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Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis.

ABSTRACT: The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in ~30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients.

SUBMITTER: Gurke R

PROVIDER: S-EPMC9598654 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis.

Gurke Robert R Bendes Annika A Bowes John J Koehm Michaela M Twyman Richard M RM Barton Anne A Elewaut Dirk D Goodyear Carl C Hahnefeld Lisa L Hillenbrand Rainer R Hunter Ewan E Ibberson Mark M Ioannidis Vassilios V Kugler Sabine S Lories Rik J RJ Resch Eduard E Rüping Stefan S Scholich Klaus K Schwenk Jochen M JM Waddington James C JC Whitfield Phil P Geisslinger Gerd G FitzGerald Oliver O Behrens Frank F Pennington Stephen R SR

Biomedicines 20220924 10

The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in ~30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, t ...[more]

PMID: 36289648

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Project description:BackgroundThe early detection of psoriatic arthritis (PSA) poses a challenge to rheumatologists, even when their diagnosis is aided by sonography. In order to facilitate early detection of PSA among patients with psoriasis (PSO), we retrospectively analyzed of the relationships between serological markers and comorbidities in 629 psoriatic patients, 102 of which had PSA, while the other 527 had PSO.ResultsSerological markers were found not to be useful in distinguishing between PSA and PSO (p > 0.05 for all comparisons). The prevalence rate of PSA among PSO patients was around 19.4%. Two components of metabolic syndrome-hyperlipidemia (2.94%) and gout (4.9%)-were significantly more prevalent in PSA patients than in PSO patients (p < 0.05). The odds ratio for PSA is 15.94 in patients with hyperlipidemia with a 95% confidence interval (CI) of 1.64-154.80; meanwhile, the odds ratio for PSA is 3.83 in patients with gout with a 95% CI of 1.19-12.31. Allergic rhinitis (5.88%) was more prevalent in PSA patients than in PSO patients (p < 0.01). The odds ratio was 8.17 in patients with allergic rhinitis with a 95% CI of 2.26-29.50. Plasma hs-miR-210-3p distinguishes PSA from PSO, and its levels can also be distinguished from PSA after treated with anti-TNFα biologics agents (both p < 0.05).ConclusionsNo clinical available serology markers, but hyperlipidemia, gout, axial spondylopathy (inflammatory back pain), or allergic rhinitis, could differentiate between psoriatic arthritis from psoriasis. Plasma hs-miR-210-3p and comorbidities may differentiate psoriatic arthritis from psoriasis. Key Points • Clinical manifestations and comorbidities are different between psoriatic arthritis and psoriasis only patients. • Traditional serology markers are similar between psoriatic arthritis and psoriasis-only patients. • Plasma hs-miR-210-3p distinguishes PSA from PSO, and its levels can also be distinguished from PSA after treated with anti-TNFα biologics agents in our study.

Project description:BackgroundPsoriasis (Pso) is a chronic inflammatory skin disease that poses both physical and psychological challenges. Dysbiosis of the skin microbiome has been implicated in Pso, yet a comprehensive multi-omics analysis of host-microbe interactions is still lacking. To bridge this gap, we conducted an exploratory study by adopting the integrated approach that combines whole metagenomic shotgun sequencing with skin transcriptomics.MethodsThis was a cross-sectional study, adult patients with plaque-type Psoriasis (Pso) and healthy volunteers were included. Skin microbiota samples and biopsies were collected from both lesional and non-lesional skin areas on the lower back. Weighted Gene Correlation Network Analysis (WGCNA) was employed for co-expression network analysis, and cell deconvolution was conducted to estimate cell fractions. Taxonomic and functional features of the microbiome were identified using whole metagenomic shotgun sequencing. Association between host genes and microbes was analyzed using Spearman correlation.FindingsHost anti-viral responses and interferon-related networks were identified and correlated with the severity of psoriasis. The skin microbiome showed a greater prevalence of Corynebacterium simulans in the PASI severe-moderate groups, which correlated with interferon-induced host genes. Two distinct psoriatic clusters with varying disease severities were identified. Variations in the expression of cell apoptosis-associated antimicrobial peptides (AMPs) and microbial aerobic respiration I pathway may partly account for these differences in disease severity.InterpretationOur multi-omics analysis revealed for the first time anti-viral responses and the presence of C. simulans associated with psoriasis severity. It also identified two psoriatic subtypes with distinct AMP and metabolic pathway expression. Our study provides new insights into understanding the host-microbe interaction in psoriasis and lays the groundwork for developing subtype-specific strategies for managing this chronic skin disease.FundingThe research has received funding from the FP7 (MAARS-Grant 261366) and the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 821511 (BIOMAP). The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. This publication reflects only the author's view and the JU is not responsible for any use that may be made of the information it contains. GAM was supported by a scholarship provided by CAPES-PRINT, financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES (Brazilian Government Agency). The authors thank all patients who participated in our study.

Dataset Information

Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis.

Publications

Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis.

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