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Live Webinar: The Molecular Human—Integrating Metabolomics in the Multi-Omics Era

Event Details

Event Date: November 30, 2023
Time: 9am – 10:15am ET

Speakers

Presenter: Dr. Anna Halama, Ph.D.
Host: Dr. Natasa Giallourou, Ph.D.

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The multi-disciplined field of biochemistry is rapidly evolving: Life scientists, food scientists, and pharmaceutical scientists are all pursuing new answers to complex problems, and integrative omics (multi-omics) with metabolomics is now critical to novel biological discovery.

Join Dr. Anna (Ania) Halama, Assistant Professor of Research in Physiology and Biophysics at Weill Cornell Medicine-Qatar, as she explores the relationship of different, integrated omics data to further understand human biology. Dr. Halama will demonstrate how longitudinal phenotyping can be used as foundational reference data when observing complex physiological processes, and how to best interpret multi-omics data, using different technologies to derive actionable insights for new scientific discoveries and functional outcomes.

During this webinar, you will learn:

  • How metabolomics can be used to assess medication usage in biobank studies with Qatar BioBank as an example
  • How deep phenotyping can significantly advance our understanding of human health and disease
  • Recommendations for integrating different technologies and data within a single study
  • The functional power of phenotypic datasets

About Metabolomics

Metabolomics is an integral component of multi-omics research. The detection, identification, and quantification of metabolites present in a biological system provides a functional snapshot—helpful when exploring health and disease and identifying predictive biomarkers for future conditions. In the context of multi-omics, metabolomics plays a pivotal role by providing valuable insights into the downstream products of cellular processes. It offers a real-time snapshot of an organism’s metabolic state, revealing the end result of gene expression, protein activity, and environmental influences. By integrating metabolomics data with genomics, transcriptomics, proteomics, and other omics disciplines, researchers can unravel intricate relationships between genes, proteins, and metabolites, enabling a more holistic and systems-level understanding of complex biological phenomena, such as disease mechanisms, drug responses, and environmental interactions.

Speakers

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Dr. Anna Halama, Ph.D.

Anna Halama received her Ph.D. from the Technical University of Munich (TUM) in Germany in 2013, where she obtained in-depth knowledge and skills in the field of metabolomics. She joined Weill Cornell Medicine Qatar (WCM-Q) in 2013 as a postdoctoral fellow in Prof. Karsten Suhre’s group and continued her career development at WCM-Q as a research associate, a position she held from 2016 to 2019. In this period, she conducted her own research in the field of metabolism and supported fellow scientists in the design of metabolomics-based experiments and analysis of metabolomics data.

Dr. Halama became an Assistant Professor of Research in Physiology and Biophysics at WCM-Q in April 2019. Her research focuses on metabolic deregulations in complex diseases, particularly cancer and diabetes. Dr. Halama is focused on the implementation of metabolomics along with other omics into the clinical pipeline. She is conducting research aiming to determine so-called “metabolic knobs” which could be used as targets for medical intervention.

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Dr. Natasa Giallourou, Ph.D.

Dr. Natasa Giallourou is a Field Metabolomics Scientist supporting Metabolon’s International Business activities. She provides scientific counsel for metabolomics applications in the biopharma and academic sectors. Natasa obtained her Ph.D. in Metabolomics from the University of Reading and holds an M.Sc. in Nutrition and Health from Wageningen University and a B.Sc. in Biology from the University of Leeds.

Prior to joining Metabolon, Natasa served as a Marie Skłodowska-Curie Postdoctoral Fellow at biobank.cy. Her research projects involved integrating metabolomic data with other omics data in population-based studies, with a focus on identifying biomarkers for complex diseases. She has also worked as a postdoctoral research associate at Imperial College London, where she specialized in utilizing metabolic phenotyping to address global health challenges, particularly in the field of public health nutrition.

Natasa sits on the Board of Directors of the International Metabolomics Society and is also an advisor to the Early-career Member’s Network for young metabolomics scientists.

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References

1. Zgoda-Pols, J.R., et al., Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: investigation of nicotinic acid receptor agonists. Toxicol Appl Pharmacol, 2011. 255(1): p. 48-56.

2. Bryant, J.A., et al., The impact of an oral purified microbiome therapeutic on the gastrointestinal microbiome. Nat Med, 2026. 32(1): p. 186-196

3. McGovern, B .H., et al., SER-109, an Investigational Microbiome Drugto Reduce Recurrence After Clostridioides difficile Infection: Lessons Learned From a Phase 2 Trial. Clin Infect Dis, 2021. 72(12): p. 2132-2140.

4. Feuerstadt, P., et al., SER-109, an Oral Microbiome Therapy for Recurrent Clostridioides difficile Infection. N Engl J Med, 2022. 386(3): p. 220-229.

5. Hu, Z., et al., Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer. Mol Oncol, 2025. 19(6): p. 1737-1750.

6. Butler, F.M., et al., Vegetarian Dietary Patterns and Diet-Related Metabolites Are Associated With Kidney Function in the Adventist Health Study-2 Cohort. J Ren Nutr, 2025.

7. Stanford, J., et al., Metabolomic Profiling and Diet Quality Scoring in a Randomized Crossover Trial of Healthy and Typical Dietary Patterns. Mol Nutr Food Res, 2025 . 69(23): p. e70271.

8. O’Connor, L.E., et al., Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial. J Nutr, 2023. 153(8): p. 2181-2192.

9. Fritsch, D.A., et al., Microbiome function underpins the efficacy of a fiber-supplemented dietary intervention in dogs with chronic large bowel diarrhea. BMC Vet Res, 2022. 18(1): p. 245.

10. Leal, L.N., et al., Preweaning nutrient supply improves lactation productivity and reduces the risk of culling in Holstein cows. J Dairy Sci, 2025. 108(6): p. 5875-5888.

11. Ahsin, M., et al., Soil and pasture health underlie improved beef nutrient density determined by untargeted metabolomics in Southern US grass finished beef systems. NPJ Sci Food, 2025. 9(1): p. 151.

12. Yin, W., et al., Plasma lipid profiling across species for the identification of optimal animal models of human dyslipidemia. J Lipid Res, 2012. 53(1): p. 51-65.

13. Porter, F .D., et al., Cholesterol oxidation products are sensitive and specific blood-based biomarkers for Niemann-Pick C1 disease. Sci Transl Med, 2010. 2(56): p. 56ra81.

14. Needham, B .D., et al., Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder. Biol Psychiatry, 2021. 89(5): p. 451-462

15. Li, C., et al., Estradiol and mTORC2 cooperate to enhance prostaglandin biosynthesis and tumorigenesis in TSC2-deficient LAM cells. J Exp Med, 2014. 211(1): p. 15-28.

16. Green, P.G., et al., Metabolic flexibility and reverse remodelling of the failing human heart. Eur Heart J, 2025. 46(25): p. 2422-2433.

17. Maekawa, H., et al., SGLT2 inhibition protects kidney function by SAM-dependent epigenetic repression of inflammatory genes under metabolic stress. J Clin Invest, 2025. 135(19).

18. Wu, D., et al., Integrated screens reveal that guanine nucleotide depletion, which is irreversible via targeting IMPDH2, inhibits pancreatic cancer and potentiates KRAS inhibition. Gut, 2026.

19. Schwerdtfeger, L.A., et al., Gut microbiota and metabolites are linked to disease progression in multiple sclerosis. Cell Rep Med, 2025. 6(4): p. 102055.

20. Wu, H., et al., Microbiome-metabolome dynamics associated with impaired glucose control and responses to lifestyle changes. Nat Med, 2025. 31(7): p. 2222-2231.

21. Jacobs, J.P., et al., Cognitive behavioral therapy for irritable bowel syndrome induces bidirectional alterations in the brain-gut-microbiome axis associated with gastrointestinal symptom improvement. Microbiome, 2021. 9(1): p. 236.

22. Pietzner, M., et al., Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nat Med, 2021. 27(3): p. 471-479.

23. Faquih, T.O., et al., Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites. J Gerontol A Biol Sci Med Sci, 2025. 80(3).

24. Scherer, N., et al., Coupling metabolomics and exome sequencing reveals graded effects of rare damaging heterozygous variants on gene function and human traits. Nat Genet, 2025. 57(1): p. 193-205.

25. Holmes, Z.C., et al., Untargeted metabolomic analysis of human milk from healthy mothers reveals drivers of metabolite variability. Sci Rep, 2024. 14(1): p. 20827.

26. Titz, B., et al., Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases. Transl Vis Sci Technol, 2024. 13(6): p. 17.

27. Bloom, S.M., et al., Cysteine dependence of Lactobacillus iners is a potential therapeutic target for vaginal microbiota modulation. Nat Microbiol, 2022. 7(3): p. 434-450.

28. Leimer, E.M., et al., Lipid profile of human synovial fluid following intra-articular ankle fracture. J Orthop Res, 2017. 35(3): p. 657-666.