(Re-)introduction of TNF antagonists and JAK inhibitors in patients with previous tuberculosis: a systematic review.

BACKGROUND: Tuberculosis (TB) is a common complication associated with treatment with tumor necrosis factor (TNF) antagonists and Janus kinase (JAK) inhibitors. However, there is uncertainty about the risk of TB relapse in patients with TB and comorbidities requiring treatment with these agents. OBJECTIVES: Partner Site Hamburg-Lübeck-Borstel-Riems. To assess the risk of TB relapse in patients (re-)started on TNF antagonists or JAK inhibitors. METHODS: Systematic review. DATA SOURCES: PubMed and Cochrane Library databases until 11 December 2023. STUDY ELIGIBILITY CRITERIA: Studies reporting on patients with current or previous TB who were (re-)started on TNF antagonists or JAK inhibitors. RESULTS: Of 5018 articles screened for eligibility, 67 publications reporting on 368 TB patients who (re-)initiated treatment with TNF antagonists for underlying diseases were included. The median age was 42.5 years (95%CI: 40.4 - 42.5) and the proportion of female patients was 36.6% (n=74) of patients whose sex was reported. A total of 14 patients (3.8%, 95% CI: 2.1 - 6.3%) developed TB relapse after a median of 8.5 months (IQR: 6.8 - 14.8 months) following (re-)initiation of anti-TNF treatment. Furthermore, among 251 articles screened for eligibility, 11 reports on TB patients who were (re-)started on JAK inhibitors for underlying diseases were identified. The median age was 62 years (IQR: 48.5 - 68.5 years) and 45.5% (n=5) were female. Only one patient (9.1%, 95% CI: 0.2 - 41.3%) had TB reactivation ten months after starting treatment with ruxolitinib. In addition, 94 patients who were treated with TNF antagonists and two patients were temporarily treated with JAK inhibitors for prevention or treatment of paradoxical reactions were analysed. None of the publications reported microbiological failure or worsening of TB-related symptoms. CONCLUSIONS: (Re-)initiation of TNF antagonists and JAK inhibitors may be relatively safe in patients with current or previous TB and the need for further treatment of underlying diseases.

A Single-Run HPLC-MS Multiplex Assay for Therapeutic Drug Monitoring of Relevant First- and Second-Line Antibiotics in the Treatment of Drug-Resistant Tuberculosis.

The treatment of drug-resistant Mycobacterium tuberculosis relies on complex antibiotic therapy. Inadequate antibiotic exposure can lead to treatment failure, acquired drug resistance, and an increased risk of adverse events. Therapeutic drug monitoring (TDM) can be used to optimize the antibiotic exposure. Therefore, we aimed to develop a single-run multiplex assay using high-performance liquid chromatography-mass spectrometry (HPLC-MS) for TDM of patients with multidrug-resistant, pre-extensively drug-resistant and extensively drug-resistant tuberculosis. A target profile for sufficient performance, based on the intended clinical application, was established and the assay was developed accordingly. Antibiotics were analyzed on a zwitterionic hydrophilic interaction liquid chromatography column and a triple quadrupole mass spectrometer using stable isotope-labeled internal standards. The assay was sufficiently sensitive to monitor drug concentrations over five half-lives for rifampicin, rifabutin, levofloxacin, moxifloxacin, bedaquiline, linezolid, clofazimine, terizidone/cycloserine, ethambutol, delamanid, pyrazinamide, meropenem, prothionamide, and para-amino salicylic acid (PAS). Accuracy and precision were sufficient to support clinical decision making (≤±15% in clinical samples and ±20-25% in spiked samples, with 80% of future measured concentrations predicted to fall within ±40% of nominal concentrations). The method was applied in the TDM of two patients with complex drug-resistant tuberculosis. All relevant antibiotics from their regimens could be quantified and high-dose therapy was initiated, followed by microbiological conversion. In conclusion, we developed a multiplex assay that enables TDM of the relevant first- and second-line anti-tuberculosis medicines in a single run and was able to show its applicability in TDM of two drug-resistant tuberculosis patients.

Tuberculosis incidence in foreign-born people residing in European countries in 2020.

BackgroundEuropean-specific policies for tuberculosis (TB) elimination require identification of key populations that benefit from TB screening.AimWe aimed to identify groups of foreign-born individuals residing in European countries that benefit most from targeted TB prevention screening.MethodsThe Tuberculosis Network European Trials group collected, by cross-sectional survey, numbers of foreign-born TB patients residing in European Union (EU) countries, Iceland, Norway, Switzerland and the United Kingdom (UK) in 2020 from the 10 highest ranked countries of origin in terms of TB cases in each country of residence. Tuberculosis incidence rates (IRs) in countries of residence were compared with countries of origin.ResultsData on 9,116 foreign-born TB patients in 30 countries of residence were collected. Main countries of origin were Eritrea, India, Pakistan, Morocco, Romania and Somalia. Tuberculosis IRs were highest in patients of Eritrean and Somali origin in Greece and Malta (both > 1,000/100,000) and lowest among Ukrainian patients in Poland (3.6/100,000). They were mainly lower in countries of residence than countries of origin. However, IRs among Eritreans and Somalis in Greece and Malta were five times higher than in Eritrea and Somalia. Similarly, IRs among Eritreans in Germany, the Netherlands and the UK were four times higher than in Eritrea.ConclusionsCountry of origin TB IR is an insufficient indicator when targeting foreign-born populations for active case finding or TB prevention policies in the countries covered here. Elimination strategies should be informed by regularly collected country-specific data to address rapidly changing epidemiology and associated risks.

[Treatment of tuberculosis: what is new?] / Therapie der Tuberkulose: Was gibt es Neues?

Never before have so many people around the world been simultaneously affected by tuberculosis. Tuberculosis is the leading cause of death from a bacterial infectious disease worldwide. The World Health Organization's ambitious goal from 2014 of achieving global elimination of tuberculosis does not seem realistic, but on current trends, tuberculosis could be eliminated in the European Union by 2040. Since the beginning of 2022, there have been more innovations for the treatment of tuberculosis than in no other comparable time period before. One month of rifapentine and isoniazid is effective in treating latent tuberculosis infection. However, rifapentine is licensed in the USA but not in the EU and must be imported for individual cases. The duration of the standard treatment for tuberculosis can be shortened to four months but this treatment regimen is also based on rifapentine, in addition to isoniazid, pyrazinamide, and moxifloxacin. The approval of rifapentine in Europe is a much-needed step towards shortening the treatment of tuberculosis. With new drugs an even shorter standard treatment of only 2 months is possible. The treatment of multidrug-resistant/rifampicin-resistant tuberculosis (MDR-/RR-TB) has been shortened to six months, the same length as the standard treatment available in Germany. The combination of bedaquiline, pretomanid, linezolid ± moxifloxacin, cured around 90% of affected patients were cured in studies with a treatment duration of six months. With 19 drugs in clinical trials, the treatment of tuberculosis is expected to continue to improve rapidly in the coming years.

Design of Multidrug-Resistant Tuberculosis Treatment Regimens Based on DNA Sequencing.

BACKGROUND: Comprehensive and reliable drug susceptibility testing (DST) is urgently needed to provide adequate treatment regimens for patients with multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB). We determined whether next-generation sequencing (NGS) analysis of Mycobacterium tuberculosis complex isolates and genes implicated in drug resistance can guide the design of effective MDR/RR-TB treatment regimens. METHODS: NGS-based genomic DST predictions of M. tuberculosis complex isolates from MDR/RR-TB patients admitted to a TB reference center in Germany between 1 January 2015 and 30 April 2019 were compared with phenotypic DST results of mycobacteria growth indicator tubes (MGIT). Standardized treatment algorithms were applied to design individualized therapies based on either genomic or phenotypic DST results, and discrepancies were further evaluated by determination of minimal inhibitory drug concentrations (MICs) using Sensititre MYCOTBI and UKMYC microtiter plates. RESULTS: In 70 patients with MDR/RR-TB, agreement among 1048 pairwise comparisons of genomic and phenotypic DST was 86.3%; 76 (7.2%) results were discordant, and 68 (6.5%) could not be evaluated due to the presence of polymorphisms with yet unknown implications for drug resistance. Importantly, 549 of 561 (97.9%) predictions of drug susceptibility were phenotypically confirmed in MGIT, and 27 of 64 (42.2%) false-positive results were linked to previously described mutations mediating a low or moderate MIC increase. Virtually all drugs (99.0%) used in combination therapies that were inferred from genomic DST were confirmed to be susceptible by phenotypic DST. CONCLUSIONS: NGS-based genomic DST can reliably guide the design of effective MDR/RR-TB treatment regimens.

Deep learning the collisional cross sections of the peptide universe from a million experimental values.

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV < 1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools peptides validate the model within a 1.4% median relative error (R > 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.

Perspective for Precision Medicine for Tuberculosis.

Tuberculosis is a bacterial infectious disease that is mainly transmitted from human to human via infectious aerosols. Currently, tuberculosis is the leading cause of death by an infectious disease world-wide. In the past decade, the number of patients affected by tuberculosis has increased by ~20 percent and the emergence of drug-resistant strains of Mycobacterium tuberculosis challenges the goal of elimination of tuberculosis in the near future. For the last 50 years, management of patients with tuberculosis has followed a standardized management approach. This standardization neglects the variation in human susceptibility to infection, immune response, the pharmacokinetics of drugs, and the individual duration of treatment needed to achieve relapse-free cure. Here we propose a package of precision medicine-guided therapies that has the prospect to drive clinical management decisions, based on both host immunity and M. tuberculosis strains genetics. Recently, important scientific discoveries and technological advances have been achieved that provide a perspective for individualized rather than standardized management of patients with tuberculosis. For the individual selection of best medicines and host-directed therapies, personalized drug dosing, and treatment durations, physicians treating patients with tuberculosis will be able to rely on these advances in systems biology and to apply them at the bedside.

The proteome landscape of the kingdoms of life.

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported1, advances in mass-spectrometry-based proteomics2 have enabled increasingly comprehensive identification and quantification of the human proteome3-6. However, there have been few comparisons across species7,8, in stark contrast with genomics initiatives9. Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides from Bacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.

Reconstructing cell cycle and disease progression using deep learning.

We show that deep convolutional neural networks combined with nonlinear dimension reduction enable reconstructing biological processes based on raw image data. We demonstrate this by reconstructing the cell cycle of Jurkat cells and disease progression in diabetic retinopathy. In further analysis of Jurkat cells, we detect and separate a subpopulation of dead cells in an unsupervised manner and, in classifying discrete cell cycle stages, we reach a sixfold reduction in error rate compared to a recent approach based on boosting on image features. In contrast to previous methods, deep learning based predictions are fast enough for on-the-fly analysis in an imaging flow cytometer.The interpretation of information-rich, high-throughput single-cell data is a challenge requiring sophisticated computational tools. Here the authors demonstrate a deep convolutional neural network that can classify cell cycle status on-the-fly.

Personalized Medicine for Chronic Respiratory Infectious Diseases: Tuberculosis, Nontuberculous Mycobacterial Pulmonary Diseases, and Chronic Pulmonary Aspergillosis.

Chronic respiratory infectious diseases are causing high rates of morbidity and mortality worldwide. Tuberculosis, a major cause of chronic pulmonary infection, is currently responsible for approximately 1.5 million deaths per year. Although important advances in the fight against tuberculosis have been made, the progress towards eradication of this disease is being challenged by the dramatic increase in multidrug-resistant bacilli. Nontuberculous mycobacteria causing pulmonary disease and chronic pulmonary aspergillosis are emerging infectious diseases. In contrast to other infectious diseases, chronic respiratory infections share the trait of having highly variable treatment outcomes despite longstanding antimicrobial therapy. Recent scientific progress indicates that medicine is presently at a transition stage from programmatic to personalized management. We explain current state-of-the-art management concepts of chronic pulmonary infectious diseases as well as the underlying methods for therapeutic decisions and their implications for personalized medicine. Furthermore, we describe promising biomarkers and techniques with the potential to serve future individual treatment concepts in this field of difficult-to-treat patients. These include candidate markers to improve individual risk assessment for disease development, the design of tailor-made drug therapy regimens, and individualized biomarker-guided therapy duration to achieve relapse-free cure. In addition, the use of therapeutic drug monitoring to reach optimal drug dosing with the smallest rate of adverse events as well as candidate agents for future host-directed therapies are described. Taken together, personalized medicine will provide opportunities to substantially improve the management and treatment outcome of difficult-to-treat patients with chronic respiratory infections.

Elevated angiopoietin-1 serum levels in patients with Alzheimer's disease.

Background. Alzheimer's disease (AD) is the most common cause of dementia in the elderly. AD is characterized by the accumulation of amyloid plaques and neurofibrillary tangles and by massive neuronal loss in the brain. There is epidemiologic and pathologic evidence that AD is associated with vascular risk factors and vascular diseases, contributing to cerebral hypoperfusion with consecutive stimulation of angiogenesis and upregulation of proangiogenic factors such as Angiopoietin-1 (Ang-1). Methods. In the present study, we measured Ang-1 serum levels in 42 patients with AD, 20 patients with mild cognitive impairment (MCI), and in 40 healthy elderly controls by ELISA. Results. We found significantly increased Ang-1 serum levels in patients with AD compared to control subjects (P = 0.003). There was no significant difference between MCI patients and healthy controls (P = 0.553) or between AD and MCI patients (P = 0.054). The degree of cognitive impairment as measured by the mini-mental status examination (MMSE) score was significantly correlated with the Ang-1 serum levels in all patients and healthy controls. Conclusions. We found significantly increased Ang-1 serum levels in AD patients. We could also show an association between Ang-1 serum levels and the cognitive status in all patients and healthy controls. Thus, serum Ang-1 could be a potential candidate for a biomarker panel for AD diagnosis.

Increased BDNF serum concentration in fibromyalgia with or without depression or antidepressants.

Fibromyalgia (FM) is still often viewed as a psychosomatic disorder. However, the increased pain sensitivity to stimuli in FM patients is not an "imagined" histrionic phenomena. Pain, which is consistently felt in the musculature, is related to specific abnormalities in the CNS pain matrix. Brain-derived neurotrophic factor (BDNF) is an endogenous protein involved in neuronal survival and synaptic plasticity of the central and peripheral nervous system (CNS and PNS). Several lines of evidence converged to indicate that BDNF also participates in structural and functional plasticity of nociceptive pathways in the CNS and within the dorsal root ganglia and spinal cord. In the latter, release of BDNF appears to modulate or even mediate nociceptive sensory inputs and pain hypersensitivity. We were interested, if BDNF serum concentration may be altered in FM. The present pilot study assessed to our knowledge for the first time BDNF serum concentrations in 41 FM patients in comparison to 45 age-matched healthy controls. Mean serum levels of BDNF in FM patients (19.6 ng/ml; SD 3.1) were significantly increased as compared to healthy controls (16.8 ng/ml; SD 2.7; p<0.0001). In addition, BDNF serum concentrations in FM patients were independent from age, gender, illness duration, preexisting recurrent major depression and antidepressive medication in low doses. In conclusion, the results from our study indicate that BDNF may be involved in the pathophysiology of pain in FM. Nevertheless, how BDNF increases susceptibility to pain is still not known.

Altered lymphocyte distribution in Alzheimer's disease.

The contribution of immunological factors in the etiopathogenesis of Alzheimer's disease (AD) is increasingly noted. Apart from cerebral immunological findings, peripheral changes of the immune systems have been reported including lymphocyte function and subset distribution. As data still remain inconsistent, we investigated a sample of 43 patients with AD and of 34 healthy age-matched controls. Distribution of the T-, B- and NK cell subsets was determined by flow cytometry (FACS). We found a significant decrease of CD3(+) lymphocytes as well as of CD19(+) lymphocytes. A slight increase of the CD4(+) and a decrease of the CD8(+) subpopulation could be observed, without significant change of the CD4(+)/CD8(+) ratio. CD16(+)56(+) cells were not altered. Our findings of decreased T- and B-Cell numbers in AD sustain the hypothesis of a general decline of immune activity in AD. A putative association with premature immunosenescence in AD and possible pathogenetic implications are discussed.