Individualized atrophy scores predict dementia onset in familial frontotemporal lobar degeneration

Adam M Staffaroni, Yann Cobigo, Sheng-Yang M Goh, John Kornak, Lynn Bajorek, Kevin Chiang, Brian Appleby, Jessica Bove, Yvette Bordelon, Patrick Brannelly, Danielle Brushaber, Christina Caso, Giovanni Coppola, Reilly Dever, Christina Dheel, Bradford C Dickerson, Susan Dickinson, Sophia Dominguez, Kimiko Domoto-Reilly, Kelly Faber, Jessica Ferrall, Julie A Fields, Ann Fishman, Jamie Fong, Tatiana Foroud, Leah K Forsberg, Ralitza Gavrilova, Debra Gearhart, Behnaz Ghazanfari, Nupur Ghoshal, Jill Goldman, Jonathan Graff-Radford, Neill Graff-Radford, Ian Grant, Murray Grossman, Dana Haley, Hilary W Heuer, Ging-Yuek Hsiung, Edward D Huey, David J Irwin, David T Jones, Lynne Jones, Kejal Kantarci, Anna Karydas, Daniel I Kaufer, Diana R Kerwin, David S Knopman, Ruth Kraft, Joel H Kramer, Walter K Kremers, Walter A Kukull, Irene Litvan, Peter A Ljubenkov, Diane Lucente, Codrin Lungu, Ian R Mackenzie, Miranda Maldonado, Masood Manoochehri, Scott M McGinnis, Emily McKinley, Mario F Mendez, Bruce L Miller, Namita Multani, Chiadi Onyike, Jaya Padmanabhan, Alex Pantelyat, Rodney Pearlman, Len Petrucelli, Madeline Potter, Rosa Rademakers, Eliana Marisa Ramos, Katherine P Rankin, Katya Rascovsky, Erik D Roberson, Emily Rogalski, Pheth Sengdy, Leslie M Shaw, Jeremy Syrjanen, M Carmela Tartaglia, Nadine Tatton, Joanne Taylor, Arthur Toga, John Q Trojanowski, Sandra Weintraub, Ping Wang, Bonnie Wong, Zbigniew Wszolek, Adam L Boxer, Brad F Boeve, Howard J Rosen, ARTFL/LEFFTDS consortium, Adam M Staffaroni, Yann Cobigo, Sheng-Yang M Goh, John Kornak, Lynn Bajorek, Kevin Chiang, Brian Appleby, Jessica Bove, Yvette Bordelon, Patrick Brannelly, Danielle Brushaber, Christina Caso, Giovanni Coppola, Reilly Dever, Christina Dheel, Bradford C Dickerson, Susan Dickinson, Sophia Dominguez, Kimiko Domoto-Reilly, Kelly Faber, Jessica Ferrall, Julie A Fields, Ann Fishman, Jamie Fong, Tatiana Foroud, Leah K Forsberg, Ralitza Gavrilova, Debra Gearhart, Behnaz Ghazanfari, Nupur Ghoshal, Jill Goldman, Jonathan Graff-Radford, Neill Graff-Radford, Ian Grant, Murray Grossman, Dana Haley, Hilary W Heuer, Ging-Yuek Hsiung, Edward D Huey, David J Irwin, David T Jones, Lynne Jones, Kejal Kantarci, Anna Karydas, Daniel I Kaufer, Diana R Kerwin, David S Knopman, Ruth Kraft, Joel H Kramer, Walter K Kremers, Walter A Kukull, Irene Litvan, Peter A Ljubenkov, Diane Lucente, Codrin Lungu, Ian R Mackenzie, Miranda Maldonado, Masood Manoochehri, Scott M McGinnis, Emily McKinley, Mario F Mendez, Bruce L Miller, Namita Multani, Chiadi Onyike, Jaya Padmanabhan, Alex Pantelyat, Rodney Pearlman, Len Petrucelli, Madeline Potter, Rosa Rademakers, Eliana Marisa Ramos, Katherine P Rankin, Katya Rascovsky, Erik D Roberson, Emily Rogalski, Pheth Sengdy, Leslie M Shaw, Jeremy Syrjanen, M Carmela Tartaglia, Nadine Tatton, Joanne Taylor, Arthur Toga, John Q Trojanowski, Sandra Weintraub, Ping Wang, Bonnie Wong, Zbigniew Wszolek, Adam L Boxer, Brad F Boeve, Howard J Rosen, ARTFL/LEFFTDS consortium

Abstract

Introduction: Some models of therapy for neurodegenerative diseases envision starting treatment before symptoms develop. Demonstrating that such treatments are effective requires accurate knowledge of when symptoms would have started without treatment. Familial frontotemporal lobar degeneration offers a unique opportunity to develop predictors of symptom onset.

Methods: We created dementia risk scores in 268 familial frontotemporal lobar degeneration family members by entering covariate-adjusted standardized estimates of brain atrophy into a logistic regression to classify asymptomatic versus demented participants. The score's predictive value was tested in a separate group who were followed up longitudinally (stable vs. converted to dementia) using Cox proportional regressions with dementia risk score as the predictor.

Results: Cross-validated logistic regression achieved good separation of asymptomatic versus demented (accuracy = 90%, SE = 0.06). Atrophy scores predicted conversion from asymptomatic or mildly/questionably symptomatic to dementia (HR = 1.51, 95% CI: [1.16,1.98]).

Discussion: Individualized quantification of baseline brain atrophy is a promising predictor of progression in asymptomatic familial frontotemporal lobar degeneration mutation carriers.

Keywords: Frontotemporal dementia; Genetics; Magnetic resonance imaging (MRI); TDP-43; Tau.

© 2019 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.

Figures

Fig. 1.
Fig. 1.
Steps to create W-score maps, W-volume masks, and W-burden masks. A linear regression was performed on a healthy control group (1A and 1B). A raw W-score map was then created for each subject (1C). Finally, each patient’s W-map was thresholded to produce the W-burden and W-volume masks (1D).
Fig. 2.
Fig. 2.
Individual W-maps for familial FTLD mutation carriers with CDR® plus NACC FTLD = 1. Axial slices displaying W-scores for 6 f-FTLD mutation carriers with (A) MAPT, (B) GRN, and (C) C9orf72 mutations. Abbreviations: FTLD, Frontotemporal lobar degeneration; CDR, Clinical Dementia Rating Scale; NACC, National Alzheimer’s Coordinating Center.
Fig. 3.
Fig. 3.
Distribution of weights in each ROI resulting from the optimization of the logistic regression model. This figure displays the fitted weights (coefficients) associated with each ROI in the logistic regression model. These weights were subsequently used to calculate prediction scores for the survival analysis. Abbreviation: ROI, Region of interest.
Fig. 4.
Fig. 4.
Prediction scores derived from the logistic regression model. Abbreviations: FTLD, frontotemporal lobar degeneration; CDR, Clinical Dementia Rating Scale.
Fig. 5.
Fig. 5.
Kaplan-Meier curve representing survival from CDR® plus NACC FTLD = (0 or 0.5) to 1+. Note: Hash marks indicate censored observations. Abbreviations: FTLD, Frontotemporal lobar degeneration; CDR, Clinical Dementia Rating Scale; NACC, National Alzheimer’s Coordinating Center.

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