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<p>Obesity is a major public health challenge affecting an ever-increasing proportion of the global population. It is associated with numerous comorbidities. Progressive expansion and remodeling of adipose tissue may lead to depot specific changes in adipose tissue biology and energy partitioning. Such changes likely precede the development of obesity-related complications. To facilitate a deeper understanding of adipose tissue biology, a comprehensive quantitative proteomic dataset is presented at the peptide and protein level. Data-independent acquisition LC-MS/MS data were acquired from matched subcutaneous and omental adipose tissues from metabolically healthy individuals with no comorbidities and covering a wide range of body mass indexes. Adipose tissue samples were collected during elective surgeries and immediately processed for histology or frozen until proteomic analysis. Internal and external quality control systems ensured high quality data. All data presented are available via ProteomeXchange. This dataset will allow new insights into biological changes that evolve with increasing adiposity captured before the onset of comorbidities. Matched sampling across fat depots provides an opportunity to uncover depot-specific physiological signatures.</p>

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Proteomic profiling of human omental and subcutaneous adipose tissue in individuals with a broad range of BMI

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月5日

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  • Alex Zelter,
  • Yue Winnie Wen,
  • Michael Riffle,
  • Lindsay C. Czuba,
  • Aprajita S. Yadav,
  • Jerry Zhu,
  • Jessica M. Snyder,
  • Aaron Maurais,
  • Jeffrey LaFrance,
  • Saurabh Khandelwal,
  • Judy Y. Chen,
  • Estell Williams,
  • Zoe Parr,
  • Daniel Kim,
  • Katya B. Rubinow,
  • Michael J. MacCoss,
  • Nina Isoherranen

摘要

Obesity is a major public health challenge affecting an ever-increasing proportion of the global population. It is associated with numerous comorbidities. Progressive expansion and remodeling of adipose tissue may lead to depot specific changes in adipose tissue biology and energy partitioning. Such changes likely precede the development of obesity-related complications. To facilitate a deeper understanding of adipose tissue biology, a comprehensive quantitative proteomic dataset is presented at the peptide and protein level. Data-independent acquisition LC-MS/MS data were acquired from matched subcutaneous and omental adipose tissues from metabolically healthy individuals with no comorbidities and covering a wide range of body mass indexes. Adipose tissue samples were collected during elective surgeries and immediately processed for histology or frozen until proteomic analysis. Internal and external quality control systems ensured high quality data. All data presented are available via ProteomeXchange. This dataset will allow new insights into biological changes that evolve with increasing adiposity captured before the onset of comorbidities. Matched sampling across fat depots provides an opportunity to uncover depot-specific physiological signatures.