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Multi-dimensional characterization of prediabetes in the Project Baseline Health Study

BACKGROUND: We examined multi-dimensional clinical and laboratory data in participants with normoglycemia, prediabetes, and diabetes to identify characteristics of prediabetes and predictors of progression from prediabetes to diabetes or reversion to no diabetes. METHODS: The Project Baseline Health...

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Autores principales: Chatterjee, Ranee, Kwee, Lydia Coulter, Pagidipati, Neha, Koweek, Lynne H., Mettu, Priyatham S., Haddad, Francois, Maron, David J., Rodriguez, Fatima, Mega, Jessica L., Hernandez, Adrian, Mahaffey, Kenneth, Palaniappan, Latha, Shah, Svati H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295520/
https://www.ncbi.nlm.nih.gov/pubmed/35850765
http://dx.doi.org/10.1186/s12933-022-01565-x
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author Chatterjee, Ranee
Kwee, Lydia Coulter
Pagidipati, Neha
Koweek, Lynne H.
Mettu, Priyatham S.
Haddad, Francois
Maron, David J.
Rodriguez, Fatima
Mega, Jessica L.
Hernandez, Adrian
Mahaffey, Kenneth
Palaniappan, Latha
Shah, Svati H.
author_facet Chatterjee, Ranee
Kwee, Lydia Coulter
Pagidipati, Neha
Koweek, Lynne H.
Mettu, Priyatham S.
Haddad, Francois
Maron, David J.
Rodriguez, Fatima
Mega, Jessica L.
Hernandez, Adrian
Mahaffey, Kenneth
Palaniappan, Latha
Shah, Svati H.
author_sort Chatterjee, Ranee
collection PubMed
description BACKGROUND: We examined multi-dimensional clinical and laboratory data in participants with normoglycemia, prediabetes, and diabetes to identify characteristics of prediabetes and predictors of progression from prediabetes to diabetes or reversion to no diabetes. METHODS: The Project Baseline Health Study (PBHS) is a multi-site prospective cohort study of 2502 adults that conducted deep clinical phenotyping through imaging, laboratory tests, clinical assessments, medical history, personal devices, and surveys. Participants were classified by diabetes status (diabetes [DM], prediabetes [preDM], or no diabetes [noDM]) at each visit based on glucose, HbA1c, medications, and self-report. Principal component analysis (PCA) was performed to create factors that were compared across groups cross-sectionally using linear models. Logistic regression was used to identify factors associated with progression from preDM to DM and for reversion from preDM to noDM. RESULTS: At enrollment, 1605 participants had noDM; 544 had preDM; and 352 had DM. Over 4 years of follow-up, 52 participants with preDM developed DM and 153 participants reverted to noDM. PCA identified 33 factors composed of clusters of clinical variables; these were tested along with eight individual variables identified a priori as being of interest. Six PCA factors and six a priori variables significantly differed between noDM and both preDM and DM after false discovery rate adjustment for multiple comparisons (q < 0.05). Of these, two factors (one comprising glucose measures and one of anthropometry and physical function) demonstrated monotonic/graded relationships across the groups, as did three a priori variables: ASCVD risk, coronary artery calcium, and triglycerides (q < 10(–21) for all). Four factors were significantly different between preDM and noDM, but concordant or similar between DM and preDM: red blood cell indices (q = 8 × 10(-10)), lung function (q = 2 × 10(-6)), risks of chronic diseases (q = 7 × 10(-4)), and cardiac function (q = 0.001), along with a priori variables of diastolic function (q = 1 × 10(-10)), sleep efficiency (q = 9 × 10(-6)) and sleep time (q = 6 × 10(-5)). Two factors were associated with progression from prediabetes to DM: anthropometry and physical function (OR [95% CI]: 0.6 [0.5, 0.9], q = 0.04), and heart failure and c-reactive protein (OR [95% CI]: 1.4 [1.1, 1.7], q = 0.02). The anthropometry and physical function factor was also associated with reversion from prediabetes to noDM: (OR [95% CI]: 1.9 [1.4, 2.7], q = 0.02) along with a factor of white blood cell indices (OR [95% CI]: 0.6 [0.4, 0.8], q = 0.02), and the a priori variables ASCVD risk score (OR [95% CI]: 0.7 [0.6, 0.9] for each 0.1 increase in ASCVD score, q = 0.02) and triglycerides (OR [95% CI]: 0.9 [0.8, 1.0] for each 25 mg/dl increase, q = 0.05). CONCLUSIONS: PBHS participants with preDM demonstrated pathophysiologic changes in cardiac, pulmonary, and hematology measures and declines in physical function and sleep measures that precede DM; some changes predicted an increased risk of progression to DM. A factor with measures of anthropometry and physical function was the most important factor associated with progression to DM and reversion to noDM. Future studies may determine whether these changes elucidate pathways of progression to DM and related complications and whether they can be used to identify individuals at higher risk of progression to DM for targeted preventive interventions. Trial registration ClinicalTrials.gov NCT03154346 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-022-01565-x.
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spelling pubmed-92955202022-07-20 Multi-dimensional characterization of prediabetes in the Project Baseline Health Study Chatterjee, Ranee Kwee, Lydia Coulter Pagidipati, Neha Koweek, Lynne H. Mettu, Priyatham S. Haddad, Francois Maron, David J. Rodriguez, Fatima Mega, Jessica L. Hernandez, Adrian Mahaffey, Kenneth Palaniappan, Latha Shah, Svati H. Cardiovasc Diabetol Research BACKGROUND: We examined multi-dimensional clinical and laboratory data in participants with normoglycemia, prediabetes, and diabetes to identify characteristics of prediabetes and predictors of progression from prediabetes to diabetes or reversion to no diabetes. METHODS: The Project Baseline Health Study (PBHS) is a multi-site prospective cohort study of 2502 adults that conducted deep clinical phenotyping through imaging, laboratory tests, clinical assessments, medical history, personal devices, and surveys. Participants were classified by diabetes status (diabetes [DM], prediabetes [preDM], or no diabetes [noDM]) at each visit based on glucose, HbA1c, medications, and self-report. Principal component analysis (PCA) was performed to create factors that were compared across groups cross-sectionally using linear models. Logistic regression was used to identify factors associated with progression from preDM to DM and for reversion from preDM to noDM. RESULTS: At enrollment, 1605 participants had noDM; 544 had preDM; and 352 had DM. Over 4 years of follow-up, 52 participants with preDM developed DM and 153 participants reverted to noDM. PCA identified 33 factors composed of clusters of clinical variables; these were tested along with eight individual variables identified a priori as being of interest. Six PCA factors and six a priori variables significantly differed between noDM and both preDM and DM after false discovery rate adjustment for multiple comparisons (q < 0.05). Of these, two factors (one comprising glucose measures and one of anthropometry and physical function) demonstrated monotonic/graded relationships across the groups, as did three a priori variables: ASCVD risk, coronary artery calcium, and triglycerides (q < 10(–21) for all). Four factors were significantly different between preDM and noDM, but concordant or similar between DM and preDM: red blood cell indices (q = 8 × 10(-10)), lung function (q = 2 × 10(-6)), risks of chronic diseases (q = 7 × 10(-4)), and cardiac function (q = 0.001), along with a priori variables of diastolic function (q = 1 × 10(-10)), sleep efficiency (q = 9 × 10(-6)) and sleep time (q = 6 × 10(-5)). Two factors were associated with progression from prediabetes to DM: anthropometry and physical function (OR [95% CI]: 0.6 [0.5, 0.9], q = 0.04), and heart failure and c-reactive protein (OR [95% CI]: 1.4 [1.1, 1.7], q = 0.02). The anthropometry and physical function factor was also associated with reversion from prediabetes to noDM: (OR [95% CI]: 1.9 [1.4, 2.7], q = 0.02) along with a factor of white blood cell indices (OR [95% CI]: 0.6 [0.4, 0.8], q = 0.02), and the a priori variables ASCVD risk score (OR [95% CI]: 0.7 [0.6, 0.9] for each 0.1 increase in ASCVD score, q = 0.02) and triglycerides (OR [95% CI]: 0.9 [0.8, 1.0] for each 25 mg/dl increase, q = 0.05). CONCLUSIONS: PBHS participants with preDM demonstrated pathophysiologic changes in cardiac, pulmonary, and hematology measures and declines in physical function and sleep measures that precede DM; some changes predicted an increased risk of progression to DM. A factor with measures of anthropometry and physical function was the most important factor associated with progression to DM and reversion to noDM. Future studies may determine whether these changes elucidate pathways of progression to DM and related complications and whether they can be used to identify individuals at higher risk of progression to DM for targeted preventive interventions. Trial registration ClinicalTrials.gov NCT03154346 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-022-01565-x. BioMed Central 2022-07-18 /pmc/articles/PMC9295520/ /pubmed/35850765 http://dx.doi.org/10.1186/s12933-022-01565-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chatterjee, Ranee
Kwee, Lydia Coulter
Pagidipati, Neha
Koweek, Lynne H.
Mettu, Priyatham S.
Haddad, Francois
Maron, David J.
Rodriguez, Fatima
Mega, Jessica L.
Hernandez, Adrian
Mahaffey, Kenneth
Palaniappan, Latha
Shah, Svati H.
Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title_full Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title_fullStr Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title_full_unstemmed Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title_short Multi-dimensional characterization of prediabetes in the Project Baseline Health Study
title_sort multi-dimensional characterization of prediabetes in the project baseline health study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9295520/
https://www.ncbi.nlm.nih.gov/pubmed/35850765
http://dx.doi.org/10.1186/s12933-022-01565-x
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