The international team — led by researchers from the Karolinska Institutet in Sweden and the University of North Carolina at Chapel Hill — say that the work should make it easier to design experiments that lead to new, improved treatments.
An account of the collaborative effort can be found in a scientific paper that was published recently in the journal Nature Genetics.
“With the results from this study,” says co-senior study author Jens Hjerling-Leffler, an assistant professor and research group leader in the Department of Medical Biochemistry and Biophysics at Karolinska Institutet, “we are giving the scientific community a chance to focus their efforts where it will give maximum effect.”
Schizophrenia is a severe and disabling long-term mental illness that affects more than 21 million individuals worldwide.
The disease impairs behavior and human attributes that many unaffected people might take for granted, such as perception, thinking, language, emotions, and having a “sense of self.”
Common symptoms include: hallucinations, in which voices are heard and “things are seen” that others say are not there; and delusions, or holding onto beliefs that are false.
Medical treatment and psychological support can be effective, but even with this help, managing one’s way in the world with such a disabling burden can make it very hard to gain qualifications, hold down a job, and lead a productive life.
New tools ‘transforming’ biological research
Schizophrenia’s causes are proving hard to pin down. Scientists believe that several factors may be involved, including interactions between genes and environment, such as problems during birth and exposure to viruses.
Significant progress has been made in identifying the genetic factors, if we take into consideration the hundreds of genes that studies have now linked to schizophrenia.
However, since each gene exerts but a small effect, this makes it very difficult to decide which ones to focus on in research experiments and treatment development.
The focus of this recent study is on how cell types — which can be characterized by gene maps — relate to disease. Such lines of investigation are now possible thanks to a new tool called “single-cell transcriptomics.”
Single-cell transcriptomics is “transforming our understanding of biology” by allowing scientists to quantify levels of gene expression in single cells.
Gene expression maps
For the new study, the researchers created gene expression maps for each cell type in the brain and compared them with the detailed list of the hundreds of schizophrenia-related genes.
This helped them to identify the specific cell types that likely contribute most to the disorder, as well as those that are likely to contribute least.
“We found,” note the authors, “that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs), and certain interneurons, but far less consistently to embryonic, progenitor, or glial cells.”
They also found that the contributing cell types are linked to particular structures and parts of the brain and may exert “distinct” effects.
“The genetic risk associated with MSNs,” the authors go on to say, “did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.”
The team suggests that the findings could serve as a “roadmap” for researching new treatments.
‘Separate drugs for each cell type?’
“One question now,” explains co-senior study author Patrick Sullivan — who holds professorships in both the Department of Medical Epidemiology and Biostatistics at the Karolinska Institutet and the Department of Genetics and Psychiatry at University of North Carolina — “is whether these brain cell types are related to the clinical features of schizophrenia.”
Such questions help, for example, to find out whether treatment response is worse if a cell type is particularly dysfunctional. Also, dysfunction in another type of cell might lead to long-term side effects such as cognitive problems.
“This would have important implications for development of new treatments, as separate drugs may be required for each cell type involved,” Prof. Sullivan explains.
The team believes that thanks to the new tools such as single-cell transcriptomics, we can expect to see breakthroughs in our understanding of the biology of other complex conditions, such as major depression, autism, and eating disorders.
“This marks a transition in how we can use large genetic studies to understand the biology of disease.”
Prof. Jens Hjerling-Leffler
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