@article {195445,
	title = {Deregulation of long noncoding RNAs ANCR, TINCR, HOTTIP and SPRY4-IT1 in plasma of systemic sclerosis patients: SPRY4-IT1 as a novel biomarker of scleroderma and its subtypes},
	journal = {Cytokine},
	volume = {133},
	year = {2020},
	note = {<p>n/a</p>
},
	month = {2020},
	pages = {155124},
	abstract = {<p>Systemic sclerosis or systemic scleroderma (SSc) is an inflammatory autoimmune disease whose pathogenesis remains ambiguous; however, epigenetics, including long noncoding RNAs (lncRNAs) is an emerging paradigm. To date, the expression, role and clinical significance of most lncRNAs in SSc remain unelucidated. Herein, we investigated the plasma expression profiles of lncRNAs; ANCR, TINCR, HOTTIP, and SPRY4-IT1, which were linked to skin biology, in SSc patients and its subtypes, their potential as diagnostic tools and their correlations with autoantibodies and disease manifestations. Sixty-three SSc patients and thirty-five healthy volunteers were recruited. Autoantibody profile (anti-Scl-70, anti-centromere, anti-RNA polymeraseIII, anti-ribonucleoprotein, antinuclear, and anti-phospholipid antibodies) was determined. lncRNAs analysis was conducted using RT-qPCR. Plasma TINCR, HOTTIP, and SPRY4-IT1 upregulation and ANCR downregulation were observed in SSc patients compared with controls. SPRY4-IT1 was superior in SSc diagnosis in ROC analysis and predicted its risk in multivariate logistic analysis. Plasma SPRT4-IT1 was higher in diffuse than limited SSc. SPRY4-IT1 and HOTTIP were positively correlated with modified Rodnan skin score while ANCR showed a negative correlation only in limited SSc. ANCR and TINCR were positively correlated with disease duration and ESR, respectively. ANCR and SPRY4-IT1 were positively correlated with pulmonary hypertension. HOTTIP was positively correlated with antinuclear antibody. SPRY4-IT1 was positively correlated with HOTTIP in the whole group, and with TINCR only in diffuse SSc. We introduce plasma SPRY4-IT1, HOTTIP, ANCR and TINCR as novel candidate biomarkers for SSc, with SPRY4-IT1 could predict SSc diagnosis and discriminate its subtypes. Our findings widen the epigenetic landscape of SSc and provide surrogates for future predictive studies.</p>
},
	isbn = {1043-4666},
	url = {http://www.sciencedirect.com/science/article/pii/S104346662030140X},
	author = {Mai A. Abd-Elmawla and Mariam Hassan and Yumn A. Elsabagh and Alshaimaa Rezk L R Alnaggar and Mahmoud A Senousy}
}
