Broader anti-EBV TCR repertoire in multiple sclerosis: disease specificity and treatment modulation.

Epstein-Barr virus (EBV) infection has long been associated with the development of multiple sclerosis (MS). MS patients have elevated titers of EBV-specific antibodies in serum and show signs of CNS damage only after EBV infection. Regarding CD8+ T-cells, an elevated but ineffective response to EBV was suggested in MS patients, who present with a broader MHC-I-restricted EBV-specific T-cell receptor beta chain (TRB) repertoire compared to controls. It is not known whether this altered EBV response could be subject to dynamic changes, e.g., by approved MS therapies, and whether it is specific for MS. 1317 peripheral blood TRB repertoire samples of healthy donors (n=409), patients with MS (n=710) before and after treatment, patients with neuromyelitis optica spectrum disorder (n=87), myelin-oligodendrocyte-glycoprotein antibody-associated disease (n=64) and Susac's syndrome (n=47) were analyzed. Apart from MS, none of the evaluated diseases presented with a broader anti-EBV TRB repertoire. In MS patients undergoing autologous hematopoietic stem-cell transplantation, EBV reactivation coincided with elevated MHC-I-restricted EBV-specific TRB sequence matches. Therapy with ocrelizumab, teriflunomide or dimethyl fumarate reduced EBV-specific, but not CMV-specific MHC-I-restricted TRB sequence matches. Together, this data suggests that the aberrant MHC-I-restricted T-cell response directed against EBV is specific to MS with regard to NMO, MOGAD and Susac's Syndrome and that it is specifically modified by MS treatments interfering with EBV host cells or activated lymphocytes.

Psychiatric and physical comorbidities and their impact on the course of bipolar disorder: A prospective, naturalistic 4-year follow-up study.

OBJECTIVES: The aim of the present study was to increase the available evidence on how physical and psychiatric comorbidities influence the long-term outcome in bipolar I and II disorder. METHODS: We examined the prevalence of comorbid physical (metabolic, cardiovascular, thyroid, and neurological) diseases and psychiatric (neurotic, stress-related, somatoform, and personality) disorders and their impact on the risk of relapse in bipolar disorder. A total of 284 consecutively admitted patients with ICD-10 bipolar I (n=161) and II (n=123) disorder were followed up naturalistically over a period of 4 years. RESULTS: Globally, 22.0% patients had metabolic, 18.8% cardiovascular, 18.8% thyroid, and 7.6% neurological diseases; 15.5% had neurotic, stress-related, and somatoform disorders; 12.0% had personality disorders; and 52.9% had nicotine dependence. We did not find any effect of comorbid metabolic, cardiovascular or neurological diseases or psychiatric disorders on the relapse risk. However, the presence of thyroid diseases, and especially hypothyroidism, was associated with an increased risk of manic relapse in bipolar disorder I (thyroid disease: hazard ratio [HR]=2.7; P=.003; hypothyroidism: HR=3.7;, P<.001). Among patients with hypothyroidism, higher blood levels of baseline thyroid-stimulating hormone (bTSH) were also associated with an increased risk of manic relapse (HR=1.07 per milli-international units per liter; P=.011), whereas blood levels of free triiodothyronine (fT3 ) or free thyroxine (fT4 ) were not found to have an influence. CONCLUSIONS: Our data underline the negative long-term impact of thyroid diseases, and especially hypothyroidism with high blood levels of bTSH, on bipolar disorder with more manic episodes, and the importance of its detection and treatment.

A single-cell analysis framework allows for characterization of CSF leukocytes and their tissue of origin in multiple sclerosis.

Peripheral central nervous system (CNS)-infiltrating lymphocytes are a hallmark of relapsing-remitting multiple sclerosis. Tissue-resident memory T cells (TRM) not only populate the healthy CNS parenchyma but also are suspected to contribute to multiple sclerosis pathology. Because cerebrospinal fluid (CSF), unlike CNS parenchyma, is accessible for diagnostics, we evaluated whether human CSF, apart from infiltrating cells, also contains TRM cells and CNS-resident myeloid cells draining from the parenchyma or border tissues. Using deep generative models, we integrated 41 CSF and 14 CNS parenchyma single-cell RNA sequencing (scRNAseq) samples from eight independent studies, encompassing 120,629 cells. By comparing CSF immune cells collected during multiple sclerosis relapse with cells collected during therapeutic very late antigen-4 blockade, we could identify immune subsets with tissue provenance across multiple lineages, including CNS border-associated macrophages, CD8 and CD4 TRM cells, and tissue-resident natural killer cells. All lymphocytic CNS-resident cells shared expression of CXCR6 but showed differential ITGAE expression (encoding CD103). A common signature defined CD4 and CD8 TRM cells by expression of ZFP36L2, DUSP1, and ID2. We further developed a user interface-driven application based on this analysis framework for atlas-level cell identity transfer onto new CSF scRNAseq data. Together, these results define CNS-resident immune cells involved in multiple sclerosis pathology that can be detected and monitored in CSF. Targeting these cell populations might be promising to modulate immunopathology in progressive multiple sclerosis and other neuroinflammatory diseases.

Broader Epstein-Barr virus-specific T cell receptor repertoire in patients with multiple sclerosis.

Epstein-Barr virus (EBV) infection precedes multiple sclerosis (MS) pathology and cross-reactive antibodies might link EBV infection to CNS autoimmunity. As an altered anti-EBV T cell reaction was suggested in MS, we queried peripheral blood T cell receptor ß chain (TCRß) repertoires of 1,395 MS patients, 887 controls, and 35 monozygotic, MS-discordant twin pairs for multimer-confirmed, viral antigen-specific TCRß sequences. We detected more MHC-I-restricted EBV-specific TCRß sequences in MS patients. Differences in genetics or upbringing could be excluded by validation in monozygotic twin pairs discordant for MS. Anti-VLA-4 treatment amplified this observation, while interferon ß- or anti-CD20 treatment did not modulate EBV-specific T cell occurrence. In healthy individuals, EBV-specific CD8+ T cells were of an effector-memory phenotype in peripheral blood and cerebrospinal fluid. In MS patients, cerebrospinal fluid also contained EBV-specific central-memory CD8+ T cells, suggesting recent priming. Therefore, MS is not only preceded by EBV infection, but also associated with broader EBV-specific TCR repertoires, consistent with an ongoing anti-EBV immune reaction in MS.

AMLVaran: a software approach to implement variant analysis of targeted NGS sequencing data in an oncological care setting.

BACKGROUND: Next-Generation Sequencing (NGS) enables large-scale and cost-effective sequencing of genetic samples in order to detect genetic variants. After successful use in research-oriented projects, NGS is now entering clinical practice. Consequently, variant analysis is increasingly important to facilitate a better understanding of disease entities and prognoses. Furthermore, variant calling allows to adapt and optimize specific treatments of individual patients, and thus is an integral part of personalized medicine.However, the analysis of NGS data typically requires a number of complex bioinformatics processing steps. A flexible and reliable software that combines the variant analysis process with a simple, user-friendly interface is therefore highly desirable, but still lacking. RESULTS: With AMLVaran (AML Variant Analyzer), we present a web-based software, that covers the complete variant analysis workflow of targeted NGS samples. The software provides a generic pipeline that allows free choice of variant calling tools and a flexible language (SSDL) for filtering variant lists. AMLVaran's interactive website presents comprehensive annotation data and includes curated information on relevant hotspot regions and driver mutations. A concise clinical report with rule-based diagnostic recommendations is generated.An AMLVaran configuration with eight variant calling tools and a complex scoring scheme, based on the somatic variant calling pipeline appreci8, was used to analyze three datasets from AML and MDS studies with 402 samples in total. Maximum sensitivity and positive predictive values were 1.0 and 0.96, respectively. The tool's usability was found to be satisfactory by medical professionals. CONCLUSION: Coverage analysis, reproducible variant filtering and software usability are important for clinical assessment of variants. AMLVaran performs reliable NGS variant analyses and generates reports fulfilling the requirements of a clinical setting. Due to its generic design, the software can easily be adapted for use with different targeted panels for other tumor entities, or even for whole-exome data. AMLVaran has been deployed to a public web server and is distributed with Docker scripts for local use.