New research into the genetic makeup of schizophrenia has confirmed what many researchers have long suspected — the genetics of schizophrenia is super complicated. In order to better understand diseases like schizophrenia, researchers developed a new algorithm to better map its genetic architecture.
The new research demonstrates why there’ll likely never be a simple way to diagnose schizophrenia through a genetic or blood test.
The new research, led by Harvard School of Public Health’s Po-Ru Loh, analyzed the genetic makeup of 22,177 people with schizophrenia and 27,629 control subjects (Loh et al., 2015). Through the researchers’ analyses, the researchers estimated that there are more than 20,000 causal single nucleotide polymorphisms (SNPs) for schizophrenia. SNPs are the most common type of genetic variation in people. Put simply, the more SNPs implicated in a disease, the more complex that disease’s genetic makeup is.
One of the innovations of the new research is its algorithm that can analyze gene sequences and components more quickly than prior efforts: “We have introduced a new fast algorithm, BOLT-REML, for variance-components analysis involving multiple variance components and multiple traits, and we demonstrated that it enables previously intractable large-sample heritability analyses,” noted the researchers.
In the case of schizophrenia, the researchers believe that each one of these more than 20,000 genetic variants account for a small component of the disease risk. This makes the disease highly polygenic.
According to researcher Po-Ru Loh in an interview with Psych Central, this “extreme number of genetic variants is far greater than the numbers predicted for other common diseases.” Loh was on the team that published the new research, which appears in the journal Nature Genetics.
Given the number of SNPs involved in schizophrenia, is a simple genetic test for this disorder possible?
“A specific genetic test for schizophrenia would be extremely difficult to develop,” according to Loh. “Such a test would need to involve aggregating effects over many genetic variants (each of small effect), and very large sample sizes (millions of study participants) would be needed to accurately estimate these small effects.”
This is the first large-scale research that has been able to examine so many genetic markers at such a high level of detail of people with schizophrenia and compared them to people without schizophrenia. As such, its findings are an important contribution to our understanding of the genetics of this disorder.
But what does the future hold?
“Larger sample sizes will be needed to confirm and expand on these findings,” noted Loh. “With ~50,000 samples (roughly 22k cases and 28k controls), we had enough statistical power to investigate genome-wide distributions of genetic effects at higher resolution than previously possible, but future studies of even larger size will no doubt provide finer resolution and further insights.”
Innovative research like this demonstrates how much we still have yet to learn about the underlying causes of mental illness.
Loh, P-R. et al. (2015). Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis. Nature Genetics. doi:10.1038/ng.3431