Proteomic analysis of human plasma in chronic rheumatic mitral stenosis reveals proteins involved in the complement and coagulation cascade

BACKGROUND: Rheumatic fever in childhood is the most common cause of Mitral Stenosis in developing countries. The disease is characterized by damaged and deformed mitral valves predisposing them to scarring and narrowing (stenosis) that results in left atrial hypertrophy followed by heart failure. Presently, echocardiography is the main imaging technique used to diagnose Mitral Stenosis. Despite the high prevalence and increased morbidity, no biochemical indicators are available for prediction, diagnosis and management of the disease. Adopting a proteomic approach to study Rheumatic Mitral Stenosis may therefore throw some light in this direction. In our study, we undertook plasma proteomics of human subjects suffering from Rheumatic Mitral Stenosis (n = 6) and Control subjects (n = 6). Six plasma samples, three each from the control and patient groups were pooled and subjected to low abundance protein enrichment. Pooled plasma samples (crude and equalized) were then subjected to in-solution trypsin digestion separately. Digests were analyzed using nano LC-MS(E). Data was acquired with the Protein Lynx Global Server v2.5.2 software and searches made against reviewed Homo sapiens database (UniProtKB) for protein identification. Label-free protein quantification was performed in crude plasma only. RESULTS: A total of 130 proteins spanning 9–192 kDa were identified. Of these 83 proteins were common to both groups and 34 were differentially regulated. Functional annotation of overlapping and differential proteins revealed that more than 50% proteins are involved in inflammation and immune response. This was corroborated by findings from pathway analysis and histopathological studies on excised tissue sections of stenotic mitral valves. Verification of selected protein candidates by immunotechniques in crude plasma corroborated our findings from label-free protein quantification. CONCLUSIONS: We propose that this protein profile of blood plasma, or any of the individual proteins, could serve as a focal point for future mechanistic studies on Mitral Stenosis. In addition, some of the proteins associated with this disorder may be candidate biomarkers for disease diagnosis and prognosis. Our findings might help to enrich existing knowledge on the molecular mechanisms involved in Mitral Stenosis and improve the current diagnostic tools in the long run. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1559-0275-11-35) contains supplementary material, which is available to authorized users

Adverse Effects of Proton Pump Inhibitors on Platelet Count: A Case Report and Review of the Literature

Proton pump inhibitors (PPIs) are the most effective and preferred class of drugs used to treat peptic ulcer disease, gastroesophageal reflux disease, and other diseases associated with increased production of gastric acid. PPIs in general have an excellent long-term safety profile and are well-tolerated. However, studies have shown some adverse reactions (e.g., osteoporosis, Clostridium difficile-associated diarrhea, Vitamin B12 and iron deficiency, and acute interstitial nephritis) on long-term PPI use. Thrombocytopenia attributed to use of PPIs has been described in a few case reports and a retrospective study. In this case report, we describe a case of PPI-induced thrombocytopenia. In our patient, thrombocytopenia immediately developed after the initiation of PPI on two separate occasions and resolved after its discontinuation. The strong association found in our case implies the potential role of PPI in causing this rare but serious adverse reaction. Based on this case report and the observation from other studies, a PPI-induced adverse event should be considered as a possible etiology for new-onset idiopathic thrombocytopenia

Mutational landscape of cytokine genes across major tumour types identifies new targets

Introduction: Components of immune system communicate extensively in tumour micro environment. Normally, immune system engages with tumours to inhibit its further progression. Simultaneously, cancer cells learn cues derived from immune system to its own growth advantage. Cytokines are cell signaling messengers that affect disease pathogenesis, non-specific response to infection, specific response to antigen, etc. A battery of cytokines are produced in the tumour microenvironment, when released in response to infections and inflammations, can function to inhibit tumour development and progression. Cancer cells also release cytokines that promote growth, extenuate apoptosis and perform invasion and metastasis. Hypothesis: Alterations in cytokine signaling genes might help tumour to misguide immune system. The aim of the study is to identify such genomic alterations in cytokine genes that may drive major human cancers. Methods: We did extensive literature survey to prepare a list of known cytokine genes (n=776) which were validated in multiple databases. To know the baseline DNA variation in cytokine genes, we analyzed DNA variations in healthy human population from the 1000 Genome project dataset. Somatic mutational landscape for cytokine genes were analyzed in 32 different human cancer types (TCGA data). Significantly mutated genes were detected using MutSig2CV and Oncodrive FM analysis. Genes found significant in both analysis were  tabulated. Standard statistical  and bioinformatic analysis were done further to identify putative driver events. Result: We detected 9 significantly mutated cytokine genes across major tumor types. EDN1 was found to be most significantly mutated, in multiple tumour types; apart from genes like CDH1, B2M, HLA-B, IL4, TRIM22, TGFB1, GDF1 and CRABP2. Discussion: Our systematic survey of somatic mutations in cytokine genes, in major tumour types, identified novel genes targets such as EDN1 gene. EDN1 is a chemokine, also a potent vasoconstrictor. EDN1 signaling modifies tumour microenvironment by regulating contribution of cells around tumor stroma through both autocrine and paracrine mechanisms, by promoting tumour cell proliferation, neovascularization, etc. Other significantly mutated genes are associated with antigen presentation, cell proliferation and chemoattraction. Rational combination therapy with current inhibitors to disrupt these signaling networks in tumor microenvironment, may improve clinical outcomes in patients

Circulating Carboxy-Terminal Propeptide of type I Procollagen is Increased in Rheumatic Heart Disease

Mitral valve is mostly affected in rheumatic heart disease which is prevalent in developing countries [1–3] and thousands of new cases are being diagnosed worldwide every year [1–3]. It is known that extensive fibrosis occurs in the rheumatic valve [4]. Serum carboxyterminal propeptide of type I procollagen (PICP), the marker of collagen synthesis was reported as a marker of extracellular matrix (ECM) remodelling in various heart diseases [5–8]. We therefore, measured the levels of circulating PICP to explore the severity of ECM remodelling in rheumatic heart disease

Receiver operating characteristics curve for biomarkers in rheumatic heart disease subjects.

<p>Receiver operating characteristics curve for biomarkers in rheumatic heart disease subjects.</p

Assessment of collagen deposition by picrosirius red staining and immunostaining methods.

<p>(A) Representative images (20× magnification) of picrosirius red stained sections of 1 normal heart valve (control) and 3 rheumatic mitral valve samples (RHD). Stained sections were observed using a binocular polarized light microscope. Under polarized light, birefringence is specific for collagen where red colour shows fibrillar type I collagen and yellow green colour indicates reticular type III collagen. Arrow indicates scattered deposition of collagen type I in diseased valve Scale bar represents 100 µm. (B) Total collagen intensity in control vs. RHD mitral valve tissue sections. (C) Type I collagen mean intensity in control vs. RHD mitral valve cross sections. (D) Type III collagen mean intensity in control vs. RHD mitral valve cross sections. (E) Ratio of Type I to Type III collagen in control vs. RHD mitral valve sections.(F) Representative images of immuno stained sections of 1 normal heart valve (control) and 3 rheumatic mitral valve samples (RHD) showing (arrow marked) collagen type 1 deposition. Scale bar represents 45 µm. *p<0.05 vs. control,***p<0.0001 vs. control. Here “n” denotes total number of tissue sections.</p

Overall Performance of Different Parameters According to ROC Curves for Prediction of Mitral Regurgitation.

<p>p<0.05 considered significantly different.</p><p>AUC, area under curve; CI, confidence interval; LR, likelihood ratio; MMP-1, matrix metalloproteinase -1; NPV, negative predictive value; PICP, carboxy terminal propeptide of type I collagen; PIIINP, amino terminal propeptide of type III collagen; PPV, positive predictive value; TIMP-1, tissue inhibitor of matrix metalloproteinase-1.</p

Relationship between plasma markers of collagen metabolism and severity of rheumatic mitral stenosis.

<p>(A) Inverse correlations of plasma PICP (y = −17.241x+2654.1; p = 0.01) and PIIINP (y = −4.6576x+938.36; p = 0.15) concentration with mitral valve area(MVA). (B) Direct correlation (y = 0.0127x−0.582; p = 0.03) between plasma MMP-1/TIMP-1 ratio and MVA. (C) Direct correlation of plasma PICP (y = 24.155x+186.83;p = 0.02) and almost no correlation of plasma PIIINP (y = −0.4083+634.78;p = 0.91) with pulmonary artery systolic pressure (PASP). (D) Inverse correlation (y = −0.0091x+0.8791; p = 0.05) between plasma MMP-1/TIMP-1 ratio and PASP.</p

Plasma concentrations of circulating biomarkers of collagen turnover in normal, MS and MR subjects.

<p>(A) Mean plasma PICP in control, MS and MR subjects before (Pre Op) valve replacement surgery. (B) Progressive reduction in plasma PICP concentration one month and one year or above following mitral valve replacement. (C) Mean plasma PIIINP in control, MS and MR subjects before (Pre Op) valve replacement surgery. (D) Progressive decrease in plasma PIIINP concentration one month and one year or more after mitral valve replacement. (E) Mean plasma concentration of total MMP-1 in control, MS and MR subjects. (F) Mean TIMP-1 concentration in control, MS and MR subjects. (G) Plasma MMP-1/TIMP-1 ratio in control, MS and MR subjects.</p

Histopathology of heart valve.

<p>(A) Representative images (100× magnification) of hematoxylin-eosin stained sections of 1 normal heart valve (control) and 3 rheumatic valve samples (RHD). Rheumatic mitral valve tissue section shows abundance of inflammatory cells (arrow head), fibrosis (blue arrow) and neovascularisation (black arrow). Normal mitral valve section shows wavy arrangement of collagen fibres (black arrow). Scale bar represents 50 µm. (B) Representative images (100×) of Masson's trichrome stained cross sections showing dense collagen deposition (arrow) in mitral valve tissue of RHD patient compared to loose parallel pattern of collagen (arrow) in normal heart valve. Scale bar represents 50 µM.</p