Identifying and predicting heterogeneity in cognitive decline among individuals with prodromal Alzheimer's disease using a latent class analysis

Abstract

AbstractBackgroundIndividuals with prodromal Alzheimer’s disease (AD) show heterogeneity in their rates of cognitive decline, which is problematic for measuring (therapeutic) effects on cognition. We aimed to identify subgroups with homogeneous cognitive trajectories among individuals with prodromal AD in two large independent cohorts, and investigate which clinical and/or biological AD risk factors predict progression rate.MethodIndividuals with an abnormal amyloid marker (determined by either CSF Aβ‐42 levels or Florbetaben/Flutametamol/Florbetapir‐AV45 PET imaging) and mild cognitive impairment who had longitudinal cognitive data available were selected from the Amsterdam Dementia Cohort and ADNI (N=340, age =71.5±8.4, 43% female). We performed latent class mixed models (LCMM) to identify subgroups based on similarity of their trajectories on the Mini‐Mental State Examination (MMSE), and performed mixture modelling using individual MMSE slopes to validate those subgroups. We compared subgroups on baseline age, sex, years of education, ApoE‐e4 status, CSF tau and phosphorylated tau (p‐tau) and hippocampal volume using univariate logistic regression, and subsequently performed stepwise logistic regression with backward elimination to identify which baseline characteristics best predicted progression.ResultParticipants had 2.3±1.8 repeated assessments and a follow‐up of 2.3±1.6 [range=1‐8] years. LCMM identified three subgroups of MMSE progression, which were confirmed by mixture modelling: Group 1 (n=303, 88%) showing slowest progression (i.e. average 0.7 [range=0.4–1.9] points annual decline on MMSE); Group 2 (n=30, 10%) intermediate progression (average 2.6 [range=1.9–4.2] points annual decline on MMSE) and Group 3 (n=7, 2%) showing fastest progression (average 4.7 [range=3.3–6.2] points annual decline on MMSE) (Figure 1). No effects on progression were observed for age, sex, education and ApoE‐e4 (Table 1). Compared to individuals who slowly progressed, those with intermediate‐to‐fast progression had higher tau (OR=1.01, 95%CI=[1.01‐1.02], p<.001) and p‐tau (OR=1.03, 95%CI=[1.02‐1.05], p<.001) levels and lower hippocampal volume (OR=0.57, 95%CI=[.37‐.84], p=.006) at baseline. The model including both p‐tau (OR=1.03, 95%CI=[1.02‐1.05], p<.001) and hippocampal volume (OR=0.55, 95%CI=[.34‐.85], p=.01) best predicted fast progression.ConclusionAmong individuals with prodromal AD, we identified three subgroups with different rates of decline on the MMSE, and demonstrated that baseline neurodegeneration markers were associated with faster decline. These findings have practical implications for clinical trial enrollment and predicting disease progression.