Identification of Urine Metabolic Markers of Stroke Risk Using Untargeted Nuclear Magnetic Resonance Analysis
Abstract
:1. Introduction
2. Results
2.1. Personal, Sociodemographic, and Clinical Data
Conditions | LSR | MSR | HSR | p-Value | Statistical Test |
---|---|---|---|---|---|
Number (n) | 73 | 87 | 17 | ||
Age (years) | 79.5 ± 0.99 | 88.1 ± 0.60 | 90.1 ± 1.33 | <0.001 * | KWT |
Female | 49.3 (36) | 81.6 (71) | 64.7 (11) | <0.001 * | FET |
Systolic blood pressure (mmHg) | 117.8 ± 2.14 | 128.7 ± 2.39 | 132.4 ± 5.44 | 0.001 * | OWAT |
Diastolic blood pressure (mmHg) | 68.1 ± 1.45 | 69.4 ± 1.17 | 72.4 ± 2.43 | 0.349 | OWAT |
Heart rate (bpm) | 73.4 ± 1.29 | 72.0 ± 1.11 | 71.8 ± 3.01 | 0.678 | OWAT |
Body mass index (kg/m2) | 25.9 ± 0.63 | 27.8 ± 0.67 | 29.6 ± 1.20 | 0.021 * | OWAT |
Serum total cholesterol (mg/dL) | 164.4 ± 5.80 | 167.4 ± 4.76 | 152.5 ± 10.8 | 0.503 | OWAT |
Serum HDL cholesterol (mg/dL) | 53.7 ± 1.35 | 56.0 ± 1.39 | 55.4 ± 3.66 | 0.518 | OWAT |
Serum LDL cholesterol (mg/dL) | 89.2 ± 5.09 | 90.2 ± 4.24 | 75.8 ± 9.36 | 0.432 | OWAT |
Serum triglyceride (mg/dL) | 107.3 ± 5.03 | 106.1 ± 5.23 | 106.5 ± 13.22 | 0.988 | OWAT |
Diseases | LSR | MSR | HSR | p-Value | Statistical Test |
---|---|---|---|---|---|
CARDIOVASCULAR DISEASES | |||||
Hypertension | 49 (67.1) | 74 (85.1) | 14 (82.4) | 0.039 * | FET |
Atrial fibrillation | 2 (2.7) | 12 (13.8) | 8 (47.1) | <0.001 * | FET |
Arrhythmia | 12 (16.4) | 19 (21.8) | 8 (52.9) | 0.044 * | FET |
Heart Failure | 11 (15.1) | 25 (28.7) | 8 (47.1) | 0.052 | FET |
Angina pectoris | 2 (2.7) | 9 (10.3) | 1 (5.9) | 0.254 | FET |
Atherosclerosis | 3 (4.1) | 4 (4.6) | 1 (5.9) | 1.000 | FET |
Valvopathies | 0 (0) | 4 (4.6) | 2 (11.8) | 0.112 | FET |
Peripheral vascular disease | 7 (10.3) | 7 (8.4) | 1 (5.9) | 0.924 | FET |
Acute myocardial infarction | 1 (1.4) | 1 (1.1) | 4 (23.5) | 0.005 * | FET |
Number of cardiovascular diseases | 1.01 ± 0.10 | 1.40 ± 0.10 | 2.00 ± 0.26 | <0.001 * | KWT |
METABOLIC DISEASES | |||||
Diabetes | 20 (27.4) | 23 (26.4) | 7 (41.2) | 0.792 | FET |
Dyslipidaemia | 29 (39.7) | 39 (44.8) | 8 (47.1) | 0.768 | FET |
RESPIRATORY DISEASES | |||||
Chronic obstructive pulmonary disease (COPD) | 4 (5.5) | 6 (6.9) | 1 (5.9) | 0.903 | FET |
Asthma | 1 (1.4) | 4 (4.6) | 1 (5.9) | 0.357 | FET |
CENTRAL NERVOUS SYSTEM DISEASES | |||||
Depression | 12 (16.4) | 15 (17.2) | 1 (5.9) | 0.624 | FET |
Treatments | LSR | MSR | HSR | p-Value | Statistical Test |
---|---|---|---|---|---|
Treatments for cardiovascular diseases | |||||
Antiarrhythmics | 2 (2.7) | 5 (5.7) | 0 (0) | 0.299 | FET |
Antianginal | 7 (9.6) | 11 (12.6) | 1 (5.9) | 0.355 | FET |
ACE inhibitors | 9 (12.3) | 18 (20.7) | 5 (29.4) | 0.070 | FET |
Angiotensin receptor antagonists | 25 (34.2) | 37 (42.5) | 8 (47.1) | 0.184 | FET |
Alpha and Beta blockers | 15 (20.5) | 14 (16.1) | 5 (29.4) | 0.175 | FET |
Calcium channel blockers | 18 (24.7) | 12 (13.8) | 4 (23.5) | 0.091 | FET |
Potassium-sparing diuretics | 2 (2.7) | 7 (8.0) | 1 (5.9) | 0.138 | FET |
Loop diuretics | 19 (26.0) | 37 (42.5) | 13 (76.5) | <0.001 * | FET |
Thiazide diuretics | 16 (21.9) | 20 (23.0) | 2 (11.8) | 0.344 | FET |
Venotropics | 6 (8.2) | 12 (13.8) | 2 (11.8) | 0.235 | FET |
Anticoagulants | 31 (42.5) | 46 (52.9) | 11 (64.7) | 0.067 | FET |
Treatments for metabolic diseases | |||||
Sulfonylureas | 4 (5.5) | 3 (3.4) | 2 (11.8) | 0.121 | FET |
Biguanides | 10 (13.7) | 16 (18.4) | 2 (11.8) | 0.340 | FET |
DPP-4 inhibitors | 12 (16.4) | 11 (12.6) | 4 (23.5) | 0.197 | FET |
Insulin | 5 (6.8) | 3 (3.4) | 1 (5.9) | 0.211 | FET |
Statins | 28 (38.4) | 33 (37.9) | 7 (41.2) | 0.438 | FET |
Treatments for respiratory diseases | |||||
Bronchodilators | 8 (11.0) | 13 (14.9) | 2 (11.8) | 0.362 | FET |
Treatments for CNS diseases | |||||
Acetylcholinesterase inhibitors | 6 (8.2) | 11 (12.6) | 1 (5.9) | 0.286 | FET |
Monoamine oxidase inhibitors | 1 (1.4) | 0 (0) | 0 (0) | 0.216 | FET |
N-methyl-D-aspartate antagonist | 5 (6.8) | 11 (12.6) | 1 (5.9) | 0.220 | FET |
Antiepileptics | 8 (11.0) | 7 (8.0) | 1 (5.9) | 0.381 | FET |
Antipsychotics | 25 (34.2) | 24 (27.6) | 4 (23.5) | 0.320 | FET |
Antidepressants | 28 (38.4) | 32 (36.8) | 7 (41.2) | 0.923 | FET |
Treatments for gastric disorders | |||||
Proton pump inhibitors | 37 (50.7) | 53 (60.9) | 13 (76.5) | 0.036 * | FET |
Laxatives | 10 (13.7) | 14 (16.1) | 3 (17.6) | 0.384 | FET |
Treatments for inflammatory diseases and pain | |||||
Opiates derivatives | 12 (16.4) | 12 (13.8) | 2 (11.8) | 0.424 | FET |
Medicines used to treat gout | 7 (9.6) | 12 (13.8) | 6 (35.3) | 0.014 * | FET |
Nonsteroidal anti-inflammatory drugs | 13 (17.8) | 25 (28.7) | 7 (41.2) | 0.034 * | FET |
2.2. NMR Spectra Peak Integration and Identification
2.3. Univariate Metabolomic Analysis of Metabolite Levels
2.4. Comorbidities and Drug Effects on Urine Metabolome
3. Discussion
4. Materials and Methods
4.1. Study Group Constitution
4.2. Sample Preparation
4.3. NMR Data Acquisition and Processing
4.4. Statistical Analysis
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Hankey, G.J. Stroke. Lancet 2017, 389, 641–654. [Google Scholar] [CrossRef] [PubMed]
- Feigin, V.L.; Brainin, M.; Norrving, B.; Martins, S.; Sacco, R.L.; Hacke, W.; Fisher, M.; Pandian, J.; Lindsay, P. World Stroke Organization (WSO): Global Stroke Fact Sheet 2022. Int. J. Stroke. 2022, 17, 18–29. [Google Scholar] [CrossRef] [PubMed]
- Montaño, A.; Hanley, D.F.; Hemphill, J.C., III. Hemorrhagic stroke. Handb. Clin. Neurol. 2021, 176, 229–248. [Google Scholar] [PubMed]
- Guzik, A.; Bushnell, C. Stroke Epidemiology and Risk Factor Management. Contin. Lifelong Learn. Neurol. 2017, 23, 15–39. [Google Scholar] [CrossRef] [PubMed]
- Pletcher, M.J.; Moran, A.E. Cardiovascular Risk Assessment. Med. Clin. North. Am. 2017, 101, 673–688. [Google Scholar] [CrossRef] [PubMed]
- Li, W.; Shao, C.; Li, C.; Zhou, H.; Yu, L.; Yang, J.; Wan, H.; He, Y. Metabolomics: A useful tool for ischemic stroke research. J. Pharm. Anal. 2023, 13, 968–983. [Google Scholar] [CrossRef] [PubMed]
- Beasley-Green, A. Urine Proteomics in the Era of Mass Spectrometry. Int. Neurourol. J. 2016, 20 (Suppl. 2), S70–S75. [Google Scholar] [CrossRef] [PubMed]
- Ma, Y.; He, F.J.; Sun, Q.I.; Yuan, C.; Kieneker, L.M.; Curhan, G.C.; MacGregor, G.A.; Bakker, S.J.; Campbell, N.R.; Wang, M.; et al. 24-Hour Urinary Sodium and Potassium Excretion and Cardiovascular Risk. N. Engl. J. Med. 2022, 386, 252–263. [Google Scholar] [CrossRef]
- Kurvits, S.; Harro, A.; Reigo, A.; Ott, A.; Laur, S.; Särg, D.; Tampuu, A.; Estonian Biobank Research Team; Alasoo, K.; Vilo, J.; et al. Common clinical blood and urine biomarkers for ischemic stroke: An Estonian Electronic Health Records database study. Eur. J. Med. Res. 2023, 28, 133. [Google Scholar] [CrossRef]
- Jung, J.Y.; Lee, H.S.; Kang, D.G.; Kim, N.S.; Cha, M.H.; Bang, O.S.; Ryu, D.H.; Hwang, G.S. 1H-NMR-based metabolomics study of cerebral infarction. Stroke 2011, 42, 1282–1288. [Google Scholar] [CrossRef]
- Petersson, J.N.; Bykowski, E.A.; Ekstrand, C.; Dukelow, S.P.; Ho, C.; Debert, C.T.; Montina, T.; Metz, G.A.S. Unraveling Metabolic Changes following Stroke: Insights from a Urinary Metabolomics Analysis. Metabolites 2024, 14, 145. [Google Scholar] [CrossRef]
- Bouatra, S.; Aziat, F.; Mandal, R.; Guo, A.C.; Wilson, M.R.; Knox, C.; Bjorndahl, T.C.; Krishnamurthy, R.; Saleem, F.; Liu, P.; et al. The human urine metabolome. PLoS ONE 2013, 8, e73076. [Google Scholar] [CrossRef] [PubMed]
- Lin, H.J.; Chen, S.T.; Wu, H.Y.; Hsu, H.C.; Chen, M.F.; Lee, Y.T.; Wu, K.Y.; Chien, K.L. Urinary biomarkers of oxidative and nitrosative stress and the risk for incident stroke: A nested case–control study from a community-based cohort. Int. J. Cardiol. 2015, 183, 214–220. [Google Scholar] [CrossRef] [PubMed]
- Bonifačić, D.; Aralica, M.; Sotošek Tokmadžić, V.; Rački, V.; Tuškan-Mohar, L.; Kučić, N. Values of vanillylmandelic acid and homovanillic acid in the urine as potential prognostic biomarkers in ischaemic stroke patients. Biomarkers 2017, 22, 790–797. [Google Scholar] [CrossRef] [PubMed]
- Balhara, N.; Devi, M.; Balda, A.; Phour, M.; Giri, A. Urine; a new promising biological fluid to act as a non-invasive biomarker for different human diseases. Urine 2023, 5, 40–52. [Google Scholar] [CrossRef]
- Bamodu, O.A.; Chan, L.; Wu, C.H.; Yu, S.F.; Chung, C.C. Beyond diagnosis: Leveraging routine blood and urine biomarkers to predict severity and functional outcome in acute ischemic stroke. Heliyon 2024, 10, e26199. [Google Scholar] [CrossRef] [PubMed]
- Kohlhase, K.; Frank, F.; Wilmes, C.; Koerbel, K.; Schaller-Paule, M.A.; Miles, M.; Betz, C.; Steinmetz, H.; Foerch, C. Brain-specific biomarkers in urine as a non-invasive approach to monitor neuronal and glial damage. Eur. J. Neurol. 2023, 30, 729–740. [Google Scholar] [CrossRef] [PubMed]
- Tasevska, N. Urinary Sugars—A Biomarker of Total Sugars Intake. Nutrients 2015, 7, 5816–5833. [Google Scholar] [CrossRef] [PubMed]
- Joosen, A.M.C.P.; Kuhnle, G.G.C.; Runswick, S.A.; Bingham, S.A. Urinary sucrose and fructose as biomarkers of sugar consumption: Comparison of normal weight and obese volunteers. Int. J. Obes. 2008, 32, 1736–1740. [Google Scholar] [CrossRef]
- Stryeck, S.; Horvath, A.; Leber, B.; Stadlbauer, V.; Madl, T. NMR spectroscopy enables simultaneous quantification of carbohydrates for diagnosis of intestinal and gastric permeability. Sci. Rep. 2018, 8, 14650. [Google Scholar] [CrossRef]
- He, S.; Jiang, H.; Zhuo, C.; Jiang, W. Trimethylamine/Trimethylamine-N-Oxide as a Key Between Diet and Cardiovascular Diseases. Cardiovasc. Toxicol. 2021, 21, 593–604. [Google Scholar] [CrossRef] [PubMed]
- Liu, Y.; Qu, J.; Xu, J.; Gu, A.; Deng, D.; Jia, X.; Wang, B. Trimethylamine-N-oxide: A potential biomarker and therapeutic target in ischemic stroke. Front. Neurol. 2023, 14, 1156879. [Google Scholar] [CrossRef] [PubMed]
- Yamashita, T.; Yoshida, N.; Emoto, T.; Hirata, K.I. Unraveling the Effects of Trimethylamine N-Oxide on Stroke: The lower, the better? J. Atheroscler. Thromb. 2021, 28, 314–316. [Google Scholar] [CrossRef] [PubMed]
- Tang, W.H.; Wang, Z.; Levison, B.S.; Koeth, R.A.; Britt, E.B.; Fu, X.; Wu, Y.; Hazen, S.L. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N. Engl. J. Med. 2013, 368, 1575–1584. [Google Scholar] [CrossRef] [PubMed]
- Koeth, R.A.; Wang, Z.; Levison, B.S.; Buffa, J.A.; Org, E.; Sheehy, B.T.; Britt, E.B.; Fu, X.; Wu, Y.; Li, L.; et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat. Med. 2013, 19, 576–585. [Google Scholar] [CrossRef] [PubMed]
- Zhu, W.; Gregory, J.C.; Org, E.; Buffa, J.A.; Gupta, N.; Wang, Z.; Li, L.; Fu, X.; Wu, Y.; Mehrabian, M.; et al. Gut Microbial Metabolite TMAO Enhances Platelet Hyperreactivity and Thrombosis Risk. Cell 2016, 165, 111–124. [Google Scholar] [CrossRef] [PubMed]
- Nie, J.; Xie, L.; Zhao, B.X.; Li, Y.; Qiu, B.; Zhu, F.; Li, G.F.; He, M.; Wang, Y.; Wang, B.; et al. Serum Trimethylamine N-Oxide Concentration Is Positively Associated With First Stroke in Hypertensive Patients. Stroke 2018, 49, 2021–2028. [Google Scholar] [CrossRef] [PubMed]
- Rexidamu, M.; Li, H.; Jin, H.; Huang, J. Serum levels of Trimethylamine-N-oxide in patients with ischemic stroke. Biosci. Rep. 2019, 39, BSR20190515. [Google Scholar] [CrossRef] [PubMed]
- Lemaitre, R.N.; Jensen, P.N.; Wang, Z.; Fretts, A.M.; Sitlani, C.M.; Nemet, I.; Sotoodehnia, N.; de Oliveira Otto, M.C.; Zhu, W.; Budoff, M.; et al. Plasma Trimethylamine-N-Oxide and Incident Ischemic Stroke: The Cardiovascular Health Study and the Multi-Ethnic Study of Atherosclerosis. J. Am. Heart Assoc. 2023, 12, e8711. [Google Scholar] [CrossRef]
- Dolkar, P.; Deyang, T.; Anand, N.; Rathipriya, A.G.; Hediyal, T.A.; Chandrasekaran, V.; Krishnamoorthy, N.K.; Gorantla, V.R.; Bishir, M.; Rashan, L.; et al. Trimethylamine-N-oxide and cerebral stroke risk: A review. Neurobiol. Dis. 2024, 192, 106423. [Google Scholar] [CrossRef]
- Yu, D.; Shu, X.O.; Rivera, E.S.; Zhang, X.; Cai, Q.; Calcutt, M.W.; Xiang, Y.B.; Li, H.; Gao, Y.T.; Wang, T.J.; et al. Urinary Levels of Trimethylamine-N-Oxide and Incident Coronary Heart Disease: A Prospective Investigation Among Urban Chinese Adults. J. Am. Heart Assoc. 2019, 8, e010606. [Google Scholar] [CrossRef] [PubMed]
- Yin, J.; Liao, S.X.; He, Y.; Wang, S.; Xia, G.H.; Liu, F.T.; Zhu, J.J.; You, C.; Chen, Q.; Zhou, L.; et al. Dysbiosis of Gut Microbiota With Reduced Trimethylamine-N-Oxide Level in Patients With Large-Artery Atherosclerotic Stroke or Transient Ischemic Attack. J. Am. Heart Assoc. 2015, 4, e002699. [Google Scholar] [CrossRef]
- Lachaux, C.; Frazao, C.J.R.; Krauβer, F.; Morin, N.; Walther, T.; François, J.M. A New Synthetic Pathway for the Bioproduction of Glycolic Acid From Lignocellulosic Sugars Aimed at Maximal Carbon Conservation. Front. Bioeng. Biotechnol. 2019, 7, 359. [Google Scholar] [CrossRef]
- Bnaya, A.; Abu-Amer, N.; Beckerman, P.; Volkov, A.; Cohen-Hagai, K.; Greenberg, M.; Ben-Chetrit, S.; Ben Tikva Kagan, K.; Goldman, S.; Navarro, H.A.; et al. Acute Kidney Injury and Hair-Straightening Products: A Case Series. Am. J. Kidney Dis. 2023, 82, 43–52. [Google Scholar] [CrossRef] [PubMed]
- Green, B.A.; Yu, R.J.; Van Scott, E.J. Clinical and cosmeceutical uses of hydroxyacids. Clin. Dermatol. 2009, 27, 495–501. [Google Scholar] [CrossRef] [PubMed]
- Chovsepian, A.; Berchtold, D.; Winek, K.; Mamrak, U.; Ramírez Álvarez, I.; Dening, Y.; Golubczyk, D.; Weitbrecht, L.; Dames, C.; Aillery, M.; et al. A Primeval Mechanism of Tolerance to Desiccation Based on Glycolic Acid Saves Neurons in Mammals from Ischemia by Reducing Intracellular Calcium-Mediated Excitotoxicity. Adv. Sci. 2022, 9, e2103265. [Google Scholar] [CrossRef]
- Choi, S.G.; Shin, J.; Lee, K.Y.; Park, H.; Kim, S.I.; Yi, Y.Y.; Kim, D.W.; Song, H.J.; Shin, H.J. PINK1 siRNA-loaded poly(lactic-co-glycolic acid) nanoparticles provide neuroprotection in a mouse model of photothrombosis-induced ischemic stroke. Glia 2023, 71, 1294–1310. [Google Scholar] [CrossRef]
- Hosaka, K.; Rojas, K.; Fazal, H.Z.; Schneider, M.B.; Shores, J.; Federico, V.; McCord, M.; Lin, L.; Hoh, B. Monocyte Chemotactic Protein-1-Interleukin-6-Osteopontin Pathway of Intra-Aneurysmal Tissue Healing. Stroke 2017, 48, 1052–1060. [Google Scholar] [CrossRef] [PubMed]
- Jeong, J.H.; Kang, S.H.; Kim, D.K.; Lee, N.S.; Jeong, Y.G.; Han, S.Y. Protective Effect of Cholic Acid-Coated Poly Lactic-Co-Glycolic Acid (PLGA) Nanoparticles Loaded with Erythropoietin on Experimental Stroke. J. Nanosci. Nanotechnol. 2019, 19, 6524–6533. [Google Scholar] [CrossRef]
- Porter, W.H.; Rutter, P.W.; Bush, B.A.; Pappas, A.A.; Dunnington, J.E. Ethylene glycol toxicity: The role of serum glycolic acid in hemodialysis. J. Toxicol. Clin. Toxicol. 2001, 39, 607–615. [Google Scholar] [CrossRef]
- Slavin, J.W.; Ritota, P.C.; Elfenbein, I.B. Renal Failure After Glycolic Acid Skin Treatments. Aesthet. Surg. J. 1996, 16, 75–76. [Google Scholar] [CrossRef]
- Liang, Y.; Dai, X.; Cao, Y.; Wang, X.; Lu, J.; Xie, L.; Liu, K.; Li, X. The neuroprotective and antidiabetic effects of trigonelline: A review of signaling pathways and molecular mechanisms. Biochimie 2023, 206, 93–104. [Google Scholar] [CrossRef]
- Kambalapally, C.; Suthar, P.K.; Patale, P.; Dhiman, S.; Gupta, V.; Thongire, V.; Sarmah, D.; Datta, A.; Kalia, K.; Bhattacharya, P. Chapter 51—Trigonelline and its uses in stroke. In Treatments, Nutraceuticals, Supplements, and Herbal Medicine in Neurological Disorders; Martin, C.R., Patel, V.B., Preedy, V.R., Eds.; Academic Press: Cambridge, MA, USA, 2023; pp. 979–992. [Google Scholar]
- Pravalika, K.; Sarmah, D.; Kaur, H.; Vats, K.; Saraf, J.; Wanve, M.; Kalia, K.; Borah, A.; Yavagal, D.R.; Dave, K.R.; et al. Trigonelline therapy confers neuroprotection by reduced glutathione mediated myeloperoxidase expression in animal model of ischemic stroke. Life Sci. 2019, 216, 49–58. [Google Scholar] [CrossRef] [PubMed]
- Qiu, Z.; Wang, K.; Jiang, C.; Su, Y.; Fan, X.; Li, J.; Xue, S.; Yao, L. Trigonelline protects hippocampal neurons from oxygen-glucose deprivation-induced injury through activating the PI3K/Akt pathway. Chem.-Biol. Interact. 2020, 317, 108946. [Google Scholar] [CrossRef]
- Nguyen, V.; Taine, E.G.; Meng, D.; Cui, T.; Tan, W. Pharmacological Activities, Therapeutic Effects, and Mechanistic Actions of Trigonelline. Int. J. Mol. Sci. 2024, 25, 3385. [Google Scholar] [CrossRef] [PubMed]
- Ilavenil, S.; Kim, D.H.; Jeong, Y.I.; Arasu, M.V.; Vijayakumar, M.; Prabhu, P.N.; Srigopalram, S.; Choi, K.C. Trigonelline protects the cardiocyte from hydrogen peroxide induced apoptosis in H9c2 cells. Asian Pac. J. Trop. Med. 2015, 8, 263–268. [Google Scholar] [CrossRef] [PubMed]
- Liu, Z.; Xi, R.; Zhang, Z.; Li, W.; Liu, Y.; Jin, F.; Wang, X. 4-hydroxyphenylacetic acid attenuated inflammation and edema via suppressing HIF-1α in seawater aspiration-induced lung injury in rats. Int. J. Mol. Sci. 2014, 15, 12861–12884. [Google Scholar] [CrossRef] [PubMed]
- Shen, Y.-P.; Fong, L.S.; Yan, Z.-B.; Liu, J.-Z. Combining directed evolution of pathway enzymes and dynamic pathway regulation using a quorum-sensing circuit to improve the production of 4-hydroxyphenylacetic acid in Escherichia coli. Biotechnol. Biofuels 2019, 12, 94. [Google Scholar] [CrossRef] [PubMed]
- Zhao, H.; Jiang, Z.; Chang, X.; Xue, H.; Yahefu, W.; Zhang, X. 4-Hydroxyphenylacetic Acid Prevents Acute APAP-Induced Liver Injury by Increasing Phase II and Antioxidant Enzymes in Mice. Front. Pharmacol. 2018, 9, 653. [Google Scholar] [CrossRef]
- Oliveira, N.; Sousa, A.; Amaral, A.P.; Graça, G.; Verde, I. Searching for Metabolic Markers of Stroke in Human Plasma via NMR Analysis. Int. J. Mol. Sci. 2023, 24, 16173. [Google Scholar] [CrossRef]
- Wolf, P.A.; D’Agostino, R.B.; Belanger, A.J.; Kannel, W.B. Probability of stroke: A risk profile from the Framingham Study. Stroke 1991, 22, 312–318. [Google Scholar] [CrossRef] [PubMed]
- Dufouil, C.; Beiser, A.; McLure, L.A.; Wolf, P.A.; Tzourio, C.; Howard, V.J.; Westwood, A.J.; Himali, J.J.; Sullivan, L.; Aparicio, H.J.; et al. Revised Framingham Stroke Risk Profile to Reflect Temporal Trends. Circulation 2017, 135, 1145–1159. [Google Scholar] [CrossRef] [PubMed]
Data | Group | Total Sugar | r | Glycolate | r | 4-HPA | r | Trigonelline | r |
---|---|---|---|---|---|---|---|---|---|
Comparison (metabolites) with age | LSR | ns | −0.033 | ns | −0.143 | ns | 0.109 | ns | −0.134 |
MSR | ns | 0.047 | ns | −0.090 | ns | 0.110 | ns | −0.111 | |
HSR | ns | −0.228 | ns | −0.166 | ns | 0.196 | ns | 0.436 | |
All | ns | −0.118 | ns | −0.082 | ▲ * | 0.162 | ▼ *** | −0.258 | |
Comparison (metabolites) with total number of cardiovascular diseases | LSR | ns | 0.036 | ns | −0.185 | ns | −0.033 | ns | 0.005 |
MSR | ns | 0.261 | ns | 0.046 | ns | 0.077 | ns | −0.054 | |
HSR | ns | −0.084 | ns | −0.290 | ns | 0.181 | ns | 0.046 | |
All | ns | 0.069 | ns | −0.046 | ▲ * | 0.178 | ns | −0.095 |
Diseases/Treatments | Group | Total Sugar | r | Glycolate | r | 4-HPA | r | Trigonelline | r |
---|---|---|---|---|---|---|---|---|---|
Comparison (metabolites) with and without Atrial fibrillation | LSR | ns | 0.168 | ns | 0.084 | ns | 0.000 | ns | 0.077 |
MSR | ns | 0.140 | ns | −0.096 | ns | 0.163 | ns | 0.011 | |
HSR | ns | −0.096 | ns | −0.322 | ns | 0.041 | ns | 0.155 | |
All | ns | 0.112 | ns | −0.097 | ns | 0.102 | ▼ *** | −0.007 | |
Comparison (metabolites) with and without loop diuretics treatment | LSR | ns | 0.108 | ns | 0.128 | ns | 0.090 | ns | 0.163 |
MSR | ▲ * | 0.225 | ns | 0.193 | ▲ * | 0.251 | ns | 0.114 | |
HSR | ns | 0.476 | ns | 0.401 | ns | 0.447 | ns | 0.452 | |
All | ▲ * | 0.186 | ns | 0.111 | ▲ * | 0.221 | ns | 0.096 | |
Comparison (metabolites) with and without proton pump inhibitor treatment | LSR | ns | 0.229 | ns | 0.168 | ns | 0.264 | ns | −0.060 |
MSR | ns | −0.089 | ns | 0.110 | ns | 0.046 | ns | −0.174 | |
HSR | ns | 0.238 | ns | 0.330 | ns | −0.136 | ns | 0.290 | |
All | ▲ * | 0.081 | ▲ * | 0.105 | ns | 0.122 | ns | −0.110 | |
Comparison (metabolites) with and without Medicines used to treat gout | LSR | ns | .0.019 | ns | −0.177 | ns | 0.003 | ns | 0.141 |
MSR | ns | 0.196 | ns | −0.117 | ns | −0.078 | ns | −0.179 | |
HSR | ns | 0.339 | ns | 0.494 | ns | −0.142 | ns | 0.332 | |
All | ns | 0.135 | ▼ * | −0.136 | ns | −0.013 | ns | −0.017 | |
Comparison (metabolites) with and without NSAID treatment | LSR | ns | 0.100 | ns | 0.002 | ns | 0.181 | ns | 0.003 |
MSR | ns | 0.006 | ns | 0.029 | ns | 0.177 | ns | −0.275 | |
HSR | ns | 0.399 | ns | 0.245 | ns | 0.310 | ns | 0.085 | |
All | ns | 0.075 | ns | 0.019 | ▲ * | 0.179 | ns | −0.142 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Oliveira, N.; Sousa, A.; Amaral, A.P.; Conde, R.; Verde, I. Identification of Urine Metabolic Markers of Stroke Risk Using Untargeted Nuclear Magnetic Resonance Analysis. Int. J. Mol. Sci. 2024, 25, 7436. https://doi.org/10.3390/ijms25137436
Oliveira N, Sousa A, Amaral AP, Conde R, Verde I. Identification of Urine Metabolic Markers of Stroke Risk Using Untargeted Nuclear Magnetic Resonance Analysis. International Journal of Molecular Sciences. 2024; 25(13):7436. https://doi.org/10.3390/ijms25137436
Chicago/Turabian StyleOliveira, Nádia, Adriana Sousa, Ana Paula Amaral, Ricardo Conde, and Ignacio Verde. 2024. "Identification of Urine Metabolic Markers of Stroke Risk Using Untargeted Nuclear Magnetic Resonance Analysis" International Journal of Molecular Sciences 25, no. 13: 7436. https://doi.org/10.3390/ijms25137436