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Untargeted serum metabolomic profiles and breast density in young women.
Jung, Seungyoun; Silva, Sarah; Dallal, Cher M; LeBlanc, Erin; Paris, Kenneth; Shepherd, John; Snetselaar, Linda G; Van Horn, Linda; Zhang, Yuji; Dorgan, Joanne F.
Afiliação
  • Jung S; Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, South Korea.
  • Silva S; Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, South Korea.
  • Dallal CM; University of Maryland School of Medicine, Baltimore, MD, USA.
  • LeBlanc E; Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, USA.
  • Paris K; Kaiser Permanente Center for Health Research, Portland, OR, USA.
  • Shepherd J; Department of Pediatrics, Louisiana State University School of Medicine, New Orleans, LA, USA.
  • Snetselaar LG; University of Hawaii Cancer Center, Honolulu, HI, USA.
  • Van Horn L; Department of Epidemiology, University of Iowa, Iowa City, IA, USA.
  • Zhang Y; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
  • Dorgan JF; Division of Cancer Epidemiology, Department of Epidemiology and Public Health, University of Maryland School of Medicine, 660 West Redwood St., Howard Hall, Room 102E, Baltimore, MD, 21201, USA.
Cancer Causes Control ; 35(2): 323-334, 2024 Feb.
Article em En | MEDLINE | ID: mdl-37737303
PURPOSE OF THE STUDY: Breast density is an established risk factor for breast cancer. However, little is known about metabolic influences on breast density phenotypes. We conducted untargeted serum metabolomics analyses to identify metabolic signatures associated with breast density phenotypes among young women. METHODS: In a cross-sectional study of 173 young women aged 25-29 who participated in the Dietary Intervention Study in Children 2006 Follow-up Study, 449 metabolites were measured in fasting serum samples using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable-adjusted mixed-effects linear regression identified metabolites associated with magnetic resonance imaging measured breast density phenotypes: percent dense breast volume (%DBV), absolute dense breast volume (ADBV), and absolute non-dense breast volume (ANDBV). Metabolite results were corrected for multiple comparisons using a false discovery rate adjusted p-value (q). RESULTS: The amino acids valine and leucine were significantly inversely associated with %DBV. For each 1 SD increase in valine and leucine, %DBV decreased by 20.9% (q = 0.02) and 18.4% (q = 0.04), respectively. ANDBV was significantly positively associated with 16 lipid and one amino acid metabolites, whereas no metabolites were associated with ADBV. Metabolite set enrichment analysis also revealed associations of distinct metabolic signatures with %DBV, ADBV, and ANDBV; branched chain amino acids had the strongest inverse association with %DBV (p = 0.002); whereas, diacylglycerols and phospholipids were positively associated with ANDBV (p ≤ 0.002), no significant associations were observed for ADBV. CONCLUSION: Our results suggest an inverse association of branched chain amino acids with %DBV. Larger studies in diverse populations are needed.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Densidade da Mama Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans Idioma: En Revista: Cancer Causes Control Assunto da revista: EPIDEMIOLOGIA / NEOPLASIAS Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Coréia do Sul

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Densidade da Mama Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans Idioma: En Revista: Cancer Causes Control Assunto da revista: EPIDEMIOLOGIA / NEOPLASIAS Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Coréia do Sul