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논문분류	춘계학술대회 초록집
제목	A virtual diagnosis of diabetic nephropathy using proteomics in place of kidney biopsy
저자	Da Woon Kim
출판정보	2024; 2024(1):
키워드
초록	Objectives: This study aims to find out serum and urine proteome as potential surrogate markers that can helpful in diagnosing nephropathy caused by diabetes instead of kidney biopsy. Methods: Patients with type 2 diatetes (T2D) who underwent kidney biopsy from 2010 to 2020 at Pusan national university hospital were retrospectively reviewed. The most combined glomerulonephritis was IgA nephropathy (IgAN) and membranous glomerulonephritis (MN). Thus, among enrolled patients with T2D, we selected age- and sex-matched patients with pure diabetic nephropathy (DN), pure non-DN (IgAN, MN) for proteomic analysis. The control group was donors for living kidney transplantation. Experimental groups were four and each group consisted of 11 patients. Comparative proteome analysis was performed using high resolution mass spectrometry coupled with nanoflow liquid chromatography. Resulting relative protein quantity of each group was extracted using label free manner and statistical analysis was performed to discover group specific protein biomarker candidate. And random forest was applied to make serum and urine protein panel to distinguish control, pure DN and non-DN group. Results: In serum sample set, total 1,220 proteins were identified and 27 proteins were clustered to be distinguishable in DN group compared to control and non-DN group. Random forest analysis, one of machine learning strategies, successfully classified DN from overall subjects (out-of bag error 0.0023). Gene ontology analysis indicated that serum DN specific proteins were mainly involved in glutathione metabolism and ferroptosis. In urine sample set, 1,579 proteins were identified and 10 proteins were clustered to be distinguishable in DN group compared to control and non-DN group. Gene ontology analysis indicated that urine DN specific proteins were mainly involved in phenylalanine and tyrosine metabolism. Conclusions: Serum and urine proteome combined with machine learning approach can be useful to diagnose DN histologically and guide the indication of kidney biopsy with T2D having kidney damage in the future.
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