Abstract
AbstractBackgroundTwo main complexities of Alzheimer’s Disease (AD) arise from pathological changes (such as amyloid accumulation) occurring a decade or more before symptom onset, and AD being a highly heterogeneous disease with various clinical subtypes. Subtype and Stage Inference (SuStaIn), a data‐driven modelling technique, has been previously applied to ADNI to better understand AD. Here we apply SuStaIn to Insight46, a sub‐study of the British 1946 Birth Cohort to detect different trajectories of preclinical neurodegeneration.MethodSuStaIn was applied to cross‐sectional MRI, amyloid PET, plasma biomarkers, and cognition (Preclinical Alzheimer Cognitive Composite [PACC]) from 466 study members (Table 1). 376 Amyloid‐negative individuals (computed as Lane et al. 2019) were designated as controls. SuStaIn subtypes were also estimated in ADNI (N=789; Tables 1 and 2) for comparison. T‐tests and Chi‐squared tests were used to assess subtype differences in baseline APOE, amyloid status, white matter hyperintensity volume (WMHV), and rates of change in whole brain, ventricular and hippocampal volume calculated using the boundary shift integral.ResultFigure 1 shows three subtypes uncovered by SuStaIn: ‘Typical’, ‘Subcortical’ and ‘Cortical’. The ‘Typical’ subtype appears to reflect a typical AD progression pattern, with early involvement of Aβ40/42 ratio and Neurofilament light (NFL), followed by the PACC and finally, plasma tau. MRI volumetric changes appear later. Both ‘Subcortical’ and ‘Cortical’ subtypes are characterised by earlier abnormality in MRI volumes.Figure 2 shows that subjects assigned to the ‘Cortical’ subtype had significantly higher WMHV than the other two subtypes (p‐value < 0.002). No other significant differences in baseline characteristics were found.Figure 3 shows ‘Typical’ subtype has significantly higher rates of ventricular expansion and whole brain atrophy compared with ‘Subcortical’ subtype (p‐values = 0.001).ConclusionThis study reveals three different subtypes (‘Typical’, ‘Subcortical’ and ‘Cortical’) of presumed neurodegeneration in an elderly, preclinical cohort; these are consistent with those found in AD patient cohorts, e.g. ADNI, meaning that these methods may have utility in population based cohorts. These results suggest that SuStaIn may be helpful in determining different subtypes of neurodegeneration at a very early stage with implications for recruitment to, and powering of, clinical trials.
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