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

In the month of September, Metabolon contributed to 36 studies that resulted in publications! Congratulations to the labs that published the following in high impact journals! 

• Shoer S, Shilo S, Godneva A, et al. Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines. Nature Communications. 2023/09/04 2023;14(1):5384. doi:10.1038/s41467-023-41042-x
• Xia Y, Xiao Y, Wang Z-H, et al. Bacteroides Fragilis in the gut microbiomes of Alzheimer’s disease activates microglia and triggers pathogenesis in neuronal C/EBPβ transgenic mice. Nature Communications. 2023/09/06 2023;14(1):5471. doi:10.1038/s41467-023-41283-w
• Ferrari V, Lo Cascio A, Melacarne A, et al. Sensitizing cancer cells to immune checkpoint inhibitors by microbiota-mediated upregulation of HLA class I. Cancer Cell. 2023;41(10):1717-1730.e4. doi:10.1016/j.ccell.2023.08.014

In September, key publications highlight the incorporation of Metabolon’s Global Discovery Panel’s metabolomic outputs in multi-omic analyses, wherein the inclusion of metabolites added key mechanistic/functional insights to the relationships between genes, epigenome, transcripts, and proteins.

In one study, Yousri NA et al. report the construction of methylome-metabolome associations, methylation QTLs, and metabolic network based multi-omic network to identify metabolic mechanisms underlying methylated gene profiles in a clinical cohort of Type 2 diabetes.

• Yousri NA, Albagha OME, Hunt SC. Integrated epigenome, whole genome sequence and metabolome analyses identify novel multi-omics pathways in type 2 diabetes: a Middle Eastern study. BMC Med. 2023;21(1):347. Published 2023 Sep 8. doi:10.1186/s12916-023-03027-x

In two separate studies, global metabolomic outputs from Metabolon’s Global Discovery Panel from public databases were used to (a) develop a computational model for interpretation and mechanistic inference of causality and (b) Mendelian Randomization to identify novel metabolite-disease associations in clinical cohorts.

• Erwin S, FLetcher JR, Sweeney DC, et al.  Distilling mechanistic models from multi-omics data. bioRxiv 2023 doi:10.1101/2023.09.06.556597
• Minoo Bagheri, Andrei Bombin, Mingjian Shi et al. Genotype-based “virtual” metabolomics in a clinical biobank identifies novel metabolite-disease associations. Research Square. 12 October 2023, doi:10.21203/rs.3.rs-3222588/v2

In the last of multi-omic efforts this month, Jackson TW et al. report the use of global metabolomic profiling changes along with transcriptomics to characterize the systems effect of ozone exposure in a preclinical model. The study describes details on tissue specific unique alterations in gene expression and metabolic phenotypes; however, both molecular alterations demonstrate initiating triggers that converge into shared pathway level responses.

• Jackson TW, House JS, Henriquez AR, et al. Multi-tissue transcriptomic and serum metabolomic assessment reveals systemic implications of acute ozone-induced stress response in male Wistar Kyoto rats. Metabolomics. 2023;19(9):81. Published 2023 Sep 10. doi:10.1007/s11306-023-02043-5

In addition to the use of metabolomics in multi-omic analyses, Metabolon’s Global Discovery Panel and other services were used to support scientific investigations and glean important insights in women’s health, pregnancy, neonatal health, cancer, and neurological diseases including major depressive disorders, schizophrenia, and Alzheimer’s diseases.

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

Women’s Health, Pregnancy, and Neonatal Health

1. Enthoven LF, Shi Y, Fay E, et al. Effects of Pregnancy on Plasma Sphingolipids Using a Metabolomic and Quantitative Analysis Approach. Metabolites. 2023;13(9):1026. Published 2023 Sep 21. doi:10.3390/metabo13091026
2. Stein TP, Schluter MD, Steer RA, Ming X. Bisphenol-A and phthalate metabolism in children with neurodevelopmental disorders. PLoS One. 2023;18(9):e0289841. Published 2023 Sep 13. doi:10.1371/journal.pone.0289841
3. Martínez-Moro Á, González-Brusi L, Querejeta-Fernández A, Padilla-Ruiz E, García-Blanco J, Bermejo-Álvarez P. Metabolomics analysis of human cumulus cells obtained from cumulus-oocyte complexes with different developmental potential [published online ahead of print, 2023 Sep 11]. Hum Reprod. 2023;dead181. doi:10.1093/humrep/dead181
4. Colicino E, Cowell W, Pedretti NF, et al. Maternal steroids during pregnancy and their associations with exposure to lifetime stressful life events, prenatal stress appraisal and psychological functioning [published online ahead of print, 2023 Sep 21]. Psychoneuroendocrinology. 2023;158:106395. doi:10.1016/j.psyneuen.2023.106395
5. Bisgaard H, Mikkelsen M, Rasmussen MA,et al. Atopic and non-atopic effects of fish oil supplementation during pregnancy. Thorax. 2023:thorax-2022-219725. doi:10.1136/thorax-2022-219725
6. Selvaratnam RJ, Sovio U, Cook E, Gaccioli F, Charnock-Jones DS, Smith GCS. Objective measures of smoking and caffeine intake and the risk of adverse pregnancy outcomes. International Journal of Epidemiology. 2023:dyad123. doi:10.1093/ije/dyad123
7. Barak O, Lovelace T, Piekos S, et al. Integrated unbiased multiomics defines disease-independent placental clusters in common obstetrical syndromes. BMC Medicine. 2023/09/08 2023;21(1):349. doi:10.1186/s12916-023-03054-8
8. Kim M, Brustad N, Ali M, et al. Maternal vitamin D–related metabolome and offspring risk of asthma outcomes. Journal of Allergy and Clinical Immunology. 2023/08/08/ 2023;doi:https://doi.org/10.1016/j.jaci.2023.06.030
9. Nader N, Zarif L, Halama A, et al. Progesterone induces meiosis through two obligate co-receptors with PLA2 activity. bioRxiv. 2023:2023.09.09.556646. doi:10.1101/2023.09.09.556646

Cancer

10. Ferrari V, Lo Cascio A, Melacarne A, et al. Sensitizing cancer cells to immune checkpoint inhibitors by microbiota-mediated upregulation of HLA class I. Cancer Cell. 2023;41(10):1717-1730.e4. doi:10.1016/j.ccell.2023.08.014
11. Mrugala MM, Zimmerman R, Greene D, et al. P11.39.B PREDICTING RESPONSE TO CHEMOTHERAPY IN RECURRENT HIGH GRADE GLIOMAS USINGEX VIVO 3D CELL CULTURE FUNCTIONAL PRECISION ONCOLOGY PLATFORM. Neuro-Oncology. 2023;25(Supplement_2):ii82-ii82. doi:10.1093/neuonc/noad137.273
12. McCune JS, Navarro SL, Risler LJ, et al. The presence of busulfan metabolites and pharmacometabolomics in plasma drawn immediately before allograft infusion in hematopoietic cell transplant recipients. Clinical and Translational Science. 2023/09/25 2023;n/a(n/a)doi:https://doi.org/10.1111/cts.13651
13. Jung S, Silva S, Dallal CM, et al. Untargeted serum metabolomic profiles and breast density in young women. Cancer Causes & Control. 2023/09/22 2023;doi:10.1007/s10552-023-01793-w
14. Ohara Y, Craig AJ, Liu H, et al. ELAPOR1 induces the classical/progenitor subtype and contributes to reduced disease aggressiveness through metabolic reprogramming in pancreatic cancer. bioRxiv. 2023:2023.09.23.558894. doi:10.1101/2023.09.23.558894
15. Teske N, Kutlu NN, Herold JJ, et al. OS09.1.AIN VIVOTWO-PHOTON TUMOR IMAGING IN AN ORTHOTOPIC MEDULLOBLASTOMA MOUSE MODEL. Neuro-Oncology. 2023;25(Supplement_2):ii20-ii20. doi:10.1093/neuonc/noad137.058
16. Pan Z, Yang G, Wang Z, et al. OS09.6.A A MULTICENTER, PHASE I/II, OPEN-LABEL STUDY OF INTRATHECAL PEMETREXED FOR LEPTOMENINGEAL METASTASES FROM SOLID TUMOR (PMLM, NCT 05289908). Neuro-Oncology. 2023;25(Supplement_2):ii21-ii22. doi:10.1093/neuonc/noad137.063
17. Sandström M, Larhed S, Axelsson J, Björblom B, Asklund T. P11.42.A LONG- AND SHORTIME SURVIVORS WITH GLIOBLASTOMA IDENTIFIED BY FLT PET/MR AND METABOLOMICS. Neuro-Oncology. 2023;25(Supplement_2):ii83-ii83. doi:10.1093/neuonc/noad137.276
18. Udumula MP, Singh H, Rashid F, et al. Intermittent fasting induced ketogenesis inhibits mouse epithelial ovarian cancer by promoting antitumor T cell response. iScience. Oct 20 2023;26(10):107839. doi:10.1016/j.isci.2023.10783

Diabetes

19. Shoer S, Shilo S, Godneva A, et al. Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines. Nature Communications. 2023/09/04 2023;14(1):5384. doi:10.1038/s41467-023-41042-x

Gastrointestinal

20. Lemons JMS, Conrad M, Tanes C, et al. Enterobacteriaceae Growth Promotion by Intestinal Acylcarnitines, a Biomarker of Dysbiosis in Inflammatory Bowel Disease. Cellular and Molecular Gastroenterology and Hepatology. 2023/09/20/ 2023;doi:https://doi.org/10.1016/j.jcmgh.2023.09.005
21. Raygoza Garay JA, Turpin W, Lee S-H, et al. Gut Microbiome Composition Is Associated With Future Onset of Crohn’s Disease in Healthy First-Degree Relatives. Gastroenterology. 2023/09/01/ 2023;165(3):670-681. doi:https://doi.org/10.1053/j.gastro.2023.05.032

Inflammation

22. Balakrishnan B, Luckey D, Wright K, Davis JM, Chen J, Taneja V. Eggerthella lenta augments preclinical autoantibody production and metabolic shift mimicking senescence in arthritis. Science Advances. 9(35):eadg1129. doi:10.1126/sciadv.adg1129

Kidney

23. Kang J, Guo X, Peng H, et al. Metabolic implications of amino acid metabolites in chronic kidney disease progression: a metabolomics analysis using OPLS-DA and MBRole2.0 database. International Urology and Nephrology. 2023/09/20 2023;doi:10.1007/s11255-023-03779-8

Multiomics/GWAS

24. Erwin S, Fletcher JR, Sweeney DC, et al. Distilling Mechanistic Models From Multi-Omics Data. bioRxiv. 2023:2023.09.06.556597. doi:10.1101/2023.09.06.556597
25. Alenbawi J, Al-Sarraj YA, Umlai UI, et al. Genome-Wide Association Study and Meta-Analysis of Phytosterols Identifies a Novel Locus for Serum Levels of Campesterol. medRxiv. 2023:2023.09.06.23295162. doi:10.1101/2023.09.06.23295162
26. Yousri NA, Albagha OME, Hunt SC. Integrated epigenome, whole genome sequence and metabolome analyses identify novel multi-omics pathways in type 2 diabetes: a Middle Eastern study. BMC Medicine. 2023/09/08 2023;21(1):347. doi:10.1186/s12916-023-03027-x
27. Schweickart A, Chetnik K, Batra R, et al. AutoFocus: A hierarchical framework to explore multi-omic disease associations spanning multiple scales of biomolecular interaction. bioRxiv. 2023:2023.09.06.556542. doi:10.1101/2023.09.06.556542 

Neuroscience

28. Rechtzigel MJ, Lee B, Neville C, et al. Longitudinal Deep Multi-Omics Profiling in a CLN3Δex7/8 Minipig Model Reveals Novel Biomarker Signatures for Batten Disease. bioRxiv. 2023:2023.09.20.558629. doi:10.1101/2023.09.20.558629
29. Vergnes L, Foucaud B, Cepeda C, Espinosa-Jeffrey A. Metabolomics Profile of the Secretome of Space-Flown Oligodendrocytes. Cells. 2023; 12(18):2249. https://doi.org/10.3390/cells12182249
30. Xia Y, Xiao Y, Wang Z-H, et al. Bacteroides Fragilis in the gut microbiomes of Alzheimer’s disease activates microglia and triggers pathogenesis in neuronal C/EBPβ transgenic mice. Nature Communications. 2023/09/06 2023;14(1):5471. doi:10.1038/s41467-023-41283-w
31. Jansen R, Milaneschi Y, Schranner D, et al. The Metabolome-Wide Signature of Major Depressive Disorder. Research Square. 21 September 2023, PREPRINT (Version 1) doi:10.21203/rs.3.rs-3127544/v1
32. Jimenez-Blasco D, Agulla J, Lapresa R, et al. Weak neuronal glycolysis sustains cognition and organismal fitness. bioRxiv. 2023:2023.09.02.556016. doi:10.1101/2023.09.02.556016
33. Jackson TW, House JS, Henriquez AR, et al. Multi-tissue transcriptomic and serum metabolomic assessment reveals systemic implications of acute ozone-induced stress response in male Wistar Kyoto rats. Metabolomics. 2023/09/10 2023;19(9):81. doi:10.1007/s11306-023-02043-5
34. Toriumi K, Iino K, Ozawa A, et al. Glucuronic acid is a novel source of pentosidine, associated with schizophrenia. Redox Biology. 2023/11/01/ 2023;67:102876. doi:https://doi.org/10.1016/j.redox.2023.102876 

Veterinary and Animal Health

35. Lin J, Min R, Yi X, Zhuang Y. Overexpression of glutathione synthetase gene improving redox homeostasis and chicken infectious bursal disease virus propagation in chicken embryo fibroblast DF-1. Bioresources and Bioprocessing. 2023/09/09 2023;10(1):60. doi:10.1186/s40643-023-00665-0

Other

36. Bagheri M, Bombin A, Shi M, et al. Genotype-based “virtual” metabolomics in a clinical biobank identifies novel metabolite-disease associations. Research Square. 12 October 2023, PREPRINT (Version 2). doi:10.21203/rs.3.rs-3222588/v2