Risk factors for non-diabetic renal disease in diabetic patients

Background. Diabetic patients with kidney disease have a high prevalence of non-diabetic renal disease (NDRD). Renal and patient survival regarding the diagnosis of diabetic nephropathy (DN) or NDRD have not been widely studied. The aim of our study is to evaluate the prevalence of NDRD in patients with diabetes and to determine the capacity of clinical and analytical data in the prediction of NDRD. In addition, we will study renal and patient prognosis according to the renal biopsy findings in patients with diabetes. Methods. Retrospective multicentre observational study of renal biopsies performed in patients with diabetes from 2002 to 2014. Results. In total, 832 patients were included: 621 men (74.6%), mean age of 61.7 6 12.8 years, creatinine was 2.8 6 2.2 mg/dL and proteinuria 2.7 (interquartile range: 1.2–5.4) g/24 h. About 39.5% (n ¼ 329) of patients had DN, 49.6% (n ¼ 413) NDRD and 10.8% (n ¼ 90) mixed forms. The most frequent NDRD was nephroangiosclerosis (NAS) (n ¼ 87, 9.3%). In the multivariate logistic regression analysis, older age [odds ratio (OR) ¼ 1.03, 95% CI: 1.02–1.05, P < 0.001], microhaematuria (OR ¼ 1.51, 95% CI: 1.03–2.21, P ¼ 0.033) and absence of diabetic retinopathy (DR) (OR ¼ 0.28, 95% CI: 0.19–0.42, P < 0.001) were independently associated with NDRD. Kaplan–Meier analysis showed that patients with DN or mixed forms presented worse renal prognosis than NDRD (P < 0.001) and higher mortality (P ¼ 0.029). In multivariate Cox analyses, older age (P < 0.001), higher serum creatinine (P < 0.001), higher proteinuria (P < 0.001), DR (P ¼ 0.007) and DN (P < 0.001) were independent risk factors for renal replacement therapy. In addition, older age (P < 0.001), peripheral vascular disease (P ¼ 0.002), higher creatinine (P ¼ 0.01) and DN (P ¼ 0.015) were independent risk factors for mortality. Conclusions. The most frequent cause of NDRD is NAS. Elderly patients with microhaematuria and the absence of DR are the ones at risk for NDRD. Patients with DN presented worse renal prognosis and higher mortality than those with NDRD. These results suggest that in some patients with diabetes, kidney biopsy may be useful for an accurate renal diagnosis and subsequently treatment and prognosis

Identification of Gene Modules Associated with Drought Response in Rice by Network-Based Analysis

Understanding the molecular mechanisms that underlie plant responses to drought stress is challenging due to the complex interplay of numerous different genes. Here, we used network-based gene clustering to uncover the relationships between drought-responsive genes from large microarray datasets. We identified 2,607 rice genes that showed significant changes in gene expression under drought stress; 1,392 genes were highly intercorrelated to form 15 gene modules. These drought-responsive gene modules are biologically plausible, with enrichments for genes in common functional categories, stress response changes, tissue-specific expression and transcription factor binding sites. We observed that a gene module (referred to as module 4) consisting of 134 genes was significantly associated with drought response in both drought-tolerant and drought-sensitive rice varieties. This module is enriched for genes involved in controlling the response of the plant to water and embryonic development, including a heat shock transcription factor as the key regulator in the expression of ABRE-containing genes. These results suggest that module 4 is highly conserved in the ABA-mediated drought response pathway in different rice varieties. Moreover, our study showed that many hub genes clustered in rice chromosomes had significant associations with QTLs for drought stress tolerance. The relationship between hub gene clusters and drought tolerance QTLs may provide a key to understand the genetic basis of drought tolerance in rice

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods

The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology

Effect of Tobacco Smoking on The Clinical, Histopathological, and Serological Manifestations of Sjögren’s Syndrome

The authors wish to thank Dr. A. Darise Farris for her critical review of the cellular immune response discussion.Objectives To assess the association of smoking habits with the clinical, serological, and histopathological manifestations of Sjögren’s syndrome (SS) and non-Sjögren’s sicca (non-SS sicca). Methods Cross-sectional case-control study of 1288 patients with sicca symptoms (587 SS and 701 non-SS sicca) evaluated in a multi-disciplinary research clinic. Smoking patterns were obtained from questionnaire data and disease-related clinical and laboratory data were compared between current, past, ever, and never smokers. Results Current smoking rates were 4.6% for SS patients compared to 14.1% in non-SS sicca (p = 5.17x10E-09), 18% in a local lupus cohort (p = 1.13x10E-14) and 16.8% in the community (p = 4.12x10E-15). Current smoking was protective against SS classification (OR 0.35, 95%CI 0.22–0.56, FDR q = 1.9E10-05), focal lymphocytic sialadenitis (OR 0.26, 95%CI 0.15–0.44, FDR q = 1.52x10E-06), focus score ≥1 (OR 0.22, 95%CI 0.13–0.39, FDR q = 1.43x10E-07), and anti-Ro/SSA(+) (OR 0.36, 95%CI 0.2–0.64, FDR q = 0.0009); ever smoking was protective against the same features and against anti-La/SSB(+) (OR 0.52, 95%CI 0.39–0.70, FDR q = 5.82x10E-05). Duration of smoking was inversely correlated with SS even after controlling for socioeconomic status, BMI, alcohol and caffeine consumption. Conclusions Current tobacco smoking is negatively and independently associated with SS, protecting against disease-associated humoral and cellular autoimmunity. The overall smoking rate amongst SS patients is significantly lower than in matched populations and the effects of smoking are proportional to exposure duration. In spite of the protective effects of tobacco on SS manifestations, it is associated with other serious comorbidities such as lung disease, cardiovascular risk and malignancy, and should thus be strongly discouraged in patients with sicca.Yeshttp://www.plosone.org/static/editorial#pee