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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.
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.
Afiliación
  • Jiang YC; Centenary Institute, The University of Sydney, Sydney, New South Wales, Australia; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
  • Lai K; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia; ANZAC Research Institute, The University of Sydney, Sydney, New South Wales, Australia.
  • Muirhead RP; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
  • Chung LH; Centenary Institute, The University of Sydney, Sydney, New South Wales, Australia; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
  • Huang Y; Centenary Institute, The University of Sydney, Sydney, New South Wales, Australia; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
  • James E; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
  • Liu XT; Centenary Institute, The University of Sydney, Sydney, New South Wales, Australia; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
  • Wu J; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; Barker College, Hornsby, New South Wales, Australia.
  • Atkinson FS; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
  • Yan S; Department of Endocrinology and Metabolism Diseases, The 4th Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Fogelholm M; Department of Food and Nutrition, University of Helsinki, Helsinki, Finland.
  • Raben A; Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark; Clinical Research, Copenhagen University Hospital-Steno Diabetes Center Copenhagen, Herlev, Denmark.
  • Don AS; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
  • Sun J; Rural Health Research Institute, Charles Sturt University, Leeds Parade, New South Wales, Australia; School of Medicine and Dentistry, Menzies Health Institute Queensland, Institute for Integrated Intelligence and Systems, Griffith University, Southport, Queensland, Australia. Electronic address: ji
  • Brand-Miller JC; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia. Electronic address: jennie.brandmiller@sydney.edu.au.
  • Qi Y; Centenary Institute, The University of Sydney, Sydney, New South Wales, Australia; Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia. Electroni
Am J Clin Nutr ; 120(4): 864-878, 2024 Oct.
Article en En | MEDLINE | ID: mdl-39182617
ABSTRACT

BACKGROUND:

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.

OBJECTIVES:

This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss.

METHODS:

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.

RESULTS:

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.

CONCLUSIONS:

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 was registered at clinicaltrials.gov as NCT01777893 (https//clinicaltrials.gov/study/NCT01777893).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Glucemia / Biomarcadores / Pérdida de Peso / Restricción Calórica / Lipidómica Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Am J Clin Nutr Año: 2024 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Glucemia / Biomarcadores / Pérdida de Peso / Restricción Calórica / Lipidómica Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Am J Clin Nutr Año: 2024 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Estados Unidos