Daniel Weintraub
VerifiedUniversity of Pennsylvania · Rehabilitation Medicine
Active 1969–2026
About
Daniel Weintraub, MD, is a Professor of Psychiatry at the Hospital of the University of Pennsylvania and an Attending Physician at the same institution in Philadelphia, PA. He also serves as a Consultant Psychiatrist at the Parkinson's Disease and Movement Disorders Center (PDMDC) at the Hospital of the University of Pennsylvania, working half a day every other week. His department is Psychiatry, and he is affiliated with the Section of Geriatric Psychiatry. Dr. Weintraub's educational background includes a B.A. in History from the University of North Carolina, Chapel Hill, obtained in 1985, and an M.D. from the University of Maryland, Baltimore, completed in 1991. His research expertise focuses on neurodegenerative and mental disorders in late life, including Parkinson's disease, Alzheimer's disease, depression, dementia, mild cognitive impairment, impulse control disorders, and psychosis. His work involves understanding the pathology, clinical features, and potential interventions for these conditions, contributing to the field through numerous publications.
Research topics
- Medicine
- Psychology
- Internal medicine
- Psychiatry
- Pathology
- Computer Science
- Neuroscience
- Bioinformatics
- Family medicine
- Biology
- Oncology
- Surgery
- Radiology
- Anesthesia
Selected publications
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-21
articleOpen accessThe shared code was created to perform analysis for the published article "Prodromal Lewy body disorder features in REM sleep behavior disorder with biomarker-defined synucleinopathy" (<article link to be added once published>). This code was created to analyze data accessed from the PPMI database (RRID:SCR 006431) on January 21, 2025. As the PPMI database is always evolving, it is possible that the code may not work if the database has changed since the date the code was created. Analytic datasets are not included in the submission. Researchers can request access to PPMI data at the PPMI Study website (https://www.ppmi-info.org/access-data-specimens/download-data).
Zenodo (CERN European Organization for Nuclear Research) · 2026-01-01
articleOpen accessSenior authorThe shared code was created to perform analysis for the published article "Prodromal Lewy body disorder features in REM sleep behavior disorder with biomarker-defined synucleinopathy" (<article link to be added once published>). This code was created to analyze data accessed from the PPMI database (RRID:SCR 006431) on January 21, 2025. As the PPMI database is always evolving, it is possible that the code may not work if the database has changed since the date the code was created. Analytic datasets are not included in the submission. Researchers can request access to PPMI data at the PPMI Study website (https://www.ppmi-info.org/access-data-specimens/download-data).
Annals of Clinical and Translational Neurology · 2026-04-21 · 1 citations
articleOpen access1st authorCorrespondingOBJECTIVE: Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal state for Lewy body disorders and exhibits biological heterogeneity that may influence clinical expression and progression. We examined clinical features in individuals with iRBD and biomarker-defined synucleinopathy. METHODS: Parkinson's Progression Markers Initiative (PPMI) is a longitudinal, multi-center observational study. Participants included polysomnogram (PSG)-confirmed iRBD individuals who were cerebrospinal fluid (CSF) α-synuclein seed amplification assay positive with no clinical diagnosis of Parkinson's disease or dementia with Lewy bodies, along with robust healthy controls (HCs). Clinical and biological features of prodromal PD and DLB, including mild cognitive impairment (MCI), subthreshold parkinsonism, and a range of neuropsychiatric, autonomic, and sensory symptoms, were assessed. RESULTS: Compared with HCs (N = 136), iRBD participants (N = 197) demonstrated worse cognitive performance, including a lower cognitive summary score (p < 0.0003, effect size = 0.41), and higher odds of subthreshold parkinsonism (OR = 24.5), and neuropsychiatric (OR = 3.5), autonomic (OR = 7.2) and sensory symptoms (OR = 13.2). Common features included hyposmia (75%), pain (54%), urinary problems (52%), constipation (49%), lightheadedness (40%) and anxiety (36%), whereas rates of MCI (32%), subthreshold parkinsonism (27%) and psychosis (7%) were lower. iRBD participants with abnormal dopamine transporter imaging had higher anxiety scores and antidepressant use. Although only 10% met criteria for prodromal DLB due to the requirement for MCI, most exhibited multi-domain impairment. INTERPRETATION: iRBD with synucleinopathy is associated with multi-domain clinical impairment before clinical neurodegenerative disease diagnosis, supporting broad clinical assessment in early biomarker-defined synuclein disease.
Synuclein and dopamine transporter biomarkers among phenoconverters to parkinsonian disorders
medRxiv · 2026-04-20
articleAbstract Background Phenoconversion to Parkinson’s disease (PD) or dementia with Lewy bodies (DLB) currently relies on established clinical diagnostic criteria. Availability of in vivo biomarkers—CSF α-synuclein seed amplification assay (CSFaSynSAA) and dopamine transporter (DAT) imaging—offer the opportunity to investigate congruency between clinical phenoconversion and biologically defined disease. Methods We analyzed Parkinsońs Progression Markers Initiative participants who phenoconverted to PD, DLB, multiple system atrophy (MSA), Alzheimer’s disease (AD) or other dementias from prodromal and non-manifesting genetic carrier (NMC) groups and controls. Site investigators determined phenoconversion based on established diagnostic criteria. All phenoconverters with ≥1 annual follow-up visit, with available biomarkers and persistent clinically defined diagnosis at last observation were included. Neuronal alpha-Synuclein Disease Integrated Staging System (NSD-ISS) staging was applied. Results Among 121 phenoconverters, 103 had evaluable CSFaSynSAA and DAT data and were included in analysis: 92 PD, 7 DLB, 2 MSA, 2 AD/other dementias. Phenoconversion annual rates varied widely across groups: iRBD 7.9%, hyposmia 4.2%, GBA1 0.3%, LRRK2 1.3%, LRRK2 + GBA1 0.9%, and controls 0.5%. Median time from baseline to phenoconversion ranged from 13-14 months in iRBD and hyposmia to 36-85 months in NMCs. The expected biomarker profile (CSFaSynSAA+/DAT+) for clinically-diagnosed synucleinopathy occurred in 74 (71.8%) participants. Biological alignment (CSFaSynSAA+/DAT+) was present in 87% hyposmics and 72% iRBD phenoconverters. CSFaSynSAA negativity was high among LRRK2 phenoconverters (67%), who also were more likely to have a preserved sense of smell (83%). Phenoconversion occurred later than onset of functional impairment: 15/47 (31.9%) iRBDs and 7/38 (18.4%) hyposmics were already NSD-ISS stage ≥4 at time of phenoconversion. Conclusions Clinical phenoconversion did not necessarily align with biological evidence of synucleinopathy or dopaminergic loss and can be delayed compared to onset of meaningful functional impairment. Longitudinal follow up on converters without biological evidence of PD is required to confirm conversion diagnosis and evaluate for a later occurrence of biomarker positivity.
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-21
articleOpen accessThe shared code was created to perform analysis for the published article "Prodromal Lewy body disorder features in REM sleep behavior disorder with biomarker-defined synucleinopathy" (<article link to be added once published>). This code was created to analyze data accessed from the PPMI database (RRID:SCR 006431) on January 21, 2025. As the PPMI database is always evolving, it is possible that the code may not work if the database has changed since the date the code was created. Analytic datasets are not included in the submission. Researchers can request access to PPMI data at the PPMI Study website (https://www.ppmi-info.org/access-data-specimens/download-data).
Neurology · 2025-04-07
articleTo determine if Parkinson’s disease (PD) with mild cognitive impairment (PD-MCI) patients and MRI evidence of cholinergic nucleus 4 (Ch4) degeneration represent a distinct subtype of PD-MCI.
Value in Health · 2025-12-01
article1st authorCorrespondingAnnals of Neurology · 2025-07-11 · 3 citations
articleOpen access1st authorCorrespondingOBJECTIVE: To determine the impact of dopamine deficiency and isolated rapid eye movement (REM) sleep behavior disorder (iRBD) on cognitive performance in early neuronal α-synuclein disease (NSD) with hyposmia but without motor disability. METHODS: Using Parkinson's Progression Markers Initiative baseline data, cognitive performance was assessed with a cognitive summary score (CSS) derived from robust healthy control (HC) norms. Performance was examined for participants with hyposmia in early NSD-Integrated Staging System (NSD-ISS), either stage 2A (cerebrospinal fluid α-synuclein seed amplification assay [SAA]+, dopamine transporter scan [DaTscan]-) or 2B (SAA+, DaTscan+). RESULTS: Participants were stage 2A (n = 101), stage 2B (N = 227), and HCs (n = 158). Although stage 2 had intact Montreal Cognitive Assessment scores (mean [SD] = 27.0 [2.3]), stage 2A had a numerically worse CSS (z-score mean difference = 0.05, p = NS; effect size = 0.09) and stage 2B a statistically worse CSS (z-score mean difference = 0.23, p < 0.05; effect size = 0.40) compared with HCs. In stage 2A, hyposmia alone was associated with normal cognition, but those with comorbid iRBD had significantly worse cognition (z-score mean difference = 0.33, p < 0.05, effect size =0.50). In stage 2B, hyposmia alone had abnormal cognition (z-score mean difference = 0.18, p = 0.0078, effect size = 0.29), and superimposed iRBD had a statistically significant additive effect. INTERPRETATION: Using a novel CSS, we demonstrated that hyposmia is associated with cognitive deficits in prodromal NSD without motor disability, particularly when comorbid dopamine system impairment or comorbid iRBD is present. Therefore, it is critical to include and assess cognition at all stages when studying synuclein disease, even in the absence of motor disability. ANN NEUROL 2025;98:482-491.
medRxiv · 2025-06-05
preprintOpen accessABSTRACT Background Impulse control disorders (ICD) in Parkinson’s disease (PD) patients mainly occur as adverse effects of dopamine replacement therapy. Despite several known risk factors associated with ICD development, this cannot yet be accurately predicted at PD diagnosis. Objectives We aimed to investigate the predictability of incident ICD by baseline measures of demographic, clinical, dopamine transporter single photon emission computed tomography (DAT-SPECT), and genetic variables. Methods We used demographic and clinical data of medication-free PD patients from two longitudinal datasets; Parkinson’s Progression Markers Initiative (PPMI) (n=311) and Amsterdam UMC (n=72). We extracted radiomic and latent features from DAT-SPECT. We used single nucleotic polymorphisms (SNPs) from PPMI’s NeuroX and Exome sequencing data. Four machine learning classifiers were trained on combinations of the input feature sets, to predict incident ICD at any follow-up assessment. Classification performance was measured with 10×5-fold cross-validation. Results ICD prevalence at any follow-up was 0.32. The highest performance in predicting incident ICD (AUC=0.66) was achieved by the models trained on clinical features only. Anxiety severity and age of PD onset were identified as the most important features. Performance did not improve with adding features from DAT-SPECT or SNPs. We observed significantly higher performance (AUC=0.74) when classifying patients who developed ICD within four years from diagnosis compared with those tested negative for seven or more years. Conclusions Prediction accuracy for later ICD development, at the time of PD diagnosis, is limited; however, it increases for shorter time-to-event predictions. Neither DAT-SPECT nor genetic data improve the predictability obtained using demographic and clinical variables alone.
Movement Disorders · 2025-05-30
articleOpen accessAbstract Background Excessive daytime sleepiness (EDS) is a disabling symptom of Lewy body disorders (LBD). The hypothalamus is a key sleep–wake regulator and is involved in Lewy pathology, but its contribution to EDS in LBD remains unclear. Objectives To use diffusion‐weighted magnetic resonance imaging (MRI) to detect hypothalamic microstructure and determine its relationship to EDS symptoms in LBD in an exploratory investigation. Methods We studied 102 patients with clinically defined LBD (Parkinson's disease [PD], n = 93; PD dementia, n = 4; and dementia with Lewy bodies, n = 5) and Epworth Sleepiness Scale (ESS) within 2 years of MRI. Mean diffusivity (MD) was compared between EDS+ (ESS ≥ 10, n = 37) and EDS– (ESS < 10, n = 65) groups in three hypothalamic subregions, covarying for age, sex, and clinical variables. Secondary analyses tested correlations between subregion MD and ESS, global cognition, motor scores, and other clinical variables, and between subregion volume and ESS. Results MD was increased in EDS+ compared with EDS– in the whole hypothalamus (Cohen's d = 0.6, P = 0.015, β = 0.106 ± 0.043), superior tuberal subregion (Cohen's d = 0.56, = 0.021, β = 0.093 ± 0.040), and inferior tuberal subregion (Cohen's d = 0.64, P = 0.009, β = 0.174 ± 0.065). No difference was seen in the posterior subregion (Cohen's d = 0.15, = 0.530, β = 0.028 ± 0.044). Significant correlations with continuous ESS were seen in the MD of whole hypothalamus ( R 2 = 0.11, P = 5.2e‐4), superior tuberal ( R 2 = 0.12, P = 3.3e‐4), and inferior tuberal ( R 2 = 0.11, = 6.7e‐4) subregions. There was no correlation of hypothalamic MD with cognitive, motor, or other clinical symptoms, and no correlation of whole/subregional hypothalamic volumes with ESS. Conclusions Daytime sleepiness associates with increased MD in the tuberal hypothalamus in an LBD cohort. Compromised integrity of the tuberal hypothalamus may contribute to EDS symptoms in LBD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Recent grants
NIH · $33.7M · 2018
Efficient statistical methods for assessing dementia risk in Parkinson's disease
NIH · $1.3M · 2017–2024
NIH · $899k · 2009
Project II "aSyn Strains & Diverse Synucleinopathies"
NIH · $16.0M · 2019–2025
NIH · $384k · 2008
Frequent coauthors
- 247 shared
Andrew Siderowf
University of Pennsylvania
- 179 shared
John Q. Trojanowski
University of Pennsylvania
- 168 shared
Alice Chen‐Plotkin
University of Pennsylvania
- 156 shared
John E. Duda
University of Pennsylvania
- 142 shared
Dag Aarsland
King's College London
- 135 shared
Matthew B. Stern
University of Pennsylvania
- 124 shared
David J. Irwin
University of Pennsylvania
- 121 shared
Sharon X. Xie
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