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脂质与补体蛋白之间的相互作用——多组学数据整合如何助力揭示年龄相关性黄斑变性的病理生理学:一项概念验证研究

Interplay between Lipids and Complement Proteins-How Multiomics Data Integration Can Help Unravel Age-related Macular Degeneration Pathophysiology: A Proof-of-concept Study.

作者信息

Nusinovici Simon, Zhou Lei, Raghavan Lavanya, Tham Yih Chung, Li Hengtong, Cheung Danny, Wang Xiaomeng, Cheung Chui Ming Gemmy, Wong Tien Yin, Chakravarthy Usha, Cheng Ching-Yu

机构信息

Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.

Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore.

出版信息

Ophthalmol Sci. 2024 Oct 1;5(1):100629. doi: 10.1016/j.xops.2024.100629. eCollection 2025 Jan-Feb.

Abstract

OBJECTIVE

Our objectives were to identify correlation patterns between complement and lipid pathways using a multiomics data integration approach and to determine how these interconnections affect age-related macular degeneration (AMD).

DESIGN

Nested case-control study.

SUBJECTS AND CONTROLS

The analyses were performed in a subset of the Singapore Indian Eye Study. We randomly selected 155 AMD cases and age- and sex-matched them with 155 controls.

METHODS

Firstly, a multiomics data integration method was used to identify correlation patterns between the omics data. Then, we tested possible interactions between the lipids and complement proteins using logistic regression models.

MAIN OUTCOME MEASURES

Age-related macular degeneration was determined according to the Beckman classification system. We measured in serum samples 35 complement proteins and 66 lipids, and used 9 genetic variants.

RESULTS

Among the 155 AMD cases, 93 (60.0%) had early and 62 (40.0%) intermediate AMD. Firstly, we identified 2 clusters between complement proteins and lipids involving (1) mannan-binding lectin serine protease 1 and several different high-density lipoprotein particles, and (2) complement factor H-related protein 1, carboxypeptidase N subunit 2 and complement component C8 gamma chain, and sphingomyelin and different cholesterol. Secondly, we identified 1 interaction between complement protein 1R and sphingomyelin with an odds of AMD 2 times higher for individuals with low levels of sphingomyelin and complement protein 1R (odds ratio = 2.13 [1.09, 4.17]).

CONCLUSIONS

We report here, using a cutting-edge multiomics integration approach, the complex interconnections between genetic, metabolomics, and proteomic data. This method permitted us to obtain a holistic picture and identify multiomics signature of AMD pathophysiology. These results advocate for a personalized therapeutic approach that accounts for multiple pathways. However, these results need to be validated in larger studies with different ethnic groups.

FINANCIAL DISCLOSURES

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

摘要

目的

我们的目标是使用多组学数据整合方法来识别补体和脂质途径之间的关联模式,并确定这些相互联系如何影响年龄相关性黄斑变性(AMD)。

设计

巢式病例对照研究。

研究对象与对照

分析在新加坡印度人眼研究的一个子集中进行。我们随机选择了155例AMD病例,并根据年龄和性别与155名对照进行匹配。

方法

首先,使用多组学数据整合方法来识别组学数据之间的关联模式。然后,我们使用逻辑回归模型测试脂质和补体蛋白之间可能的相互作用。

主要观察指标

根据贝克曼分类系统确定年龄相关性黄斑变性。我们在血清样本中测量了35种补体蛋白和66种脂质,并使用了9个基因变体。

结果

在155例AMD病例中,93例(60.0%)为早期AMD,62例(40.0%)为中期AMD。首先,我们在补体蛋白和脂质之间识别出2个聚类,涉及(1)甘露聚糖结合凝集素丝氨酸蛋白酶1和几种不同的高密度脂蛋白颗粒,以及(2)补体因子H相关蛋白1、羧肽酶N亚基2和补体成分C8γ链,以及鞘磷脂和不同的胆固醇。其次,我们识别出补体蛋白1R和鞘磷脂之间的1种相互作用,鞘磷脂和补体蛋白1R水平低的个体患AMD的几率高出2倍(比值比 = 2.13 [1.09, 4.17])。

结论

我们在此报告,使用前沿的多组学整合方法,基因、代谢组学和蛋白质组学数据之间存在复杂的相互联系。这种方法使我们能够获得整体情况并识别AMD病理生理学的多组学特征。这些结果支持采用考虑多种途径的个性化治疗方法。然而,这些结果需要在不同种族的更大规模研究中得到验证。

财务披露

在本文末尾的脚注和披露中可能会找到专有或商业披露信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13a2/11609548/bcfca7ea5e59/gr1.jpg

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