Fully Bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression
Joana B Pereira,
for the Alzheimer’s Disease Neuroimaging Initiative
Posted 25 Nov 2019
bioRxiv DOI: 10.1101/854356 (published DOI: 10.18632/aging.103623)
Posted 25 Nov 2019
Tau pathology and regional brain atrophy are the closest correlate of cognitive decline in Alzheimer’s disease (AD). Understanding heterogeneity and longitudinal progression of brain atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows to study confounding effects, 5) provides clusters visualization, 6) measures clustering uncertainty, all these simultaneously. We used amyloid-β positive AD and negative healthy subjects, three longitudinal sMRI scans (cortical thickness and subcortical volume) over two years. We found 3 distinct longitudinal AD brain atrophy patterns: a typical diffuse pattern (n=34, 47.2%), and 2 atypical patterns: Minimal atrophy (n=23 31.9%) and Hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.
- Downloaded 277 times
- Download rankings, all-time:
- Site-wide: 90,107
- In neuroscience: 13,941
- Year to date:
- Site-wide: 111,890
- Since beginning of last month:
- Site-wide: 92,778
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!