Sridevi Krishnan, MSc, PhD
EDUCATION & PROFESSIONAL TRAINING
- Biomedical Scientist Career Development Fellow. University of California San Diego, CA
- Postdoctoral Fellow. Texas Tech University, Lubbock, TX & University of California Davis, CA
- PhD, Nutritional Biology. University of California Davis, Davis CA
- MSc, Food Science and Nutrition. University of Madras, Chennai, India
- RD – Sundaram Medical Foundation, Chennai, India.
- BSc, Food Service Management, Nutrition, and Dietetics. University of Madras, Chennai, India
RESEARCH & INTERESTS
Our lab investigates how diet interacts with biology to shape metabolic health and healthy aging. We combine nutritional biology, glycobiology, multi-omics, and artificial intelligence to study cardiometabolic (type 2 diabetes, insulin resistance, inflammation, cardiovascular) and age-related diseases. Our work ranges from identifying glycan biomarkers and testing dietary and microbiome-directed interventions to developing transparent, evidence-grounded Food-is-Medicine tools. Through clinical, computational, and community-engaged research, we focus on translating nutrition science into precise, practical, and effective strategies for improving health.
Lab research outline
- Nutrition, metabolism, and healthy aging
- Dietary interventions, caloric restriction, and weight-loss maintenance
- Insulin resistance, type 2 diabetes, metabolic syndrome, and cardiometabolic health
- Glycobiology and biomarker discovery
- Plasma and immunoglobulin glycosylation
- Glycan markers of biological aging, inflammation, and proteostasis
- On going projects in AGP1 and CALERIE2 studies (CALERIE2 investigator)
- Genetic determinants of glycosylation and glucose metabolism
- Ongoing PRS-diet link projects in Ola (HCHS study) and CD-DOM (El Banco study) cohorts.
- Immune glycome and Aging – 2-sample MR
- HILIC-UHPLC-FLD glycomic methods and quality-control workflows
- Ongoing lab protocols (see lab video for further details)
- Precision nutrition and multi-omics
- Integration of dietary, clinical, genomic, glycomic, lipidomic, and metabolomic data including network and machine-learning approaches for identifying metabolic phenotypes
- Ongoing follow-up from DGA study
- Integration of dietary, clinical, genomic, glycomic, lipidomic, and metabolomic data including network and machine-learning approaches for identifying metabolic phenotypes
- Microbiome-directed nutrition
- Probiotic and synbiotic interventions
- Coming soon - study in adults with type 2 diabetes
- Probiotic and synbiotic interventions
- AI-enabled Food-is-Medicine
- Chatbots to augment EFNEP and DSMES programs
- OpenFIM tools for personalized, culturally relevant nutrition guidance, including evidence-grounded RAG systems, benchmark datasets, safety controls, and transparent provenance
- Open-FIM link (website)
- Integration of dietary recalls, health needs, food access, budget, and cooking resources
- US installation of the Intake24 tool– contact to collaborate.
- Food composition and nutrition-data infrastructure
- Studying nutrient variability within foods - tools for communicating uncertainty in food-composition data
- Foundation Foods database explorer – Coming soon!
- Studying nutrient variability within foods - tools for communicating uncertainty in food-composition data
SELECTED PUBLICATIONS
Yujie Zhang, Sridevi Krishnan, Bokan Bao, Austin WT Chiang, James T Sorrentino, Song-Min Schinn, Benjamin P Kellman, Nathan E Lewis Preparing glycomics data for robust statistical analysis with GlyCompareCT. STAR protocols 4 (2), 102162 2022
John W. Newman, Sridevi Krishnan, Kamil Borkowski, Sean H. Adams, Charles B. Stephensen, and Nancy L. Keim. Assessing insulin sensitivity and postprandial triglyceridemic response phenotypes with a mixed macronutrient challenge. Frontiers in Nutrition 2022.
Tyler Kim, Yixuan Xie, Qiongyu Li, Virginia M. Artegoitia, Carlito Lebrilla, Nancy L Keim, Sean H Adams, Sridevi Krishnan. Diet affects glycosylation of serum proteins in women at risk for cardiometabolic disease. European Journal of Nutrition, doi.org/10.1007/s00394-021-02539-7; 2021.
Sridevi Krishnan and Giri P Krishnan. N-glycosylation network construction and analysis to modify glycans on the spike S glycoprotein of SARS-CoV-2. Frontiers in Bioinformatics, doi: 10.3389/find.2021.667012; 2021
Sridevi Krishnan and Ramyaa Ramyaa, When Two Heads Are Better Than One: Nutritional Epidemiology Meets Machine Learning, Volume 111, Issue 6, June 2020, Pages 1124–1126, https://doi.org/10.1093/ajcn/nqaa113. Invited editorial to the American Journal of Clinical Nutrition,
Ramyaa Ramyaa, Omid Husseini, Giri P Krishnan, and Sridevi Krishnan. Phenotyping women based on dietary macronutrients, physical activity, and body weight using machine-learning tools. Nutrients, July 22nd, 11(7)- 1682, 2019
Sridevi Krishnan, Sean H Adams, Lindsay H Allen, Kevin D Laugero, John W Newman, Charles B Stephensen, Dustin J Burnett, Megan Witbracht, Lucas C Welch, Excel S Que, Nancy L Keim. A Controlled Feeding Trial Based on the Dietary Guidelines for Americans on Cardiometabolic Health Indices. American Journal of Clinical Nutrition, August 1 108(2):266-278; 2018
Sridevi Krishnan, Michiko Shimoda, Romina Sacchi, John K. Muchena, Guillaume Luxardi, George A. Kaysen, Atul N. Parikh, Viviane N Ngassam, Kirsten Johansen, Glenn Chertow, Barbara Grimes, Jennifer T. Smilowitz, Emanual Maverakis, Carlito B. Lebrilla, Angela M. Zivkovic. HDL Glycoprotein Composition and Site-Specific Glycosylation Differentiates Between Clinical Groups and Affects IL-6 Secretion in Lipopolysaccharide-Stimulated Monocytes. Scientific Reports, Mar 13;7:43728; 2017
Sridevi Krishnan, Jincui Huang, Andres Guerrero, Carlito B Lebrilla, Lars Berglund, Anuurad Erdembileg and Angela M Zivkovic. HDL Proteome and Glycome Profiling: Development of Novel Markers for Coronary Artery Disease Risk. Journal of Proteomics Research, 14 (12), pp 5109–5118, 2015