{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T14:41:27Z","timestamp":1791816087103,"version":"4.3.4"},"reference-count":91,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,2,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Clinical variants of Alzheimer\u2019s disease and frontotemporal lobar degeneration display a spectrum of cognitive-behavioural changes varying between individuals and over time. Understanding the landscape of these graded individual\/group level longitudinal variations is critical for precise phenotyping; however, this remains challenging to model.<\/jats:p>\n               <jats:p>Addressing this challenge, we leverage the National Alzheimer\u2019s Coordinating Center database to derive a unified geometric framework of graded longitudinal phenotypic variation in Alzheimer\u2019s disease and frontotemporal lobar degeneration. We included three time point, cognitive-behavioural and clinical data from 390 typical, atypical and intermediate Alzheimer\u2019s disease and frontotemporal lobar degeneration variants (114 typical Alzheimer\u2019s disease; 107 behavioural variant frontotemporal dementia; 42 motor variants of frontotemporal lobar degeneration; and 103 primary progressive aphasia patients). On these data, we applied advanced data-science approaches to derive low-dimensional geometric spaces capturing core features underpinning clinical progression of Alzheimer\u2019s disease and frontotemporal lobar degeneration syndromes.<\/jats:p>\n               <jats:p>To do so, we first used principal component analysis to derive six axes of graded longitudinal phenotypic variation capturing patient-specific movement along and across these axes. Then, we distilled these axes into a visualizable 2D manifold of longitudinal phenotypic variation using Uniform Manifold Approximation and Projection. Both geometries together enabled the assimilation and interrelation of paradigmatic and mixed cases, capturing dynamic individual trajectories and linking syndromic variability to neuropathology and key clinical end points, such as survival.<\/jats:p>\n               <jats:p>Through these low-dimensional geometries, we show that (i) specific syndromes (Alzheimer\u2019s disease and primary progressive aphasia) converge over time into a de-differentiated pooled phenotype, while others (frontotemporal dementia variants) diverge to look different from this generic phenotype; (ii) phenotypic diversification is predicted by simultaneous progression along multiple axes, varying in a graded manner between individuals and syndromes; and (iii) movement along specific principal axes predicts survival at 36 months in a syndrome-specific manner and in individual pathological groupings. The resultant mapping of dynamics underlying cognitive-behavioural evolution potentially holds paradigm-changing implications to predicting phenotypic diversification and phenotype-neurobiological mapping in Alzheimer\u2019s disease and frontotemporal lobar degeneration.<\/jats:p>","DOI":"10.1093\/brain\/awae233","type":"journal-article","created":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T21:59:50Z","timestamp":1721080790000},"page":"448-466","source":"Crossref","is-referenced-by-count":16,"title":["The graded multidimensional geometry of phenotypic variation and progression in neurodegenerative syndromes"],"prefix":"10.1093","volume":"148","author":[{"given":"Siddharth","family":"Ramanan","sequence":"first","affiliation":[{"name":"Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge , Cambridge CB2 7EF 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, Cambridge CB2 7EF ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kieren","family":"Allinson","sequence":"additional","affiliation":[{"name":"Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge , Cambridge CB2 0SZ ,","place":["UK"]},{"name":"Department of Pathology, Cambridge University Hospitals NHS Trust , Cambridge CB2 1QP ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1927-7424","authenticated-orcid":false,"given":"Karalyn","family":"Patterson","sequence":"additional","affiliation":[{"name":"Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge , Cambridge CB2 7EF ,","place":["UK"]},{"name":"Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge , Cambridge CB2 0SZ ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James B","family":"Rowe","sequence":"additional","affiliation":[{"name":"Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge , Cambridge CB2 7EF ,","place":["UK"]},{"name":"Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge , Cambridge CB2 0SZ ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5907-2488","authenticated-orcid":false,"given":"Matthew A","family":"Lambon Ralph","sequence":"additional","affiliation":[{"name":"Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge , Cambridge CB2 7EF 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