Plasma high-resolution metabolomics identifies linoleic acid and linked metabolic pathways associated with bone mineral density. Issue 2 (February 2021)

• Record Type: Journal Article
• Authors: Bellissimo, Moriah P.; Ziegler, Thomas R.; Jones, Dean P.; Liu, Ken H.; Fernandes, Jolyn; Roberts, Joseph L.; Weitzmann, M. Neale; Pacifici, Roberto; Alvarez, Jessica A.
• Is Part Of: Clinical nutrition. Volume 40:Issue 2(2021)
• Page Start: 467
• Page End: 475
• Publication Date: 2021-02
• Subjects: Inflammation -- Nutrition -- Omega-6 -- Fats -- PUFA -- Skeletal health; BMD bone mineral density -- HRM high-resolution metabolomics -- BMI body mass index -- ARA arachidonic acid -- n-6 omega-6 -- n-3 omega-3 -- PUFA polyunsaturated fatty acid -- DHA docosahexaenoic acid -- EPA eicosapentaenoic acid; Critically ill -- Nutrition -- Periodicals; Diet therapy -- Periodicals; Parenteral feeding -- Periodicals; Enteral feeding -- Periodicals; Enteral Nutrition -- Periodicals; Parenteral Nutrition -- Periodicals; Metabolism -- Periodicals; Diétothérapie -- Périodiques; Alimentation parentérale -- Périodiques; Alimentation entérale -- Périodiques; Nutrition -- Périodiques; Diet therapy; Enteral feeding; Nutrition; Parenteral feeding; Electronic journals; Periodicals; Electronic journals; 615.854
• DOI: 10.1016/j.clnu.2020.05.041
• Languages: English
• ISSNs: 0261-5614

Abstract

Summary: Background & aims: There is a considerable degree of variation in bone mineral density (BMD) within populations. Use of plasma metabolomics may provide insight into established and novel determinants of BMD variance, such as nutrition and gut microbiome composition, to inform future prevention and treatment strategies for loss of BMD. Using high-resolution metabolomics (HRM), we examined low-molecular weight plasma metabolites and nutrition-related metabolic pathways associated with BMD. Methods: This cross-sectional study included 179 adults (mean age 49.5 ± 10.3 yr, 64% female). Fasting plasma was analyzed using ultra-high-resolution mass spectrometry with liquid chromatography. Whole body and spine BMD were assessed by dual energy X-ray absorptiometry and expressed as BMD (g/cm 2 ) or Z-scores. Multiple linear regression, pathway enrichment, and module analyses were used to determine key plasma metabolic features associated with bone density. Results: Of 10, 210 total detected metabolic features, whole body BMD Z-score was associated with 710 metabolites, which were significantly enriched in seven metabolic pathways, including linoleic acid, fatty acid activation and biosynthesis, and glycerophospholipid metabolism. Spine BMD was associated with 970 metabolites, significantly enriched in pro-inflammatory pathways involved in prostaglandin formation and linoleic acid metabolism. In module analyses, tryptophan- and polyamine-derived metabolites formed a network that was significantly associated with spine BMD, supporting a link with the gut microbiome. Conclusions: Plasma HRM provides comprehensive information relevant to nutrition and components of the microbiome that influence bone health. This data supports pro-inflammatory fatty acids and the gut microbiome as novel regulators of postnatal bone remodeling. Highlights: A variety of modifiable factors, including diet, influence bone health. Metabolomics is a novel tool to explore factors related to bone health. Plasma linoleic acid and oxidized metabolites were inversely related to bone density. Gut microbiome-related metabolites were also associated with bone density. Metabolomics is a valuable method for examining regulators of bone metabolism.