Molecular Phenotyping of Immune Cells from Young NOD Mice Reveals Abnormal Metabolic Pathways in the Early Induction Phase of Autoimmune Diabetes
Open accessAbstract
Islet leukocytic infiltration (insulitis) is first obvious at around 4 weeks of age in the NOD mouse--a model for human type 1 diabetes (T1D). The molecular events that lead to insulitis and initiate autoimmune diabetes are poorly understood. Since TID is caused by numerous genes, we hypothesized that multiple molecular pathways are altered and interact to initiate this disease. We evaluated the molecular phenotype (mRNA and protein expression) and molecular networks of ex vivo unfractionated spleen leukocytes from 2 and 4 week-old NOD mice in comparison to two control strains. Analysis of the global gene expression profiles and hierarchical clustering revealed that the majority (~90%) of the differentially expressed genes in NOD mice were repressed. Furthermore, analysis using a modern suite of multiple bioinformatics approaches identified abnormal molecular pathways that can be divided broadly into 2 categories: metabolic pathways, which were predominant at 2 weeks, and immune response pathways, which were predominant at 4 weeks. Network analysis by Ingenuity pathway analysis identified key genes/molecules that may play a role in regulating these pathways. These included five that were common to both ages (TNF, HNF4A, IL15, Progesterone, and YWHAZ), and others that were unique to 2 weeks (e.g. MYC/MYCN, TGFB1, and IL2) and to 4 weeks (e.g. IFNG, beta-estradiol, p53, NFKB, AKT, PRKCA, IL12, and HLA-C). Based on the literature, genes that may play a role in regulating metabolic pathways at 2 weeks include Myc and HNF4A, and at 4 weeks, beta-estradiol, p53, Akt, HNF4A and AR. Our data suggest that abnormalities in regulation of metabolic pathways in the immune cells of young NOD mice lead to abnormalities in the immune response pathways and as such may play a role in the initiation of autoimmune diabetes. Thus, targeting metabolism may provide novel approaches to preventing and/or treating autoimmune diabetes.
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References 60 · Cited by 31
- Authors
- Wu, J., Kakoola, D. N., Lenchik, N. I., Desiderio, D. M., Marshall, D. R., & Gerling, I. C.
- Affiliations
- University of Tennessee Health Science Center (US)
- Meharry Medical College (US)
- Corresponding author
- Gerling, Ivan C.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-10-11
- Volume
- 7
- Issue
- 10
- Pages
- e46941
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3469658
- OpenAlex
- W2006118793
- Cited by
- 31
- References
- 60
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 1 · 2022: 4 · 2021: 4 · 2020: 2 · 2018: 2 · 2017: 1 · 2016: 1 · 2015: 4 · 2014: 3 · 2013: 4
- FWCI
- 2.12
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- American Diabetes Association (ADA 7-11-BS-49)
- National Institutes of Health (1s10rr010522-01a2)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK62103, R01DK062103)
- National Center for Research Resources (RR14583, RR 10522)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Health Sciences › Medicine › Surgery › Pancreatic function and diabetes
- Keywords
- type 1 diabetes, NOD mice, insulitis, immune cell metabolism, metabolic pathways, immune pathways, spleen leukocytes, gene expression profiling, c-Myc, HNF4α, beta-estradiol, p53, Akt, TNF-α, IL-15, interleukin-2, IL-12, HLA-C, immunometabolism, disease prevention
- MeSH terms
- Analysis of Variance, Animals, Diabetes Mellitus, Type 1, Humans, Leukocytes, Mice, Inbred C57BL, Phenotype, Spleen, Time Factors, Electrophoresis, Gel, Two-Dimensional, Cluster Analysis, Mice, Inbred NOD, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Proteome, Mice, Gene Regulatory Networks, Metabolic Networks and Pathways, Transcriptome
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