RNAseq-Based Prioritization Revealed COL6A5, COL8A1, COL10A1 and MIR146A as Common and Differential Susceptibility Biomarkers for Psoriasis and Psoriatic Arthritis: Confirmation from Genotyping Analysis of 1417 Italian Subjects.
Valerio CaputoClaudia StrafellaAndrea TermineElena CampioneLuca BianchiGiuseppe NovelliEmiliano GiardinaRaffaella CascellaPublished in: International journal of molecular sciences (2020)
Psoriasis (Ps) and Psoriatic Arthritis (PsA) are characterized by a multifactorial etiology, involving genetic and environmental factors. The present study aimed to investigate polymorphisms (SNPs) within genes involved in extracellular matrix and cell homeostasis and microRNA genes as susceptibility biomarkers for Ps and PsA. Bioinformatic analysis on public RNA-seq data allowed for selection of rs12488457 (A/C, COL6A5), rs13081855 (G/T, COL8A1), rs3812111 (A/T, COL10A1) and rs2910164 (C/G, MIR146A) as candidate biomarkers. These polymorphisms were analyzed by Real-Time PCR in a cohort of 1417 Italian patients (393 Ps, 424 PsA, 600 controls). Statistical and bioinformatic tools were utilized for assessing the genetic association and predicting the effects of the selected SNPs. rs12488457, rs13081855 and rs2910164 were significantly associated with both Ps (p = 1.39 × 10-8, p = 4.52 × 10-4, p = 0.04, respectively) and PsA (p = 5.12 × 10-5, p = 1.19 × 10-6, p = 0.01, respectively). rs3812111, instead, was associated only with PsA (p = 0.005). Bioinformatic analysis revealed common and differential biological pathways involved in Ps and PsA. COL6A5 and COL8A1 take part in the proliferation and angiogenic pathways which are altered in Ps/PsA and contribute to inflammation together with MIR146A. On the other hand, the exclusive association of COL10A1 with PsA highlighted the specific involvement of bone metabolism in PsA.
Keyphrases
- prostate cancer
- radical prostatectomy
- single cell
- genome wide
- rna seq
- cell proliferation
- extracellular matrix
- long non coding rna
- long noncoding rna
- oxidative stress
- mental health
- dna methylation
- newly diagnosed
- healthcare
- ejection fraction
- signaling pathway
- high throughput
- machine learning
- stem cells
- emergency department
- gene expression
- chronic kidney disease
- patient reported outcomes
- deep learning
- real time pcr
- cell therapy
- data analysis
- patient reported
- genetic diversity
- drug induced