Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome
Xue Cai#, Zhangzhi Xue#, Fang-Fang Zeng#, Jun Tang#, Liang Yue#, Bo Wang#, Weigang Ge, Yuting Xie, Zelei Miao, Wanglong Gou, Yuanqing Fu, Sainan Li, Jinlong Gao, Menglei Shuai, Ke Zhang, Fengzhe Xu, Yunyi Tian, Nan Xiang, Yan Zhou, Peng-Fei Shan, Yi Zhu*, Yu-ming Chen*, Ju-Sheng Zheng*, Tiannan Guo*
Cell Reports Medicine. 2023 Sep 19;4(9). doi: https://doi.org/10.1016/j.xcrm.2023.101172. PMID: 37652016.
Supplementary Tables:
The Supplementary Tables can be Downloaded
Supplementary Table 1. Clinical information of the study participants from our GNHS cohort. tableS1
Supplementary Table 2. Proteomics data of the discovery cohort. tableS2
Supplementary Table 3. Proteomics data of the validation cohort. tableS3
Supplementary Table 4. Proteomics and clinical data for our machine learning modeling. tableS4
Supplementary Table 5. Proteins associated with MetS and its development. tableS5
Supplementary Table 6. Proteomics data for the analysis of different MetS subtypes. tableS6
Supplementary Table 7. Proteomics data for the analysis of MetS development. tableS7
DATA AVAILIABILITY
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository 81,82 with the da-taset identifier PXD039236, PXD039231, and PXD038253. The phenotype data can be requested by email from the corresponding author (Y.C).