Characterising heterogeneous disease trajectories in neurodegenerative conditions using Subtype and Stage Inference

Mapping the progression and heterogeneity of a disease can provide insights into the disease biology and a mechanism for stratifying individuals. Disease progression models can identify the stages of a disease from a dataset of individuals on a common disease trajectory. Clustering tools can identify subtype heterogeneity from a dataset of individuals at a common disease stage. However, commonly within a dataset, there is variability in both disease subtype and stage. This variability confounds the use of disease progression models to identify disease stages and the use of clustering tools to identify disease subtypes. The Subtype and Stage Inference (SuStaIn) algorithm combines ideas from disease progression modeling and clustering to identify subgroups of individuals with distinct progression patterns, simultaneously resolving both progression stages and subtype heterogeneity. In this talk, Dr Young will present the SuStaIn algorithm (PMID: 30323170) and applications to imaging, biomarker, and pathology data, primarily in neurodegenerative diseases but also more broadly in other chronic conditions such as psychiatric disorders and lung diseases. In particular, Dr. Young will focus on recent developments and applications of SuStaIn that use longitudinal data to infer the timescale of disease progression patterns and characterize mixed pathology.