OP0194 COMPUTATIONAL SYSTEMS BIOLOGY APPROACH TO UNVEIL MOLECULAR INTERACTIONS IN SJÖGREN’S SYNDROME PATHOGENESIS

发病机制 计算生物学 计算机科学 系统生物学 生物 免疫学
作者
Sacha E Silva-Saffar,Jacques‐Eric Gottenberg,Stefano Bombardieri,Divi Cornec,Jacques‐Olivier Pers,Marta E. Alarcón‐Riquelme,Philippe Moingeon,M. Barnes,Shu‐Kay Ng,Wan‐Fai Ng,Xavier Mariette,Gaétane Nocturne,Anna Niarakis
出处
期刊:Annals of the Rheumatic Diseases [BMJ]
卷期号:: 43.1-43
标识
DOI:10.1136/annrheumdis-2024-eular.2526
摘要

Background:

Sjögren's disease (SjD) presents an unmet medical challenge as there is currently no cure. Despite advances in understanding the immunopathogenesis of SjD, there is still a pressing need to identify novel biomarkers and therapeutic targets, for better patient stratification and personalized treatment.

Objectives:

To create a fully-detailed molecular interaction map (MIM) including all the signalling and molecular pathways implicated in SjD pathogenesis. To create a large-scale mechanistic model to enable in silico simulations of perturbations including drug interventions, and the generation of hypothesis-driven predictions.

Methods:

Differential expression analysis was performed on blood samples from SjD patients vs controls on 3 datasets: the publicly available GSE51092 and the accessible via the NECESSITY consortium UKPSSR and PRECISEADS datasets. GSE51092 contains transcriptomic data of 190 SjD patients and 32 controls, UKPSSR of 151 SjD patients and 29 controls, and PRECISESADS, RNASeq data for 304 SjD patients and 341 controls. Pathway enrichment analysis was subsequently performed using GSEA and the Reactome pathway database[1,2]. Additional literature-based evidence was used to develop a molecular interaction map, combining the results of the previous analytical steps. The SjD specific map was then converted into a Boolean model using the CaSQ tool[3]. Logic rules based on Boolean algebra are used to describe every interaction between the molecular entities.

Results:

Our analysis unveiled a set of differentially expressed genes (DEG) and related pathways associated with immune dysregulation and inflammatory responses in SjD. We obtained a total of 1625 DEG, 725 DEG from PRECISESADS, 1161 DEG from GSE51092 and 239 DEG from UKPSSR, with 25 DEG common for all three datasets. Nine common DEG were associated with Interferon signalling. Twenty-one pathways were identified with both GSEA and Reactome-based analysis. The building of the SjD MIM was performed based on literature search and the 21 identified pathways, from the data analysis. The MIM includes so far 16 pathways (5 present in the identified pathways and 11 literature-mined), comprising 187 species (genes, RNAs proteins) and 132 reactions. The SjD-specific Boolean model obtained after conversion of the SjD MIM, represents a more compact and fully executable version of the SjD molecular network, containing 111 nodes and 130 edges. In Sjögren-specific conditions the model is able to reproduce the activation of main inflammation pathways and predict the inflammatory response.

Conclusion:

We have built the first SjD-specific MIM integrating omic data analyses and information from literature-based evidence and pathway enrichment analysis. The current SjD map contains hallmark disease pathways and is constantly being enriched with data-driven highlighted pathways. The preliminary computational model based on the SjD map is able to reproduce inflammatory response scenarios, however further training is needed to improve performance and robustness.

REFERENCES:

[1] Fabregat, A. et al. The Reactome pathway Knowledgebase. Nucleic Acids Research 44, D481–D487 (2016). [2] Subramanian, A. et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences 102, 15545–15550 (2005). [3] Aghamiri, S. S. et al. Automated inference of Boolean models from molecular interaction maps using CaSQ. Bioinformatics 36, 4473–4482 (2020).

Acknowledgements:

I express my gratitude to the NECESSITY consortium members for the materials they made available to me, which enabled me to carry out this research. I would also like to thank the doctoral school SDSV of Paris-Saclay University and Genopole for financing respectively my PhD studies and formations I followed.

Disclosure of Interests:

Sacha E Silva-Saffar: None declared, Jacques-Eric Gottenberg BMS, Pfizer, Lilly, Abbvie, AstraZeneca, Gilead, Galapagos, MSD, Roche-Chugai, Sanofi, UCB, Michele Bombardieri: None declared, Divi Cornec: None declared, Jacques-Olivier Pers: None declared, Marta Alarcon-Riquelme: None declared, Philippe MOINGEON Sanofi, Stallergenes, Servier, Michael Barnes: None declared, Sandra Ng: None declared, Wan-Fai Ng GlaxoSmithKline, MedImmune, Novartis and BMS, Abbvie, Resolves Therapeutics, Nascient, Xavier Mariette Sanofi, Servier, BMS, Gaetane Nocturne Amgen, Novartis, Anna Niarakis Sanofi.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Jasper应助抹茶味的奶酥采纳,获得10
1秒前
2秒前
酷波er应助坚强的如蓉采纳,获得10
2秒前
3秒前
3秒前
龘龘龘发布了新的文献求助10
4秒前
打打应助活泼的飞双采纳,获得10
5秒前
小巧的世倌完成签到,获得积分10
5秒前
GaoY完成签到,获得积分10
6秒前
SOBER刘晗完成签到 ,获得积分10
6秒前
Levieus完成签到,获得积分10
6秒前
6秒前
奶瓶守护者完成签到 ,获得积分10
7秒前
8秒前
花生壳完成签到,获得积分10
8秒前
乎乎发布了新的文献求助10
9秒前
科研通AI6应助yyyyy采纳,获得10
9秒前
9秒前
青年才俊发布了新的文献求助10
9秒前
9秒前
不安啤酒完成签到,获得积分20
10秒前
炼丹师应助aaaabc采纳,获得20
10秒前
seele完成签到,获得积分10
11秒前
11秒前
轻松曲奇发布了新的文献求助30
11秒前
11秒前
奶瓶守护者关注了科研通微信公众号
11秒前
满意妙梦发布了新的文献求助10
12秒前
优雅沛凝发布了新的文献求助20
13秒前
li发布了新的文献求助10
13秒前
月月完成签到,获得积分20
14秒前
李健应助kaka采纳,获得10
15秒前
15秒前
15秒前
嘚嘚发布了新的文献求助10
15秒前
16秒前
浮游应助清爽的海瑶采纳,获得10
16秒前
16秒前
瑜衡完成签到,获得积分20
16秒前
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Einführung in die Rechtsphilosophie und Rechtstheorie der Gegenwart 1500
Binary Alloy Phase Diagrams, 2nd Edition 1000
青少年心理适应性量表(APAS)使用手册 700
Air Transportation A Global Management Perspective 9th Edition 700
Socialization In The Context Of The Family: Parent-Child Interaction 600
DESIGN GUIDE FOR SHIPBOARD AIRBORNE NOISE CONTROL 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4991412
求助须知:如何正确求助?哪些是违规求助? 4239905
关于积分的说明 13208671
捐赠科研通 4034805
什么是DOI,文献DOI怎么找? 2207529
邀请新用户注册赠送积分活动 1218522
关于科研通互助平台的介绍 1136959