -0.085, p = 0.015). At baseline, those who had suffered four or more mTBIs demonstrated poorer attention (B = -0.135, p < 0.001), processing speed (B = -0.072, p = 0.009), and working memory (B = -0.052, p = 0.036), compared with those reporting no mTBI. TBI is associated with fixed, dose, and severity-dependent cognitive deficits. The most sensitive cognitive domains are attention and executive function, with approximately double the effect compared with processing speed and working memory. Post-TBI cognitive rehabilitation should be targeted appropriately to domain-specific effects. Significant long-term cognitive deficits were associated with three or more lifetime mTBIs, a critical consideration when counseling individuals post-TBI about continuing high-risk activities.

Longitudinal trajectories in clinical progression of Alzheimer’s disease tau positron emission tomography subtypes

AbstractBackgroundRecent evidence suggests substantial heterogeneity in Alzheimer's disease (AD). Distinct subtypes have been identified using tau pet positron emissions tomography. There is only limited knowledge about the longitudinal cognitive and clinical trajectories of these subtypes.MethodThree hundred and twenty‐one participants were included with 155 amyloid‐β (Aβ) negative and cognitively normal healthy controls (HC, 74 years, 85 female) and 166 Aβ positive patients with mild cognitive impairment or AD dementia (Alzheimer’s disease spectrum, ADS, 75 years, 76 female). We identified distinct subtypes using an unbiased, data‐driven and similarity‐based Louvain clustering algorithm, modified using a consensus method. Longitudinal trajectories in cognitive domain scores and clinical severity were compared between tau subtypes using mixed effect models.ResultFour distinct tau PET imaging subtypes were identified, including a posterior, a limbic, a medio‐temoral lobe (MTL) sparing and a temporal subtype (Figure 1). In longitudinal analyses, the subtypes differed substantially in disease progression in the different cognitive domains, i.e. episodic memory, executive functioning, language and visual memory. The temporal subtype showed the steepest decline in visual memory and language, the medial temporal lobe sparing subtype showed only minor language degradation and the limbic subtype showed relatively preserved executive functioning but decline in all other cognitive domains. The MTLs was by far worst affected by clinical progression. The remaining subtypes showed only slight deterioration in clinical severity (Figure 2).ConclusionOur results suggest characteristic differences in longitudinal cognitive and clinical trajectories of the tau PET imaging subtypes. Analyzing the heterogeneity in AD using tau PET spatial distribution patterns, significantly improves our understanding of the biological underpinnings of individual differences in clinical presentation and progression. An in‐depth understanding of the subtype’s characteristics in the longitudinal trajectories contributes significantly to improved prevention strategies and individualized precision treatments.

Sex differences in the protective effects of APOE ε2 on longitudinal cognitive decline

AbstractBackgroundThe APOE ε2 allele confers protection against cognitive decline and Alzheimer’s disease. There is some suggestion that APOE ε2 may have sex‐specific effects on cognition. We investigated sex differences in associations between APOE ε2 and longitudinal cognitive trajectories in a large sample of older adults.MethodWe used data from the National Alzheimer’s Coordinating Centre (NACC) database. We included participants who were ≥ 50 years old, White, free from dementia at baseline, and completed at least one follow‐up cognitive assessment. We categorized participants as APOE ε2 carriers (combining heterozygous and homozygous ε2 carriers) or APOE ε3 homozygote carriers. APOE ε4 carriers (including ε2/ε4 carriers) were excluded. Cognition was assessed approximately annually. We computed composite scores for memory, language, attention, and executive function. We examined the interaction between APOE allele (ε2 vs ε3), sex, and time on longitudinal cognition in linear mixed models, adjusting for baseline age, baseline MMSE, education, number of follow‐up visits, NACC test version, and their interactions with time.ResultWe included 6,733 participants classified as cognitively normal at baseline (mean age=72.9±9.12 years, mean education=16.0±2.87 years, 62.5% female), and 1,932 participants classified as mild cognitive impairment (MCI) at baseline (mean age=75.2±8.91 years, mean education=15.6±3.28 years, 44% female). Among participants with normal cognition, we observed significant interactions between sex, genotype, and time on longitudinal memory (β=0.022, p=0.039) and language (β=0.015, p=0.038), but not attention (β=0.01, p=0.09) or executive function (β=0.006, p=0.30). In sex stratified analyses, relative to male APOE ε3 carriers, male APOE ε2 carriers showed slower rates of decline in domains of memory and language. This effect was not observed in females. No significant interactions between sex, genotype, and time were observed in participants with MCI (memory: β=‐0.04, p=0.1; language: β=‐0.02, p=0.4; attention: β=‐0.01, p=0.5; executive function: β=‐0.02, p=0.3).ConclusionAmong cognitively normal adults, APOE ε2 carriage protects males but not females against longitudinal memory and language decline. The sex‐specific effect of APOE ε2 may contribute to the lower incidence of Alzheimer’s disease in males compared to females. Future research is needed to elucidate the mechanisms behind the observed sex disparities in cognitive decline.

Associations of Amyloid, White Matter Hyperintensities, and Hippocampal Volume with Cognitive Trajectories in the Oldest‐Old: The 90+ Study

AbstractBackgroundAmyloid pathology, vascular disease pathology, and hippocampal atrophy are associated with cognitive trajectories in older adults. However, there is almost no prior evidence on how these pathologies influence cognition in the oldest‐old.MethodWe included 216 individuals from The 90+ Study, a longitudinal study of aging and dementia in people aged 90 years and older, who had 18F‐florbetapir PET and MRI imaging. We examined the association of amyloid, white matter hyperintensities (WMH) volume, and hippocampal volume (HV) with baseline cognition and longitudinal cognitive decline. Amyloid burden was measured using the standardized uptake value ratio (SUVR) in the precuneus/posterior cingulate with white matter mask as reference. WMH volume and HV were normalized by intracranial volume (IV) and normalized WMH were log‐transformed. SUVR and HV for each individual were Z‐scored using the sample mean and standard deviation. Global cognitive performance was measured by Mental State Examination (MMSE) and modified MMSE (3MS) tests, repeated every six months. We defined baseline (time=0) as the visit closest to the PET imaging and included all visits starting from one year before baseline (time=‐1). We used linear mixed‐effects models with a random intercept to estimate the effect of pathologies on cognitive trajectories. All models included baseline age, sex, education, APOE‐ε4, time, time squared, amyloid, WMH, HV, and interactions between linear time and pathology variables.ResultAt baseline, participants were 93.2 years old on average, 65.3% were females, 10.6% were APOE‐ε4 carriers, and 66.2% had normal cognition (Table 1). Higher HV was associated with higher MMSE and 3MS scores at baseline. Both lower amyloid burden and higher HV were associated with slower rate of cognitive decline longitudinally. WMH was not associated with baseline cognition or cognitive trajectory. Parameter estimates are shown in Table 2 and illustrative cognitive trajectories predicted for a 93.2‐year‐old female with APOE‐ε4 alleles and a college degree predicted at varying degrees of amyloid, HV, and WMH are shown in Figure 1.ConclusionAmyloid burden and HV are associated with longitudinal cognitive trajectories, highlighting the utility of amyloid and HV in predicting future cognitive decline for the oldest‐old.

Tau‐Neurodegeneration mismatch reveals vulnerability and resilience in Alzheimer’s continuum and Non‐Alzheimer’s pathophysiology

AbstractBackgroundIn previous work (Das et al., 2021), we exploited the non‐specific nature of neurodegeneration by investigating the amount and spatial pattern of deviation from the level of neurodegeneration (N) expected for a given level of tau (T). Using a data‐driven clustering approach based on T‐N mismatch, we found phenotypes that had greater N than expected for T (“vulnerable”) and phenotypes with less N than expected for T (“resilient”) in specific patterns. Here we extend this work to include amyloid positive (A+) and negative (A‐) participants. The logic of inclusion of A‐ individuals is that areas of mismatch in A+ individuals is likely driven by factors outside of AD pathology, which can be present in the absence of AD pathology.MethodWe employed cortical thickness to represent N and 18F‐flortaucipir tracer uptake as T for 104 bilateral cortical regions of interest (ROI) in 343 symptomatic individuals including both A+ and A‐ from ADNI. We established T‐N robust regression and partitioned participants based on thresholded residuals. Longitudinal trajectories of cognitive scores were assessed with linear mixed‐effects model effect models using CDRSB as the dependent variable.ResultWe replicated prior work and obtained clusters with distinct T‐N mismatch patterns. We defined the largest group as “canonical”, as it displayed typical T‐N relationships (N∼T, low residuals). The limbic vulnerable cluster displayed N&gt;T (negative residuals) in limbic regions, while diffuse vulnerable group displayed N&gt;T throughout the cortex. Alternatively, the resilient (N&lt;T, positive residuals) clusters were classified as limbic resilient or prefrontal resilient based on the pattern of this relationship. Note the highly similar regional patterns of the A+ and A‐ subgroups, supporting our hypothesis that this residual reflects non‐AD related phenomenology which could be present irrespective of amyloid status. Phenotypes differed in longitudinal cognitive trajectories. The vulnerable clusters declined significantly faster than the canonical cluster regardless of amyloid status likely attributable to the presence of non‐AD pathologies. The resilient groups tended to progress less than the canonical group.ConclusionOur findings suggest T‐N mismatch depicts vulnerability and resilience likely attributable to non‐AD factors. This may provide an approach for detecting co‐pathologies in AD continuum and benefiting therapeutic management.