Novel associations between inflammation-related proteins and adiposity: A targeted proteomics approach across four population-based studies.

作者
Mariana Ponce de Leon Rodriguez,Jakob Linseisen,Annette Peters,Birgit Linkohr,Margit Heier,Harald Grallert,Ben Schöttker,Kira Trares,Megha Bhardwaj,Xīn Gào,Herman Brenner,Karol Kamiński,Marlena Paniczko,Irina Kowalska,Sebastian-Edgar Baumeister,Christa Meisinger
出处
期刊:Translational Research [Elsevier BV]
标识
DOI:10.1016/j.trsl.2021.11.004
摘要

Abstract Chronic low-grade inflammation has been proposed as a linking mechanism between obesity and the development of inflammation-related conditions such as insulin resistance and cardiovascular disease. Despite major advances in the last two decades, the complex interplay between immune regulators and obesity remains poorly understood. Therefore, we aimed to identify novel inflammation-related proteins associated with adiposity. We investigated the association between BMI and waist circumference and 72 circulating inflammation-related proteins, measured using the Proximity Extension Assay (Olink Proteomics), in 3,308 participants of four independent European population-based studies (KORA-Fit, BVSII, ESTHER, and Bialystok PLUS). In addition, we used body fat mass measurements obtained by Dual-energy X-ray absorptiometry (DXA) in the Bialystok PLUS study to further validate our results and to explore the relationship between inflammation-related proteins and body fat distribution. We found 14 proteins associated with at least one measure of adiposity across all four studies, including four proteins for which the association is novel: DNER, SLAMF1, RANKL, and CSF-1. We confirmed previously reported associations with CCL19, CCL28, FGF-21, HGF, IL-10RB, IL-18, IL-18R1, IL-6, SCF, and VEGF-A. The majority of the identified inflammation-related proteins were associated with visceral fat as well as with the accumulation of adipose tissue in the abdomen and the trunk. In conclusion, our study provides new insights into the immune dysregulation observed in obesity that might help uncover pathophysiological mechanisms of disease development.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
田様的应助被asdas采纳,获得10
刚刚
梦在远方完成签到 ,获得积分10
1秒前
梦梦完成签到 ,获得积分10
1秒前
1秒前
小鱼发布了新的文献求助10
1秒前
Li完成签到 ,获得积分20
1秒前
咪不知发布了新的文献求助10
1秒前
999发布了新的文献求助10
2秒前
李春霞完成签到 ,获得积分10
2秒前
001完成签到,获得积分10
2秒前
4秒前
4秒前
A12345678完成签到,获得积分10
5秒前
千辞完成签到 ,获得积分10
5秒前
TCY发布了新的文献求助10
5秒前
6秒前
波博士完成签到,获得积分10
6秒前
liqianniu完成签到,获得积分10
6秒前
111完成签到,获得积分10
7秒前
7秒前
向柯大大完成签到,获得积分10
7秒前
9秒前
机灵的沂发布了新的文献求助10
9秒前
半夏完成签到 ,获得积分10
9秒前
如意的捕完成签到,获得积分10
10秒前
飘逸的听露完成签到 ,获得积分10
10秒前
Backkkyeom完成签到,获得积分10
11秒前
无花果的应助被咪不知采纳,获得10
12秒前
DW的应助被无理采纳,获得10
12秒前
要天天开心完成签到,获得积分10
12秒前
奕苼发布了新的文献求助10
12秒前
TX发布了新的文献求助10
13秒前
鸟不雷完成签到,获得积分20
13秒前
YY的应助被kaifangfeiyao采纳,获得10
13秒前
13秒前
Fan发布了新的文献求助30
14秒前
14秒前
14秒前
彭于晏的应助被Jack_Zhang采纳,获得10
15秒前
科目三的应助被刘陌陌采纳,获得10
16秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
The Student's Guide to Social Neuroscience 800
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Production Logging: Theoretical and Interpretive Elements 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7813440
求助须知:如何正确求助?哪些是违规求助? 9344199
关于积分的说明 20521575
捐赠科研通 7406347
什么是DOI,文献DOI怎么找? 3330447
关于科研通互助平台的介绍 2477095
邀请新用户注册赠送积分活动 2349999