Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy

Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impac...

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Veröffentlicht in:The American journal of clinical nutrition 2024-10, Vol.120 (4), p.864-878
Hauptverfasser: Jiang, Yingxin Celia, Lai, Kaitao, Muirhead, Roslyn Patricia, Chung, Long Hoa, Huang, Yu, James, Elizaveta, Liu, Xin Tracy, Wu, Julian, Atkinson, Fiona S, Yan, Shuang, Fogelholm, Mikael, Raben, Anne, Don, Anthony Simon, Sun, Jing, Brand-Miller, Jennie Cecile, Qi, Yanfei
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container_issue 4
container_start_page 864
container_title The American journal of clinical nutrition
container_volume 120
creator Jiang, Yingxin Celia
Lai, Kaitao
Muirhead, Roslyn Patricia
Chung, Long Hoa
Huang, Yu
James, Elizaveta
Liu, Xin Tracy
Wu, Julian
Atkinson, Fiona S
Yan, Shuang
Fogelholm, Mikael
Raben, Anne
Don, Anthony Simon
Sun, Jing
Brand-Miller, Jennie Cecile
Qi, Yanfei
description Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk. This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss. We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses. We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance. Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study w
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However, &gt;50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk. This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss. We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses. We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance. Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. 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Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. 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identifier ISSN: 0002-9165
ispartof The American journal of clinical nutrition, 2024-10, Vol.120 (4), p.864-878
issn 0002-9165
1938-3207
1938-3207
language eng
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source MEDLINE; Alma/SFX Local Collection
subjects Adult
Aged
Biomarkers
Biomarkers - blood
Blood Glucose - analysis
Blood Glucose - metabolism
Body weight
Caloric Restriction
Diabetes
Diabetes mellitus
Diabetes Mellitus, Type 2 - blood
Diet
Diglycerides
Europe
Fatty acids
Female
Health risks
Hemoglobin
Homeostasis
Humans
Insulin
Insulin resistance
Intervention
Lecithin
Life Style
Lifestyles
Lipidomics
Lipids
Lipids - blood
low-energy diet
Machine learning
Male
Middle Aged
Nutrient deficiency
Organic acids
Overweight
Overweight - blood
Overweight - diet therapy
Overweight - therapy
Parameters
Phosphatidylcholine
Phosphatidylethanolamine
Population studies
Population-based studies
prediabetes
Prediabetic State - blood
Prediabetic State - diet therapy
Prediabetic State - therapy
PREVIEW study
Serum lipids
Sphingolipids
Triglycerides
Weight Loss
title Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy
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