Systematic review and meta-analysis of the association between Epstein-Barr virus, multiple sclerosis and other risk factors.

BACKGROUND: Epstein-Barr virus (EBV) infection is thought to play a central role in the development of multiple sclerosis (MS). If causal, it represents a target for interventions to reduce MS risk. OBJECTIVE: To examine the evidence for interaction between EBV and other risk factors, and explore mechanisms via which EBV infection may influence MS risk. METHODS: Pubmed was searched using the terms 'multiple sclerosis' AND 'Epstein Barr virus', 'multiple sclerosis' AND EBV, 'clinically isolated syndrome' AND 'Epstein Barr virus' and 'clinically isolated syndrome' AND EBV. All abstracts were reviewed for possible inclusion. RESULTS: A total of 262 full-text papers were reviewed. There was evidence of interaction on the additive scale between anti-EBV antibody titre and HLA genotype (attributable proportion due to interaction (AP) = 0.48, p < 1 × 10-4). Previous infectious mononucleosis (IM) was associated with increased odds ratio (OR) of MS in HLA-DRB1*1501 positive but not HLA-DRB1*1501 negative persons. Smoking was associated with a greater risk of MS in those with high anti-EBV antibodies (OR = 2.76) but not low anti-EBV antibodies (OR = 1.16). No interaction between EBV and risk factors was found on a multiplicative scale. CONCLUSION: EBV appears to interact with at least some established MS risk factors. The mechanism via which EBV influences MS risk remains unknown

Stochastic Analysis of a Churn-Tolerant Structured Peer-to-Peer Scheme

We present and analyze a simple and general scheme to build a churn (fault)-tolerant structured Peer-to-Peer (P2P) network. Our scheme shows how to "convert" a static network into a dynamic distributed hash table(DHT)-based P2P network such that all the good properties of the static network are guaranteed with high probability (w.h.p). Applying our scheme to a cube-connected cycles network, for example, yields a $O(\log N)$ degree connected network, in which every search succeeds in $O(\log N)$ hops w.h.p., using $O(\log N)$ messages, where $N$ is the expected stable network size. Our scheme has an constant storage overhead (the number of nodes responsible for servicing a data item) and an $O(\log N)$ overhead (messages and time) per insertion and essentially no overhead for deletions. All these bounds are essentially optimal. While DHT schemes with similar guarantees are already known in the literature, this work is new in the following aspects: (1) It presents a rigorous mathematical analysis of the scheme under a general stochastic model of churn and shows the above guarantees; (2) The theoretical analysis is complemented by a simulation-based analysis that validates the asymptotic bounds even in moderately sized networks and also studies performance under changing stable network size; (3) The presented scheme seems especially suitable for maintaining dynamic structures under churn efficiently. In particular, we show that a spanning tree of low diameter can be efficiently maintained in constant time and logarithmic number of messages per insertion or deletion w.h.p. Keywords: P2P Network, DHT Scheme, Churn, Dynamic Spanning Tree, Stochastic Analysis

Regarding: Nicotinic acetylcholine receptors α7 and α9 modify tobacco smoke risk for multiple sclerosis.

This is a author manuscript of an article accepted for publication in Multiple Sclerosis Journal. Version of record is available online at Jacobs BM, Smets I, Giovannoni G, Noyce A, Jokubaitis V, Dobson R. Regarding: Nicotinic acetylcholine receptors α7 and α9 modify tobacco smoke risk for multiple sclerosis. Multiple Sclerosis Journal. December 2020. doi:10.1177/1352458520969941. Copyright (c) 2020. The Authors. doi:10.1177/135245852096994

Plasma proteomic profiles of UK Biobank participants with multiple sclerosis.

OBJECTIVE: We aimed to describe plasma protein biomarkers of multiple sclerosis risk and to explore protein biomarkers of disease severity using radiological outcome measures. METHODS: Multiple sclerosis cases and controls were identified in UK Biobank, a longitudinal cohort study of ~500,000 British adults. Plasma proteins were assayed in ~50,000 UK Biobank participants using the Olink proximity extension assay. We performed case-control association testing to examine the association between 2911 proteins and multiple sclerosis, using linear models adjusted for confounding covariates. Associations with radiological lesion burden and brain volume were determined in a subset of the cohort with available magnetic resonance imaging, using normalized T2-hyperintensity volume or whole brain volume as the outcome measure. RESULTS: In total, 407 prevalent multiple sclerosis cases and 39,979 healthy controls were included. We discovered 72 proteins associated with multiple sclerosis at a Bonferroni-adjusted p value of 0.05, including established markers such as neurofilament light chain and glial fibrillary acidic protein. We observed a decrease in plasma Granzyme A, a marker of T cell and NK cell degranulation, which was specific to multiple sclerosis. Higher levels of plasma proteins involved in coagulation were associated with lower T2 lesion burden and preserved brain volume. INTERPRETATION: We report the largest plasma proteomic screen of multiple sclerosis, replicating important known associations and suggesting novel markers, such as the reduction in granzyme A. While these findings require external validation, they demonstrate the power of biobank-scale datasets for discovering new biomarkers for multiple sclerosis

Age-specific effects of childhood body mass index on multiple sclerosis risk

OBJECTIVE: Higher body mass index (BMI) during early life is thought to be a causal risk factor for multiple sclerosis (MS). We used longitudinal Mendelian randomisation (MR) to determine whether there is a critical window during which BMI influences MS risk. METHODS: Summary statistics for childhood BMI (n ~ 28,000 children) and for MS susceptibility were obtained from recent large genome-wide association studies (GWAS) (n = 14,802 MS, 26,703 controls). We generated exposure instruments for BMI during four non-overlapping age epochs (< 3 months, 3 months–1.5 years, 2–5 years, and 7–8 years) and performed MR using the inverse variance weighted method with standard sensitivity analyses. Multivariable MR was used to account for effects mediated via later-life BMI. RESULTS: For all age epochs other than birth, genetically determined higher BMI was associated with an increased liability to MS: Birth [Odds Ratio (OR) 0.81, 95% Confidence Interval (CI) 0.50–1.31, Number of Single-Nucleotide Polymorphisms (N(SNPs)) = 7, p = 0.39], Infancy (OR 1.18, 95% CI 1.04–1.33, N(SNPs) = 18, p = 0.01), Early childhood (OR 1.31, 95% CI 1.03–1.66, N(SNPs) = 4, p = 0.03), Later childhood (OR 1.34, 95% CI 1.08–1.66, N(SNPs) = 4, p = 0.01). Multivariable MR suggested that these effects may be mediated by effects on adult BMI. CONCLUSION: We provide evidence using MR that genetically determined higher BMI during early life is associated with increased MS risk. This effect may be driven by shared genetic architecture with later-life BMI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00415-022-11161-4

Neuroanatomical and prognostic associations of depression in Parkinson's disease.

BACKGROUND: Depression is reported as a risk factor, prodromal feature and late consequence of Parkinson's disease (PD). We aimed to evaluate the timing, neuroanatomy and prognostic implications of depression in PD. METHODS: We used data from 434 023 participants from UK Biobank with 14.1 years of follow-up. Multivariable regression models established associations of depression with incident PD and regional brain volumes. Cox proportional hazards models assessed prognostic associations of depression in PD with incident dementia and all-cause mortality. RESULTS: Of 2632 individuals with incident PD, 539 (20.5%) were diagnosed with depression at some point. Depression was associated with an increased risk of subsequent PD (risk ratio 1.53, 95% CI 1.37 to 1.72). Among incident PD cases, depression prevalence rose progressively from 10 years pre-PD diagnosis (OR 2.10, 95% CI 1.57 to 2.83) to 10 years postdiagnosis (OR 3.51, 95% CI 1.33 to 9.22). Depression severity in PD was associated with reduced grey matter volume in structures including the thalamus and amygdala. Depression prior to PD diagnosis increased risk of dementia (HR 1.47, 95% CI 1.05 to 2.07) and mortality (HR 1.30, 95% CI 1.07 to 1.58). CONCLUSIONS: This large-scale prospective study demonstrated that depression prevalence increases from 10 years before PD diagnosis and is a marker of cortical and subcortical volume loss. Depression before PD diagnosis signals a worse prognosis in terms of dementia and mortality. This has clinical implications in stratifying people with poorer cognitive and prognostic trajectory in PD

Gene-Environment Interactions for Parkinson's Disease.

OBJECTIVE: Parkinson's disease (PD) is a neurodegenerative disorder with complex etiology. Multiple genetic and environmental factors have been associated with PD, but most PD risk remains unexplained. The aim of this study was to test for statistical interactions between PD-related genetic and environmental exposures in the 23andMe, Inc. research dataset. METHODS: Using a validated PD polygenic risk score and common PD-associated variants in the GBA gene, we explored interactions between genetic susceptibility factors and 7 lifestyle and environmental factors: body mass index (BMI), type 2 diabetes (T2D), tobacco use, caffeine consumption, pesticide exposure, head injury, and physical activity (PA). RESULTS: We observed that T2D, as well as higher BMI, caffeine consumption, and tobacco use, were associated with lower odds of PD, whereas head injury, pesticide exposure, GBA carrier status, and PD polygenic risk score were associated with higher odds. No significant association was observed between PA and PD. In interaction analyses, we found statistical evidence for an interaction between polygenic risk of PD and the following environmental/lifestyle factors: T2D (p = 6.502 × 10-8 ), PA (p = 8.745 × 10-5 ), BMI (p = 4.314 × 10-4 ), and tobacco use (p = 2.236 × 10-3 ). Although BMI and tobacco use were associated with lower odds of PD regardless of the extent of individual genetic liability, the direction of the relationship between odds of PD and T2D, as well as PD and PA, varied depending on polygenic risk score. INTERPRETATION: We provide preliminary evidence that associations between some environmental and lifestyle factors and PD may be modified by genotype. ANN NEUROL 2024

Lower lymphocyte count is associated with increased risk of Parkinson's disease

Objectives: Patients with established Parkinson’s disease (PD) display differences in peripheral blood biomarkers of immune function, including leukocyte differential counts, compared to controls. These differences may be useful biomarkers to predict PD and shed light on pathogenesis. We sought to identify whether peripheral immune dysregulation was associated with increased risk of subsequent PD diagnosis. Methods: We examined the relationship between incident PD and baseline differential leukocyte count and other blood markers of acute inflammation in UK Biobank, a longitudinal cohort with >500 000 participants. We used a range of sensitivity analyses and Mendelian randomization (MR) to further explore the nature of associations. Results: After excluding individuals with comorbidities which could influence biomarkers of inflammation, 465 incident PD cases and 312,125 controls remained. Lower lymphocyte count was associated with increased risk of subsequent PD diagnosis (per 1‐SD decrease in lymphocyte count OR 1.18, 95% CI 1.07‐1.32, padjusted=0.01). There was some evidence that reductions in eosinophil and monocyte counts and CRP were associated with increased PD risk, as was higher neutrophil count. Only the association between lower lymphocyte count and increased PD risk remained robust to sensitivity analyses. MR suggested that the effect of lower lymphocyte count on PD risk may be causal (per 1‐SD decrease in lymphocyte count; ORMR 1.09, 95% CI 1.01‐1.18, p=0.02). Interpretation: We provide converging evidence from observational analyses in UKB and MR that lower lymphocyte count is associated with an increased risk of subsequent PD