Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Abstract

SummaryThe heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we present a new machine learning technique – Subtype and Stage Inference (SuStaIn) – able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available crosssectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal new subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes, and characterises within-group heterogeneity for the first time. In Alzheimer’s disease, SuStaIn uncovers three subtypes, uniquely revealing their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p=7.18×10--4) or temporal stage (p=3.96×10−5). SuStaIn thus offers new promise for enabling disease subtype discovery and precision medicine.

Aging related cognitive changes associated with Alzheimer's disease in Down syndrome

“…Previous EBM models have shown that in sporadic AD, changes in cognitive abilities, including memory and attention, follow changes in CSF biomarkers, but occur before brain volumetric changes. 16,42 The cognitive tests used in these models have tended to combine several cognitive processes. Here, by including tests for more specific cognitive processes as separate biomarkers, we can look more closely at the sequence of decline in populations where obtaining CSF biomarkers, for example, may be challenging.…”

Adiposity‐related insulin resistance and thickness of the cerebral cortex in middle‐aged adults

“…Thickness of the cerebral cortex decreases with ageing 10,11 . Accelerated cortical thinning is a characteristic feature of cognitive impairment and dementia and may start years before clinical diagnosis 12 . Furthermore, the current understanding is that both obesity and T2DM accelerate brain ageing, and that ageing of the cerebral cortex demonstrates sex‐specific trajectories, with a gradual shift beginning in midlife (around age 50‐59 years) 10,13‐16 …”

Neurological update: neuroimaging in dementia

“…Changes in brain structure continue to provide insight, particularly on the subtypes of disease. For example, the identification of distinct atrophy patterns associated with different rates of disease progression in Alzheimer’s disease and Frontotemporal Dementia [ 9 ]. The SuStaIn model used in this work adds to an understanding of clinical heterogeneity in disease progression by associating differential rates of changes over time with specific patterns of atrophy.…”