|
Type |
Poster Presentation |
Area |
Analytical Chemistry |
Room No. |
Event Hall |
Time |
4월 19일 (목요일) 11:00~12:30 |
Code |
ANAL.P-294 |
Subject |
Extensive Serum Proteome Profiling to Uncover Biomarkers for Early Diagnosis of Diabetes Mellitus |
Authors |
Seunghoon Back, jingi Bae, Hokeun Kim, Jiwon Ha, Sang-Won Lee* Department of Chemistry, Korea University, Korea |
Abstract |
Diabetes Mellitus (DM) is a chronic disease that occurs with complications such as cardiovascular disease. One-third of high risk population in DM undergo the disease but early diagnosis of DM could prevent the progress of disease. Thus the biomarker discovery for early diagnosis of DM is very important. Here, we report the quantitative proteomic analyses results from 80 high risk DM patient serum samples for development of diagnostic methods for diabetes. Two groups of baseline and follow up serum samples were obtained each patient for analyzing changes in protein expression: 20 Low ISI & High IGI group (ISI: Insulin Sensitivity Index, IGI: Insulinogenic Index), 20 High ISI & Low IGI group. Each group was consisted of 10 control patients and 10 disease patients.
For deep serum proteome profiling, highly abundant serum proteins were depleted using IgY14 column and then low abundant proteins were digested using trypsin enzyme. 6-plex TMT labeling was performed on five peptide samples and a universal reference sample, a combined peptide sample from all 80 serums, resulting in a total of 16 TMT labeled peptide sets. Each of the TMT peptide sets was divided into 24 fractions using mid-pH RPLC fractionation. A total of 384 fractions were generated and each fraction was individually analyzed by LC-MS/MS.
A total 3,198 serum protein groups were identified by 63,724 unique serum peptides resulting from 384 LC-MS/MS datasets. We selected the 68 biomarker candidates generated by clustering analysis of 253 differentially expressed proteins for high risk population in DM. |
E-mail |
likeone61@korea.ac.kr |
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