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Iranian Biomedical Journal، جلد ۲۲، شماره ۶، صفحات ۳۷۴-۳۸۴
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چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Application of Sparse Linear Discriminant Analysis and Elastic Net for Diagnosis of IgA Nephropathy: Statistical and Biological Viewpoints
چکیده انگلیسی مقاله Background: IgA nephropathy (IgAN) is the most common primary glomerulonephritis diagnosed based on renal biopsy. Mesangial IgA deposits along with the proliferation of mesangial cells are the histologic hallmark of IgAN. Non-invasive diagnostic tools may help to prompt diagnosis and therapy. The discovery of potential and reliable urinary biomarkers for diagnosis of IgAN depends on applying robust and suitable models. Applying two multivariate modeling methods on a urine proteomic dataset obtained from IgAN patients, and comparison of the results of these methods were the purpose of this study. Methods: Two models were constructed for urinary protein profiles of 13 patients and 8 healthy individuals, based on sparse linear discriminant analysis (SLDA) and elastic net regression methods. A panel of selected biomarkers with the best coefficients were proposed and further analyzed for biological relevance using functional annotation and pathway analysis. Results: Transferrin, α1-antitrypsin, and albumin fragments were the most important up-regulated biomarkers, while fibulin-5, YIP1 family member 3, prasoposin, and osteopontin were the most important down-regulated biomarkers. Pathway analysis revealed that complement and coagulation cascades and extracellular matrix-receptor interaction pathways impaired in the pathogenesis of IgAN. Conclusion: SLDA and elastic net had an equal importance for diagnosis of IgAN and were useful methods for exploring and processing proteomic data. In addition, the suggested biomarkers are reliable candidates for further validation to non-invasive diagnose of IgAN based on urine examination.
کلیدواژه‌های انگلیسی مقاله IgA nephropathy, Proteomics, Biomarker, Diagnosis
نویسندگان مقاله | Tahereh Mohammadi Majd
Department of Biostatistics and Epidemiology, Kermanshah University of Medical Sciences, School of Public Health, Kermanshah, Iran


| Shiva Kalantari
Chronic Kidney Disease Research Center, Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Hadi Raeisi Shahraki
Department of Biostatistics, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran


| Mohsen Nafar
Urology-Nephrology Research Center, Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Afshin Almasi
Department of Biostatistics and Epidemiology, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran


| Shiva Samavat
Department of Nephrology, Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Mahmoud Parvin
Department of pathology, Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran


| Amirhossein Hashemian
Research Center for Environmental Determinants of Health (RCEDH), Kermanshah University of Medical Sciences, Kermanshah, Iran
نشانی اینترنتی http://ibj.pasteur.ac.ir/browse.php?a_code=A-10-1-721&slc_lang=fa&sid=1
فایل مقاله اشکال در دسترسی به فایل - ./files/site1/rds_journals/125/article-125-931971.pdf
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زبان مقاله منتشر شده fa
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