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Background Knowledge of the window of SARS-CoV-2 infectiousness is crucial in developing policies to curb transmission. Mathematical modelling based on scarce empirical evidence and key assumptions has driven isolation and testing policy, but real-world data are needed. We aimed to characterise infectiousness across the full course of infection in a real-world community setting. Methods The Assessment of Transmission and Contagiousness of COVID-19 in Contacts (ATACCC) study was a UK prospective, longitudinal, community cohort of contacts of newly diagnosed, PCR-confirmed SARS-CoV-2 index cases. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. The primary objective was to define the window of SARS-CoV-2 infectiousness and its temporal correlation with symptom onset. We quantified viral RNA load by RT-PCR and infectious viral shedding by enumerating cultivable virus daily across the course of infection. Participants completed a daily diary to track the emergence of symptoms. Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. Findings Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. The onset and end of infectious viral shedding were captured in 42 cases and the median duration of infectiousness was 5 (IQR 3–7) days. Although 24 (63%) of 38 cases had PCR-detectable virus before symptom onset, only seven (20%) of 35 shed infectious virus presymptomatically. Symptom onset was a median of 3 days before both peak viral RNA and peak infectious viral load (viral RNA IQR 3–5 days, n=38; plaque-forming units IQR 3–6 days, n=35). Notably, 22 (65%) of 34 cases and eight (24%) of 34 cases continued to shed infectious virus 5 days and 7 days post-symptom onset, respectively (survival probabilities 67% and 35%). Correlation of lateral flow device (LFD) results with infectious viral shedding was poor during the viral growth phase (sensitivity 67% [95% CI 59–75]), but high during the decline phase (92% [86–96]). Infectious virus kinetic modelling suggested that the initial rate of viral replication determines the course of infection and infectiousness. Interpretation Less than a quarter of COVID-19 cases shed infectious virus before symptom onset; under a crude 5-day self-isolation period from symptom onset, two-thirds of cases released into the community would still be infectious, but with reduced infectious viral shedding. Our findings support a role for LFDs to safely accelerate deisolation but not for early diagnosis, unless used daily. These high-resolution, community-based data provide evidence to inform infection control guidance. Funding National Institute for Health and Care Research.

BACKGROUND: Despite circumstantial evidence for aerosol and fomite spread of SARS-CoV-2, empirical data linking either pathway with transmission are scarce. Here we aimed to assess whether the presence of SARS-CoV-2 on frequently-touched surfaces and residents' hands was a predictor of SARS-CoV-2 household transmission. METHODS: In this longitudinal cohort study, during the pre-alpha (September to December, 2020) and alpha (B.1.1.7; December, 2020, to April, 2021) SARS-CoV-2 variant waves, we prospectively recruited contacts from households exposed to newly diagnosed COVID-19 primary cases, in London, UK. To maximally capture transmission events, contacts were recruited regardless of symptom status and serially tested for SARS-CoV-2 infection by RT-PCR on upper respiratory tract (URT) samples and, in a subcohort, by serial serology. Contacts' hands, primary cases' hands, and frequently-touched surface-samples from communal areas were tested for SARS-CoV-2 RNA. SARS-CoV-2 URT isolates from 25 primary case-contact pairs underwent whole-genome sequencing (WGS). FINDINGS: From Aug 1, 2020, until March 31, 2021, 620 contacts of PCR-confirmed SARS-CoV-2-infected primary cases were recruited. 414 household contacts (from 279 households) with available serial URT PCR results were analysed in the full household contacts' cohort, and of those, 134 contacts with available longitudinal serology data and not vaccinated pre-enrolment were analysed in the serology subcohort. Household infection rate was 28·4% (95% CI 20·8-37·5) for pre-alpha-exposed contacts and 51·8% (42·5-61·0) for alpha-exposed contacts (p=0·0047). Primary cases' URT RNA viral load did not correlate with transmission, but was associated with detection of SARS-CoV-2 RNA on their hands (p=0·031). SARS-CoV-2 detected on primary cases' hands, in turn, predicted contacts' risk of infection (adjusted relative risk [aRR]=1·70 [95% CI 1·24-2·31]), as did SARS-CoV-2 RNA presence on household surfaces (aRR=1·66 [1·09-2·55]) and contacts' hands (aRR=2·06 [1·57-2·69]). In six contacts with an initial negative URT PCR result, hand-swab (n=3) and household surface-swab (n=3) PCR positivity preceded URT PCR positivity. WGS corroborated household transmission. INTERPRETATION: Presence of SARS-CoV-2 RNA on primary cases' and contacts' hands and on frequently-touched household surfaces associates with transmission, identifying these as potential vectors for spread in households. FUNDING: National Institute for Health Research Health Protection Research Unit in Respiratory Infections, Medical Research Council.

Biomarkers to aid diagnosis and delineate the progression of Parkinson’s disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson’s and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson’s Disease Centre and Tracking Parkinson’s) and the Parkinson’s Disease Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis were performed to identify functional and mechanistic disease associations. The most consistent diagnostic classifier signature was tested across modalities [cerebrospinal fluid (area under curve) = 0.74, P = 0.0009; brain area under curve = 0.75, P = 0.006; serum area under curve = 0.66, P = 0.0002]. Focusing on serum samples and using only those with severe disease compared with controls increased the area under curve to 0.72 (P = 1.0 × 10−4). In the validation data set, we showed that the same classifiers were significantly related to disease status (P < 0.001). Differential expression analysis and weighted gene correlation network analysis highlighted key proteins and pathways with known relationships to Parkinson’s. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response. The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provide mechanistic insights into the disease as well as nominate a protein signature classifier that deserves further biomarker evaluation.

ObjectiveParkinson’s disease is characterised neuropathologically by α-synuclein aggregation. Currently, there is no blood test to predict the underlying pathology or distinguish Parkinson’s from atypical parkinsonian syndromes. We assessed the clinical utility of serum neuronal exosomes as biomarkers across the spectrum of Parkinson’s disease, multiple system atrophy and other proteinopathies.MethodsWe performed a cross-sectional study of 664 serum samples from the Oxford, Kiel and Brescia cohorts consisting of individuals with rapid eye movement sleep behavioural disorder, Parkinson’s disease, dementia with Lewy bodies, multiple system atrophy, frontotemporal dementia, progressive supranuclear palsy, corticobasal syndrome and controls. Longitudinal samples were analysed from Parkinson’s and control individuals. We developed poly(carboxybetaine-methacrylate) coated beads to isolate L1 cell adhesion molecule (L1CAM)-positive extracellular vesicles with characteristics of exosomes and used mass spectrometry or multiplexed electrochemiluminescence to measure exosomal proteins.ResultsMean neuron-derived exosomal α-synuclein was increased by twofold in prodromal and clinical Parkinson’s disease when compared with multiple system atrophy, controls or other neurodegenerative diseases. With 314 subjects in the training group and 105 in the validation group, exosomal α-synuclein exhibited a consistent performance (AUC=0.86) in separating clinical Parkinson’s disease from controls across populations. Exosomal clusterin was elevated in subjects with non-α-synuclein proteinopathies. Combined neuron-derived exosomal α-synuclein and clusterin measurement predicted Parkinson’s disease from other proteinopathies with AUC=0.98 and from multiple system atrophy with AUC=0.94. Longitudinal sample analysis showed that exosomal α-synuclein remains stably elevated with Parkinson’s disease progression.ConclusionsIncreased α-synuclein egress in serum neuronal exosomes precedes the diagnosis of Parkinson’s disease, persists with disease progression and in combination with clusterin predicts and differentiates Parkinson’s disease from atypical parkinsonism.

Biomarkers to aid diagnosis and delineate progression of Parkinson’s Disease (PD) are vital for targeting treatment in the early phases of disease. Here, we aim to discover a multi-protein panel representative of PD and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers.We used aptamer-based technology (SomaLogic®) to measure proteins in 1,599 serum samples, 85 CSF samples and 37 brain tissue samples collected from two observational longitudinal cohorts (Oxford Parkinson’s Disease Centre and Tracking Parkinson’s) and the PD Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis was performed to identify functional and mechanistic disease associations.The most consistent diagnostic classifier signature was tested across modalities (CSF AUC = 0.74, p-value = 0.0009; brain AUC = 0.75, p-value = 0.006; serum AUC = 0.66, p-value = 0.0002). In the validation dataset we showed that the same classifiers were significantly related to disease status (p-values < 0.001). Differential expression analysis and Weighted Gene Correlation Network Analysis (WGCNA) highlighted key proteins and pathways with known relationships to PD. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response.The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provides mechanistic insights into the disease as well as nominating a protein signature classifier that deserves further biomarker evaluation.

Background The SARS-CoV-2 delta (B.1.617.2) variant is highly transmissible and spreading globally, including in populations with high vaccination rates. We aimed to investigate transmission and viral load kinetics in vaccinated and unvaccinated individuals with mild delta variant infection in the community. Methods Between Sept 13, 2020, and Sept 15, 2021, 602 community contacts (identified via the UK contract-tracing system) of 471 UK COVID-19 index cases were recruited to the Assessment of Transmission and Contagiousness of COVID-19 in Contacts cohort study and contributed 8145 upper respiratory tract samples from daily sampling for up to 20 days. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. We analysed transmission risk by vaccination status for 231 contacts exposed to 162 epidemiologically linked delta variant-infected index cases. We compared viral load trajectories from fully vaccinated individuals with delta infection (n=29) with unvaccinated individuals with delta (n=16), alpha (B.1.1.7; n=39), and pre-alpha (n=49) infections. Primary outcomes for the epidemiological analysis were to assess the secondary attack rate (SAR) in household contacts stratified by contact vaccination status and the index cases’ vaccination status. Primary outcomes for the viral load kinetics analysis were to detect differences in the peak viral load, viral growth rate, and viral decline rate between participants according to SARS-CoV-2 variant and vaccination status. Findings The SAR in household contacts exposed to the delta variant was 25% (95% CI 18–33) for fully vaccinated individuals compared with 38% (24–53) in unvaccinated individuals. The median time between second vaccine dose and study recruitment in fully vaccinated contacts was longer for infected individuals (median 101 days [IQR 74–120]) than for uninfected individuals (64 days [32–97], p=0·001). SAR among household contacts exposed to fully vaccinated index cases was similar to household contacts exposed to unvaccinated index cases (25% [95% CI 15–35] for vaccinated vs 23% [15–31] for unvaccinated). 12 (39%) of 31 infections in fully vaccinated household contacts arose from fully vaccinated epidemiologically linked index cases, further confirmed by genomic and virological analysis in three index case–contact pairs. Although peak viral load did not differ by vaccination status or variant type, it increased modestly with age (difference of 0·39 [95% credible interval –0·03 to 0·79] in peak log10 viral load per mL between those aged 10 years and 50 years). Fully vaccinated individuals with delta variant infection had a faster (posterior probability >0·84) mean rate of viral load decline (0·95 log10 copies per mL per day) than did unvaccinated individuals with pre-alpha (0·69), alpha (0·82), or delta (0·79) variant infections. Within individuals, faster viral load growth was correlated with higher peak viral load (correlation 0·42 [95% credible interval 0·13 to 0·65]) and slower decline (–0·44 [–0·67 to –0·18]). Interpretation Vaccination reduces the risk of delta variant infection and accelerates viral clearance. Nonetheless, fully vaccinated individuals with breakthrough infections have peak viral load similar to unvaccinated cases and can efficiently transmit infection in household settings, including to fully vaccinated contacts. Host–virus interactions early in infection may shape the entire viral trajectory. Funding National Institute for Health Research.

BackgroundPredicting prognosis in Parkinson's disease (PD) has important implications for individual prognostication and clinical trials design and targeting novel treatments. Blood biomarkers could help in this endeavor.MethodsWe identified 4 blood biomarkers that might predict prognosis: apolipoprotein A1, C‐reactive protein, uric acid and vitamin D. These biomarkers were measured in baseline serum from 624 Parkinson's disease subjects (median disease duration, 1.0 years; interquartile range, 0.5–2.0) from the Oxford Discovery prospective cohort. We compared these biomarkers against PD subtypes derived from clinical features in the baseline cohort using data‐driven approaches. We used multilevel models with MDS‐UPDRS parts I, II, and III and Montreal Cognitive Assessment as outcomes to test whether the biomarkers predicted subsequent progression in motor and nonmotor domains. We compared the biomarkers against age of PD onset and age at diagnosis. The q value, a false‐discovery rate alternative to P values, was calculated as an adjustment for multiple comparisons. ResultsApolipoprotein A1 and C‐reactive protein levels differed across our PD subtypes, with severe motor disease phenotype, poor psychological well‐being, and poor sleep subtype having reduced apolipoprotein A1 and higher C‐reactive protein levels. Reduced apolipoprotein A1, higher C‐reactive protein, and reduced vitamin D were associated with worse baseline activities of daily living (MDS‐UPDRS II).ConclusionBaseline clinical subtyping identified a pro‐inflammatory biomarker profile significantly associated with a severe motor/nonmotor disease phenotype, lending biological validity to subtyping approaches. No blood biomarker predicted motor or nonmotor prognosis. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Non-neuronal cell types such as astrocytes can contribute to Parkinson's disease (PD) pathology. The G2019S\udmutation in leucine-rich repeat kinase 2 (LRRK2) is one of the most common known causes of familial PD. To\udcharacterize its effect on astrocytes, we developed a protocol to produce midbrain-patterned astrocytes from\udhuman induced pluripotent stem cells (iPSCs) derived from PD LRRK2 G2019S patients and healthy controls.\udRNA sequencing analysis revealed the downregulation of genes involved in the extracellular matrix in PD cases.\udIn particular, transforming growth factor beta 1 (TGFB1), which has been shown to inhibit microglial inflammatory\udresponse in a rat model of PD, and matrix metallopeptidase 2 (MMP2), which has been shown to\uddegrade α-synuclein aggregates, were found to be down-regulated in LRRK2 G2019S astrocytes. Our findings\udsuggest that midbrain astrocytes carrying the LRRK2 G2019S mutation may have reduced neuroprotective capacity\udand may contribute to the development of PD pathology.

Background: Although primarily a neurodegenerative process, there is increasing awareness of peripheral disease mechanisms in Parkinson's disease. To investigate disease processes in accessible patient cells, we studied peripheral blood mononuclear cells in recently diagnosed PD patients and rapid eye movement‐sleep behavior disorder patients who have a greatly increased risk of developing PD. We hypothesized that peripheral blood mononuclear cells may recapitulate cellular pathology found in the PD brain and investigated these cells for mitochondrial dysfunction and oxidative stress. Methods: Peripheral blood mononuclear cells were isolated and studied from PD patients, rapid eye movement‐sleep behavior disorder patients and age‐ and sex‐matched control individuals from the well‐characterized Oxford Discovery cohort. All participants underwent thorough clinical assessment. Results: Initial characterization showed that PD patients had elevated levels of CD14 + monocytes and monocytes expressing C‐C motif chemokine receptor 2. Mitochondrial dysfunction and oxidative stress were increased in PD patient peripheral blood mononuclear cells, with elevated levels of mitochondrial reactive oxygen species specifically in patient monocytes. This was combined with reduced levels of the antioxidant superoxide dismutase in blood cells from PD patients and, importantly, also in rapid eye movement‐sleep behavior disorder patients. This mitochondrial dysfunction was associated with a concomitant increase in glycolysis in both PD and rapid eye movement‐sleep behavior disorder patient blood cells independent of glucose uptake or monocyte activation. Conclusions: This work demonstrates functional bioenergetic deficits in PD and rapid eye movement‐sleep behavior disorder patient blood cells during the early stages of human disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

OBJECTIVE The neurodegenerative disease, amyotrophic lateral sclerosis (ALS), is a heterogeneous clinical syndrome involving multiple molecular pathways. The development of biomarkers for use in therapeutic trials is a priority. We sought to use a high-throughput proteomic method to identify novel biomarkers in individual cerebrospinal fluid (CSF) samples. METHODS Liquid chromatography/tandem mass spectrometry with label-free quantification was used to identify CSF proteins using samples from a well-characterized longitudinal cohort comprising patients with ALS (n = 43), the upper motor neuron variant, primary lateral sclerosis (PLS; n = 6), and cross-sectional healthy (n = 20) and disease controls (Parkinsons' disease, n = 20; ALS mimic disorders, n = 12). RESULTS Three macrophage-derived chitinases showed increased abundance in ALS: chitotriosidase (CHIT1), chitinase-3-like protein 1 (CHI3L1), and chitinase-3-like protein 2 (CHI3L2). Elevated CHI3L1 was common to ALS and PLS, whereas CHIT1 and CHI3L2 levels differed. Chitinase levels correlated with disease progression rate (CHIT1, r = 0.56, p < 0.001; CHI3L1, r = 0.31; p = 0.028; CHI3L2, r = 0.29, p = 0.044). CHIT1, CHI3L1, and CHI3L2 levels correlated with phosphorylated neurofilament heavy chain (pNFH; r = 0.62, p < 0.001; r = 0.49, p < 0.001; r = 0.41, p < 0.001). CHI3L1 levels, but not CHIT1 or CHI3L2, increased over time in those with low initial levels (gradient = 0.005 log abundance units/month, p = 0.001). High CHIT1 was associated with shortened survival (hazard ratio [HR] 2.84; p = 0.009). Inclusion of pNFH in survival models left only an association of pNFH and survival (HR 1.26; p = 0.019). INTERPRETATION Neuroinflammatory mechanisms have been consistently implicated through various experimental paradigms. These results support a key role for macrophage activity in ALS pathogenesis, offering novel target engagement and pharmacodynamic biomarkers for neuroinflammation-focused ALS therapy. Ann Neurol 2018;83:258-268.

PurposeThe Oxford Parkinson’s Disease Centre (OPDC) Discovery Cohort magnetic resonance imaging (MRI) sub-study (OPDC-MRI) collects high quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson’s, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson’s and at-risk individuals.ParticipantsParticipants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data is currently available for 290 participants: 119 patients with early idiopathic Parkinson’s, 15 Parkinson’s patients with pathogenic mutations of the LRRK2 or GBA genes, 68 healthy controls and 87 individuals at risk of Parkinson’s (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder - RBD).Findings to dateDifferences in brain structure in early Parkinson’s were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson’s, and RBD, but not Alzheimer’s, suggesting that the effect is pathology specific. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease.Future plansOngoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.Article SummaryStrengths and limitations of this studyHigh quality 3T MRI data in a very well phenotyped and longitudinally followed cohort of Parkinson’s and RBD.All imaging data were acquired on the same MRI scanner, quite unique for a study of this duration. The protocol includes both standard sequences, comparable across other studies, and sequences acquired to investigate study-specific research questions.Clinical longitudinal data are acquired every 18 months and will be used to relate baseline imaging with clinical progression. Information about conversion to Parkinson’s of the at-risk individuals will also be available, providing the ultimate validation of potential biomarkers. MRI follow-up is also ongoing, which will allow longitudinal imaging analyses.Statistical maps of published results and support data relative to the analyses are available to share.OPDC-MRI phenotyping is deep and relatively frequent, however the size of the cohort is not at the level of population-level cohort studies. MRI sequences are high quality, but could not exploit the latest advances in the field in order to maintain continuity.

Mechanistic disease stratification will be crucial to develop a precision medicine approach for future disease modifying therapy in sporadic Parkinson’s disease (sPD). Mitochondrial and lysosomal dysfunction are key mechanisms in the pathogenesis of sPD and therefore promising targets for therapeutic intervention. We investigated mitochondrial and lysosomal function in skin fibroblasts of 100 sPD patients and 50 age-matched controls. A combination of cellular assays, RNA-seq based pathway analysis and genotyping was applied. Distinct subgroups with mitochondrial (mito-sPD) or lysosomal (lyso-sPD) dysfunction were identified. Mitochondrial dysfunction correlated with reduction in complex I and IV protein levels. RNA-seq based pathway analysis revealed marked activation of the lysosomal pathway with enrichment for lysosomal disease gene variants in lyso-sPD. Conversion of fibroblasts to induced neuronal progenitor cells and subsequent differentiation into tyrosine hydroxylase positive neurons confirmed and further enhanced both mitochondrial and lysosomal abnormalities. Treatment with ursodeoxycholic acid improved mitochondrial membrane potential and intracellular ATP levels even in sPD patient fibroblast lines with comparatively mild mitochondrial dysfunction. The results of our study suggest that in-depth phenotyping and focussed assessment of putative neuroprotective compounds in peripheral tissue are a promising approach towards disease stratification and precision medicine in sPD.

The neurodegenerative disease, amyotrophic lateral sclerosis (ALS), is a heterogeneous clinical syndrome involving multiple molecular pathways. The development of biomarkers for use in therapeutic trials is a priority. We sought to use a high-throughput proteomic method to identify novel biomarkers in individual cerebrospinal fluid (CSF) samples.Liquid chromatography/tandem mass spectrometry with label-free quantification was used to identify CSF proteins using samples from a well-characterized longitudinal cohort comprising patients with ALS (n = 43), the upper motor neuron variant, primary lateral sclerosis (PLS; n = 6), and cross-sectional healthy (n = 20) and disease controls (Parkinsons' disease, n = 20; ALS mimic disorders, n = 12).Three macrophage-derived chitinases showed increased abundance in ALS: chitotriosidase (CHIT1), chitinase-3-like protein 1 (CHI3L1), and chitinase-3-like protein 2 (CHI3L2). Elevated CHI3L1 was common to ALS and PLS, whereas CHIT1 and CHI3L2 levels differed. Chitinase levels correlated with disease progression rate (CHIT1, r = 0.56, p0.001; CHI3L1, r = 0.31; p = 0.028; CHI3L2, r = 0.29, p = 0.044). CHIT1, CHI3L1, and CHI3L2 levels correlated with phosphorylated neurofilament heavy chain (pNFH; r = 0.62, p0.001; r = 0.49, p0.001; r = 0.41, p0.001). CHI3L1 levels, but not CHIT1 or CHI3L2, increased over time in those with low initial levels (gradient = 0.005 log abundance units/month, p = 0.001). High CHIT1 was associated with shortened survival (hazard ratio [HR] 2.84; p = 0.009). Inclusion of pNFH in survival models left only an association of pNFH and survival (HR 1.26; p = 0.019).Neuroinflammatory mechanisms have been consistently implicated through various experimental paradigms. These results support a key role for macrophage activity in ALS pathogenesis, offering novel target engagement and pharmacodynamic biomarkers for neuroinflammation-focused ALS therapy. Ann Neurol 2018;83:258-268.

International audience; The present study aimed to examine whether the APOE ε4 allele, associated with dementia with Lewy bodies (DLB), and possibly with dementia in Parkinson's disease (PD), is also associated with idiopathic rapid eye movement sleep behavior disorder (RBD). Two single nucleotide polymorphisms, rs429358 and rs7412, were genotyped in RBD patients (n = 480) and in controls (n = 823). APOE ε4 allele frequency was 0.14 among RBD patients and 0.13 among controls (OR = 1.11, 95% CI: 0.88-1.40, p = 0.41). APOE ε4 allele frequencies were similar in those who converted to DLB (0.14) and those who converted to Parkinson's disease (0.12) or multiple system atrophy (0.14, p = 1.0). The APOE ε4 allele is neither a risk factor for RBD nor it is associated with conversion from RBD to DLB or other synucleinopathies.

α-Synuclein (α-Syn), a protein synthesized by neurons, as the major protein component of Lewy body inclusions, undoubtedly has a prominent role in the pathogenesis of Parkinson's Disease (PD). In an attempt to enable pre-symptomatic and definitive diagnosis, numerous attempts have been made to align assayed total α-Syn levels in serum (where there is a native presence) to PD disease status. Results have been conflicting. The status of circulating and potentially neuroprotective α-Syn autoantibodies in PD subjects is also unclear. In previous work we demonstrated that electrochemically assayed autoantibody levels were higher in PD patients compared to controls and, significantly, noted that this differentiation was most marked early in disease. Herein we report a robust (coefficient of variation 3.0%) single step and label free analysis of 90 subjects, including 60 PD patients, with a mean disease duration of 1.4 years and 29 control subjects. In this cross sectional cohort we observe a statistically significant (p < 0.05; Mann-Whitney U test) difference in autoantibody levels in PD patients versus controls, although there was no resolved scaling with symptomatic disease stage (p > 0.05; Kruskal-Wallis test).

IntroductionPatients with idiopathic RBD have an increased risk of developing a defined neurodegenerative disorder, the majority developing PD. Is it possible to detect features of PD in RBD, before a diagnosis of PD is established?MethodsFifty-seven patients with polysomnography-proven idiopathic RBD and seventy-four control and drug-naïve PD subjects were recruited. All participants underwent a thorough motor and non-motor assessment, and were screened for mutations in glucocerebrosidase (GBA) genes. Visual working memory was separately assessed in 21 RBD, 15 drug-naïve PD and 21 controls using a serial order task testing both recall precision and the pattern of impairment.ResultsRBD patients had increased motor and postural impairment compared to controls. Non-motor deficits (hyposmia, constipation, depression, anxiety) were similar between RBD and PD cases. Furthermore, there was a significant deficit of working memory memory recall precision in PD and RBD, with the pattern of deficit being similar in both groups.ConclusionRBD is associated with motor and non-motor impairment often seen in early PD. The pattern of visual working memory impairment in RBD is equivalent to that observed in early PD. These results support the hypothesis that idiopathic RBD is representative of prodromal sporadic PD.

Nonmotor symptoms (NMS) are an important prodromal feature of Parkinson's disease (PD). However, their frequency, treatment rates, and impact on health‐related quality of life (HRQoL) in the early motor phase is unclear. Rates of NMS in enriched at‐risk populations, such as first‐degree PD relatives, have not been delineated. We assessed NMS in an early cohort of PD, first‐degree PD relatives and control subjects to address these questions. In total, 769 population‐ascertained PD subjects within 3.5 years of diagnosis, 98 first‐degree PD relatives, and 287 control subjects were assessed at baseline across the following NMS domains: (1) neuropsychiatric; (2) gastrointestinal; (3) sleep; (4) sensory; (5) autonomic; and (6) sexual. NMS were much more common in PD, compared to control subjects. More than half of the PD cases had hyposmia, pain, fatigue, sleep disturbance, or urinary dysfunction. NMS were more frequent in those with the postural instability gait difficulty phenotype, compared to the tremor dominant (mean total number of NMS 7.8 vs. 6.2; P

Objectives There is a critical need to develop robust biomarkers for Parkinson9s diasease (PD) research. We aimed to determine whether a serum biomarker could be used: to predict cognitive decline in PD or a diagnosis of PD. Five of the most promising serum biomarkers were identified based on recent and current evidence: Vitamin D, Apolipoprotein A1 (ApoA1), Uric Acid, C-reactive protein and Epidermal Growth Factor. Method A peripheral blood sample was taken at baseline, spun in a centrifuge and then stored at −80°C. PD patients (n=641) diagnosed within 3.5 years, a control population (n=146) and patients with REM sleep behaviour disorder (n=74) were included at baseline. 3 year follow up data was available from 229 PD patients. Serum analysis was conducted either using Abbott systems or ELISA techniques. Age, gender, disease duration and seasonality (for vitamin D) were adjusted for using statistical models. Results: There was no strong evidence that the potential biomarkers predicted either baseline or change in cognition. Uric acid was lower in the PD group compared to controls (p=0.008), though this effect was not replicated in the RBD group. EGF (p

ObjectiveTo delineate treatment and quality of life of non-motor symptoms (NMS) in early Parkinson's disease (PD) and first-degree relatives.BackgroundNon-motor symptoms (NMS) are an important prodromal feature of Parkinson's disease (PD). However, their frequency, treatment rates and impact on health-related quality of life (HRQoL) in the early motor phase is unclear.Methods769 population-ascertained PD subjects within 3.5 years of diagnosis and 287 control subjects were assessed. Validated severity questionnaires were employed to assess NMS symptoms across the following domains: (1) neuropsychiatric (2) gastrointestinal (3) sleep (4) sensory (5) autonomic (6) sexual. Health related quality of life (HRQoL), functional status and management were also evaluated.ResultsNMS were common in early PD. More than half of the PD cases had hyposmia, pain, fatigue, sleep disturbance or urinary dysfunction. PD cases had worse HRQoL scores than controls (OR 4.1, pConclusionsDespite their major impact on HRQoL, NMS are usually under-recognised and treated. The use of screening tools could improve recognition and treatment of NMS in early PD.