Summary The disease burden of chronic‐relapsing and therapy‐refractory superficial dermatophytosis dramatically increased in India within the past 5‐6 years. In order to evaluate the prevalence of this trend, 201 skin scrapings were collected from patients from all parts of India and were tested for dermatophytes using both fungal culture and a PCR‐ELISA directly performed with native skin scrapings. Fungal culture material was identified by genomic Sanger sequencing of the internal transcribed spacer (ITS) region and the translation elongation factor (TEF)‐1α gene. In total, 149 (74.13%) out of the 201 samples showed a dermatophyte‐positive culture result. Out of this, 138 (92.62%) samples were identified as Trichophyton (T.) mentagrophytes and 11 (7.38%) as Trichophyton rubrum. The PCR‐ELISA revealed similar results: 162 out of 201 (80.56%) samples were dermatophyte‐positive showing 151 (93.21%) T mentagrophytes‐ and 11 (6.79%) T rubrum‐positive samples. In this study, we show for the first time a dramatic Indian‐wide switch from T rubrum to T mentagrophytes. Additionally, sequencing revealed a solely occurring T mentagrophytes “Indian ITS genotype” that might be disseminated Indian‐wide due to the widespread abuse of topical clobetasol and other steroid molecules mixed with antifungal and antibacterial agents.

Aberrant innate immune signaling has been identified as a potential key driver of the complex pathophysiology of myelodysplastic neoplasms (MDS). This study of a large, clinically and genetically well-characterized cohort of treatment-naïve MDS patients confirms intrinsic activation of inflammatory pathways in general mediated by caspase-1, interleukin (IL)-1β and IL-18 in low-risk (LR)-MDS bone marrow and reveals a previously unrecognized heterogeneity of inflammation between genetically defined LR-MDS subgroups. Principal component analysis resolved two LR-MDS phenotypes with low (cluster 1) and high (cluster 2) levels of IL1B gene expression, respectively. Cluster 1 contained 14/17 SF3B1-mutated cases, while cluster 2 contained 8/8 del(5q) cases. Targeted gene expression analysis of sorted cell populations showed that the majority of the inflammasome-related genes, including IL1B, were primarily expressed in the monocyte compartment, consistent with a dominant role in determining the inflammatory bone marrow environment. However, the highest levels of IL18 expression were found in hematopoietic stem and progenitor cells (HSPCs). The colony forming activity of healthy donor HSPCs exposed to monocytes from LR-MDS was increased by the IL-1β-neutralizing antibody canakinumab. This work reveals distinct inflammatory profiles in LR-MDS that are of likely relevance to the personalization of emerging anti-inflammatory therapies.

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Background For many drugs, mechanisms of action with regard to desired effects and/or unwanted side effects are only incompletely understood. To investigate possible pleiotropic effects and respective molecular mechanisms, we describe here a catalogue of commonly used drugs and their impact on the blood transcriptome. Methods and results From a population-based cohort in Germany (LIFE-Adult), we collected genome-wide gene-expression data in whole blood using in Illumina HT12v4 micro-arrays (n = 3,378; 19,974 gene expression probes per individual). Expression profiles were correlated with the intake of active substances as assessed by participants’ medication. This resulted in a catalogue of fourteen substances that were identified as associated with differential gene expression for a total of 534 genes. As an independent replication cohort, an observational study of patients with suspected or confirmed stable coronary artery disease (CAD) or myocardial infarction (LIFE-Heart, n = 3,008, 19,966 gene expression probes per individual) was employed. Notably, we were able to replicate differential gene expression for three active substances affecting 80 genes in peripheral blood mononuclear cells (carvedilol: 25; prednisolone: 17; timolol: 38). Additionally, using gene ontology enrichment analysis, we demonstrated for timolol a significant enrichment in 23 pathways, 19 of them including either GPER1 or PDE4B. In the case of carvedilol, we showed that, beside genes with well-established association with hypertension (GPER1, PDE4B and TNFAIP3), the drug also affects genes that are only indirectly linked to hypertension due to their effects on artery walls or their role in lipid biosynthesis. Conclusions Our developed catalogue of blood gene expressions profiles affected by medication can be used to support both, drug repurposing and the identification of possible off-target effects.

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