Psychiatric disorders can be described on many levels, the most traditional of which are subjective descriptions of the experience of being depressed and the use of rating scales that quantify depressive symptoms. Over the past two decades, research has developed other strategies for describing the biological underpinnings of depression
, including volumetric brain measurements using magnetic resonance imaging (MRI) and the patterns of gene expression in white blood cells.
During this period, a great deal of research has attempted to characterize the genes that cause depression as reflected in rating scales of mood states, alterations in brain structure and function as measured by MRI, and gene expression patterns in post-mortem brain tissue from people who had depression.
So what would happen if one tried to find the gene or genes that explained the "whole picture" by combining all of the different types of information that one could collect? This is exactly what was attempted by Dr. David Glahn, of Yale University and Hartford Hospital's Institute of Living, and his colleagues.
"They have provided a very exciting strategy for uniting the various types of data that we collect in clinical research in studies attempting to identify risk genes," said Dr. John Krystal, Editor of Biological Psychiatry.
Their work localized a gene, called RNF123, which may play a role in major depression.
They set out with two clear goals: to describe a new method for ranking measures of brain structure and function on their genetic 'importance' for an illness, and then to localize a candidate gene for major depression.
"We were trying to come up with a way that could generally be used to link biological measurements to (psychiatric) disease risk," said Dr. John Blangero, director of the AT&T Genomics Computing Center at the Texas Biomedical Research Institute. "And in our first application of this, in relation to majo...