117 research outputs found

    EEG spectral coherence data distinguish chronic fatigue syndrome patients from healthy controls and depressed patients-A case control study

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    <p>Abstract</p> <p>Background</p> <p>Previous studies suggest central nervous system involvement in chronic fatigue syndrome (CFS), yet there are no established diagnostic criteria. CFS may be difficult to differentiate from clinical depression. The study's objective was to determine if spectral coherence, a computational derivative of spectral analysis of the electroencephalogram (EEG), could distinguish patients with CFS from healthy control subjects and not erroneously classify depressed patients as having CFS.</p> <p>Methods</p> <p>This is a study, conducted in an academic medical center electroencephalography laboratory, of 632 subjects: 390 healthy normal controls, 70 patients with carefully defined CFS, 24 with major depression, and 148 with general fatigue. Aside from fatigue, all patients were medically healthy by history and examination. EEGs were obtained and spectral coherences calculated after extensive artifact removal. Principal Components Analysis identified coherence factors and corresponding factor loading patterns. Discriminant analysis determined whether spectral coherence factors could reliably discriminate CFS patients from healthy control subjects without misclassifying depression as CFS.</p> <p>Results</p> <p>Analysis of EEG coherence data from a large sample (n = 632) of patients and healthy controls identified 40 factors explaining 55.6% total variance. Factors showed highly significant group differentiation (p < .0004) identifying 89.5% of unmedicated female CFS patients and 92.4% of healthy female controls. Recursive jackknifing showed predictions were stable. A conservative 10-factor discriminant function model was subsequently applied, and also showed highly significant group discrimination (p < .001), accurately classifying 88.9% unmedicated males with CFS, and 82.4% unmedicated male healthy controls. No patient with depression was classified as having CFS. The model was less accurate (73.9%) in identifying CFS patients taking psychoactive medications. Factors involving the temporal lobes were of primary importance.</p> <p>Conclusions</p> <p>EEG spectral coherence analysis identified unmedicated patients with CFS and healthy control subjects without misclassifying depressed patients as CFS, providing evidence that CFS patients demonstrate brain physiology that is not observed in healthy normals or patients with major depression. Studies of new CFS patients and comparison groups are required to determine the possible clinical utility of this test. The results concur with other studies finding neurological abnormalities in CFS, and implicate temporal lobe involvement in CFS pathophysiology.</p

    Effectiveness of the adapted bivalent mRNA COVID-19 vaccines against hospitalisation in individuals aged ≥ 60 years during the Omicron XBB lineage-predominant period: VEBIS SARI VE network, Europe, February to August, 2023

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    Members of the European Hospital Vaccine Effectiveness Group: Portugal: Ana Paula Rodrigues, Débora Pereira, Susana Costa Maia e Silva, Paula Pinto, Cristina Bárbara, António Pais de Lacerda, Raquel Guiomar and Camila Henriques.The European Medicines Agency (EMA) authorised four adapted bivalent mRNA COVID-19 vaccines for use against COVID-19 in September/October 2022: Comirnaty (BNT162b2; Pfizer-BioNTech) and Spikevax (mRNA-1273; Moderna) Original/Omicron BA.1 and Original/Omicron BA.4–5 [1]. During autumn 2022, all European Union/European Economic Area (EU/EEA) countries had vaccination campaigns in place to administer a booster dose, with several countries using the adapted bivalent vaccines [2]. The Omicron-descendent XBB lineage and XBB.1.5 sub-lineage became variants of interest in March 2023 [3]. We estimated the effectiveness of the COVID-19 bivalent vaccines against hospitalisation with PCR-confirmed SARS-CoV-2 infection among patients aged ≥ 60 years with severe acute respiratory infection (SARI) during the XBB lineage-predominant period.The ‘Vaccine Effectiveness, Burden and Impact Studies studies’ (VEBIS) is a project of the European Centre for Disease Prevention and Control (ECDC) run under the framework con tract No. ECDC/2021/016.info:eu-repo/semantics/publishedVersio

    A Customized Pigmentation SNP Array Identifies a Novel SNP Associated with Melanoma Predisposition in the SLC45A2 Gene

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    As the incidence of Malignant Melanoma (MM) reflects an interaction between skin colour and UV exposure, variations in genes implicated in pigmentation and tanning response to UV may be associated with susceptibility to MM. In this study, 363 SNPs in 65 gene regions belonging to the pigmentation pathway have been successfully genotyped using a SNP array. Five hundred and ninety MM cases and 507 controls were analyzed in a discovery phase I. Ten candidate SNPs based on a p-value threshold of 0.01 were identified. Two of them, rs35414 (SLC45A2) and rs2069398 (SILV/CKD2), were statistically significant after conservative Bonferroni correction. The best six SNPs were further tested in an independent Spanish series (624 MM cases and 789 controls). A novel SNP located on the SLC45A2 gene (rs35414) was found to be significantly associated with melanoma in both phase I and phase II (P<0.0001). None of the other five SNPs were replicated in this second phase of the study. However, three SNPs in TYR, SILV/CDK2 and ADAMTS20 genes (rs17793678, rs2069398 and rs1510521 respectively) had an overall p-value<0.05 when considering the whole DNA collection (1214 MM cases and 1296 controls). Both the SLC45A2 and the SILV/CDK2 variants behave as protective alleles, while the TYR and ADAMTS20 variants seem to function as risk alleles. Cumulative effects were detected when these four variants were considered together. Furthermore, individuals carrying two or more mutations in MC1R, a well-known low penetrance melanoma-predisposing gene, had a decreased MM risk if concurrently bearing the SLC45A2 protective variant. To our knowledge, this is the largest study on Spanish sporadic MM cases to date

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN
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