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BACKGROUND AND OBJECTIVES: It is widely cited that dementia occurs in up to 80% of patients with Parkinson disease (PD), but studies reporting such high rates were published over two decades ago, had relatively small samples, and had other limitations. We aimed to determine long-term dementia risk in PD using data from two large, ongoing, prospective, observational studies. METHODS: Participants from the Parkinsons Progression Markers Initiative (PPMI), a multisite international study, and a long-standing PD research cohort at the University of Pennsylvania (Penn), a single site study at a tertiary movement disorders center, were recruited. PPMI enrolled de novo, untreated PD participants and Penn a convenience cohort from a large clinical center. For PPMI, a cognitive battery is administered annually, and a site investigator makes a cognitive diagnosis. At Penn, a comprehensive cognitive battery is administered either annually or biennially, and a cognitive diagnosis is made by expert consensus. Interval-censored survival curves were fit for time from PD diagnosis to stable dementia diagnosis for each cohort, using cognitive diagnosis of dementia as the primary end point and Montreal Cognitive Assessment (MoCA) score

Abstract Lewy body dementia (LBD), a class of disorders comprising Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer’s disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson’s disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or “modules” of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Abstract Observational studies in Parkinson’s disease (PD) deeply characterize relatively small numbers of participants. The Molecular Integration in Neurological Diagnosis Initiative seeks to characterize molecular and clinical features of every PD patient at the University of Pennsylvania (UPenn). The objectives of this study are to determine the feasibility of genetic characterization in PD and assess clinical features by sex and GBA1/LRRK2 status on a clinic-wide scale. All PD patients with clinical visits at the UPenn PD Center between 9/2018 and 12/2022 were eligible. Blood or saliva were collected, and a clinical questionnaire administered. Genotyping at 14 GBA1 and 8 LRRK2 variants was performed. PD symptoms were compared by sex and gene groups. 2063 patients were approached and 1,689 (82%) were enrolled, with 374 (18%) declining to participate. 608 (36%) females were enrolled, 159 (9%) carried a GBA1 variant, and 44 (3%) carried a LRRK2 variant. Compared with males, females across gene groups more frequently reported dystonia (53% vs 46%, p = 0.01) and anxiety (64% vs 55%, p

Abstract Objective Alzheimer's disease neuropathologic change and alpha‐synucleinopathy commonly co‐exist and contribute to the clinical heterogeneity of dementia. Here, we examined tau epitopes marking various stages of tangle maturation to test the hypotheses that tau maturation is more strongly associated with beta‐amyloid compared to alpha‐synuclein, and within the context of mixed pathology, mature tau is linked to Alzheimer's disease clinical phenotype and negatively associated with Lewy body dementia. Methods We used digital histology to measure percent area‐occupied by pathology in cortical regions among individuals with pure Alzheimer's disease neuropathologic change, pure alpha‐synucleinopathy, and a co‐pathology group with both Alzheimer's and alpha‐synuclein pathologic diagnoses. Multiple tau monoclonal antibodies were used to detect early (AT8, MC1) and mature (TauC3) epitopes of tangle progression. We used linear/logistic regression to compare groups and test the association between pathologies and clinical features. Results There were lower levels of tau pathology (β = 1.86–2.96, p

Abstract Diagnosis of dementia with Lewy bodies (DLB) is challenging and specific biofluid biomarkers are highly needed. We employed proximity extension-based assays to measure 665 proteins in the cerebrospinal fluid (CSF) from patients with DLB (n = 109), Alzheimer´s disease (AD, n = 235) and cognitively unimpaired controls (n = 190). We identified over 50 CSF proteins dysregulated in DLB, enriched in myelination processes among others. The dopamine biosynthesis enzyme DDC was the strongest dysregulated protein, and could efficiently discriminate DLB from controls and AD (AUC:0.91 and 0.81 respectively). Classification modeling unveiled a 7-CSF biomarker panel that better discriminate DLB from AD (AUC:0.93). A custom multiplex panel for six of these markers (DDC, CRH, MMP-3, ABL1, MMP-10, THOP1) was developed and validated in independent cohorts, including an AD and DLB autopsy cohort. This DLB CSF proteome study identifies DLB-specific protein changes and translates these findings to a practicable biomarker panel that accurately identifies DLB patients, providing promising diagnostic and clinical trial testing opportunities.

Abstract Objective Within Lewy body spectrum disorders (LBSD) with α‐synuclein pathology (αSyn), concomitant Alzheimer's disease (AD) pathology is common and is predictive of clinical outcomes, including cognitive impairment and decline. Plasma phosphorylated tau 181 (p‐tau181) is sensitive to AD neuropathologic change (ADNC) in clinical AD, and plasma glial fibrillary acidic protein (GFAP) is associated with the presence of β‐amyloid plaques. While these plasma biomarkers are well tested in clinical and pathological AD, their diagnostic and prognostic performance for concomitant AD in LBSD is unknown. Methods In autopsy‐confirmed αSyn‐positive LBSD, we tested how plasma p‐tau181 and GFAP differed across αSyn with concomitant ADNC (αSyn+AD; n = 19) and αSyn without AD (αSyn; n = 30). Severity of burden was scored on a semiquantitative scale for several pathologies (e.g., β‐amyloid and tau), and scores were averaged across sampled brainstem, limbic, and neocortical regions. Results Linear models showed that plasma GFAP was significantly higher in αSyn+AD compared to αSyn (β = 0.31, 95% CI = 0.065–0.56, and P = 0.015), after covarying for age at plasma, plasma‐to‐death interval, and sex; plasma p‐tau181 was not (P = 0.37). Next, linear models tested associations of AD pathological features with both plasma analytes, covarying for plasma‐to‐death, age at plasma, and sex. GFAP was significantly associated with brain β‐amyloid (β = 15, 95% CI = 6.1–25, and P = 0.0018) and tau burden (β = 12, 95% CI = 2.5–22, and P = 0.015); plasma p‐tau181 was not associated with either (both P > 0.34). Interpretation Findings indicate that plasma GFAP may be sensitive to concomitant AD pathology in LBSD, especially accumulation of β‐amyloid plaques.

Many single nucleotide polymorphisms (SNPs) identified by genome-wide association studies exert their effects on disease risk as expression quantitative trait loci (eQTL) via allele-specific expression (ASE). While databases for probing eQTLs in tissues from normal individuals exist, one may wish to ascertain eQTLs or ASE in specific tissues or disease-states not characterized in these databases. Here, we present a protocol to assess ASE of two possible target genes (GPNMB and KLHL7) of a known genome-wide association study (GWAS) Parkinson’s disease (PD) risk locus in postmortem human brain tissue from PD and neurologically normal individuals. This was done using a sequence of RNA isolation, cDNA library generation, enrichment for transcripts of interest using customizable cDNA capture probes, paired-end RNA sequencing, and subsequent analysis. This method provides increased sensitivity relative to traditional bulk RNAseq-based and a blueprint that can be extended to the study of other genes, tissues, and disease states.Key features• Analysis of GPNMB allele-specific expression (ASE) in brain lysates from cognitively normal controls (NC) and Parkinson’s disease (PD) individuals.• Builds on the ASE protocol of Mayba et al. (2014) and extends application from cells to human tissue.• Increased sensitivity by enrichment for desired transcript via RNA CaptureSeq (Mercer et al., 2014).• Optimized for human brain lysates from cingulate gyrus, caudate nucleus, and cerebellum.Graphical overview

ObjectivesTo investigate the impact of Alzheimer's disease (AD) co-pathology on an in vivo structural measure of neurodegeneration in Lewy body disorders (LBD).MethodsWe studied 72 LBD patients (Parkinson disease (PD) = 2, PD-MCI = 25, PD with dementia = 10, dementia with Lewy bodies = 35) with either CSF analysis or neuropathological examination and structural MRI during life. The cohort was divided into those harboring significant AD co-pathology, either at autopsy (intermediate/high AD neuropathologic change) or with CSF signature indicating AD co-pathology (t-tau/Aβ1-42  > 0.3) (LBD+AD, N = 19), and those without AD co-pathology (LBD-AD, N = 53). We also included a reference group of 25 patients with CSF biomarker-confirmed amnestic AD. We investigated differences in MRI cortical thickness estimates between groups, and in the 21 autopsied LBD patients (LBD-AD = 14, LBD+AD = 7), directly tested the association between antemortem MRI and post-mortem burdens of tau, Aβ, and alpha-synuclein using digital histopathology in five representative neocortical regions.ResultsThe LBD+AD group was characterized by cortical thinning in anterior/medial and lateral temporal regions (P

Abstract Objective To determine if plasma tau phosphorylated at threonine 181 (p‐tau181) distinguishes pathology‐confirmed Alzheimer's disease (AD) from normal cognition (NC) adults, to test if p‐tau181 predicts cognitive and functional decline, and to validate findings in an external cohort. Methods Thirty‐one neuropathology‐confirmed AD cases, participants with clinical diagnoses of mild cognitive impairment (MCI, N = 91) or AD dementia (N = 64), and NC (N = 241) had plasma collected at study entry. The clinical diagnosis groups had annual cognitive (Mini‐Mental State Examination, MMSE) and functional (Clinical Dementia Rating Scale, CDR) measures. NC (N = 70), MCI (N = 75), and AD dementia (N = 50) cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used as a validation cohort. Plasma p‐tau181 was measured using the Quanterix SiMoA HD‐X platform. Results Plasma p‐tau181 differentiated pathology‐confirmed AD from NC with negative amyloid PET scans with an AUC of 0.93. A cut point of 3.44 pg/mL (maximum Youden Index) had a sensitivity of 0.77, specificity of 0.96. p‐Tau181 values above the cut point were associated with the faster rate of decline in MMSE in AD dementia and MCI and a shorter time to a clinically significant functional decline in all groups. In a subset of MCI cases from ADNI, p‐tau181 values above the cut point associated with faster rate of decline in MMSE, and a shorter time to a clinically significant functional decline and conversion to dementia. Interpretation Plasma p‐tau181 differentiates AD pathology cases from NC with high accuracy. Higher levels of plasma p‐tau181 are associated with faster cognitive and functional decline.

Abstract Objective To develop a clinico‐genetic predictor of impulse control disorder (ICD) risk in Parkinson's disease (PD). Methods In 5770 individuals from three PD cohorts (the 23andMe, Inc.; the University of Pennsylvania [UPenn]; and the Parkinson's Progression Markers Initiative [PPMI]), we used a discovery‐replication strategy to develop a clinico‐genetic predictor for ICD risk. We first performed a Genomewide Association Study (GWAS) for ICDs anytime during PD in 5262 PD individuals from the 23andMe cohort. We then combined newly discovered ICD risk loci with 13 ICD risk loci previously reported in the literature to develop a model predicting ICD in a Training dataset (n = 339, from UPenn and PPMI cohorts). The model was tested in a non‐overlapping Test dataset (n = 169, from UPenn and PPMI cohorts) and used to derive a continuous measure, the ICD‐risk score (ICD‐RS), enriching for PD individuals with ICD (ICD+ PD). Results By GWAS, we discovered four new loci associated with ICD at p‐values of 4.9e‐07 to 1.3e‐06. Our best logistic regression model included seven clinical and two genetic variables, achieving an area under the receiver operating curve for ICD prediction of 0.75 in the Training and 0.72 in the Test dataset. The ICD‐RS separated groups of PD individuals with ICD prevalence of nearly 40% (highest risk quartile) versus 7% (lowest risk quartile). Interpretation In this multi‐cohort, international study, we developed an easily computed clinico‐genetic tool, the ICD‐RS, that substantially enriches for subgroups of PD at very high versus very low risk for ICD, enabling pharmacogenetic approaches to PD medication selection.

Abstract The pathological hallmark of neurodegenerative diseases is the formation of toxic oligomers by proteins such as alpha-synuclein (aSyn) or microtubule-associated protein tau (Tau). Consequently, such oligomers are promising biomarker candidates for diagnostics as well as drug development. However, measuring oligomers and other aggregates in human biofluids is still challenging as extreme sensitivity and specificity are required. We previously developed surface-based fluorescence intensity distribution analysis (sFIDA) featuring single-particle sensitivity and absolute specificity for aggregates. In this work, we measured aSyn and Tau aggregate concentrations of 237 cerebrospinal fluid (CSF) samples from five cohorts: Parkinson’s disease (PD), dementia with Lewy bodies (DLB), Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), and a neurologically-normal control group. aSyn aggregate concentration discriminates PD and DLB patients from normal controls (sensitivity 73%, specificity 65%, area under the receiver operating curve (AUC) 0.68). Tau aggregates were significantly elevated in PSP patients compared to all other groups (sensitivity 87%, specificity 70%, AUC 0.76). Further, we found a tight correlation between aSyn and Tau aggregate titers among all patient cohorts (Pearson coefficient of correlation r = 0.81). Our results demonstrate that aSyn and Tau aggregate concentrations measured by sFIDA differentiate neurodegenerative disease diagnostic groups. Moreover, sFIDA-based Tau aggregate measurements might be particularly useful in distinguishing PSP from other parkinsonisms. Finally, our findings suggest that sFIDA can improve pre-clinical and clinical studies by identifying those individuals that will most likely respond to compounds designed to eliminate specific oligomers or to prevent their formation.

Abstract Background Synapse degeneration is an early event in pathological frontotemporal lobar degeneration (FTLD). Consequently, a surrogate marker of synapse loss could be used to monitor early pathologic changes in patients with underlying FTLD. The aim of this study was to evaluate the relationship of antemortem cerebrospinal fluid (CSF) levels of 8 synaptic proteins with postmortem global tau and TDP-43 burden and cognitive performance and to assess their diagnostic capacity in a neuropathological FTLD cohort. Methods We included patients with a neuropathological confirmation of FTLD-Tau (n = 24, mean age-at-CSF 67 years ± 11), FTLD-TDP (n = 25, 66 years ± 9) or AD (n = 25, 73 years ± 6) as well as cognitively normal controls (n = 35, 69 years ± 7) from the Penn FTD Center and ADRC. We used a semi-quantitative measure of tau and TDP-43 inclusions to quantify pathological burden across 16 brain regions. Statistical methods included Spearman rank correlations, one-way analysis of covariance, ordinal regression, step-wise multiple linear regression and receiver-operating characteristic curves. Result CSF calsyntenin-1 and neurexin-2a were correlated in all patient groups (r s = .55 to .88). In FTLD-TDP, we observed low antemortem CSF levels of calsyntenin-1 and neurexin-2a compared to AD (.72-fold, p = .001, .77-fold, p = .04, respectively) and controls (.80-fold, p = .02, .78-fold, p = .02, respectively), which were inversely associated with post-mortem global TDP-43 burden (regression r 2 = .56, p = .007 and r 2 = .57, p = .006, respectively). A multimarker panel including calsyntenin-1 was associated with TDP-43 burden (r 2 = .69, p = .003) and MMSE score (r 2 = .19, p = .03) in FTLD. A second multimarker synaptic panel, also including calsyntenin-1, was associated with MMSE score in FTLD-tau (r 2 = .49, p = .04) and improved diagnostic performance to discriminate FTLD-Tau and FTLD-TDP neuropathologic subtypes (AUC = .83). Conclusion These synaptic panels have potential in the differential diagnosis of FTLD neuropathologic subtypes and as surrogate markers of cognitive performance in future clinical trials targeting TDP-43 or tau.

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins [proximity extension-based (PEA) immunoassays] in a deeply-phenotyped mixed memory clinic cohort [ n = 502, mean age (standard deviation, SD) = 64.1 (8.7) years, 181 female (35.4%)], including patients with Alzheimer's disease (AD, n = 213), dementia with Lewy bodies (DLB, n = 50) and frontotemporal dementia (FTD, n = 93), and controls (n = 146). Validation was assessed in independent cohorts (n = 99 PEA platform, n = 198, mass reaction monitoring-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1 -CR2 (rs3818361, P = 1.65 × 10−8), ZCWPW1 -PILRB (rs1476679, P = 2.73 × 10−32), CTSH -CTSH (rs3784539, P = 2.88 × 10−24) and HESX1 -RETN (rs186108507, P = 8.39 × 10−8), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90 × 10−7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for FTD loci, either for the total sample as for analyses performed within FTD only. Protein QTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia. [ABSTRACT FROM AUTHOR]

Lewy bodies commonly occur in Alzheimer's disease, and Alzheimer's disease pathology is frequent in Lewy body diseases, but the burden of co-pathologies across neurodegenerative diseases is unknown. We assessed the extent of tau, amyloid-β, α-synuclein and TDP-43 proteinopathies in 766 autopsied individuals representing a broad spectrum of clinical neurodegenerative disease. We interrogated pathological Alzheimer's disease (n = 247); other tauopathies (n = 95) including Pick's disease, corticobasal disease and progressive supranuclear palsy; the synucleinopathies (n = 164) including multiple system atrophy and Lewy body disease; the TDP-43 proteinopathies (n = 188) including frontotemporal lobar degeneration with TDP-43 inclusions and amyotrophic lateral sclerosis; and a minimal pathology group (n = 72). Each group was divided into subgroups without or with co-pathologies. Age and sex matched logistic regression models compared co-pathology prevalence between groups. Co-pathology prevalence was similar between the minimal pathology group and most neurodegenerative diseases for each proteinopathy: tau was nearly universal (92-100%), amyloid-β common (20-57%); α-synuclein less common (4-16%); and TDP-43 the rarest (0-16%). In several neurodegenerative diseases, co-pathology increased: in Alzheimer's disease, α-synuclein (41-55%) and TDP-43 (33-40%) increased; in progressive supranuclear palsy, α-synuclein increased (22%); in corticobasal disease, TDP-43 increased (24%); and in neocortical Lewy body disease, amyloid-β (80%) and TDP-43 (22%) increased. Total co-pathology prevalence varied across groups (27-68%), and was increased in high Alzheimer's disease, progressive supranuclear palsy, and neocortical Lewy body disease (70-81%). Increased age at death was observed in the minimal pathology group, amyotrophic lateral sclerosis, and multiple system atrophy cases with co-pathologies. In amyotrophic lateral sclerosis and neocortical Lewy body disease, co-pathologies associated with APOE ɛ4. Lewy body disease cases with Alzheimer's disease co-pathology had substantially lower Mini-Mental State Examination scores than pure Lewy body disease. Our data imply that increased age and APOE ɛ4 status are risk factors for co-pathologies independent of neurodegenerative disease; that neurodegenerative disease severity influences co-pathology as evidenced by the prevalence of co-pathology in high Alzheimer's disease and neocortical Lewy body disease, but not intermediate Alzheimer's disease or limbic Lewy body disease; and that tau and α-synuclein strains may also modify co-pathologies since tauopathies and synucleinopathies had differing co-pathologies and burdens. These findings have implications for clinical trials that focus on monotherapies targeting tau, amyloid-β, α-synuclein and TDP-43.

The Dementia with Lewy Bodies (DLB) Consortium has refined its recommendations about the clinical and pathologic diagnosis of DLB, updating the previous report, which has been in widespread use for the last decade. The revised DLB consensus criteria now distinguish clearly between clinical features and diagnostic biomarkers, and give guidance about optimal methods to establish and interpret these. Substantial new information has been incorporated about previously reported aspects of DLB, with increased diagnostic weighting given to REM sleep behavior disorder and 123iodine-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. The diagnostic role of other neuroimaging, electrophysiologic, and laboratory investigations is also described. Minor modifications to pathologic methods and criteria are recommended to take account of Alzheimer disease neuropathologic change, to add previously omitted Lewy-related pathology categories, and to include assessments for substantia nigra neuronal loss. Recommendations about clinical management are largely based upon expert opinion since randomized controlled trials in DLB are few. Substantial progress has been made since the previous report in the detection and recognition of DLB as a common and important clinical disorder. During that period it has been incorporated into DSM-5, as major neurocognitive disorder with Lewy bodies. There remains a pressing need to understand the underlying neurobiology and pathophysiology of DLB, to develop and deliver clinical trials with both symptomatic and disease-modifying agents, and to help patients and carers worldwide to inform themselves about the disease, its prognosis, best available treatments, ongoing research, and how to get adequate support.

Past clinical trials of putative neuroprotective therapies have targeted PD as a single pathogenic disease entity. From an Oslerian clinicopathological perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: A single-mechanism therapy can affect most of those sharing the classic pathological hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological, and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers), rather than clinical definitions, are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller, but well-defined, subsets of PD amenable to successful neuroprotection. © 2017 International Parkinson and Movement Disorder Society.

ObjectiveParkinson's disease (PD) presents clinically with several motor subtypes that exhibit variable treatment response and prognosis. Here, we investigated genetic variants for their potential association with PD motor phenotype and progression.MethodsWe screened 10 SNPs, previously associated with PD risk, for association with tremor-dominant (TD) versus postural-instability gait disorder (PIGD) motor subtypes. SNPs that correlated with the TD/PIGD ratio in a discovery cohort of 251 PD patients were then evaluated in a multi-site replication cohort of 559 PD patients. SNPs associated with motor phenotype in both cross-sectional cohorts were next evaluated for association with (1) rates of motor progression in a longitudinal subgroup of 230 PD patients and (2) brain alpha-synuclein (SNCA) expression in the GTEx (Genotype-Tissue Expression project) consortium database.ResultsGenotype at rs356182, near SNCA, correlated with the TD/PIGD ratio in both the discovery (Bonferroni-corrected P = 0.04) and replication cohorts (P = 0.02). The rs356182 GG genotype was associated with a more tremor-predominant phenotype and predicted a slower rate of motor progression (1-point difference in annual rate of UPDRS-III motor score change, P = 0.01). The rs356182 genotype was associated with SNCA expression in the cerebellum (P = 0.005).InterpretationOur study demonstrates that the GG genotype at rs356182 provides molecular definition for a clinically important endophenotype associated with (1) more tremor-predominant motor phenomenology, (2) slower rates of motor progression, and (3) decreased brain expression of SNCA. Such molecularly defined endophenotyping in PD may benefit both clinical trial design and tailoring of clinical care as we enter the era of precision medicine.

Summary: Background: Immunosenescence (ISC) describes age-related changes in immune-system composition and function. Multiple sclerosis (MS) is a lifelong inflammatory condition involving effector and regulatory T-cell imbalance, yet little is known about T-cell ISC in MS. We examined age-associated changes in circulating T cells in MS compared to normal controls (NC). Methods: Forty untreated MS (Mean Age 43·3, Range 18–72) and 49 NC (Mean Age 48·6, Range 20–84) without inflammatory conditions were included in cross-sectional design. T-cell subsets were phenotypically and functionally characterized using validated multiparametric flow cytometry. Their aging trajectories, and differences between MS and NC, were determined using linear mixed-effects models. Findings: MS patients demonstrated early and persistent redistribution of naïve and memory CD4 T-cell compartments. While most CD4 and CD8 T-cell aging trajectories were similar between groups, MS patients exhibited abnormal age-associated increases of activated (HLA-DR+CD38+; (P = 0·013) and cytotoxic CD4 T cells, particularly in patients >60 (EOMES: P

ImportanceParkinson disease (PD) is heterogeneous in symptom manifestation and rate of progression. Identifying factors that influence disease progression could provide mechanistic insight, improve prognostic accuracy, and elucidate novel therapeutic targets.ObjectiveTo determine whether GBA mutations and the E326K polymorphism modify PD symptom progression.Design, setting, and participantsThe entire GBA coding region was screened for mutations and E326K in 740 patients with PD enrolled at 7 sites from the PD Cognitive Genetics Consortium. Detailed longitudinal motor and cognitive assessments were performed with patients in the on state.Main outcomes and measuresLinear regression was used to test for an association between GBA genotype and motor progression, with the Movement Disorder Society-sponsored version of the Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III) score at the last assessment as the outcome and GBA genotype as the independent variable, with adjustment for levodopa equivalent dose, sex, age, disease duration, MDS-UPDRS III score at the first assessment, duration of follow-up, and site. Similar methods were used to examine the association between genotype and tremor and postural instability and gait difficulty (PIGD) scores. To examine the effect of GBA genotype on cognitive progression, patients were classified into those with conversion to mild cognitive impairment or dementia during the study (progression) and those without progression. The association between GBA genotype and progression status was then tested using logistic regression, adjusting for sex, age, disease duration, duration of follow-up, years of education, and site.ResultsOf the total sample of 733 patients who underwent successful genotyping, 226 (30.8%) were women and 507 (69.2%) were men (mean [SD] age, 68.1 [8.8] years). The mean (SD) duration of follow-up was 3.0 (1.7) years. GBA mutations (β = 4.65; 95% CI, 1.72-7.58; P = .002), E326K (β = 3.42; 95% CI, 0.66-6.17; P = .02), and GBA variants combined as a single group (β = 4.01; 95% CI, 1.95-6.07; P = 1.5 × 10-4) were associated with a more rapid decline in MDS-UPDRS III score. Combined GBA variants (β = 0.38; 95% CI, 0.23-0.53; P = .01) and E326K (β = 0.64; 95% CI, 0.43-0.86; P = .002) were associated with faster progression in PIGD scores, but not in tremor scores. A significantly higher proportion of E326K carriers (10 of 21 [47.6%]; P = .01) and GBA variant carriers (15 of 39 [38.5%]; P = .04) progressed to mild cognitive impairment or dementia.Conclusions and relevanceGBA variants predict a more rapid progression of cognitive dysfunction and motor symptoms in patients with PD, with a greater effect on PIGD than tremor. Thus, GBA variants influence the heterogeneity in symptom progression observed in PD.

The development of biomarkers to predict the progression of Parkinson's disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson's Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1-42 (Aβ1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1-42, or highest t-tau/Aβ1-42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.

BackgroundLoss-of-function mutations in the GBA gene are associated with more severe cognitive impairment in PD, but the nature of these deficits is not well understood and whether common GBA polymorphisms influence cognitive performance in PD is not yet known.MethodsWe screened the GBA coding region for mutations and the E326K polymorphism in 1,369 PD patients enrolled at eight sites from the PD Cognitive Genetics Consortium. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised), working memory/executive function (Letter-Number Sequencing Test and Trail Making Test A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation), and global cognitive function (MoCA). We used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates and accounted for multiple testing using Bonferroni's corrections.ResultsMutation carriers (n = 60; 4.4%) and E326K carriers (n = 65; 4.7%) had a higher prevalence of dementia (mutations, odds ratio = 5.1; P = 9.7 × 10(-6) ; E326K, odds ratio = 6.4; P = 5.7 × 10(-7) ) and lower performance on Letter-Number Sequencing (mutations, corrected P[Pc ] = 9.0 × 10(-4) ; E326K, Pc  = 0.036), Trail Making B-A (mutations, Pc  = 0.018; E326K, Pc  = 0.018), and Benton Judgment of Line Orientation (mutations, Pc  = 0.0045; E326K, Pc  = 0.0013).ConclusionsBoth GBA mutations and E326K are associated with a distinct cognitive profile characterized by greater impairment in working memory/executive function and visuospatial abilities in PD patients. The discovery that E326K negatively impacts cognitive performance approximately doubles the proportion of PD patients we now recognize are at risk for more severe GBA-related cognitive deficits.

BACKGROUND. From March 2, 2020, to April 12, 2020, New York City (NYC) experienced exponential growth of the COVID-19 pandemic due to novel coronavirus (SARS-CoV-2). Little is known regarding how physicians have been affected. We aimed to characterize the COVID-19 impact on NYC resident physicians. METHODS. IRB-exempt and expedited cross-sectional analysis through survey to NYC residency program directors April 3-12, 2020, encompassing events from March 2, 2020, to April 12, 2020. RESULTS. From an estimated 340 residency programs around NYC, recruitment yielded 91 responses, representing 24 specialties and 2306 residents. In 45.1% of programs, at least 1 resident with confirmed COVID-19 was reported. One hundred one resident physicians were confirmed COVID-19-positive, with an additional 163 residents presumed positive for COVID-19 based on symptoms but awaiting or unable to obtain testing. Two COVID-19-positive residents were hospitalized, with 1 in intensive care. Among specialties with more than 100 residents represented, negative binomial regression indicated that infection risk differed by specialty (P = 0.039). In 80% of programs, quarantining a resident was reported. Ninety of 91 programs reported reuse or extended mask use, and 43 programs reported that personal protective equipment (PPE) was suboptimal. Sixty-five programs (74.7%) redeployed residents elsewhere to support COVID-19 efforts. CONCLUSION. Many resident physicians around NYC have been affected by COVID-19 through direct infection, quarantine, or redeployment. Lack of access to testing and concern regarding suboptimal PPE are common among residency programs. Infection risk may differ by specialty. FUNDING. National Eye Institute Core Grant P30EY019007; Research to Prevent Blindness Unrestricted Grant; Parker Family Chair; University of Pennsylvania., Introduction The United States is part of a global pandemic known as COVID-19 (1), which has characteristics that overlap with the Spanish flu of 1918. The causative novel coronavirus (2019-nCoV, [...]

BackgroundAccurate diagnosis and early detection of complex diseases, such as Parkinson's disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinson's disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts.MethodsWe developed a model for disease classification using data from the Parkinson's Progression Marker Initiative (PPMI) study for 367 patients with Parkinson's disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinson's disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinson's disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinson's Disease Biomarkers Program (PDBP), the Parkinson's Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinson's Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD).FindingsIn the population from PPMI, our initial model correctly distinguished patients with Parkinson's disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900-0·946) with high sensitivity (0·834, 95% CI 0·711-0·883) and specificity (0·903, 95% CI 0·824-0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinson's disease, with AUCs of 0·894 (95% CI 0·867-0·921) in the PDBP cohort, 0·998 (0·992-1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896-0·962) in LABS-PD, and 0·939 (0·891-0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinson's disease converted to Parkinson's disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinson's disease underwent conversion (test of proportions, p=0·003).InterpretationOur model provides a potential new approach to distinguish participants with Parkinson's disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinson's disease in prospective cohorts, it could facilitate identification of biomarkers and interventions.FundingNational Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.