Neurofilament light in plasma is a potential biomarker of central nervous system involvement in systemic lupus erythematosus

BACKGROUND: Neuropsychiatric manifestations (NP) are common in systemic lupus erythematosus (SLE). However, the pathophysiological mechanisms are not completely understood. Neurofilament light protein (NfL) is part of the neuronal cytoskeleton. Increased NfL concentrations, reflecting neurodegeneration, is observed in cerebrospinal fluid (CSF) in several neurodegenerative and neuroinflammatory conditions. We aimed to explore if plasma NfL could serve as a biomarker for central nervous system (CNS) involvement in SLE. METHODS: Sixty-seven patients with SLE underwent neurological examination; 52 underwent lumbar puncture, while 62 underwent cerebral magnetic resonance imaging (MRI). We measured selected auto-antibodies and other laboratory variables postulated to have roles in NP pathophysiology in the blood and/or CSF. We used SPM12 software for MRI voxel-based morphometry. RESULTS: Age-adjusted linear regression analyses revealed increased plasma NfL concentrations with increasing creatinine (β = 0.01, p < 0.001) and Q-albumin (β = 0.07, p = 0.008). We observed higher plasma NfL concentrations in patients with a history of seizures (β = 0.57, p = 0.014), impaired motor function (β = 0.36, p = 0.008), increasing disease activity (β = 0.04, p = 0.008), and organ damage (β = 0.10, p = 0.002). Voxel-based morphometry suggested an association between increasing plasma NfL concentrations and the loss of cerebral white matter in the corpus callosum and hippocampal gray matter. CONCLUSION: Increased plasma NfL concentrations were associated with some abnormal neurological, cognitive, and neuroimaging findings. However, plasma NfL was also influenced by other factors, such as damage accrual, creatinine, and Q-albumin, thereby obscuring the interpretation of how plasma NfL reflects CNS involvement. Taken together, NfL in CSF seems a better marker of neuronal injury than plasma NfL in patients with SLE

DataSHIELD: Taking the analysis to the data, not the data to the analysis

\ua9 The Author 2014; all rights reserved. Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK\u27s proposed \u27care.data\u27 initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis

Stromal gene signatures in large-B-cell lymphomas.

BACKGROUND: The addition of rituximab to combination chemotherapy with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP), or R-CHOP, has significantly improved the survival of patients with diffuse large-B-cell lymphoma. Whether gene-expression signatures correlate with survival after treatment of diffuse large-B-cell lymphoma is unclear. METHODS: We profiled gene expression in pretreatment biopsy specimens from 181 patients with diffuse large-B-cell lymphoma who received CHOP and 233 patients with this disease who received R-CHOP. A multivariate gene-expression-based survival-predictor model derived from a training group was tested in a validation group. RESULTS: A multivariate model created from three gene-expression signatures--termed germinal-center B-cell, stromal-1, and stromal-2 --predicted survival both in patients who received CHOP and patients who received R-CHOP. The prognostically favorable stromal-1 signature reflected extracellular-matrix deposition and histiocytic infiltration. By contrast, the prognostically unfavorable stromal-2 signature reflected tumor blood-vessel density. CONCLUSIONS: Survival after treatment of diffuse large-B-cell lymphoma is influenced by differences in immune cells, fibrosis, and angiogenesis in the tumor microenvironment

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure–associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure–related pathways and highlight tissues beyond the classical renal system in blood pressure regulation