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Weidinger, S.

Publications and source records attributed to Weidinger, S..

2 recordsLinked to original sources

Tryptophan wasting and disease activity as a systems phenomenon in inflammation - an analysis across 13 chronic inflammatory diseases.

Chronic inflammatory diseases (CID) are systems disorders affecting various organs including the intestine, joint and skin. The essential amino acid tryptophan (Trp) is not only used for protein synthesis but can also be catabolized to various bioactive derivatives that are important for cellular energy metabolism and immune regulation. Increased Trp catabolism via the kynurenine pathway is seen across individual CID entities1-5. Here, we assessed the levels of Trp and tryptophan derivatives across 13 CID to investigate the extent and nature of Trp wasting as a systems phenomenon in CID. We found reduced serum Trp levels across the majority of CID and a prevailing negative relationship between Trp and systemic inflammatory marker C-reactive protein (CRP). Increases in the kynurenine-to-Trp ratio (Kyn:Trp) indicate that the kynurenine pathway is a major route for CID-related Trp wasting. However, the extent of Trp depletion and its relationship with disease activity varies by disease, indicating potential differences in Trp metabolism. In addition, we find that amino acid catabolism in chronic inflammation is specific to tryptophan wasting, whereas other proteinogenic amino acids are not affected. Hence, our results suggest that increased Trp catabolism is a common metabolic occurrence in CID that may directly affect systemic immunity. Grant supportThis work was supported by the DFG Cluster of Excellence 1261 "Precision medicine in chronic inflammation" (KA, SSchr, PR, BH, SWa), the BMBF (e:Med Juniorverbund "Try-IBD" 01ZX1915A and 01ZX2215, the e:Med Network iTREAT 01ZX2202A, and GUIDE-IBD 031L0188A), DFG RU5042 (PR, KA), and Innovative Medicines Initiative 2 Joint Undertakings ("Taxonomy, Treatments, Targets and Remission", No. 831434, "ImmUniverse", grant agreement No. 853995, "BIOMAP", grant agreement No. 821511).

immunology↗

The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we collected, curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated transcriptomics analysis of public datasets shed light on a number of genes which are frequently deregulated in the psoriatic lesion compared with the unaffected skin in a large number of studies. In particular, CRABP2, LCN2, S100A12 and PDZK1IP1 were found to be deregulated in all of the datasets analyzed. Furthermore, the analysis of co-expression networks highlights genes showing aberrant patterns of connectivity in the lesional network as compared to the network inferred from unaffected skin samples. For instance, we identified co-expression patterns of SERPINB4, KYNU and S100A12 as being the most affected by the disease. Network analysis allowed us to identify YPEL1 and HUS1 as plausible, previously unknown, actors in the expression of the psoriasis phenotype. In addition, by exploiting topological properties of the network models, we highlighted a set of 250 non-deregulated genes, 223 of which have never been associated with the disease before, including CACNA1A, HADH, ATP5MC1 and CBARP among others. Finally, we characterized specific communities of co-expressed genes sustaining relevant molecular functions and specific immune cell types expression signatures playing a role in the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases.

systems biology↗