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Nat Commun. 2018 Oct 15;9(1):4273. doi: 10.1038/s41467-018-05892-0.

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

Collaborators (348)

Andersson C, Archetti S, Arighi A, Benussi L, Binetti G, Black S, Cosseddu M, Fallström M, Ferreira C, Fenoglio C, Freedman M, Fumagalli GG, Gazzina S, Ghidoni R, Grisoli M, Jelic V, Jiskoot L, Keren R, Lombardi G, Maruta C, Meeter L, Mead S, van Minkelen R, Nacmias B, Öijerstedt L, Padovani A, Panman J, Pievani M, Polito C, Premi E, Prioni S, Rademakers R, Redaelli V, Rogaeva E, Rossi G, Rossor M, Scarpini E, Tang-Wai D, Thonberg H, Tiraboschi P, Verdelho A, Weiner MW, Aisen P, Petersen R, Jack CR, Jagust W, Trojanowki JQ, Toga AW, Beckett L, Green RC, Saykin AJ, Morris J, Shaw LM, Khachaturian Z, Sorensen G, Kuller L, Raichle M, Paul S, Davies P, Fillit H, Hefti F, Holtzman D, Mesulam MM, Potter W, Snyder P, Schwartz A, Montine T, Thomas RG, Donohue M, Walter S, Gessert D, Sather T, Jiminez G, Harvey D, Bernstein M, Thompson P, Schuff N, Borowski B, Gunter J, Senjem M, Vemuri P, Jones D, Kantarci K, Ward C, Koeppe RA, Foster N, Reiman EM, Chen K, Mathis C, Landau S, Cairns NJ, Householder E, Taylor-Reinwald L, Lee V, Korecka M, Figurski M, Crawford K, Neu S, Foroud TM, Potkin S, Shen L, Faber K, Kim S, Nho K, Thal L, Buckholtz N, Albert M, Frank R, Hsiao J, Kaye J, Quinn J, Lind B, Carter R, Dolen S, Schneider LS, Pawluczyk S, Beccera M, Teodoro L, Spann BM, Brewer J, Vanderswag H, Fleisher A, Heidebrink JL, Lord JL, Mason SS, Albers CS, Knopman D, Johnson K, Doody RS, Villanueva-Meyer J, Chowdhury M, Rountree S, Dang M, Stern Y, Honig LS, Bell KL, Ances B, Carroll M, Leon S, Mintun MA, Schneider S, Oliver A, Marson D, Griffith R, Clark D, Geldmacher D, Brockington J, Roberson E, Grossman H, Mitsis E, de Toledo-Morrell L, Shah RC, Duara R, Varon D, Greig MT, Roberts P, Albert M, Onyike C, D'Agostino D, Kielb S, Galvin JE, Cerbone B, Michel CA, Rusinek H, de Leon MJ, Glodzik L, De Santi S, Doraiswamy PM, Petrella JR, Wong TZ, Arnold SE, Karlawish JH, Wolk D, Smith CD, Jicha G, Hardy P, Sinha P, Oates E, Conrad G, Lopez OL, Oakley M, Simpson DM, Porsteinsson AP, Goldstein BS, Martin K, Makino KM, Ismail MS, Brand C, Mulnard RA, Thai G, Mc-Adams-Ortiz C, Womack K, Mathews D, Quiceno M, Diaz-Arrastia R, King R, Weiner M, Martin-Cook K, DeVous M, Levey AI, Lah JJ, Cellar JS, Burns JM, Anderson HS, Swerdlow RH, Apostolova L, Tingus K, Woo E, Silverman DH, Lu PH, Bartzokis G, Graff-Radford NR, Parfitt F, Kendall T, Johnson H, Farlow MR, Hake AM, Matthews BR, Herring S, Hunt C, van Dyck CH, Carson RE, MacAvoy MG, Chertkow H, Bergman H, Hosein C, Stefanovic B, Caldwell C, Hsiung GR, Feldman H, Mudge B, Assaly M, Kertesz A, Rogers J, Bernick C, Munic D, Kerwin D, Mesulam MM, Lipowski K, Wu CK, Johnson N, Sadowsky C, Martinez W, Villena T, Turner RS, Johnson K, Reynolds B, Sperling RA, Johnson KA, Marshall G, Frey M, Lane B, Rosen A, Tinklenberg J, Sabbagh MN, Belden CM, Jacobson SA, Sirrel SA, Kowall N, Killiany R, Budson AE, Norbash A, Johnson PL, Allard J, Lerner A, Ogrocki P, Hudson L, Fletcher E, Carmichael O, Olichney J, DeCarli C, Kittur S, Borrie M, Lee TY, Bartha R, Johnson S, Asthana S, Carlsson CM, Potkin SG, Preda A, Nguyen D, Tariot P, Reeder S, Bates V, Capote H, Rainka M, Scharre DW, Kataki M, Adeli A, Zimmerman EA, Celmins D, Brown AD, Pearlson GD, Blank K, Anderson K, Santulli RB, Kitzmiller TJ, Schwartz ES, Sink KM, Williamson JD, Garg P, Watkins F, Ott BR, Querfurth H, Tremont G, Salloway S, Malloy P, Correia S, Rosen HJ, Miller BL, Mintzer J, Spicer K, Bachman D, Pasternak S, Rachinsky I, Drost D, Pomara N, Hernando R, Sarrael A, Schultz SK, Ponto LLB, Shim H, Smith KE, Relkin N, Chaing G, Raudin L, Smith A, Fargher K, Raj BA, Neylan T, Grafman J, Davis M, Morrison R, Hayes J, Finley S, Friedl K, Fleischman D, Arfanakis K, James O, Massoglia D, Fruehling JJ, Harding S, Peskind ER, Petrie EC, Li G, Yesavage JA, Taylor JL, Furst AJ.

Author information

1
Centre for Medical Image Computing, University College London, London, WC1E 6BT, UK. alexandra.young@ucl.ac.uk.
2
Department of Computer Science, University College London, London, WC1E 6BT, UK. alexandra.young@ucl.ac.uk.
3
Centre for Medical Image Computing, University College London, London, WC1E 6BT, UK.
4
Department of Computer Science, University College London, London, WC1E 6BT, UK.
5
Dementia Research Centre, Institute of Neurology, University College London, London, WC1N 3BG, UK.
6
Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology, University College London, London, WC1N 3BG, UK.
7
Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, WC1N 3BG, UK.
8
School of Biomedical Engineering and Imaging Sciences, King's College London, London, WC2R 2LS, UK.
9
Erasmus Medical Center, 3000 CA, Rotterdam, The Netherlands.
10
Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, 25121, Brescia, Italy.
11
Dept. of Physiopathology and Transplantation, University of Milan, Centro Dino Ferrari, 20122, Milan, Italy.
12
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via F. Sforza, 35, 20122, Milan, Italy.
13
Sunnybrook Health Sciences Centre, University of Toronto, ON, M4N 3M5, Canada.
14
Centre for Research in Neurodegenerative Diseases, University of Toronto, ON, Toronto, M5T 0S8, Canada.
15
University of Cambridge, Department of Clinical Neurosciences, Cambridge, CB2 0SZ, UK.
16
Karolinska Institutet, 171 77, Solna, Sweden.
17
Istituto Neurologico Carlo Besta, 20133, Milan, Italy.
18
University Hospitals and University of Geneva, Geneva, Switzerland.
19
Université Laval, Quebec, QC, G1V 0A6, Canada.
20
University of Western Ontario, London, ON, N6A 3K7, Canada.
21
Faculdade de Medicina, Universidade de Lisboa, 1649-028, Lisboa, Portugal.
22
Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, 50121, Florence, Italy.
23
IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.

Abstract

The 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 introduce a machine-learning technique-Subtype and Stage Inference (SuStaIn)-able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer's disease, SuStaIn uncovers three subtypes, uniquely characterising 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 offers new promise for enabling disease subtype discovery and precision medicine.

PMID:
30323170
PMCID:
PMC6189176
DOI:
10.1038/s41467-018-05892-0
[Indexed for MEDLINE]
Free PMC Article

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