Back

Region- and variance-based DNA methylation analyses reveal novel disease genes and pathways for systemic lupus erythematosus

Guo, M.; Wang, T.-Y.; Shen, J. J.; Wang, Y.-F.; Lau, Y.-L.; Yang, W.

2022-11-24 bioinformatics
10.1101/2022.11.23.516835 bioRxiv
Show abstract

BackgroundSystemic lupus erythematosus (SLE) is a prototype autoimmune disease with unclear pathogenesis. DNA methylation is an important regulatory mechanism on gene expression, providing a key angle to understand disease mechanisms. To understand the pathways involved in SLE, and to develop biomarkers for its diagnosis and treatment, we analyzed DNA methylation profiles on blood cells from SLE patients and healthy controls. ResultsWe identified most differentially methylated regions (DMRs) in T cells, while majority of differentially variable sites (DVSs) were found in B cells, featuring hypervariability in enhancers. We observed a prominent T cell receptor (TCR) signaling cluster with consistent hypermethylation and a B cell receptor (BCR) cluster with highly increased variability in SLE. Genes involved in innate immunity were often found hypomethylated, while adaptive immunity genes were featured with hypermethylation. Using a machine learning approach, we identified 60 genes that accurately distinguished SLE patients from healthy individuals, which also showed correlation with disease activities. ConclusionsThis study highlights the role of lymphocyte receptor aberrations in the disease and identified a list of genes showing great potential as biomarkers and shedding new light on disease mechanisms, through novel analyses of methylation data.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Frontiers in Genetics
197 papers in training set
Top 0.1%
18.9%
2
BMC Medical Genomics
36 papers in training set
Top 0.1%
12.7%
3
Clinical Immunology
21 papers in training set
Top 0.1%
6.5%
4
Clinical Epigenetics
53 papers in training set
Top 0.2%
4.9%
5
Immunology
29 papers in training set
Top 0.1%
4.4%
6
Scientific Reports
3102 papers in training set
Top 30%
4.0%
50% of probability mass above
7
Frontiers in Immunology
586 papers in training set
Top 2%
3.7%
8
Frontiers in Pharmacology
100 papers in training set
Top 1%
2.6%
9
PLOS ONE
4510 papers in training set
Top 47%
2.1%
10
Computational and Structural Biotechnology Journal
216 papers in training set
Top 3%
1.9%
11
JCI Insight
241 papers in training set
Top 4%
1.5%
12
International Journal of Molecular Sciences
453 papers in training set
Top 9%
1.4%
13
Epigenetics
43 papers in training set
Top 0.6%
1.2%
14
Bioinformatics
1061 papers in training set
Top 8%
1.1%
15
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 4%
1.0%
16
Journal of Personalized Medicine
28 papers in training set
Top 0.9%
0.9%
17
Frontiers in Medicine
113 papers in training set
Top 5%
0.9%
18
ImmunoInformatics
11 papers in training set
Top 0.2%
0.8%
19
Genomics
60 papers in training set
Top 2%
0.8%
20
Clinical Infectious Diseases
231 papers in training set
Top 5%
0.8%
21
The Journal of Immunology
146 papers in training set
Top 2%
0.7%
22
BMC Genomic Data
12 papers in training set
Top 0.2%
0.7%
23
Gene
41 papers in training set
Top 3%
0.7%
24
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
25 papers in training set
Top 1%
0.7%
25
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 10%
0.7%
26
International Immunopharmacology
15 papers in training set
Top 0.6%
0.7%
27
PLOS Computational Biology
1633 papers in training set
Top 27%
0.7%
28
Human Molecular Genetics
130 papers in training set
Top 4%
0.5%
29
PLOS Neglected Tropical Diseases
378 papers in training set
Top 6%
0.5%
30
Archives of Clinical and Biomedical Research
28 papers in training set
Top 3%
0.5%