Cameron Miller-Patterson1, Jennifer Han2, Kristine Yaffe3, Andrea L Rosso4, Lenore J Launer5, Stephen B Kritchevsky6, Robert M Boudreau4, Caterina Rosano4. 1. University of Pittsburgh School of Medicine, Department of Neurology, 3550 Terrace St, Pittsburgh, PA, 15213, USA. Electronic address: millerpatterson@gmail.com. 2. University of Pittsburgh School of Medicine, Department of Neurology, 3550 Terrace St, Pittsburgh, PA, 15213, USA. 3. University of California San Francisco School of Medicine, Department of Psychiatry, 533 Parnassus Ave, San Francisco, CA, 94143, USA; University of California San Francisco School of Medicine, Department of Neurology, 533 Parnassus Ave, San Francisco, CA, 94143, USA; University of California San Francisco School of Medicine, Department of Epidemiology, 533 Parnassus Ave, San Francisco, CA, 94143, USA. 4. University of Pittsburgh School of Public Health, Department of Epidemiology, 130 De Soto St, Pittsburgh, PA, 15213, USA. 5. National Institutes of Health, 251 Bayview Blvd, Bethesda, MD, 21224, USA; National Institute on Aging, 251 Bayview Blvd, Bethesda, MD, 21224, USA. 6. Wake Forest University School of Medicine, Stricht Center for Healthy Aging and Alzheimer's Prevention, Winston-Salem, NC, USA.
Abstract
INTRODUCTION: Mild parkinsonian signs (MPS) are associated with morbidity. Identification of MPS progression markers may be vital for preventive management, yet has not been pursued. This study aimed to ascertain clinical/neuroimaging features predictive of MPS progression. METHODS: 205 participants in the Health ABC Study were included. MPS was defined using published guidelines. MPS progression was evaluated by determining UPDRS-III change between baseline and follow-up ≥2 years later. Standard brain MRI and DTI were obtained at baseline. Correlation coefficients between demographics, vascular risk factors, imaging markers, and UPDRS-III change were adjusted for follow-up time. Linear regression was used to adjust for possible confounders in the relationship between imaging markers and MPS progression. RESULTS: 30% of participants had baseline MPS. Demographics and risk factors did not differ significantly between participants with MPS (MPS+) and without MPS (MPS-). Mean follow-up time was 3.8±0.8 years. Older age, male gender, diabetes were associated with faster rate of UPDRS-III change in MPS- but not MPS+ participants. Among MPS- participants, the only imaging marker associated with faster UPDRS-III progression was higher gray matter mean diffusivity (MD), widespread in various cortico-subcortical bihemispheric regions, independent of age, gender, diabetes. No imaging features were associated with UPDRS-III change among MPS+ participants. CONCLUSIONS: Lower gray matter integrity predicted MPS progression in those who did not have baseline MPS. Microstructural imaging may capture early changes related to MPS development, prior to macrostructural change. Any future management promoting gray matter preservation may inhibit MPS development.
INTRODUCTION: Mild parkinsonian signs (MPS) are associated with morbidity. Identification of MPS progression markers may be vital for preventive management, yet has not been pursued. This study aimed to ascertain clinical/neuroimaging features predictive of MPS progression. METHODS: 205 participants in the Health ABC Study were included. MPS was defined using published guidelines. MPS progression was evaluated by determining UPDRS-III change between baseline and follow-up ≥2 years later. Standard brain MRI and DTI were obtained at baseline. Correlation coefficients between demographics, vascular risk factors, imaging markers, and UPDRS-III change were adjusted for follow-up time. Linear regression was used to adjust for possible confounders in the relationship between imaging markers and MPS progression. RESULTS: 30% of participants had baseline MPS. Demographics and risk factors did not differ significantly between participants with MPS (MPS+) and without MPS (MPS-). Mean follow-up time was 3.8±0.8 years. Older age, male gender, diabetes were associated with faster rate of UPDRS-III change in MPS- but not MPS+ participants. Among MPS- participants, the only imaging marker associated with faster UPDRS-III progression was higher gray matter mean diffusivity (MD), widespread in various cortico-subcortical bihemispheric regions, independent of age, gender, diabetes. No imaging features were associated with UPDRS-III change among MPS+ participants. CONCLUSIONS: Lower gray matter integrity predicted MPS progression in those who did not have baseline MPS. Microstructural imaging may capture early changes related to MPS development, prior to macrostructural change. Any future management promoting gray matter preservation may inhibit MPS development.
Authors: Aron S Buchman; Joshua M Shulman; Sukriti Nag; Sue E Leurgans; Steven E Arnold; Martha C Morris; Julie A Schneider; David A Bennett Journal: Ann Neurol Date: 2012-02 Impact factor: 10.422
Authors: Karlijn F de Laat; Andrew T Reid; David C Grim; Alan C Evans; Rolf Kötter; Anouk G W van Norden; Frank-Erik de Leeuw Journal: Neuroimage Date: 2011-08-11 Impact factor: 6.556
Authors: Vijay K Venkatraman; Howard J Aizenstein; Anne B Newman; Kristine Yaffe; Tamara Harris; Stephen Kritchevsky; Hilsa N Ayonayon; Caterina Rosano Journal: Front Aging Neurosci Date: 2011-09-27 Impact factor: 5.750