Genes related to fibrosis, extracellular matrix deposition, and immune response were found up-regulated in CAN. Markers resulting from the microarray analysis were differentially expressed in Ur samples of the CAN patients and in concordance with the microarray profiles.

Non-invasive monitoring may be useful after kidney transplantation (KT), particularly for predicting acute rejection (AR). It is less clear whether chronic allograft nephropathy (CAN) is also associated with changes in urine cells. To identify non-invasive markers of allograft function in kidney transplant patients (KTP), mRNA levels of AGT, TGF-β1, EGFR, IFN-γ, TSP-1, and IL-10 in urine (Ur) samples were studied using QRT-PCR. Ninety-five KTP and 111 Ur samples were evaluated. Patients (Pts) were divided as, within six months (N = 31), and with more than six months post-KT (N = 64). KTP with more than six months post-KT were classified as KTP with stable kidney function (SKF) (N = 32), KTP with SKF (creatinine < 2 mg/dL) and proteinuria > 500 mg/24 h (N = 18), and KTP with biopsy proven CAN (N = 14). F-test was used to test for equality of variances between groups. IL-10 mRNA was decreased in Ur samples from KTP with less than six months post-KT (P = 0.005). For KTR groups with more than six months post-KT, AGT and EGFR mRNA were statistically different among KTP with SKF, KTP with SKF and proteinuria, and CAN Pts (P = 0.003, and P = 0.01), with KTP with SKF having higher mean expression. TSP-1 mRNA levels also were significantly different among these three groups (P = 0.04), with higher expression observed in CAN Pts. Using the random forest algorithm, AGT, EGFR, and TGF-β1 were identified as predictors of CAN, SKF, SKF with proteinuria. A characteristic pattern of mRNA levels in the different KTP groups was observed indicating that the mRNA levels in Ur cells might reflect allograft function.

We describe monozygotic twins with immune thrombocytopenia (ITP) associated to antiphospholipid antibodies with a dissimilar clinical expression. The first patient was diagnosed to have ITP at 63 years old and was treated with corticosteroids. She presented ulterior exacerbations of thrombocytopenia requiring intravenous immunoglobulin and subsequent treatment with rituximab. She ultimately had a favorable response without thrombotic events during follow-up. The second patient who had a history of three spontaneous abortions and endometrial adenocarcinoma in complete remission was evaluated for severe thrombocytopenia, ITP was diagnosed at the age of 63. She was treated with steroids and had a favorable response. After few months she developed deep venous thrombosis and pulmonary embolism requiring anticoagulation therapy without hemorrhagic events. Both patients were found to have antiphospholipid antibodies and HLA DR4 (DRB1*04) and HLA DR5 (DRB1*12). The association of those two entities in monozygotic twins could support the presence of common predisposing genes. However, with both patients being genotipically identical, the clinical expression was different. Those cases highlight the possibility that environmental factors may affect the expression of those disorders.

No abstract

BackgroundLupus nephritis (LN) is one of the most frequent and serious complications in the patients with systemic lupus erythematosus. Several studies have identified risk factors for poor kidney prognosis in patients with SLE, including age, sex, hypertension, decreased estimated GFR (eGFR), proteinuria, and renal pathologic types.1 Biopsy allows classifying the type of renal involvement, assessing its activity, and thus guiding the therapeutic behaviours. It has been shown that structural changes and inflammatory infiltrate associated with LN contribute to a hypoxic state which induces angiogenesis.2 Herein, it was hypothesised that differential expression of angiogenic genes could classify Lupus Nephritis Patients (LNP) with the same histological score but different “clinical status”.ObjectivesTo investigate if there is a differential angiogenic gene expression in biopsies of LNP under the same histological classification but different “clinical status” measured by eGFR.MethodsTwenty four kidney biopsies samples classified according to ISN/RPS scoring system as Class IV from 24 LNP were divided into eGFR <60 ml/min (n=10, age: 31.00±10.93, range: 17–46) and eGFR >60 ml/min (n=14, age: 32.64±11.34, range: 21–64). RNA was isolated using TRIzol-Chloroform technique and then was reverse-transcribed using random primers. Gene expression level of pro-angiogenic factors: VCAM-1, VEGF, TGF-β and ANGPT-1 were evaluated using Quantitative Real Time PCR (QPCR). The threshold cycle (Ct) scores were averaged for calculations of relative expression values. The Ct scores were normalised by subtracting β2Microglobuline (β2M) control, or ΔCt=Ct, gene- Ct,β2M. To test for differential gene expression between groups, a two sample T-test was performed to compare the ΔCt in the two groups.ResultsΔCt is inversely proportional to the gene expression level. Significant differences between groups was found in VEGF-A gene (p=0.0326), where the greatest expression corresponding to eGFR <60 ml/min group. However, there were not statistically significant differences in VCAM-1, ANGPT1 and TGF-β expression (table 1). Particularly TGF-β, a proangiogenic and profibrotic gene showed a uniform expression level in both groups.Abstract AB0018 – Table 1Levels of gene expression and laboratory parameters in eGFR <60 ml/min and eGFR >60 mil/min expressed as ΔCt values.GeneeGFR<60 ml/mineGFR>60 ml/minp value n=10n=14 VCAM-15,021±17686,248±32640,3165VEGF-A3,414±11614,651±14090,0326TGF-β6,168±10116,699±13510,3421ANGPT110,330±22949,891±21130,5007ConclusionsIn the present cross-sectional study, increased levels of VEGF-A were observed in biopsies Class IV from LNP with eGFR <60 ml/min. These findings suggest a differential gene expression that may be associated with an impaired renal function, reflected by eGFR.References[1] Thong B, Olsen NJ. Systemic lupus erythematosus diagnosis and management. Rheumatology (Oxford)2017;56(suppl_1):i3–13.[2] Carmeliet P, Jain RK. Molecular mechanisms and clinical applications of angiogenesis. Nature2011;19:298–307.[3]...