November 2023 Publication Summary of Studies Using Metabolon’s Panels and Services

Metabolon contributed to 39 studies that were published in November!! Congratulations to the labs that published the following in high impact journals! 

1. Pham VN, Bruemmer KJ, Toh JDW, et al. Formaldehyde regulates S-adenosylmethionine biosynthesis and one-carbon metabolism. Science. 2023;382(6670):eabp9201. doi:10.1126/science.abp9201
2. Baker ES, Hoang C, Uritboonthai W, et al. METLIN-CCS: an ion mobility spectrometry collision cross section database. Nat Methods. Published online November 6, 2023. doi:10.1038/s41592-023-02078-5
3. Dunder L, Salihovic S, Varotsis G, Lind PM, Elmståhl S, Lind L. Plasma levels of per- and polyfluoroalkyl substances (PFAS) and cardiovascular disease – Results from two independent population-based cohorts and a meta-analysis. Environ Int. 2023;181:108250. doi:10.1016/j.envint.2023.108250
4. Fino N, Adingwupu OM, Coresh J, et al. Evaluation of novel candidate filtration markers from a global metabolomic discovery for glomerular filtration rate estimation. Kidney International. 2023/11/23/ 2023;doi:https://doi.org/10.1016/j.kint.2023.11.007
5. Schmidt S, Stautner C, Vu DT, et al. A reversible state of hypometabolism in a human cellular model of sporadic Parkinson’s disease. Nature Communications. 2023/11/23 2023;14(1):7674. doi:10.1038/s41467-023-42862-7
6. Elgart M, Zhang Y, Zhang Y, et al. Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletion. EBioMedicine. 2023;98:104891. doi:10.1016/j.ebiom.2023.104891

Neuroscience and oncology were common themes in November’s publications. In neurology, most studies used metabolomics to investigate how lifestyle choices (smoking, diet, social isolation) impact disease mechanisms. One study combined AI with metabolomics to predict myalgic encephalomyelitis and chronic fatigue syndrome. These studies contribute to the understanding of neurological conditions, providing insights into the complex interplay between genetics, environment, and metabolic processes in diseases like ME/CFS, stress-related responses, and neurodegenerative disorders. In oncology, disease prediction was also a topic, as well as disease mechanisms, investigated via the study of functional genomics. Collectively, these studies provide insights into the intricate metabolic pathways and microbial contributions to various types of cancer, contributing to the ongoing efforts in developing targeted therapeutic strategies and early detection methods. Improved and personalized therapeutics continue to be highly sought after in oncology, goals toward which metabolomics can contribute.

These topics are representative of a larger goal across research, medicine, and wellness. How can we identify contributors to disease, modify system input, or change disease outcomes? Whether we are changing lifestyles (diet) or the environment (regulating industries to reduce human exposure), metabolomics can help guide the way in determining the most relevant contributors so that we can make wise decisions about what needs to be changed to improve human health and well-being. 

For a convenient resource, you can access a searchable directory of metabolomics-related publications here.

Agriculture

1. Chmielewski F-M, Götz K-P. Towards a Physiological Modeling of Sweet Cherry Blossom. Horticulturae. 2023;9(11):1207. 
2. Wang X, Zhang X, Tzin V, Han L. Jasmonic acid signaling induced by caterpillar damage causes reduced resistance to target insect feeding by the brown planthopper, Nilaparvata lugens (Stål), in rice. 2023;PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3595183/v1]
3. de Barros Rates A, Cesarino I. Pour some sugar on me: The diverse functions of phenylpropanoid glycosylation. Journal of Plant Physiology. 2023:154138. doi:10.1016/j.jplph.2023.154138

Cardiology

4. Kwee LC, Truby LK, Page S, et al. Integrative Omics in Failing Myocardium Highlights Metabolic Substrate Utilization Defects in Human Heart Failure. Circulation. 2023;148(Suppl_1):A16786-A16786. Presented at AHA Scientific Sessions 2023.
5. Nayak MK, Ghatge M, Flora GD, Chauhan AK. Metabolomics Reveals Aerobic Glycolysis and 1-Carbon Metabolism as Major Metabolic Signature During Human Platelet Activation. Circulation. 2023;148(Suppl_1):A19037-A19037. Presented at AHA Scientific Sessions 2023.
6. Wittenbecher C, Eichelmann F, Schulze M, et al. Deep lipidomics profiling captures the impact of improved dietary fat quality on cardiometabolic risk and provides potential tools for precision nutrition approaches. 2023;PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3653633/v1]

Environment and Exposure

7. Pham VN, Bruemmer KJ, Toh JDW, et al. Formaldehyde regulates S-adenosylmethionine biosynthesis and one-carbon metabolism. Science. 2023;382(6670):eabp9201. doi:10.1126/science.abp9201
8. Dunder L, Salihovic S, Varotsis G, Lind PM, Elmståhl S, Lind L. Plasma levels of per- and polyfluoroalkyl substances (PFAS) and cardiovascular disease – Results from two independent population-based cohorts and a meta-analysis. Environ Int. 2023;181:108250. doi:10.1016/j.envint.2023.108250

Kidney Function

9. Ermakov VS, Granados JC, Nigam SK. Remote effects of kidney drug transporter OAT1 on gut microbiome composition and urate homeostasis. JCI Insight. 2023;8(21):e172341. Published 2023 Nov 8. doi:10.1172/jci.insight.172341
10. Heruye S, Myslinski J, Zeng C, et al. Inflammation primes the kidney for recovery by activating AZIN1 A-to-I editing. bioRxiv. 2023:2023.11. 09.566426. 
11. Nealon NJ, Summers S, Quimby J, Winston J. Untargeted metabolomic profiling of serum from client-owned cats with early and late-stage chronic kidney disease. 2023;PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3538472/v1]
12. Fino N, Adingwupu OM, Coresh J, et al. Evaluation of novel candidate filtration markers from a global metabolomic discovery for glomerular filtration rate estimation. Kidney International. 2023/11/23/ 2023;doi:https://doi.org/10.1016/j.kint.2023.11.007

Microbiome

13. Pan Y, Wang Y, Hao W, Zhou S, Duan C, Li Q, Wei J, Liu G. Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation. Foods. 2023; 12(22):4140. https://doi.org/10.3390/foods12224140
14. Beer J, Saravi SSS, Pugin B, et al. Gut microbiota-dependent increase in phenylacetic acid induces endothelial cell senescence during aging. 2023;PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3615762/v1]

Neurology

15. Yagin FH, Alkhateeb A, Raza A, Samee NA, Mahmoud NF, Colak C, Yagin B. An Explainable Artificial Intelligence Model Proposed for the Prediction of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and the Identification of Distinctive Metabolites. Diagnostics. 2023; 13(23):3495. https://doi.org/10.3390/diagnostics13233495
16. Valdez MC, Freeborn DL, Valdez JM, Henriquez AR, Snow SJ, Jackson TW, Kodavanti PRS, Kodavanti UP. Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar–Kyoto Rats. Antioxidants. 2023; 12(11):1964. https://doi.org/10.3390/antiox12111964
17. Choi JJ, Koscik RL, Jonaitis EM, Panyard DJ, Morrow AR, Johnson SC, Engelman CD, Schmitz LL. Assessing the Biological Mechanisms Linking Smoking Behavior and Cognitive Function: A Mediation Analysis of Untargeted Metabolomics. Metabolites. 2023; 13(11):1154. https://doi.org/10.3390/metabo13111154
18. Schweickart A, Batra R, Neth BJ, et al. A Modified Mediterranean Ketogenic Diet mitigates modifiable risk factors of Alzheimer’s Disease: a serum and CSF-based metabolic analysis. medRxiv. 2023:2023.11. 27.23298990. 
19. Schmidt S, Stautner C, Vu DT, et al. A reversible state of hypometabolism in a human cellular model of sporadic Parkinson’s disease. Nature Communications. 2023/11/23 2023;14(1):7674. doi:10.1038/s41467-023-42862-7
20. Gusdon AM, Savarraj JP, Feng D, et al. High-Protein Supplementation and Neuromuscular Electric Stimulation after Aneurysmal Subarachnoid Hemorrhage Increases Systemic Amino Acid and Oxidative Metabolism: A Plasma Metabolomics Approach. 2023;PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3600439/v1]

Obesity

21. Lovric M, Wang T, Staffe MR, et al. A chemical structure and machine learning approach to assess the potential bioactivity of endogenous metabolites and their association with early-childhood hs-CRP levels. bioRxiv. 2023:2023.11. 15.567095. 
22. Aparicio A, Sun Z, Gold DR, et al. Genotype-microbiome-metabolome associations in early childhood, and their link to BMI and childhood obesity. medRxiv. 2023:2023.11. 13.23298467. 
23. McCall KD, Walter D, Patton A, et al. Anti-Inflammatory and Therapeutic Effects of a Novel Small-Molecule Inhibitor of Inflammation in a Male C57BL/6J Mouse Model of Obesity-Induced NAFLD/MAFLD. Journal of Inflammation Research. 2023/12/31 2023;16(null):5339-5366. doi:10.2147/JIR.S413565
24. Elgart M, Zhang Y, Zhang Y, et al. Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletion. EBioMedicine. 2023;98

Oncology

25. Ohara Y, Craig AJ, Liu H, et al. LMO3 is a suppressor of the basal-like/squamous PDAC subtype and reduces disease aggressiveness of pancreatic cancer through glycerol 3-phosphate metabolism. bioRxiv. 2023:2023.11. 01.564448. 
26. Benedetti E, Chetnik K, Flynn T, et al. Plasma metabolomics profiling of 580 patients from an Early Detection Research Network prostate cancer cohort. Scientific Data. 2023/11/25 2023;10(1):830. doi:10.1038/s41597-023-02750-7
27. Tu KJ, Diplas BH, Regal JA, Waitkus MS, Pirozzi CJ, Reitman ZJ. Mining cancer genomes for change-of-metabolic-function mutations. Communications Biology. 2023/11/10 2023;6(1):1143. doi:10.1038/s42003-023-05475-w
28. Kang Z-R, Jiang S, Han J-X, et al. Deficiency of BCAT2-mediated branched-chain amino acid catabolism promotes colorectal cancer development. Biochimica et Biophysica Acta (BBA) – Molecular Basis of Disease. 2024/02/01/ 2024;1870(2):166941. doi:https://doi.org/10.1016/j.bbadis.2023.166941
29. Crossland NA, Beck S, Tan WY, et al. Fecal microbiota transplanted from old mice promotes more colonic inflammation, proliferation, and tumor formation in azoxymethane-treated A/J mice than microbiota originating from young mice. Gut Microbes. 2023;15(2):2288187. 

Pregnancy and Childbirth

30. Czuba LC, Malhotra K, Enthoven L, et al. CYP2D6 activity is correlated with changes in plasma concentrations of taurocholic acid during pregnancy and postpartum in CYP2D6 extensive metabolizers. Drug Metabolism and Disposition. 2023;51(11):1474-1482. 
31. Al Ghadban Y, Du Y, Charnock-Jones DS, Garmire LX, Smith GCS, Sovio U. Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case–cohort study. BJOG: An International Journal of Obstetrics & Gynaecology. 2023/11/20 2023;n/a(n/a)doi:https://doi.org/10.1111/1471-0528.17723
32. Symul L, Jeganathan P, Costello EK, et al. Sub-communities of the vaginal microbiota in pregnant and non-pregnant women. Proceedings of the Royal Society B: Biological Sciences. 2023/11/29 2023;290(2011):20231461. doi:10.1098/rspb.2023.1461

Respiratory Disease

33. Kyo M, Zhu Z, Shibata R, et al. Respiratory Virus–Specific Nasopharyngeal Lipidome Signatures and Severity in Infants With Bronchiolitis: A Prospective Multicenter Study. The Journal of Infectious Diseases. 2023;228(10):1410-1420. doi:10.1093/infdis/jiad156
34. Choi B, San José Estépar R, Godbole S, et al. Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers. Respiratory Research. 2023/11/04 2023;24(1):265. doi:10.1186/s12931-023-02576-2
35. Balachandar S, Oconnell TM, Aldred MA. Abstract 14665: Cybrid Analysis Delineates Nuclear and Mitochondrial Contributions to Oxidative Stress in Pulmonary Arterial Hypertension. Circulation. 2023/11/07 2023;148(Suppl_1):A14665-A14665. doi:10.1161/circ.148.suppl_1.14665

Other

36. Gygi JP, Maguire C, Patel RK, et al. Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants. bioRxiv. 2023:2023.11. 03.565292. doi:10.1101/2023.11.03.565292
37. Calzadilla N, Zilberstein N, Hanscom M, et al. Serum metabolomic analysis in cirrhotic alcohol-associated liver disease patients identified differentially altered microbial metabolites and novel potential biomarkers for disease severity. Digestive and Liver Disease. 2023/11/01/ 2023;doi:https://doi.org/10.1016/j.dld.2023.10.006
38. Baker ES, Hoang C, Uritboonthai W, et al. METLIN-CCS: an ion mobility spectrometry collision cross section database. Nat Methods. Published online November 6, 2023. doi:10.1038/s41592-023-02078-5
39. Du Y, Li Y-Y, Choi BY, et al. Metabolomic profiles associated with physical activity in White and African American adult men. Plos one. 2023;18(11):e0289077.