Distinct subtypes of behavioral variant frontotemporal dementia based on patterns of network degeneration

Kamalini G. Ranasinghe, Katherine P. Rankin, Peter S. Pressman, David C. Perry, Iryna V. Lobach, William W. Seeley, Giovanni Coppola, Anna M. Karydas, Lea T. Grinberg, Tal Shany-Ur, Suzee E. Lee, Gil D. Rabinovici, Howard J. Rosen, Maria Luisa Gorno-Tempini, Adam L. Boxer, Zachary A. Miller, Winston Chiong, Mary DeMay, Joel H. Kramer, Katherine L. PossinVirginia E. Sturm, Brianne M. Bettcher, Michael Neylan, Diana D. Zackey, Lauren A. Nguyen, Robin Ketelle, Nikolas Block, Teresa Q. Wu, Alison Dallich, Natanya Russek, Alyssa Caplan, Daniel H. Geschwind, Keith A. Vossel, Bruce L. Miller

Research output: Contribution to journalArticle

49 Scopus citations

Abstract

IMPORTANCE Clearer delineation of the phenotypic heterogeneity within behavioral variant frontotemporal dementia (bvFTD) will help uncover underlying biological mechanisms and improve clinicians' ability to predict disease course and to design targeted management strategies. OBJECTIVE To identify subtypes of bvFTD syndrome based on distinctive patterns of atrophy defined by selective vulnerability of specific functional networks targeted in bvFTD using statistical classification approaches. DESIGN, SETTING AND PARTICIPANTS In this retrospective observational study, 90 patients meeting the Frontotemporal Dementia Consortium consensus criteria for bvFTD underwent evaluation at the Memory and Aging Center of the Department of Neurology at University of California, San Francisco. Patients underwent a multidisciplinary clinical evaluation, including clinical demographics, genetic testing, symptom evaluation, neurologic examination, neuropsychological bedside testing, and socioemotional assessments. All patients underwent structural magnetic resonance imaging at their earliest evaluation at the memory clinic. From each patient's structural imaging scans, the mean volumes of 18 regions of interest (ROI) constituting the functional networks specifically vulnerable in bvFTD, including the salience network (SN), with key nodes in the frontoinsula and pregenual anterior cingulate, and the semantic appraisal network (SAN), anchored in the anterior temporal lobe and subgenual cingulate, were estimated. Principal component and cluster analyses of ROI volumes were used to identify patient clusters with anatomically distinct atrophy patterns. Data were collected from from June 19, 2002, to January 13, 2015. MAIN OUTCOMES AND MEASURES Evaluation of brain morphology and other clinical features, including presenting symptoms, neurologic examination signs, neuropsychological performance, rate of dementia progression, and socioemotional function, in each patient cluster. RESULTS Ninety patients (54 men [60%]; 36 women [40%]; mean [SD] age at evaluation, 55.1 [9.7] years) were included in the analysis. Four subgroups of patients with bvFTD with distinct anatomic patterns of network degeneration were identified, including 2 salience network-predominant subgroups (frontal/temporal [SN-FT] and frontal [SN-F]), a semantic appraisal network-predominant group (SAN), and a subcortical-predominant group. Subgroups demonstrated distinct patterns of cognitive, socioemotional, and motor symptoms, as well as genetic compositions and estimated rates of disease progression. CONCLUSIONS AND RELEVANCE Divergent patterns of vulnerability in specific functional network components make an important contribution to the clinical heterogeneity of bvFTD. The data-driven anatomic classification identifies biologically meaningful anatomic phenotypes and provides a replicable approach to disambiguate the bvFTD syndrome.

Original languageEnglish (US)
Pages (from-to)1078-1088
Number of pages11
JournalJAMA Neurology
Volume73
Issue number9
DOIs
StatePublished - Sep 1 2016

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