Evidence map›Paper›PMID 39935908›Full record

ArticleImmunoTargets and therapy2025

Genetic and Plasma Proteomic Approaches to Identify Therapeutic Targets for Graves' Disease and Graves' Ophthalmopathy.

Chenxin Ke, Yuefeng Yu, Jiang Li, Yuetian Yu, Ying Sun, Yuying Wang, Bin Wang, Yingli Lu, Mengjun Tang, Ningjian Wang and 1 more

Abstract read
In one paragraph

Article in ImmunoTargets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Chenxin Ke *Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Yuefeng Yu *Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Jiang LiInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.ORCID 0009-0005-6253-618X
Yuetian YuInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Ying SunInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Yuying WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Bin WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Yingli LuInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.ORCID 0000-0002-5117-1614
Mengjun TangOrthopedic Department, Taizhou Hospital of Zhejiang Province, Zhejiang University, Taizhou, People's Republic of China.
Ningjian WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.
Yi ChenInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The blood proteome is a major source of biomarkers and therapeutic targets. We aimed to identify the causal proteins and potential targets for Graves' disease (GD) and Graves' ophthalmopathy (GO) via systematic genetic analyses. Methods: Genome-wide association studies (GWASs) on the UK Biobank- Pharma Proteomics Project (UKB-PPP) collected 2923 Olink proteins from 54,219 participants. We conducted a proteome-wide Mendelian randomization (MR) study with cis-pQTLs to identify candidate proteins for GD and GO risk. Colocalization analysis and the Heidi test were used to examine whether the identified proteins and diseases shared the same variant. More proteins with potential causal associations were identified in Summary-data-based MR (SMR) analyses using trans-pQTLs. Then, downstream analyses were performed to detect protein interactions, gene function, cell type-specific expression and druggable information. Results: This study genetically predicted levels of 62 plasma proteins were associated with GD risk. Four proteins (CD40, TINAGL1, GMPR and CXCL10) were prioritized with the evidence of sharing the same variants with GD. Specifically, some proteins had potential associations with GD with trans-pQTLs mapping in CD40. The four prioritized protein-coding genes were mainly enriched in the regulation of apoptotic and death processes. In addition, GMPR was associated with both GO and GD in a consistent direction. BTN1A1 and FCRL1 were prioritized as the causal proteins for GO onset and were not associated with GD. Conclusion: By synthesizing proteomic and genetic data, we identified several protein biomarkers for GD, with one linked to both GD and GO and two other protein biomarkers specific to GO onset, which provides valuable insights into the etiology and potential therapeutic targets for the two diseases.

Indexed as

Graves’ diseaseMendelian randomizationOlinkplasma proteomics

Identifiers

PMID39935908
PMCPMC11812558

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.