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1. Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort

Author

Simuni, T, Merchant, K, Brumm, MC, Cho, H, Caspell-Garcia, C, Coffey, CS, Chahine, LM, Alcalay, RN, Nudelman, K, Foroud, T, Mollenhauer, B, Siderowf, A, Tanner, C, Iwaki, H, Sherer, T, Marek, K, Seibyl, J, Coffey, C, Tosun-Turgut, D, Shaw, LM, Trojanowski, JQ, Singleton, A, Kieburtz, K, Toga, A, Galasko, D, Poewe, W, Poston, K, Bressman, S, Reimer, A, Arnedo, V, Clark, A, Frasier, M, Kopil, C, Chowdhury, S, Casaceli, C, Dorsey, R, Wilson, R, Mahes, S, Salerno, C, Ahrens, M, Brumm, M, Cho, HR, Fedler, J, LaFontant, D-E, Kurth, R, Crawford, K, Casalin, P, Malferrari, G, Weisz, MG, Orr-Urtreger, A, Trojanowski, J, Shaw, L, Montine, T, Baglieri, C, Christini, A, Russell, D, Dahodwala, N, Giladi, N, Factor, S, Hogarth, P, Standaert, D, Hauser, R, Jankovic, J, Saint-Hilaire, M, Richard, I, Shprecher, D, Fernandez, H, Brockmann, K, Rosenthal, L, Barone, P, Espayc, A, Rowe, D, Marder, K, Santiago, A, Hu, S-C, Isaacson, S, Corvol, J-C, Martinez, JR, Tolosa, E, Tai, Y, Politis, M, Smejdir, D, Rees, L, Williams, K, Kausar, F, Richardson, W, Willeke, D, Peacock, S, Sommerfeld, B, Freed, A, Wakeman, K, Blair, C, Guthrie, S, Harrell, L, Hunter, C, Thomas, C-A, James, R, Zimmerman, G, Brown, V, Mule, J, Hilt, E, Ribb, K, Ainscough, S, Wethington, M, Ranola, M, Santana, HM, Moreno, J, Raymond, D, Speketer, K, Carvajal, L, Carvalo, S, Croitoru, I, Garrido, A, Payne, LM, Viswanth, V, Severt, L, Facheris, M, Soares, H, Mintun, MA, Cedarbaum, J, Taylor, P, Biglan, K, Vandenbroucke, E, Sheikh, ZH, Bingol, B, Fischer, T, Sardi, P, Forrat, R, Reith, A, Egebjerg, J, Hillert, GA, Saba, B, Min, C, Umek, R, Mather, J, De Santi, S, Post, A, Boess, F, Taylor, K, Grachev, I, Avbersek, A, Muglia, P, Tauscher, J, and Michael J Fox Foundation

Abstract

We examined 2-year longitudinal change in clinical features and biomarkers in LRRK2 non-manifesting carriers (NMCs) versus healthy controls (HCs) enrolled in the Parkinson’s Progression Markers Initiative (PPMI). We analyzed 2-year longitudinal data from 176 LRRK2 G2019S NMCs and 185 HCs. All participants were assessed annually with comprehensive motor and non-motor scales, dopamine transporter (DAT) imaging, and biofluid biomarkers. The latter included cerebrospinal fluid (CSF) Abeta, total tau and phospho-tau; serum urate and neurofilament light chain (NfL); and urine bis(monoacylglycerol) phosphate (BMP). At baseline, LRRK2 G2019S NMCs had a mean (SD) age of 62 (7.7) years and were 56% female. 13% had DAT deficit (defined as

Published
2022

2. Predicting Progression in Parkinson’s Disease Using Baseline and 1-Year Change Measures

Author

Chahine, LM, Siderowf, A, Barnes, J, Seedorff, N, Caspell-Garcia, C, Simuni, T, Coffey, CS, Galasko, D, Mollenhauer, B, Arnedo, V, Daegele, N, Frasier, M, Tanner, C, Kieburtz, K, Marek, K, Seibyl, J, Coffey, C, Tosun-Turgut, D, Shaw, L, Trojanowski, J, Singleton, A, Toga, A, Chahine, L, Poewe, W, Foroud, T, Poston, K, Sherer, T, Chowdhury, S, Kopil, C, Casaceli, C, Dorsey, R, Wilson, R, Mahes, S, Salerno, C, Crawford, K, Casalin, P, Malferrari, G, Weisz, MG, Orr-Urtreger, A, Montine, T, Russell, D, Dahodwala, N, Giladi, N, Factor, S, Hogarth, P, Standaert, D, Hauser, R, Jankovic, J, Saint-Hilaire, M, Richard, I, Shprecher, D, Fernandez, H, Brockmann, K, Rosenthal, L, Barone, P, Espay, A, Rowe, D, Marder, K, Santiago, A, Bressman, S, Hu, S-C, Isaacson, S, Corvol, J-C, Ruiz Martinez, J, Tolosa, E, Tai, Y, Politis, M, Smejdir, D, Rees, L, Williams, K, Kausar, F, Richardson, W, Willeke, D, Peacock, S, Sommerfeld, B, Freed, A, Wakeman, K, Blair, C, Guthrie, S, Harrell, L, Hunter, C, Thomas, C-A, James, R, Zimmerman, G, Brown, V, Mule, J, Hilt, E, Ribb, K, Ainscough, S, Wethington, M, Ranola, M, Santana, HM, Moreno, J, Raymond, D, Speketer, K, Carvajal, L, Carvalho, S, Croitoru, I, Garrido, A, Payne, LM, Viswanth, V, Severt, L, Facheris, M, Soares, H, Mintun, MA, Cedarbaum, J, Taylor, P, Biglan, K, Vandenbroucke, E, Sheikh, ZH, Bingol, B, Fischer, T, Sardi, P, Forrat, R, Reith, A, Egebjerg, J, Hillert, GA, Saba, B, Min, C, Umek, R, Mather, J, De Santi, S, Post, A, Boess, F, Taylor, K, Grachev, I, Avbersek, A, Muglia, P, Merchant, K, Tauscher, J, and Michael J Fox Foundation

Subjects
Male, Research Report, 0301 basic medicine, Movement disorders, Parkinson's disease, MOTOR PROGRESSION, Disease, 0601 Biochemistry and Cell Biology, Severity of Illness Index, Behavior disorder, PROGNOSTIC-FACTORS, 0302 clinical medicine, BOOTSTRAP, Medicine, Parkinson’s disease, biomarkers, disease progression, surrogate endpoint, Prospective Studies, RATING-SCALE, Brain, Parkinson Disease, Middle Aged, SPECT, Female, medicine.symptom, Life Sciences & Biomedicine, medicine.medical_specialty, Disease duration, Rapid eye movement sleep, The Parkinson’s Progression Markers Initiative, 03 medical and health sciences, Cellular and Molecular Neuroscience, Rating scale, Internal medicine, Humans, Aged, Dopamine Plasma Membrane Transport Proteins, Science & Technology, IDENTIFICATION, business.industry, Surrogate endpoint, Neurosciences, medicine.disease, 030104 developmental biology, SLEEP BEHAVIOR DISORDER, Neurosciences & Neurology, Neurology (clinical), sense organs, TAU, 1109 Neurosciences, business, 030217 neurology & neurosurgery
Abstract

Author(s): Chahine, Lana M; Siderowf, Andrew; Barnes, Janel; Seedorff, Nicholas; Caspell-Garcia, Chelsea; Simuni, Tanya; Coffey, Christopher S; Galasko, Douglas; Mollenhauer, Brit; Arnedo, Vanessa; Daegele, Nichole; Frasier, Mark; Tanner, Caroline; Kieburtz, Karl; Marek, Kenneth; The Parkinson’s Progression Markers Initiative | Abstract: BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.

Published
2019

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