Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults

Danielle E Haslam; Liming Liang; Kai Guo; Marijulie Martínez-Lozano; Cynthia M Pérez; Chih-Hao Lee; Evangelia Morou-Bermudez; Clary Clish; David T W Wong; JoAnn E Manson; Frank B Hu; Meir J Stampfer; Kaumudi Joshipura; Shilpa N Bhupathiraju

doi:10.1007/s00125-024-06169-6

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults

Diabetologia. 2024 May 21. doi: 10.1007/s00125-024-06169-6. Online ahead of print.

Authors

Danielle E Haslam^{1

2}, Liming Liang^{3

4}, Kai Guo⁵, Marijulie Martínez-Lozano⁵, Cynthia M Pérez⁶, Chih-Hao Lee⁷, Evangelia Morou-Bermudez⁸, Clary Clish⁹, David T W Wong¹⁰, JoAnn E Manson^{1

3

11}, Frank B Hu^{1

2

3}, Meir J Stampfer^{1

2

3}, Kaumudi Joshipura^{3

5}, Shilpa N Bhupathiraju^{12

13}

Affiliations

¹ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
² Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
³ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁵ Center for Clinical Research and Health Promotion, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico.
⁶ Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico.
⁷ Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁸ School of Dental Medicine, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico.
⁹ Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
¹⁰ Center for Oral/Head and Neck Oncology Research, School of Dentistry, University of California Los Angeles, Los Angeles, CA, USA.
¹¹ Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹² Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. nhsnb@channing.harvard.edu.
¹³ Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. nhsnb@channing.harvard.edu.

PMID: 38772919
DOI: 10.1007/s00125-024-06169-6

Abstract

Aims/hypothesis: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites.

Methods: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA_1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors.

Results: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures.

Conclusions/interpretation: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Keywords: Epidemiology; Insulin sensitivity and resistance; Metabolomics; Prediction and prevention of type 2 diabetes.

Abstract

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