UC Irvine Health researchers have helped discover that genes controlling circadian clock rhythms are profoundly altered in the brains of people with severe depression. These clock genes regulate 24-hour circadian rhythms affecting hormonal, body temperature, sleep and behavioral patterns.
Depression is a serious disorder with a high risk for suicide affecting approximately one in 10 Americans, according to the Centers for Disease Control, and is ranked as fourth of all diseases by the World Health Organization in terms of lifetime disability. Study findings provide the first evidence of altered circadian gene rhythms in brain tissue of people with depression and suggest a physical basis for many of the symptoms that depressed patients report.
The study – which appears online this week in the Proceedings of the National Academy of Sciences – involved researchers from UC Irvine Health, University of Michigan, UC Davis, Cornell University, the Hudson Alpha Institute for Biotechnology and Stanford University.
“Our findings involved the analysis of a large amount of data involving 12,000 gene transcripts obtained from donated brain tissue from depressed and normal people. We were amazed that our data revealed that clock gene rhythms varied in synchrony across six regions of normal human brain and that these rhythms were significantly disrupted in depressed patients. The findings provide clues for potential new classes of compounds to rapidly treat depression that may reset abnormal clock genes and normalize circadian rhythms,” said Dr. William Bunney, the study’s senior author, and Distinguished Professor of Psychiatry & Human Behavior at UC Irvine.
Circadian clock genes play an important role in regulating many body rhythms over a 24-hour cycle. Although animal data provide evidence for the circadian expression of genes in brain, little has been known as to whether there is a similar rhythmicity in the human brain.
In the study, the researchers analyzed genome-wide gene expression patterns in brain samples from 55 individuals with no history of psychiatric or neurological illness and compared them to the expression patterns in samples from 34 severely depressed patients.
The investigators isolated multiple RNA samples from six regions of each brain and arranged the gene expression data around a 24-hour cycle based on time of death. Several hundred genes in each of six brain regions displayed rhythmic patterns of expression over the 24-hour cycle, including many genes essential to the body’s circadian machinery.
In the end, they had a near-complete understanding of how gene activity varied throughout the day in the cells of the six brain regions they studied.
“There really was a moment of discovery when we realized that many of the genes that we saw expressed in the normal individuals were well-known circadian rhythm genes – and when we saw that the people with depression were not synchronized to the usual solar day in terms of this gene activity,” said Jun Li, an assistant professor in the Department of Human Genetics at the University of Michigan who led the analysis of the massive amount of data generated by the rest of the team.
The researchers add that this information can be used to help find new ways to predict depression, and fine-tune treatment for depressed patients.
Blynn Bunney, David Walsh, Marquis Vawter and Preston Cartagena of UC Irvine; Fan Meng, Simon Evans, Megan Hagenauer, Stanley Watson Jr., and Huda Akil from Michigan; Edward Jones and Prabakhara Choudary with UC Davis; Jack Barchas with Weill Cornell Medical College, New York; Alan Schatzberg with Stanford; and Richard Myers with the HudsonAlpha Institute for Biotechnology, Huntsville, Ala., also contributed to the study.
The Pritzker Neuropsychiatric Disorders Research Fund, the National Institute of Mental Health, William Lion Penzner Foundation, the Della Martin Foundation, the Office of Naval Research, the National Alliance for Research on Schizophrenia and Depression’s Abramson Family Foundation Investigator Award, and an International Mental Health Research Organization – Johnson & Johnson Rising Star Translational Research Award supported the research.
