Comorbid neuropathological diagnoses in early versus late-onset Alzheimer's disease

Abstract

Co-pathologies play an important role in the expression of the Alzheimer's disease clinical phenotype and may influence treatment efficacy. Early-onset Alzheimer's disease, defined as manifesting before age 65, is viewed as a relatively pure form of Alzheimer's disease with a more homogeneous neuropathological substrate. We sought to compare the frequency of common neuropathological diagnoses in a consecutive autopsy series of 96 patients with early-onset Alzheimer's disease (median age of onset = 55 years, 44 females) and 48 with late-onset Alzheimer's disease (median age of onset = 73 years, 14 females). The UCSF Neurodegenerative Disease Brain Bank database was reviewed to identify patients with a primary pathological diagnosis of Alzheimer's disease. Prevalence and stage of Lewy body disease, limbic age-related TDP-43 encephalopathy (LATE), argyrophilic grain disease, hippocampal sclerosis, cerebral amyloid angiopathy, and vascular brain injury were compared between the two cohorts. We found at least one non-Alzheimer's disease pathological diagnosis in 98% of patients with early-onset Alzheimer's disease (versus 100% of late onset), and the number of comorbid diagnoses per patient was lower in early-onset than in late-onset Alzheimer's disease (median = 2 versus 3, Mann-Whitney Z = 3.00, P = 0.002). Lewy body disease and cerebral amyloid angiopathy were common in both early and late onset Alzheimer's disease (cerebral amyloid angiopathy: 86% versus 79%, Fisher exact P = 0.33; Lewy body disease: 49% versus 42%, P = 0.48, respectively), although amygdala-predominant Lewy body disease was more common in early than late onset Alzheimer's disease (22% versus 6%, P = 0.02). In contrast, LATE (35% versus 8%, P < 0.001), hippocampal sclerosis (15% versus 3%, P = 0.02), argyrophilic grain disease (58% versus 41%, P = 0.052), and vascular brain injury (65% versus 39%, P = 0.004) were more common in late than in early onset Alzheimer's disease, respectively. The number of co-pathologies predicted worse cognitive performance at the time of death on Mini-Mental State Examination [1.4 points/pathology (95% confidence interval, CI -2.5 to -0.2) and Clinical Dementia Rating-Sum of Boxes (1.15 point/pathology, 95% CI 0.45 to 1.84)], across early and late onset cohorts. The effect of sex on the number of co-pathologies was not significant (P = 0.17). Prevalence of at least one APOE ε4 allele was similar across the two cohorts (52% and 54%) and was associated with a greater number of co-pathologies (+0.40, 95% CI 0.01 to 0.79, P = 0.047), independent of age of symptom onset, sex, and disease duration. Females showed higher density of neurofibrillary tangles compared to males, controlling for age of onset, APOE ε4, and disease duration. Our findings suggest that non-Alzheimer's disease pathological diagnoses play an important role in the clinical phenotype of early onset Alzheimer's disease with potentially significant implications for clinical practice and clinical trials design.

Keywords: Alzheimer's disease; Apo E; copathologies; early-onset; late-onset.

Figure 1

Flow chart of patient selection. AD = Alzheimer’s disease; CTE = chronic traumatic encephalopathy; CAA-IR = CAA-related neuroinflammation; CBD = corticobasal degeneration/syndrome; FTLD = frontotemporal lobar degeneration; PLS-TDP = primary lateral sclerosis with TDP-43 inclusions; VBI = vascular brain injury

Figure 2

Alzheimer’s disease pathology in EOAD and LOAD. (A) Ordinal neuropathological scales. (B) quantitative analyses of NFT density in six predefined regions (density/mm³); bars indicate median and interquartile range. For all variables, Mann-Whitney U-tests were conducted to compare the two groups; common language effect sizes [_CLEF = U / (n_EOAD × n_LOAD)] represent the probability that a random value from the EOAD group is greater than a random value from the LOAD group. n_EOAD = 96 and n_LOAD = 48, unless otherwise specified. Aβ = amyloid-β.

Figure 3

Number of coexistent pathologies. (A) The table indicates the numbers of EOAD/LOAD patients with respective total number of co-pathologies, while the stacked bars illustrate the higher number of co-pathologies in the LOAD group. Mann-Whitney U-tests were conducted to compare the two groups; common language effect size [_CLEF = U / (n_EOAD × n_LOAD)] represents the probability that a random value from the EOAD group is greater than a random value from the LOAD group. A Fisher’s exact test was also run to compare the proportion of co-pathology-free cases between the two groups. (B) Analyses conducted with age of onset as a continuous variable. Black crosses indicate the median ages for each level of co-pathology; a random jitter was applied on the y-axis to visualize all individual data-points.

Figure 4

Details of coexistent non-Alzheimer’s disease pathologies. For all co-pathologies, Fisher’s exact tests were run to compare the proportion of co-pathology-free cases between the two groups. For LBD, an additional Fisher’s exact test was run to compare the frequency of amygdala-predominant patterns between the two groups. For ordinal variables (TDP-43, AGD), Mann-Whitney U-tests were conducted to compare the two groups; common language effect sizes [_CLEF = U / (n_EOAD × n_LOAD)] represent the probability that a random value from the EOAD group is greater than a random value from the LOAD group. n_EOAD = 96 and n_LOAD = 48, unless otherwise specified.

Figure 5

Antemortem cognitive decline based on MMSE. (A) Raw individual trajectories in MMSE scores (raw values), stratified by age of onset group (columns) and number of co-pathologies (rows). Colour variations were randomly assigned to help distinguish overlapping lines. (B) Results of the optimal linear mixed effect model as identified in Supplementary Table 3. The predicted MMSE trajectories for EOAD and LOAD patients with two co-pathologies (the median number of co-pathologies in the whole cohort) are emphasized by a thicker line.