Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort
Abstract
1. Introduction
2. Materials and Methods
2.1. Chemicals and Reagents
2.2. Preparation of Standard Solutions
2.3. Lipid Extraction
2.4. Liquid Chromatography Separation and Mass Spectrometry Detection
2.5. Data Analysis
2.6. Development and Validation of the LC-MS Method
2.6.1. Selectivity
- A signal is visible on an MS1 chromatogram extracted using the analyte mass and a mass tolerance of ±5 ppm;
- A signal is visible on an MS2 chromatogram extracted using a characteristic fragment mass (fatty acid, phospholipid head group for lysophospholipids, and conjugated group for bile acids) and a mass tolerance of ±5 ppm;
- The retention time of the analyte matches the result obtained with a reference standard.
2.6.2. Recovery of Extraction
2.6.3. Dynamic Range, Limits of Detection, and Quantification
2.6.4. Matrix Effect
2.6.5. Trueness, Precision, and Repeatability
2.7. Untargeted Screening of Bile Acids and Lysophospholipids
2.8. Experimental Model and Subjects’ Details
2.9. Statistical Analysis on the Clinical Cohort
- -
- A clinical model based solely on baseline clinical parameters, including total lipid levels (triglycerides, HDL, cholesterol, and LDL), the Body Mass Index (BMI), homeostasis model assessment of insulin resistance (HOMA-IR), gender, and age;
- -
- A model consisting of only baseline bile acid and lysophoslipid levels;
- -
- A model consisting of only the log2 fold-change that occurred during weight loss in bile acids and lysophoslipids.
3. Results and Discussion
3.1. Method Development and Validation
3.2. Application of the High Throughput Screening Method for Biomarker Discovery: Predicting the Response to a Controlled Weight Loss Intervention
3.3. Application of the High Throughput Screening Method for Biomarker Discovery: Predicting Insulin Resistance
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | All Subjects (N = 100) | Non Responders (N = 50) | Responders (N = 50) | p-Value |
---|---|---|---|---|
age, y | 42+/−6 | 41+/−6 | 43+/−6 | 0.0423 |
BMI, kg/2 | 35.2703+/−5.1284 | 36.0502+/−5.3902 | 34.4904+/−4.7794 | 0.129 |
fasting cholesterol levels, mmol/L | 4.6770+/−0.9588 | 4.5218+/−0.8869 | 4.8323+/−1.0107 | 0.106 |
HOMA-IR | 3.4239+/−1.8902 | 3.2890+/−2.1510 | 3.5588+/−1.5983 | 0.478 |
fasting LDL, mmol/L | 2.8845+/−0.8245 | 2.7662+/−0.7372 | 3.0053+/−0.8964 | 0.151 |
gender | M = 44, F = 56 | M = 14, F = 36 | M = 30, F = 20 | 0.002333 |
fasting HDL, mmol/L | 1.1104+/−0.3039 | 1.2044+/−0.3291 | 1.0164+/−0.2453 | 0.00168 |
fasting triglycerides, mmol/L | 1.4660+/−0.6817 | 1.2244+/−0.5851 | 1.7124+/−0.6904 | 0.000265 |
Symbol | Bile Acid | Concentration (µM) |
---|---|---|
CA | Cholic acid | 0.132 (0.069–0.976) |
CDCA | Chenodeoxycholic acid | 0.265 (0.058–2.027) |
DCA | Deoxycholic acid | 1.221 (0.208–3.697) |
LCA | Lithocholic acid | 0.125 (0.038–0.318) |
UDCA | Ursodeoxycholic acid | 0.728 (0.210–3.343) |
HCA | Hyocholic acid | 0.016 (0.008–0.042) |
HDCA | Hyodeoxycholic acid | 0.075 (0.025–0.185) |
GCA | Glycocholic acid | 0.282 (0.095–0.955) |
GCDCA | Glycochenodeoxycholic acid | 1.445 (0.406–4.155) |
GDCA | Glycodeoxycholic acid | 0.252 (0.060–1.017) |
GLCA | Glycolithocholic acid | ND |
GUDCA | Glycoursodeoxycholic acid | 0.113 (0.060–0.387) |
GHDCA | Glycohyodeoxycholic acid | ND |
TCA | Taurocholic acid | 0.058 (0.044–0.129) |
TCDCA | Taurochenodeoxycholic acid | 0.081 (0.026–0.270) |
TDCA | Taurodeoxycholic acid | 0.033 (0.014–0.109) |
TLCA | Taurolithocholic acid | 0.022 (0.009–0.042) |
TUDCA | Tauroursodeoxycholic acid | 0.025 (0.016–0.246) |
THDCA | Taurohyodeoxycholic acid | ND |
α-MCA | α-muricholic acid | 0.015 (0.008–0.031) |
β-MCA | β-muricholic acid | ND |
ω-MCA | ω-muricholic acid | 0.027 (0.012–0.074) |
7S-CA | Cholic acid 7-sulfate | ND |
3S-TLCA | Taurolitocholic acid 3-sulfate | 0.055 (0.016–0.174) |
3S-TCA | Taurocholic acid 3-sulfate | ND |
MDCA | Murideoxycholic acid | ND |
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Christinat, N.; Valsesia, A.; Masoodi, M. Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort. Biomolecules 2020, 10, 1049. https://doi.org/10.3390/biom10071049
Christinat N, Valsesia A, Masoodi M. Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort. Biomolecules. 2020; 10(7):1049. https://doi.org/10.3390/biom10071049
Chicago/Turabian StyleChristinat, Nicolas, Armand Valsesia, and Mojgan Masoodi. 2020. "Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort" Biomolecules 10, no. 7: 1049. https://doi.org/10.3390/biom10071049
APA StyleChristinat, N., Valsesia, A., & Masoodi, M. (2020). Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort. Biomolecules, 10(7), 1049. https://doi.org/10.3390/biom10071049