High-throughput quantitative histology in systemic sclerosis skin disease using computer vision.

BACKGROUND: Skin fibrosis is the clinical hallmark of systemic sclerosis (SSc), where collagen deposition and remodeling of the dermis occur over time. The most widely used outcome measure in SSc clinical trials is the modified Rodnan skin score (mRSS), which is a semi-quantitative assessment of skin stiffness at seventeen body sites. However, the mRSS is confounded by obesity, edema, and high inter-rater variability. In order to develop a new histopathological outcome measure for SSc, we applied a computer vision technology called a deep neural network (DNN) to stained sections of SSc skin. We tested the hypotheses that DNN analysis could reliably assess mRSS and discriminate SSc from normal skin. METHODS: We analyzed biopsies from two independent (primary and secondary) cohorts. One investigator performed mRSS assessments and forearm biopsies, and trichrome-stained biopsy sections were photomicrographed. We used the AlexNet DNN to generate a numerical signature of 4096 quantitative image features (QIFs) for 100 randomly selected dermal image patches/biopsy. In the primary cohort, we used principal components analysis (PCA) to summarize the QIFs into a Biopsy Score for comparison with mRSS. In the secondary cohort, using QIF signatures as the input, we fit a logistic regression model to discriminate between SSc vs. control biopsy, and a linear regression model to estimate mRSS, yielding Diagnostic Scores and Fibrosis Scores, respectively. We determined the correlation between Fibrosis Scores and the published Scleroderma Skin Severity Score (4S) and between Fibrosis Scores and longitudinal changes in mRSS on a per patient basis. RESULTS: In the primary cohort (n = 6, 26 SSc biopsies), Biopsy Scores significantly correlated with mRSS (R = 0.55, p = 0.01). In the secondary cohort (n = 60 SSc and 16 controls, 164 biopsies; divided into 70% training and 30% test sets), the Diagnostic Score was significantly associated with SSc-status (misclassification rate = 1.9% [training], 6.6% [test]), and the Fibrosis Score significantly correlated with mRSS (R = 0.70 [training], 0.55 [test]). The DNN-derived Fibrosis Score significantly correlated with 4S (R = 0.69, p = 3 × 10- 17). CONCLUSIONS: DNN analysis of SSc biopsies is an unbiased, quantitative, and reproducible outcome that is associated with validated SSc outcomes.

Mycophenolate Mofetil Treatment of Systemic Sclerosis Reduces Myeloid Cell Numbers and Attenuates the Inflammatory Gene Signature in Skin.

Fewer than half of patients with systemic sclerosis demonstrate modified Rodnan skin score improvement during mycophenolate mofetil (MMF) treatment. To understand the molecular basis for this observation, we extended our prior studies and characterized molecular and cellular changes in skin biopsies from subjects with systemic sclerosis treated with MMF. Eleven subjects completed ≥24 months of MMF therapy. Two distinct skin gene expression trajectories were observed across six of these subjects. Three of the six subjects showed attenuation of the inflammatory signature by 24 months, paralleling reductions in CCL2 mRNA expression in skin and reduced numbers of macrophages and myeloid dendritic cells in skin biopsies. MMF cessation at 24 months resulted in an increased inflammatory score, increased CCL2 mRNA and protein levels, modified Rodnan skin score rebound, and increased numbers of skin myeloid cells in these subjects. In contrast, three other subjects remained on MMF >24 months and showed a persistent decrease in inflammatory score, decreasing or stable modified Rodnan skin score, CCL2 mRNA reductions, sera CCL2 protein levels trending downward, reduction in monocyte migration, and no increase in skin myeloid cell numbers. These data summarize molecular changes during MMF therapy that suggest reduction of innate immune cell numbers, possibly by attenuating expression of chemokines, including CCL2.

Brief Report: Association of Elevated Adipsin Levels With Pulmonary Arterial Hypertension in Systemic Sclerosis.

OBJECTIVE: Adipose tissues secrete adipokines, peptides with potent effects modulating fibrosis, inflammation, and vascular homeostasis. Dysregulated adipose tissue biology and adipokine balance have recently been implicated in systemic sclerosis (SSc). This study was undertaken to determine whether altered circulating adipokine levels correlate with SSc disease subsets or clinical manifestations. METHODS: Multiplex assays were used to measure circulating adipokine levels in 198 patients with SSc and 33 healthy controls. Data were evaluated for correlations between serum adipokine levels and demographic and clinical features, including pulmonary arterial hypertension (PAH). To assess the relevance of adipsin, an adipokine involved in complement pathway activation, in SSc, we analyzed publicly available genetic and transcriptomic data. RESULTS: Levels of adiponectin and adipsin differed significantly between controls and patients. Adipsin was significantly elevated in patients with limited cutaneous SSc (odds ratio [OR] 28.3 [95% confidence interval (95% CI) 7.0-113.8]; P < 0.0001), and its levels were associated with serum autoantibody status, pulmonary function and cardiovascular parameters, and PAH (OR 3.3 [95% CI 1.3-8.7]; P = 0.02). Elevated adipsin was more strongly associated with PAH than B-type natriuretic peptide was. Moreover, in SSc patients, adipsin gene single-nucleotide polymorphisms were associated with PAH. Transcriptome data set analysis demonstrated elevated adipsin expression in patients with SSc-related PAH. CONCLUSION: We identify adipsin as a novel adipose tissue-derived marker of SSc-related PAH. Circulating adipsin levels might serve as predictive biomarkers in SSc. Mechanistically, adipsin might represent a pathogenic link between adipocyte dysfunction and complement pathway activation and play an important role in the pathogenesis of SSc-related PAH.