In a new study, researchers have developed the world’s first test to accurately predict mood disorders in people, based on the levels of a specific protein found in the brain.
The research was conducted by a team at the University of South Australia and elsewhere.
Links between low levels of mature brain-derived neurotrophic factor (mBDNF) and depression are well known.
But, until now, it hasn’t been possible to distinguish between the three forms of the BDNF protein in blood samples.
The mature form promotes the growth of neurons and protects the brain, but the other two BDNF forms – its precursor and the prodomain of BDNF – bind to different receptors, causing nerve degeneration and inflammation.
An assay kit developed by the team can now precisely distinguish between these proteins, unlike other commercial kits in the market.
In a study of 215 people in China, including 90 patients with clinical depression and 15 with bipolar disorder, researchers found clear links with low levels of mBDNF in their blood.
The more severe the depression, the lower the mBDNF level.
Mature BDNF levels in patients not on antidepressants were also lower than patients treated with antidepressants.
Surprisingly, there was no difference in mBDNF levels between 14 people with a history of suicide attempts and the control group of 96 people.
No strong gender differences were found.
The team says the existing commercial BDNF ELISA (enzyme-linked immunosorbent assay) kits are not specific and can cross-react with each other.
The kit we have developed has an accuracy rate of 80%-83%.
The researchers say serum mBDNF levels less than 12.4 ng/ml could be used as a cut-off point to diagnose depression and bipolar disorder.
This could be an objective biomarker in addition to a clinical assessment by a doctor.
The next step is to examine whether imbalances between proBDNF and mature BDNF can be restored in electric convulsion therapy.
One author of the study is UniSA Professor Xin-Fu Zhou.
The study is published in the Journal of Psychiatric Research.
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