Transferability of Alzheimer's disease progression subtypes to an independent population cohort
Year: 2023
Type: article
Abstract: In the past, methods to subtype or biotype patients using brain imaging data have been developed. However, it is unclear whether and how these trained machine learning models can be successfully applied to population cohorts to study the genetic and lifestyle factors underpinning these subtypes. This work, using the Subtype and Stage Inference (SuStaIn) algorithm, examines the generalisability of data-driven Alzheimer's disease (AD) progression models. We first compared SuStaIn models trained separately on Alzheimer's disease neuroimaging initiative (ADNI) data and an AD-at-risk population constructed from the UK Biobank dataset. We further applied data harmonization techniques to remove cohort effects. Next, we built SuStaIn models on the harmonized datasets, which were then used to subtype and stage subjects in the other harmonized dataset. The first key finding is that three consistent atrophy subtypes were found in both datasets, which match the previously identified subtype progression patterns in AD: 'typical', 'cortical' and 'subcortical'. Next, the subtype agreement was further supported by high consistency in individuals' subtypes and stage assignment based on the different models: more than 92% of the subjects, with reliable subtype assignment in both ADNI and UK Biobank dataset, were assigned to an identical subtype under the model built on the different datasets. The successful transferability of AD atrophy progression subtypes across cohorts capturing different phases of disease development enabled further investigations of associations between AD atrophy subtypes and risk factors. Our study showed that (1) the average age is highest in the typical subtype and lowest in the subcortical subtype; (2) the typical subtype is associated with statistically more-AD-like cerebrospinal fluid biomarkers values in comparison to the other two subtypes; and (3) in comparison to the subcortical subtype, the cortical subtype subjects are more likely to associate with prescription of cholesterol and high blood pressure medications. In summary, we presented cross-cohort consistent recovery of AD atrophy subtypes, showing how the same subtypes arise even in cohorts capturing substantially different disease phases. Our study opened opportunities for future detailed investigations of atrophy subtypes with a broad range of early risk factors, which will potentially lead to a better understanding of the disease aetiology and the role of lifestyle and behaviour on AD.
Source: NeuroImage
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,450
Funders: EU Joint Programme – Neurodegenerative Disease Research, UK Research and Innovation, National Institute for Health and Care Research, University College London, Agence Nationale de la Recherche, ZonMw, Ministero della Salute, Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, Medical Research Council, Engineering and Physical Sciences Research Council, National Health and Medical Research Council, UCLH Biomedical Research Centre, National Research, Development and Innovation Office
Awards: G134402982, G1735096943, G1852158666, G2442727729, G2632470839, G2714209059, G2810537366, G3010527862, E-DADS: Early Detection of Alzheimer’s Disease Subtypes, Medical image computing for next-generation healthcare technology, I-AIM: Individualised Artificial Intelligence for Medicine, Identifying the genetic architecture of brain health and disease in the presence of heterogeneity and multi-morbidity, G4266322423, G4669776581, G5619513383, MICA: Medical Bioinformatics: Data-Driven Discovery for Personalised Medicine, G7316841254, G7417995046, G7748914543, G8268424837, G844244329, JPND: Early Detection of Alzheimer's Disease Subtypes, Early Detection of Alzheimer’s Disease Subtypes, G8936014493, G902693135
OpenAlex ID: W4323929003
