<p>Obesity is a multifaceted metabolic disorder characterized by dysregulated glucose and lipid metabolism, often comorbid with conditions such as diabetes, hypertension, hyperlipidemia, cardiovascular diseases, and cancers. Due to its diverse etiological factors and inherent heterogeneity, obesity poses significant challenges for management. The advent of multiomics technologies has opened new avenues for a deeper exploration of the molecular underpinnings and clinical biomarkers of obesity, improving our ability to predict and monitor associated metabolic syndromes. However, a holistic understanding of obesity that incorporates physical fitness, living conditions, and other contributing factors remains elusive. In this review, we summarize various factors that affect the occurrence of obesity, emphasizing the diversity and complexity of obesity and its complications. We provided a detailed overview of the expression of biomarkers identified through epigenetics, transcriptomics, proteomics, metabolomics, and gut microbiome, shedding light on the latent etiological mechanisms of obesity. Additionally, we discuss the methodological landscape for data integration in multiomics research and highlight the current progress in identifying obesity biomarkers through integrative multiomics strategies. We also critically evaluate the pitfalls and limitations of current multiomics studies on obesity, emphasizing the challenges of integrating data across different omics layers and the necessity for longitudinal and population-specific studies. Furthermore, we assess the clinical applicability of obesity biomarkers, noting that although many promising biomarkers have been identified, their validation and implementation in clinical settings remain limited. These biotargets offer new directions for precision treatment of obesity, such as targeted epigenetic modifications or modulation of specific microbiome populations, which have the potential to change clinical approaches to dynamic weight management and metabolic health.</p>

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Multiomics strategy-based obesity biomarkers discovery for precision medicine

  • Zu-Wen Ye,
  • Qi-Yue Yang,
  • Wen-Ting Xu,
  • Feng-Qin Li,
  • Ping Luo,
  • Si Qin,
  • Fang Wang

摘要

Obesity is a multifaceted metabolic disorder characterized by dysregulated glucose and lipid metabolism, often comorbid with conditions such as diabetes, hypertension, hyperlipidemia, cardiovascular diseases, and cancers. Due to its diverse etiological factors and inherent heterogeneity, obesity poses significant challenges for management. The advent of multiomics technologies has opened new avenues for a deeper exploration of the molecular underpinnings and clinical biomarkers of obesity, improving our ability to predict and monitor associated metabolic syndromes. However, a holistic understanding of obesity that incorporates physical fitness, living conditions, and other contributing factors remains elusive. In this review, we summarize various factors that affect the occurrence of obesity, emphasizing the diversity and complexity of obesity and its complications. We provided a detailed overview of the expression of biomarkers identified through epigenetics, transcriptomics, proteomics, metabolomics, and gut microbiome, shedding light on the latent etiological mechanisms of obesity. Additionally, we discuss the methodological landscape for data integration in multiomics research and highlight the current progress in identifying obesity biomarkers through integrative multiomics strategies. We also critically evaluate the pitfalls and limitations of current multiomics studies on obesity, emphasizing the challenges of integrating data across different omics layers and the necessity for longitudinal and population-specific studies. Furthermore, we assess the clinical applicability of obesity biomarkers, noting that although many promising biomarkers have been identified, their validation and implementation in clinical settings remain limited. These biotargets offer new directions for precision treatment of obesity, such as targeted epigenetic modifications or modulation of specific microbiome populations, which have the potential to change clinical approaches to dynamic weight management and metabolic health.