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Assessing Obesity-Related Adipose Tissue Disease (OrAD) to Improve Precision Medicine for Patients Living With
Yair Pincu1,2,3, Uri Yoel1,4, Yulia Haim1,5
1Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University, Beer-Sheva, Israel.
Abstract:
Obesity is a heterogenous condition that affects the life and health of patients to different degrees and in different ways. Yet, most approaches to treat obesity are not currently prescribed, at least in a systematic manner, based on individual obesity sub-phenotypes or specifically-predicted health risks. Adipose tissue is one of the most evidently affected tissues in obesity. The degree of adipose tissue changes - "adiposopathy", or as we propose to relate to herein as Obesity-related Adipose tissue Disease (OrAD), correspond, at least cross-sectionally, to the extent of obesity-related complications inflicted on an individual patient. This potentially provides an opportunity to better personalize anti-obesity management by utilizing the information that can be retrieved by assessing OrAD. This review article will summarize current knowledge on histopathological OrAD features which, beyond cross-sectional analyses, had been shown to predict future obesity-related endpoints and/or the response to specific anti-obesity interventions. In particular, the review explores adipocyte cell size, adipose tissue inflammation, and fibrosis. Rather than highly-specialized methods, we emphasize standard pathology laboratory approaches to assess OrAD, which are readily-available in most clinical settings. We then discuss how OrAD assessment can be streamlined in the obesity/weight-management clinic. We propose that current studies provide sufficient evidence to inspire concerted efforts to better explore the possibility of predicting obesity related clinical endpoints and response to interventions by histological OrAD assessment, in the quest to improve precision medicine in obesity.
Insights
Obesity-related Adipose tissue Disease (OrAD) assessment using standard pathology can predict patient health risks and treatment responses. This approach offers a path toward personalized obesity management and precision medicine.
Area of Science:
- Endocrinology and Metabolic Diseases
- Pathology
- Precision Medicine
Background:
- Obesity is a complex condition with varied patient impacts, yet current treatments lack systematic personalization based on individual sub-phenotypes or predicted risks.
- Adipose tissue alterations, termed Obesity-related Adipose tissue Disease (OrAD), correlate with obesity severity and complications, presenting a potential biomarker for personalized care.
Purpose of the Study:
- To review current knowledge on histopathological features of OrAD that predict future obesity-related health outcomes and responses to anti-obesity interventions.
- To emphasize the use of standard pathology methods for assessing OrAD, making it accessible in clinical settings for personalized obesity management.
Main Methods:
- Review of existing literature on histopathological features of OrAD, including adipocyte cell size, adipose tissue inflammation, and fibrosis.
- Focus on standard pathology laboratory approaches readily available in most clinical settings.
- Discussion on streamlining OrAD assessment within obesity and weight-management clinics.
Main Results:
- Histopathological features of OrAD, such as adipocyte hypertrophy, inflammation, and fibrosis, have shown cross-sectional correlations with obesity-related complications.
- Evidence suggests these features can predict future clinical endpoints and patient responses to specific anti-obesity interventions.
- Standard pathology methods are sufficient for assessing OrAD, requiring no highly specialized techniques.
Conclusions:
- Histopathological assessment of OrAD offers a viable strategy for predicting obesity-related clinical endpoints and treatment responses.
- Integrating OrAD assessment into clinical practice can significantly advance precision medicine in obesity management.
- Further concerted efforts are needed to fully explore and validate the predictive power of OrAD assessment for personalized obesity care.
