Relationships of circular RNA with diabetes and depression
Open accessAbstract
Type 2 diabetes mellitus (T2DM) is closely related to depression; however, the exact molecular mechnisms of this association are unknown. Here, we investigated whether circular RNAs (circRNAs) in the blood are related to the occurrence of depression in patients with T2DM. Fourteen patients with T2DM and depressive symptoms, as assessed by the Self-Rating Depression Scale, were included in this study. Cutoff points of 44 (total coarse points) and 55 (standard score) were used to define depression. The Patient Health Questionnaire 9 was used for common mental disorders, and a score of 5 or more the cutoff for depression. Microarray assays and quantitative real-time reverse transcription polymerase chain reaction showed that 183 hsa-circRNAs were significantly upregulated, whereas 64 were downregulated in the T2DM with depression group (p < 0.05) compared with that in the T2DM group. Differentially expressed hsa-circRNAs could interact with microRNAs to target mRNA expression. KEGG pathway analysis predicted that upregulation of hsa-circRNA_003251, hsa-circRNA_015115, hsa-circRNA_100918, and hsa_circRNA_001520 may participate in the thyroid hormone, Wnt, ErbB, and mitogen-activated protein kinase signalling pathways. We speculate that differentially expressed hsa-circRNAs could help us to clarify the pathogenesis of depression in patients with T2DM and could represent novel molecular targets for clinical diagnosis and therapy.
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Abnormal expressions of circRNAs are present in the blood of patients with major depressive disorder.
“abnormal expressions of circRNAs are present in the blood of MDD patients.51”
From Microglia secrete miR-146a-5p-containing exosomes to regulate neurogenesis in depression (2022) · cites this paper as [51]
Jiang et al. found 183 circRNAs upregulated and 64 downregulated in T2DM patients with depression compared with diabetic patients without depression.
“Another study by Jiang et al. also found that 183 circRNAs were upregulated and 64 circRNAs were downregulated in T2DM patients with depression compared with diabetic patients without depression.”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
hsa_circRNA_003251 and hsa_circRNA_015115 may function as miR-761 sponges and participate in the circRNA-miRNA-mRNA network associated with depression.
“Among them, hsa_circRNA_003251 and hsa_circRNA_015115 may function as miR-761 sponges and participate in the circRNA-miRNA-mRNA network associated with depression [80].”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
hsa_circRNA_015115 is upregulated in human blood.
“| 16 | hsa_circRNA_015115 | - | Human | √ | | Blood | [80] |”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
hsa_circRNA_003251 is upregulated in human blood.
“| 15 | hsa_circRNA_003251 | - | Human | √ | | Blood | [80] |”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
hsa_circRNA_005019 is downregulated in human blood.
“| 18 | hsa_circRNA_005019 | - | Human | | √ | Blood | [80] |”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
hsa_circRNA_100918 is upregulated in human blood.
“| 17 | hsa_circRNA_100918 | - | Human | √ | | Blood | [80] |”
From Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential (2021) · cites this paper as [80]
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Cites
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
Circular RNAs are a large class of animal RNAs with regulatory potency
Memczak, S., Jens, M., Elefsinioti, A., Torti, F., Krueger, J., Rybak, A., Maier, L., Mackowiak, S. D., Gregersen, L. H., Munschauer, M., et al. (2013) · Nature · doi:10.1038/nature11928 · Cited by 7,990 · see citing works
Natural RNA circles function as efficient microRNA sponges
Hansen, T. B., Jensen, T. I., Clausen, B. H., Bramsen, J. B., Finsen, B., Damgaard, C. K., & Kjems, J. (2013) · Nature · doi:10.1038/nature11993 · Cited by 7,985 · see citing works
PICALM modulates autophagy activity and tau accumulation
Moreau, K., Fleming, A., Imarisio, S., Lopez Ramirez, A., Mercer, J. L., Jimenez-Sanchez, M., Bento, C. F., Puri, C., Zavodszky, E., Siddiqi, F., et al. (2014) · Nature Communications · doi:10.1038/ncomms5998 · Cited by 281 · see citing works
Vancampfort, D., Mitchell, A. J., De Hert, M., Sienaert, P., Probst, M., Buys, R., & Stubbs, B. (2015) · Depression and Anxiety · doi:10.1002/da.22387 · Cited by 171 · see citing works
CircRNAs: a regulator of cellular stress
Fischer, J. W., & Leung, A. K. L. (2017) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.1080/10409238.2016.1276882 · Cited by 154 · see citing works
miR-761 regulates the mitochondrial network by targeting mitochondrial fission factor
Long, B., Wang, K., Li, N., Murtaza, I., Xiao, J. Y., Fan, Y. Y., Liu, C.-Y., Li, W. H., Cheng, Z., & Li, P. (2013) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2013.07.009 · Cited by 95 · see citing works
The link between long noncoding RNAs and depression
Huang, X., Luo, Y., Mao, Y.-S., & Jian-lin, J. (2016) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2016.06.004 · Cited by 92 · see citing works
Ma, K., Guo, L., Xu, A., Cui, S., & Wang, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159093 · Cited by 84 · see citing works
Phenome-transcriptome correlation unravels anxiety and depression related pathways
Gormanns, P., Mueller, N. S., Ditzen, C., Wolf, S., Holsboer, F., & Turck, C. W. (2011) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2010.12.010 · Cited by 68 · see citing works
Danna, S. M., Graham, E. A., Burns, R. J., Deschênes, S. S., & Schmitz, N. (2016) · PLoS ONE · doi:10.1371/journal.pone.0160809 · Cited by 68 · see citing works
A genome-wide association study of a sustained pattern of antidepressant response
Hunter, A. M., Leuchter, A. F., Power, R. A., Muthén, B., McGrath, P. J., Lewis, C. M., Cook, I. A., Garriock, H. A., McGuffin, P., Uher, R., et al. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2013.05.002 · Cited by 59 · see citing works
Ahmed, I., Buchert, R., Zhou, M., Jiao, X., Mittal, K., Sheikh, T. I., Scheller, U., Vasli, N., Rafiq, M., Brohi, M. Q., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv069 · Cited by 54 · see citing works
Cohen, J. E., Lee, P. R., & Fields, R. D. (2014) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0509 · Cited by 51 · see citing works
Circular RNAs throw genetics for a loop
Ledford, H. K. (2013) · Nature · doi:10.1038/494415a · Cited by 49 · see citing works
Davidsson, J., Collin, A., Björkhem, G., & Soller, M. (2008) · BMC Medical Genetics · doi:10.1186/1471-2350-9-2 · Cited by 48 · see citing works
Depression and diabetes: unhealthy bedfellows
Katon, W. J. (2010) · Depression and Anxiety · doi:10.1002/da.20683 · Cited by 44 · see citing works
Identification of an mRNA-Decapping Regulator Implicated in X-Linked Mental Retardation
Jiao, X., Wang, Z., & Kiledjian, M. (2006) · Molecular Cell · doi:10.1016/j.molcel.2006.10.013 · Cited by 44 · see citing works
Determinants of mortality in patients with type 2 diabetes: a review
Engelmann, J., Manuwald, U., Rubach, C., Kügler, J., Birkenfeld, A. L., Hanefeld, M., & Rothe, U. (2016) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-016-9349-0 · Cited by 40 · see citing works
MicroRNA-761 regulates mitochondrial biogenesis in mouse skeletal muscle in response to exercise
Xu, Y., Zhao, C., Sun, X., Liu, Z., & Zhang, J. (2015) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2015.09.113 · Cited by 38 · see citing works
Avcı, D., & Kelleci, M. (2016) · Patient Preference and Adherence · doi:10.2147/ppa.s110903 · Cited by 27 · see citing works
Ji, H., Zhuang, Q., & Shen, L. (2016) · Oncotarget · doi:10.18632/oncotarget.8202 · Cited by 24 · see citing works
McFall, G. P., Wiebe, S. A., Vergote, D., Anstey, K. J., & Dixon, R. A. (2015) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2015.08.002 · Cited by 23 · see citing works
Mental illness: the forgotten burden on diabetes populations?
Macdonald, G. C., & Campbell, L. V. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31213-2 · Cited by 20 · see citing works
A novel CHSY1 gene mutation underlies Temtamy preaxial brachydactyly syndrome in a Pakistani family
Sher, G., & Naeem, M. (2013) · European Journal of Medical Genetics · doi:10.1016/j.ejmg.2013.11.001 · Cited by 18 · see citing works
Wang, J., Zhao, J., Zhang, J., Luo, X., Gao, K., Zhang, M., Li, L., Wang, C., & Hu, D. (2015) · Nutrients · doi:10.3390/nu7064763 · Cited by 16 · see citing works
Wang, X., Shen, B.-Y., Zhuang, X., Wang, X.-Q., & Weng, W. (2017) · Journal of Diabetes Research · doi:10.1155/2017/1769897 · Cited by 16 · see citing works
Introduction to Hanefeld Symposium: 40+ years of metabolic syndrome
Koch, C. A., Bornstein, S. R., & Birkenfeld, A. L. (2016) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-016-9356-1 · Cited by 10 · see citing works
Overview of Sodium-Glucose Co-Transport Inhibitors
de Groot, M. (2015) · Journal of Diabetes Research and Therapy · doi:10.16966/2380-5544.108 · Cited by 9 · see citing works
Wang (1997) · doi:10.1002/(sici)1098-2396(199709)27:1
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Sorted by citations
Microglia secrete miR-146a-5p-containing exosomes to regulate neurogenesis in depression
Fan, C., Li, Y., Lan, T., Wang, W., Long, Y., & Yu, S. Y. (2022) · Molecular Therapy · doi:10.1016/j.ymthe.2021.11.006 · Cited by 227 · see citing works
Zhang, Y., Du, L., Bai, Y., Han, B., He, C., Gong, L., Huang, R., Shen, L., Chao, J., Liu, P., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-018-0285-0 · Cited by 184 · see citing works
Shi, Y., Song, R., Wang, Z., Zhang, H., Zhu, J., Yue, Y., Zhao, Y., & Zhang, Z. (2021) · eBioMedicine · doi:10.1016/j.ebiom.2021.103337 · Cited by 65 · see citing works
An, T., He, Z.-C., Zhang, X.-Q., Li, J., Chen, A.-L., Tan, F., Chen, H.-D., Lv, B.-H., Lian, J., Gao, S.-H., et al. (2019) · Chinese Medicine · doi:10.1186/s13020-019-0225-1 · Cited by 63 · see citing works
Circular RNAs in depression: Biogenesis, function, expression, and therapeutic potential
Gan, H., Lei, Y., Yuan, N., Tang, K., Hao, W., Ma, Q., Wu, M., Zhou, X., Li, X., Huang, J., et al. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111244 · Cited by 41 · see citing works
Zhang, H., Chen, Z., Zhong, Z., Gong, W., & Li, J. (2018) · Brain and Behavior · doi:10.1002/brb3.1127 · Cited by 37 · see citing works
Ciuculete, D. M., Voisin, S., Kular, L., Jonsson, J., Rask-Andersen, M., Mwinyi, J., & Schiöth, H. B. (2020) · Clinical Epigenetics · doi:10.1186/s13148-020-00884-8 · Cited by 35 · see citing works
Relationships of Non-coding RNA with diabetes and depression
An, T., Zhang, J., Ma, Y., Lian, J., Wu, Y.-X., Lv, B.-H., Ma, M.-H., Meng, J.-H., Zhou, Y.-T., Zhang, Z.-Y., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-47077-9 · Cited by 27 · see citing works
Self-citation
- Authors
- Jiang, G., Ma, Y., An, T., Pan, Y., Mo, F., Zhao, D., Liu, Y., Miao, J.-N., Gu, Y.-J., Wang, Y., & Gao, S.-H.
- Affiliations
- Beijing University of Chinese Medicine (CN)
- Corresponding author
- Wang, Yangang
- Gao, Si-Hua
- Venue
- Scientific Reports
- Published
- 2017-08-04
- Volume
- 7
- Issue
- 1
- Pages
- 7285-7285
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5544722
- OpenAlex
- W2741786914
- Cited by
- 75
- References
- 30
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 5 · 2022: 5 · 2021: 12 · 2020: 17 · 2019: 15 · 2018: 11 · 2017: 1
- FWCI
- 4.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (81274041, 2011DFA30920)
- Ministry of Education, India
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Circular RNAs in diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- circular RNA, type 2 diabetes, depression, blood biomarkers, miRNA-target interactions, Wnt signalling pathway, differential gene expression, depression pathogenesis
- MeSH terms
- RNA, Circular, Depression, Diabetes Mellitus, Type 2, Gene Expression Regulation, Humans, RNA, RNA, Messenger, Reproducibility of Results, Biomarkers, Computational Biology, 3' Untranslated Regions, Gene Expression Profiling, RNA Interference, MicroRNAs, Gene Regulatory Networks, Molecular Sequence Annotation, Transcriptome
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