| Chapter title |
Noncoding RNAs in Depression
|
|---|---|
| Chapter number | 11 |
| Book title |
Neuroepigenomics in Aging and Disease
|
| Published in |
Advances in experimental medicine and biology, May 2017
|
| DOI | 10.1007/978-3-319-53889-1_11 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-953888-4, 978-3-31-953889-1
|
| Authors |
Lin, Rixing, Turecki, Gustavo, Rixing Lin B.A., Gustavo Turecki M.D., Ph.D., Rixing Lin, Gustavo Turecki |
| Editors |
Raul Delgado-Morales |
| Abstract |
Major depressive disorder (MDD) is a common psychiatric disorder affecting millions of people worldwide, yet its etiology remains elusive. The last decades have seen great advances in our understanding of the genome structure and functional organization. Noncoding RNAs (ncRNAs) are RNAs that do not code for proteins but have important regulatory roles. The investigation of ncRNAs as regulators of gene expression has been a topic of growing interest in health research, including in studies investigating etiological and therapeutic factors in major depression. Several different species of ncRNAs have been identified in association to and have shown to be dysregulated in depressed individuals or in animal models of depression. This review will detail the complex relation between ncRNAs and major depression and the studies that propose mechanisms and pathways that specific ncRNAs may be involved in major depression. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Germany | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 20% |
| Student > Bachelor | 5 | 17% |
| Researcher | 4 | 13% |
| Other | 2 | 7% |
| Student > Ph. D. Student | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 9 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 27% |
| Neuroscience | 4 | 13% |
| Psychology | 3 | 10% |
| Medicine and Dentistry | 2 | 7% |
| Computer Science | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 9 | 30% |