Early-onset Alzheimer's disease shows a distinct neuropsychological profile and more aggressive trajectories of cognitive decline than late-onset

OBJECTIVES

Early- and late-onset Alzheimer's disease (EOAD and LOAD) share the same neuropathological traits but show distinct cognitive features. We aimed to explore baseline and longitudinal outcomes of global and domain-specific cognitive function in a well characterized cohort of patients with a biomarker-based diagnosis.

METHODS

In this retrospective cohort study, 195 participants were included and classified according to their age, clinical status, and CSF AD biomarker profile: 89 EOAD, 37 LOAD, 46 young healthy controls (age ≤ 65 years), and 23 old healthy controls (>65 years). All subjects underwent clinical and neuropsychological assessment, neuroimaging, APOE genotyping and lumbar puncture.

RESULTS

We found distinct neuropsychological profiles between EOAD and LOAD at the time of diagnosis. Both groups showed similar performances on memory and language domains, but the EOAD patients displayed worsened deficits in visual perception, praxis, and executive tasks (p < 0.05). Longitudinally, cognitive decline in EOAD was more pronounced than LOAD in the global outcomes at the expense of these non-amnestic domains. We found that years of education significantly influenced the decline in most of the neuropsychological tests. Besides, the APOE ε4 status showed a significant effect on the decline of memory-related tasks within the EOAD cohort (p < 0.05).

INTERPRETATION

Age of onset is a main factor shaping the cognitive trajectories in AD patients, with younger age driving to a steeper decline of the non-memory domains. Years of education are related to a transversal decline in all cognitive domains and APOE ε4 status to a specific decline in memory performance in EOAD.

Impact of COVID‐19 pandemic in an early‐onset dementia clinic in Barcelona

Background

The ongoing COVID‐19 pandemic and related care policies have affected dementia patients. The characteristics of early‐onset dementia (EOD, <65 years) patients in 2020 may provide insights on how to rearrange the provision of care.

Method

We retrospectively reviewed, from 2016 to 2020, the demographic and clinical data of the new referrals at our EOD clinic (Hospital Clínic Barcelona). We used Fisher’s Exact test and Mann–Whitney U test in R4.0.2 (http://www.R‐project.org/) to analyze differences between 2020 and the period 2016‐2019.

Result

In 2020, we did not visit any new referral from 15th march to 31th may. We evaluated 104 patients in 2020 and 392 patients in 2016‐2019 (mean=98(SD=11.8) patients/year). No differences were found in age at onset (AAO), sex, diagnostic delay and MMSE score (Table1). Significant differences were found in the diagnoses obtained in each period (p<0.000005, Figure1A). In 2020, 19.2% of the patients were diagnosed with neurodegenerative diseases (ND), 48.1% with non‐neurodegenerative diseases (NND) and 32.7% with subjective cognitive decline (SCD). On contrast, in 2016‐2019, 26% of the patients were diagnosed with ND, 22.2% with NND and 51.8% with SCD. Compared to 2016‐2019, ND, but not SCD or NND, presented longer diagnostic delay in 2020 (p<0.0005, Figure1B). ND, NND and SCD did not show differences between periods in AAO, sex or MMSE.

We did not find differences in the type of ND in each period (Figure1A). Compared to 2016‐2019, Frontotemporal Lobar Degeneration (FTLD) presented longer diagnostic delay in 2020 (p<0.005, Figure1B) while ND subgroups did not show differences in AAO, sex or MMSE. Cognitive disturbances in recovered COVID‐19 patients accounted for 16% of NND in 2020 [N=8, AAO 50.63(12), 63% female, MMSE 26.8(2.3)].

Conclusion

In 2020, albeit we were forced to stop our normal activity during 2.5 months, we visited a similar number of patients among which we observed an increase in NND, including cognitive disturbances in patients with recovered COVID‐19. On contrast, we found a reduction in SCD and, to a lesser extent, ND. ND showed a longer diagnostic delay in 2020 that mainly affected FTLD. Whether COVID‐19 pandemic entails a diagnostic delay in dementia patients must be confirmed in 2021.

Sex differences in the behavioral variant of frontotemporal dementia: A new window to executive and behavioral reserve

INTRODUCTION

Biological sex is an increasingly recognized factor driving clinical and structural heterogeneity in Alzheimer's disease, but its role in the behavioral variant of frontotemporal dementia (bvFTD) is unknown.

METHODS

We included 216 patients with bvFTD and 235 controls with magnetic resonance imaging (MRI) from a large multicenter cohort. We compared the clinical characteristics and cortical thickness between men and women with bvFTD and controls. We followed the residuals approach to study behavioral and cognitive reserve.

RESULTS

At diagnosis, women with bvFTD showed greater atrophy burden in the frontotemporal regions compared to men despite similar clinical characteristics. For a similar amount of atrophy, women demonstrated better-than-expected scores on executive function and fewer changes in apathy, sleep, and appetite than men.

DISCUSSION

Our findings suggest that women might have greater behavioral and executive reserve than men, and neurodegeneration must be more severe in women to produce symptoms similar in severity to those in men.

Cognitive decline in amyotrophic lateral sclerosis: Neuropathological substrate and genetic determinants

Cognitive impairment and behavioral changes in amyotrophic lateral sclerosis (ALS) are now recognized as part of the disease. Whether it is solely related to the extent of TDP-43 pathology is currently unclear. We aim to evaluate the influence of age, genetics, neuropathological features, and concomitant pathologies on cognitive impairment in ALS patients. We analyzed a postmortem series of 104 ALS patients and retrospectively reviewed clinical and neuropathological data. We assessed the burden and extent of concomitant pathologies, the role of APOE ε4 and mutations, and correlated these findings with cognitive status. We performed a logistic regression model to identify which pathologies are related to cognitive impairment. Cognitive decline was recorded in 38.5% of the subjects. Neuropathological features of frontotemporal lobar degeneration (FTLD) were found in 32.7%, explaining most, but not all, cases with cognitive impairment. Extent of TDP-43 pathology and the presence of hippocampal sclerosis were associated with cognitive impairment. Mutation carriers presented a higher burden of TDP-43 pathology and FTLD more frequently than sporadic cases. Most cases (89.4%) presented some degree of concomitant pathologies. The presence of concomitant pathologies was associated with older age at death. FTLD, but also Alzheimer's disease, were the predominant underlying pathologies explaining the cognitive impairment in ALS patients. In sum, FTLD explained the presence of cognitive decline in most but not all ALS cases, while other non-FTLD related findings can influence the cognitive status, particularly in older age groups.

Contribution of CSF biomarkers to early-onset Alzheimer's disease and frontotemporal dementia neuroimaging signatures

Prior studies have described distinct patterns of brain gray matter and white matter alterations in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), as well as differences in their cerebrospinal fluid (CSF) biomarkers profiles. We aim to investigate the relationship between early-onset AD (EOAD) and FTLD structural alterations and CSF biomarker levels. We included 138 subjects (64 EOAD, 26 FTLD, and 48 controls), all of them with a 3T MRI brain scan and CSF biomarkers available (the 42 amino acid-long form of the amyloid-beta protein [Aβ42], total-tau protein [T-tau], neurofilament light chain [NfL], neurogranin [Ng], and 14-3-3 levels). We used FreeSurfer and FSL to obtain cortical thickness (CTh) and fraction anisotropy (FA) maps. We studied group differences in CTh and FA and described the "AD signature" and "FTLD signature." We tested multiple regression models to find which CSF-biomarkers better explained each disease neuroimaging signature. CTh and FA maps corresponding to the AD and FTLD signatures were in accordance with previous literature. Multiple regression analyses showed that the biomarkers that better explained CTh values within the AD signature were Aβ and 14-3-3; whereas NfL and 14-3-3 levels explained CTh values within the FTLD signature. Similarly, NfL levels explained FA values in the FTLD signature. Ng levels were not predictive in any of the models. Biochemical markers contribute differently to structural (CTh and FA) changes typical of AD and FTLD.