PPMI Cognitive-Behavioral Working Group Daniel Weintraub, MD PPMI - PowerPoint PPT Presentation

PPMI Cognitive-Behavioral Working Group Daniel Weintraub, MD PPMI Annual Meeting - May 13-14, 2015

Membership Daniel Weintraub – WG Chair Tanya Simuni – Steering Committee Shirley Lasch – IND Chris Coffey, Chelsea Caspell-Garcia – Statistics Core Dag Aarsland Keith Hawkins Roy Alcalay David Hewitt Paolo Barone Jim Leverenz Melanie Braddabur Irene Litvan David Burn Anita McCoy Cindy Casacelli Susanne Ostrowitzki Lama Chahine Bernard Ravina William Cho Alistair Reith Thomas Comery Irene Richard Autilia Cozzolino Liana Rosenthal Johnna Devoto Holly Shill Chris Dodds Andrew Siderowf Jamie Eberling John Sims Alberto Espay Gretchen Todd Stewart Factor Eduardo Tolosa Hubert Fernandez Matt Troyer Regan Fong Michael Ward Douglas Galasko Michele York Sandeep Gupta

Overview • Review of assessments • Baseline manuscript from CBWG • Preliminary longitudinal results • Individuals’ work

Study Assessments

Cognitive Assessments • Global - Montreal Cognitive Assessment (MoCA) ----------------------------------------------------------------- • Memory - Hopkins Verbal Learning Test (HVLT) • Visuospatial - Benton Judgment of Line Orientation (JOLO) • Working memory - Letter-Number Sequencing (LNS) • Executive - Semantic fluency (animals, fruits, vegetables) • Attention - Symbol-Digit Modalities Test (SDMT)

Behavioral Assessments • Geriatric Depression Scale (GDS-15) • State-Trait Anxiety (STAI) – State and trait subscales • Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease (QUIP) – Screening instrument for ICDs and related behaviors • MDS-UPDRS Part I (psychosis, apathy, etc.)

Steps for Determining Annual Cognitive Diagnosis in PPMI 1. Investigator determines presence of cognitive decline from pre-PD state based on clinical interview and knowledge of patient 2. Investigator determines presence of significant functional impairment due to cognitive deficits interfering with routine instrumental activities of daily living (IADLs) 3. Subject has neuropsychological testing at study visit 4. Categorization of normal cognition, MCI, or dementia made centrally based on steps #1, #2 and #3

Baseline CBWG Manuscript

• 20% of PD patients screen positive for MCI and close to 10% meet cognitive test-based criteria • Multiple NPS (e.g., depression, anxiety and apathy) more common in untreated PD patients compared with general population • Rates of NPS associated with DRT (e.g., psychosis and ICDs) either low or similar to controls Weintraub et al. Movement Disorders (10.1002/mds.26170).

Preliminary Longitudinal Results: Cognition and Biomarkers Courtesy Chelsea Caspell-Garcia, MS

Cohort Size (data submitted as of 4/13/15) Baseline Year 1 Year 2 Year 3 # Seen (%) # Seen (%) # Seen (%) # Seen (%) GROUPS: PD Subjects 423 (100%) 393 (96%) 318 (91%) 145 (87%) Healthy Controls 196 (100%) 185 (98%) 158 (95%) 125 (93%) TOTAL 619 (100%) 578 (97%) 476 (92%) 270 (90%)

Psychiatric and Cognitive Outcomes

Baseline DAT as Predictor of Global Cognition and Depression Over Time Depression Cognition Univariate Univariate Univariate Univariate Variable Estimate (95% CI) p-value Variable Estimate (95% CI) p-value Contralateral Caudate -0.251 (-0.60, 0.09) 0.1529 Contralateral Caudate 0.303 (-0.12, 0.72) 0.1577 Ipsilateral Caudate 0.270 (-0.13, 0.67) 0.1842 Ipsilateral Caudate -0.140 (-0.46, 0.18) 0.3968 Contralateral Putamen -0.303 (-1.22, 0.61) 0.5156 Contralateral Putamen -0.241 (-0.99, 0.51) 0.5272 Ipsilateral Putamen 0.469 (-0.16, 1.10) 0.1415 Ipsilateral Putamen -0.090 (-0.60, 0.42) 0.7257 Contralateral Striatum 0.132 (-0.18, 0.44) 0.4091 Contralateral Striatum -0.166 (-0.42, 0.09) 0.2017 Ipsilateral Striatum 0.199 (-0.06, 0.46) 0.1368 Ipsilateral Striatum -0.076 (-0.29, 0.14) 0.4826 Mean Caudate 0.308 (-0.12, 0.73) 0.1551 Mean Caudate -0.207 (-0.55, 0.14) 0.2408 Mean Putamen 0.278 (-0.54, 1.10) 0.5046 Mean Putamen -0.173 (-0.84, 0.49) 0.6093 Mean Striatum 0.378 (-0.22, 0.98) 0.2142 Mean Striatum -0.250 (-0.74, 0.24) 0.3127 Analyses adjusted for age, gender, education, APOE e4 status, and PD medication use.

Baseline AD CSF Biomarkers as Predictors of Global Cognitive Decline Univariate Univariate Variable Estimate (95% CI) p-value A-Beta 1-42 0.0017 (-0.0004, 0.0037) 0.11 t-tau -0.0008 (-0.0029, 0.0013) 0.45 p-tau 0.0008 (-0.0012, 0.0027) 0.45 t-tau/A-Beta 1-42 -0.0023 (-0.0045, -0.0002) 0.03 • Lower A-Beta 1-42 associated with lower MoCA scores (marginal). • Higher t-tau/A-Beta 1-42 associated with lower MoCA scores. Analyses adjusted for age, gender, education, APOE e4 status, and PD medication use.

Draft Planned Analyses Baseline Change in Cognitive STATUS From Baseline Change in Individual MoCA score MoCA <26 Any 2 tests >1.5 SD NEW MoCA <26 LAST MoCA >3 NEW any last 2 NEW MCI NEW dementia Cognition SCORES below mean (last point) point decrease from tests >1.5 SD below diagnosis diagnosis From Baseline BL mean Cognitive Clinical Outcome N/A N (%) N (%) N (%) N (%) N (%) N (%) N (%) N/A Biomarker Baseline Change BL to Year 1 CSF CSF 1. A-syn 1. A-syn 2. t-tau 2. t-tau 3. ptau 181 3. ptau 181 4. AB 1-42 4. AB 1-42 5. t-tau/AB 1-42 5. t-tau/AB 1-42 6. ptau 181 /AB 1-42 6.ptau 181 /AB 1-42 7. p-tau 181 /t-tau 7. p-tau 181 /t-tau Plasma 1. Urate 2. α -synuclein 3. IGF Structural MRI Structural MRI 1. Major ROI’s 1. Major ROI’s 2. Cortical thickness 2. Cortical thickness 3. Subcortical 3. Subcortical DTI DTI 1. FA (anisotropy) 1. FA (anisotropy) 2. MD (diffusivity) 2. MD (diffusivity) DAT DAT 1. Mean striatal 1. Mean striatal 2. Mean putamen 2. Mean putamen 3. Mean caudate 3. Mean caudate 4. Ipsi. caudate 4. Ipsi. caudate 5. Contra. caudate 5. Contra. caudate 6. Ipsi. putamen 6. Ipsi. putamen 7. Contra. putamen 7. Contra. putamen Genetics 1. APOE 2. GBA 3. LRRK 4. Synuclein (SNCA) 5. MAPT 6. COMT 7. HLA 8. KLOTHO

Individuals’ Work

Early Disease Course: Depression de al Riva et al. Neurology 2014;83:1096-1103.

Early Disease Course: Psychosis Variable PD Healthy Statistic df p-value Subjects Controls (Chi- 12 24 Change Change Psychosis BL UPDRS Part I (N = 423) (N = 196) square) months months in PD between “The frequency of new-onset psychosis was (% present) Hallucinations and over time groups nearly three times as high in the DRT group Psychosis item over time compared with the untreated group.” 3.1% 5.4 % 10.4% PD (13/423) (14/261) (10/96) Negative 410 (97%) 194 (99%) 11.64 (2), 1.49 (2), 0.5% 0% 2.4% HC 3.95 1 0.047 p=0.003 0.59 Any positive score 13 (3%) 1 (1%) (1/195) (0/145) (2/83) Fischer test, p 0.076 0.003 0.038 de al Riva et al. Neurology 2014;83:1096-1103.

Early Disease Course: Global Cognition de al Riva et al. Neurology 2014;83:1096-1103.

Impact of DRT Initiation de al Riva et al. Neurology 2014;83:1096-1103.

Change in DAT Availability and Incident ICD Behaviors All subjects Subjects on DRT OR P OR P Baseline DAT binding Right caudate 1.07 .82 1.12 .71 Left caudate .905 .70 .94 .84 Right putamen .77 .58 .99 .99 Left putamen .55 .18 .78 .63 Mean total striatal .82 .64 .99 .98 Change in DAT binding (baseline-year 1) Right caudate 2.75 .08 4.03 .01 Left caudate 1.58 .35 1.78 .26 Right putamen 2.37 .33 3.28 .25 Left putamen 1.66 .48 2.52 .24 Mean total striatal 4.04 .14 6.90 .04 DAT binding (post-baseline) Right caudate .66 .31 .47 .07 Left caudate .66 .31 .62 .32 Right putamen .17 .04 .06 .01 Left putamen .17 .03 .15 .07 Mean total striatal .36 .09 .25 .04 Smith et al. (unpublished data ) .

(Logistic regression model) Genes implicating serotonin, dopamine and opioid systems. Another model implicated noradrenergic system. Smith et al. (unpublished data) . In collaboration with Julia Kraemmer and JC Corvol.

CBWG Members: Published or In Progress Dag Aarsland and colleagues • – Lebedev et al. Large-scale resting state network correlates of cognitive impairment in Parkinson's disease and related dopaminergic deficits. Frontiers in systems neuroscience, 2014. – Siepel et al. Cognitive executive impairment and dopaminergic deficits in de novo Parkinson's disease. Movement Disorders, 2014. – Pereira et al. Initial cognitive decline is associated with cortical thinning in early Parkinson disease. Neurology, 2014. – Pereira et al. Aberrant cerebral network topology and mild cognitive impairment in early Parkinson’s disease. Human Brain Mapping, 2015. – Skogseth et al. Associations between cerebrospinal fluid biomarkers and cognition in early Parkinson’s disease (submitted). – Pereira et al. Cerebrospinal fluid Aβ 1-42 levels are associated with functional network disruption in early Parkinson’s disease (submitted).

Liu et al. Neurology 2015;8:1-9.

Neuropsychiatric Symptoms in SWEDDs Sprenger et al. Movement Disorders 2015 (10.1002/mds.26204).

CPWG Members: Sampling of Ongoing Work • Lama Chahine - Baseline sleep and daytime sleepiness symptoms as predictors of cognitive decline • Alberto Espay - Differential effect of dopaminergic medications on depression and anxiety symptoms • Maria Teresa Pellecchia and Paolo Barone - Insulin- like growth factor-1 (IGF) as biomarker for early cognitive impairment • Roy Alcalay - CSF β -amyloid 1-42 predicting progression to cognitive impairment