Back

Multi-omics integration prioritizes potential drug targets for multiple sclerosis

Jiang, Y.; Liu, Q.; Stridh, P.; Kockum, I.; Olsson, T.; Alfredsson, L.; Diaz-Gallo, L. M.; Jiang, X.

2024-09-27 neurology
10.1101/2024.09.26.24314450 medRxiv
Show abstract

Background and ObjectivesMultiple sclerosis (MS) is a chronic autoimmune disease with limited treatment options. Thus, drug discovery and repurposing are essential to enhance treatment efficacy and safety. MethodsWe obtained summary statistics for protein quantitative trait loci (pQTL) of 2,004 plasma proteins and 1,443 brain proteins, a genome-wide association study (GWAS) of MS susceptibility with 14,802 cases and 26,703 controls, and expression quantitative trait loci (eQTL) for 8,000 genes in peripheral blood and 16,704 genes in brain tissue. Our integrative analysis included a proteome-wide association study to identify MS-associated proteins, followed by summary-data-based Mendelian randomization (SMR) to determine causal associations. We used the HEIDI test and Bayesian colocalization analysis to distinguish pleiotropy from linkage. Proteins passing SMR, HEIDI, and colocalization analyses were considered potential drug targets. We further conducted pathway annotations, protein-protein interaction (PPI) network analysis, and examined mRNA levels of these targets. ResultsWe identified hundreds of MS-associated proteins in plasma and brain, confirming the causal roles of 18 proteins (nine in plasma and nine in brain). Among these, we found 78 annotated pathways and 16 existing non-MS drugs targeting six proteins. We also discovered intricate PPIs among seven potential drug targets and 19 existing MS drug targets, as well as PPIs of four targets across plasma and brain. Combining expression data, we identified two targets adhering to the central dogma of molecular biology. DiscussionWe prioritized 18 potential drug targets in plasma and brain, elucidating the underlying pathology and providing evidence for drug discovery and repurposing in MS.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Neurology Neuroimmunology & Neuroinflammation
12 papers in training set
Top 0.1%
18.7%
2
Annals of Clinical and Translational Neurology
34 papers in training set
Top 0.1%
7.9%
3
Brain
168 papers in training set
Top 0.6%
5.5%
4
Multiple Sclerosis Journal
21 papers in training set
Top 0.1%
5.5%
5
Annals of Neurology
64 papers in training set
Top 0.3%
4.9%
6
Journal of Neurology, Neurosurgery & Psychiatry
30 papers in training set
Top 0.1%
4.9%
7
Frontiers in Neurology
102 papers in training set
Top 0.8%
4.4%
50% of probability mass above
8
Nature Communications
5641 papers in training set
Top 30%
4.4%
9
Neurology
50 papers in training set
Top 0.3%
4.1%
10
eBioMedicine
183 papers in training set
Top 0.9%
3.2%
11
Neurobiology of Disease
148 papers in training set
Top 2%
2.1%
12
Clinical Immunology
21 papers in training set
Top 0.1%
2.1%
13
BMC Medicine
176 papers in training set
Top 2%
1.7%
14
Scientific Reports
3612 papers in training set
Top 55%
1.7%
15
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 34%
1.1%
16
Brain Communications
166 papers in training set
Top 3%
1.1%
17
Multiple Sclerosis and Related Disorders
15 papers in training set
Top 0.1%
1.1%
18
Nature Medicine
125 papers in training set
Top 2%
1.1%
19
Journal of the Neurological Sciences
18 papers in training set
Top 0.5%
1.0%
20
Journal of Translational Medicine
57 papers in training set
Top 2%
1.0%
21
International Journal of Molecular Sciences
494 papers in training set
Top 13%
1.0%
22
Journal of Advanced Research
14 papers in training set
Top 0.2%
0.9%
23
Frontiers in Immunology
638 papers in training set
Top 9%
0.9%
24
Briefings in Bioinformatics
354 papers in training set
Top 7%
0.9%
25
Human Genetics and Genomics Advances
84 papers in training set
Top 2%
0.9%
26
Acta Neuropathologica
58 papers in training set
Top 1%
0.9%
27
Journal of Neurology
28 papers in training set
Top 0.9%
0.9%
28
Clinical and Translational Medicine
31 papers in training set
Top 1%
0.6%
29
Clinical and Experimental Immunology
12 papers in training set
Top 0.2%
0.6%
30
PLOS Computational Biology
1863 papers in training set
Top 21%
0.6%