Thanaj Marjola, Basty Nicolas, Cule Madeleine, Sorokin Elena P, Whitcher Brandon, Srinivasan Ramprakash, Bell Jimmy D, Thomas E Louise
Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Calico Life Sciences LLC, South San Francisco, CA, USA.
Int J Obes (Lond). 2025 Jul 9. doi: 10.1038/s41366-025-01829-y.
Three-dimensional (3D) mesh-derived phenotypes enable detailed characterisation of organ morphology and regional variation through statistical parametric maps (SPMs) and statistical shape analysis (SSA). While these techniques have been widely used for organ studies, their application to abdominal subcutaneous adipose tissue (ASAT) has been limited. This study investigates the associations between ASAT thickness, anthropometric traits, and clinical conditions, including type 2 diabetes (T2D) and hypertension.
We analysed ASAT using MRI data from 44,515 participants in the UK Biobank who underwent baseline imaging, with a subset of 3088 participants receiving a follow-up scan approximately 2 years later. ASAT thickness was quantified using 3D surface meshes. Regional associations with anthropometric and clinical variables were examined using SPMs. Additionally, principal components of ASAT thickness, derived via SSA, were analysed for their association with future cardiovascular disease (CVD) risk.
ASAT thickness was significantly associated with age, alcohol consumption, visceral fat, total muscle mass, and various health-related traits. Longitudinal analysis revealed significant changes in ASAT thickness over a 2.5-year period in both sexes, independent of disease status at baseline. Notably, regional variations in hip ASAT thickness were associated with incident CVD in women (hazard ratio [HR]: 0.90, 95% CI: 0.84-0.97, p = 0.023) and with hypertension in both women (HR: 1.10, 95% CI: 1.03-1.21, p = 0.045) and men (HR: 0.88, 95% CI: 0.82-0.96, p = 0.014).
3D quantification and morphometric analysis of ASAT offer novel insights into the associations between abdominal fat distribution, lifestyle factors, and chronic disease risk. These techniques hold promise for enhancing our understanding of fat-related disease mechanisms in population-level studies.
三维（3D）网格衍生的表型能够通过统计参数映射（SPM）和统计形状分析（SSA）对器官形态和区域差异进行详细表征。虽然这些技术已广泛应用于器官研究，但其在腹部皮下脂肪组织（ASAT）中的应用却很有限。本研究调查了ASAT厚度、人体测量学特征与临床状况之间的关联，包括2型糖尿病（T2D）和高血压。
我们使用来自英国生物银行44515名参与者的MRI数据对ASAT进行分析，这些参与者均接受了基线成像，其中3088名参与者的子集在大约2年后接受了随访扫描。使用3D表面网格对ASAT厚度进行量化。使用SPM检查与人体测量学和临床变量的区域关联。此外，通过SSA得出的ASAT厚度主成分被分析其与未来心血管疾病（CVD）风险的关联。
ASAT厚度与年龄、饮酒量、内脏脂肪、总肌肉量以及各种与健康相关的特征显著相关。纵向分析显示，在2.5年的时间里，无论男女，ASAT厚度均有显著变化，且与基线时的疾病状态无关。值得注意的是，髋部ASAT厚度的区域差异与女性的新发CVD相关（风险比[HR]：0.90，95%置信区间：0.84 - 0.97，p = 0.023），与女性（HR：1.10，95%置信区间：1.03 - 1.21，p = 0.045）和男性（HR：0.88，95%置信区间：0.82 - 0.96，p = 0.014）的高血压相关。
ASAT的3D量化和形态计量分析为腹部脂肪分布、生活方式因素和慢性病风险之间的关联提供了新的见解。这些技术有望在人群水平研究中增强我们对脂肪相关疾病机制的理解。
