Summary of Study ST002733

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001697. The data can be accessed directly via it's Project DOI: 10.21228/M8BT6J This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST002733
Study TitlePlasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome
Study SummaryDirect diagnosis and accurate assessment of metabolic syndrome (MetS) would allow for prompt clinical interventions. However, diagnostic strategies use only traditional risk factors, without considering the complex heterogeneity of MetS. Here, we performed an advanced ferric particle-assisted laser desorption/ionization mass spectrometry (LDI-MS)-based metabolomic analysis of 100 nL of plasma per participant collected from the largest general community cohort (n=13,554) reported to date and extracted a set of 26 hub plasma metabolic fingerprints (PMFs) for MetS and its early identification (pre-MetS). We develop machine learning-based diagnostic models for pre-MetS and MetS with convincing performance through independent validation. These PMFs were applied to assess the contributions of four MetS risk factors in the general population as follows, from large to small contribution: hyperglycemia, hypertension, dyslipidemia, and obesity. We devised a personalized three-dimensional plasma metabolic risk (PMR) stratification to decode the individual metabolic risk into three patterns. During the 4-year follow-up period of 13,554 participants, the accumulation analysis of all-cause death events showed that patients with medium and high risk had HRs of 1.54 (95% CI 1.05-2.28, p = 0.029) and 1.85 (95% CI 1.22-2.79, p = 0.004), respectively, compared to those with low risk. Overall, we provided efficient screening tools to identify patients with pre-MetS and MetS who require treatments in the general community and defined the heterogeneous risk stratification of metabolic phenotypes in real-world settings.
Institute
Shanghai Jiao Tong University affiliated Renji Hospital
Last NameChen
First NameYifan
Addressdongfang road.1630
Emailyifanchen@sjtu.edu.cn
Phone+8613917129357
Submit Date2023-05-21
Analysis Type DetailMALDI-MS
Release Date2023-06-15
Release Version1
Yifan Chen Yifan Chen
https://dx.doi.org/10.21228/M8BT6J
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001697
Project DOI:doi: 10.21228/M8BT6J
Project Title:Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome
Project Type:Human, Plasma, LDI-MS
Project Summary:LDI-MS-based metabolomic analysis of 100 nL of plasma per participant collected from the largest general community cohort (n=13,554) reported to date and extracted a set of 26 hub plasma metabolic fingerprints (PMFs) for MetS and its early identification (pre-MetS).
Institute:Shanghai Jiao Tong University affiliated Renji Hospital
Department:Division of Cardiology
Laboratory:Cardiology Lab
Last Name:Chen
First Name:Yifan
Address:160 Pujian Road, Shanghai, 200127, P. R. China, Shanghai, Shanghai, 200032, China
Email:yifanchen@sjtu.edu.cn
Phone:+8617321400424

Subject:

Subject ID:SU002839
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Male and female

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Disease sex
SA274999Sa_1608Healthy Control Female
SA275000Sa_10301Healthy Control Female
SA275001Sa_1599Healthy Control Female
SA275002Sa_1590Healthy Control Female
SA275003Sa_1597Healthy Control Female
SA275004Sa_13148Healthy Control Female
SA275005Sa_10303Healthy Control Female
SA275006Sa_1642Healthy Control Female
SA275007Sa_1643Healthy Control Female
SA275008Sa_1639Healthy Control Female
SA275009Sa_13138Healthy Control Female
SA275010Sa_10863Healthy Control Female
SA275011Sa_1611Healthy Control Female
SA275012Sa_1589Healthy Control Female
SA275013Sa_13165Healthy Control Female
SA275014Sa_1564Healthy Control Female
SA275015Sa_1557Healthy Control Female
SA275016Sa_1556Healthy Control Female
SA275017Sa_13168Healthy Control Female
SA275018Sa_12181Healthy Control Female
SA275019Sa_1573Healthy Control Female
SA275020Sa_1586Healthy Control Female
SA275021Sa_1588Healthy Control Female
SA275022Sa_1582Healthy Control Female
SA275023Sa_1580Healthy Control Female
SA275024Sa_13157Healthy Control Female
SA275025Sa_1647Healthy Control Female
SA275026Sa_1654Healthy Control Female
SA275027Sa_4985Healthy Control Female
SA275028Sa_4948Healthy Control Female
SA275029Sa_4989Healthy Control Female
SA275030Sa_4990Healthy Control Female
SA275031Sa_4993Healthy Control Female
SA275032Sa_4942Healthy Control Female
SA275033Sa_4934Healthy Control Female
SA275034Sa_4908Healthy Control Female
SA275035Sa_4892Healthy Control Female
SA275036Sa_4916Healthy Control Female
SA275037Sa_4918Healthy Control Female
SA275038Sa_4925Healthy Control Female
SA275039Sa_4996Healthy Control Female
SA275040Sa_5002Healthy Control Female
SA275041Sa_13134Healthy Control Female
SA275042Sa_10307Healthy Control Female
SA275043Sa_1661Healthy Control Female
SA275044Sa_1657Healthy Control Female
SA275045Sa_5423Healthy Control Female
SA275046Sa_13126Healthy Control Female
SA275047Sa_10314Healthy Control Female
SA275048Sa_5036Healthy Control Female
SA275049Sa_5010Healthy Control Female
SA275050Sa_13119Healthy Control Female
SA275051Sa_10315Healthy Control Female
SA275052Sa_10902Healthy Control Female
SA275053Sa_1652Healthy Control Female
SA275054Sa_12172Healthy Control Female
SA275055Sa_1479Healthy Control Female
SA275056Sa_5489Healthy Control Female
SA275057Sa_1475Healthy Control Female
SA275058Sa_5499Healthy Control Female
SA275059Sa_1469Healthy Control Female
SA275060Sa_5486Healthy Control Female
SA275061Sa_5485Healthy Control Female
SA275062Sa_1489Healthy Control Female
SA275063Sa_5474Healthy Control Female
SA275064Sa_5482Healthy Control Female
SA275065Sa_5483Healthy Control Female
SA275066Sa_1485Healthy Control Female
SA275067Sa_10293Healthy Control Female
SA275068Sa_5506Healthy Control Female
SA275069Sa_7569Healthy Control Female
SA275070Sa_1442Healthy Control Female
SA275071Sa_5534Healthy Control Female
SA275072Sa_5537Healthy Control Female
SA275073Sa_1436Healthy Control Female
SA275074Sa_5524Healthy Control Female
SA275075Sa_5523Healthy Control Female
SA275076Sa_5512Healthy Control Female
SA275077Sa_1460Healthy Control Female
SA275078Sa_5517Healthy Control Female
SA275079Sa_1453Healthy Control Female
SA275080Sa_5522Healthy Control Female
SA275081Sa_5471Healthy Control Female
SA275082Sa_5469Healthy Control Female
SA275083Sa_5438Healthy Control Female
SA275084Sa_5437Healthy Control Female
SA275085Sa_5439Healthy Control Female
SA275086Sa_5440Healthy Control Female
SA275087Sa_5441Healthy Control Female
SA275088Sa_5434Healthy Control Female
SA275089Sa_5433Healthy Control Female
SA275090Sa_5429Healthy Control Female
SA275091Sa_4887Healthy Control Female
SA275092Sa_5430Healthy Control Female
SA275093Sa_1535Healthy Control Female
SA275094Sa_5432Healthy Control Female
SA275095Sa_1519Healthy Control Female
SA275096Sa_1518Healthy Control Female
SA275097Sa_5467Healthy Control Female
SA275098Sa_1500Healthy Control Female
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Collection:

Collection ID:CO002832
Collection Summary:All human peripheral venous blood samples were obtained following the protocols approved by the Institutional Review Board at Shanghai Jiao Tong University. To avert the diet disturbance, blood samples were collected from induvial peripheral vein and gently mixed in the heparin antifreeze tubes after overnight fasting (more than 8 hours). The plasma was separated after centrifugation for 10min (4000 rpm; 4 ℃) within 2 hours of collection. All plasma samples were stored at -80 ℃ for future assays.
Sample Type:Blood (plasma)
Storage Conditions:-80℃

Treatment:

Treatment ID:TR002848
Treatment Summary:This is a natural population study without treatment

Sample Preparation:

Sampleprep ID:SP002845
Sampleprep Summary:For plasma sample detection, the samples were firstly prepared through protein precipitation, centrifugation, and supernatant filtration according to a commonly applied procedure. Then, a volume of 100nL of plasma solution was spotted on the plate and dried in air at room temperature, followed by adding 100nL of matrix slurry and drying for LDI MS analysis.

Combined analysis:

Analysis ID AN004431
Analysis type MS
Chromatography type None (Direct infusion)
Chromatography system Bruker Autoflex speed TOF/TOF
Column None
MS Type MALDI
MS instrument type TOF
MS instrument name Bruker Autoflex speed TOF/TOF
Ion Mode POSITIVE
Units Peak Area

Chromatography:

Chromatography ID:CH003329
Instrument Name:Bruker Autoflex speed TOF/TOF
Column Name:None
Column Temperature:NA
Flow Gradient:NA
Flow Rate:NA
Solvent A:NA
Solvent B:NA
Chromatography Type:None (Direct infusion)

MS:

MS ID:MS004178
Analysis ID:AN004431
Instrument Name:Bruker Autoflex speed TOF/TOF
Instrument Type:TOF
MS Type:MALDI
MS Comments:In a typical LDI MS experiment, ferric particles were dispersed in deionized water at a concentration of 1mg mL-1 for use as a matrix. The organic matrices of CHCA and DHB were dissolved in TA30 solution (acetonitrile/0.1% TFA in water, 7/3, v/v) at a concentration of 10 mg/mL. For the detection of the standards, 100nL of analyte solution (each standard listed in the part of chemicals and reagents) with different density (100ng mL-1, 1μg mL-1, 10μg mL-1, 100μg mL-1, 1mg mL-1) was mixed with 100nL of matrix slurry on the plate and dried for LDI MS analysis. For plasma sample detection, the samples were firstly prepared through protein precipitation, centrifugation, and supernatant filtration according to a commonly applied procedure. Then, a volume of 100nL of plasma solution was spotted on the plate and dried in air at room temperature, followed by adding 100nL of matrix slurry and drying for LDI MS analysis. Then, mass spectra were performed on a 5800 Proteomics Analyzer (Applied Biosystems, Framingham, MA, USA) equipped with a Nd:YAG laser (2 kHz, 355 nm). The acquisitions were extracted in positive reflector ion mode employing delayed extraction with a repetition rate of 1,000Hz and an acceleration voltage of 20 kV. The delay time for this experiment was optimized to 250 ns. The 2,000 laser shots per analysis were for all LDI MS experiments. All the original mass spectra data were visualized in DataExplorer (Version 4.5). Only the m/z signals within 100–300Da and with a signal-to-noise ratio over 3 were then acquired without smoothing processes. For pre-processing, we applied a “home-developed” program using MATLAB (R2016a, The Mathworks, Natick, MA, USA) to normalize and standardize the mass spectra data after peak extraction and alignment59. And standard molecules for the accurate mass measurement (±0.05Da) of both Na+-adducted and K+-adducted signals were used to perform the mass calibration. The detection limit of standard metabolites (listed in chemicals and reagents’ part) obtained by ferric particle, DHB, and CHCA-assisted LDI MS were calculated as previously reported
Ion Mode:POSITIVE
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