Using new statistical tools, Carnegie Mellon University's Kathryn Roeder
has led an international team of researchers to discover that most of
the genetic risk for autism comes from versions of genes that are common
in the population rather than from rare variants or spontaneous
glitches.
The bulk of risk, or liability, for autism spectrum disorders was traced
to inherited variations in the genetic code shared by many people.
These and other (unaccounted) factors dwarfed contributions from rare
inherited, non-additive and spontaneous (de novo) genetic factors.
Published in the July 20 issue of the journal Nature Genetics,
the study found that about 52 percent of autism was traced to common
genes and rarely inherited variations, with spontaneous mutations
contributing a modest 2.6 percent of the total risk. The research team
-- from the Population-Based-Autism Genetics and Environment Study
(PAGES) Consortium -- used data from Sweden's universal health registry
to compare roughly 3,000 subjects, including autistic individuals and a
control group. The largest study of its kind to date, the team also
showed that inheritability outweighs environmental risk.
"From this study, we can see that genetics plays a major role in the
development of autism compared to environmental risk factors, making
autism more like height than we thought -- many small risk factors add
up, each pushing a person further out on the spectrum," said Roeder,
professor of statistics and computational biology at Carnegie Mellon and
a leading expert on statistical genomics and the genetic basis of
complex disease. "These findings could not have happened without
statistics, and now we must build off of what we learned and use
statistical approaches to determine where to put future resources, and
decide what is the most beneficial direction to pursue to further
pinpoint what causes autism."
Although autism is thought to be caused by an interplay of genetic
and other factors, including environmental forces, consensus on their
relative contributions and the outlines of its genetic architecture has
remained elusive, until now. With this new study, the researchers
believe that autism genetics is beginning to catch up.
Led by Roeder, the researchers used new statistical methods -- such
as machine learning techniques and dimension reduction tools -- that
allowed them to more reliably sort out the inheritability of the
disorder. In addition, they were able to compare their results with a
parallel family-based study in the Swedish population, which took into
account data from twins, cousins, and factors like age of the father at
birth and parents' psychiatric history. A best-fit statistical model
took form, based mostly on additive genetic and non-shared environmental
effects.
"Thanks to the boost in statistical power that comes with ample
sample size, autism geneticists can now see the forest for the trees,"
said Thomas R. Insel, director of the National Institute of Mental
Health (NIMH). "Knowing the nature of the genetic risk will help focus
the search for clues to the molecular roots of the disorder."
Thomas Lehner, chief of the NIMH's Genomics Research Branch, agreed
and added, "This is a different kind of analysis than employed in
previous studies. Data from genome-wide association studies was used to
identify a genetic model instead of focusing just on pinpointing genetic
risk factors. The researchers were able to pick from all of the cases
of illness within a population-based registry."
Now that the genetic architecture is better understood, the
researchers are identifying specific genetic risk factors detected in
the sample, such as deletions and duplications of genetic material and
spontaneous mutations. The researchers said even though such rare
spontaneous mutations accounted for only a small fraction of autism
risk, the potentially large effects of these glitches make them
important clues to understanding the molecular underpinnings of the
disorder.
"Within a given family, the mutations could be a critical determinant
that leads to the manifestation of ASD in a particular family member,"
said Joseph Buxbaum, the study's first author and professor of
psychiatry, neuroscience, genetics and genomic sciences at the Icahn
School of Medicine at Mount Sinai (ISMMS). "The family may have common
variation that puts it at risk, but if there is also a 'de novo'
mutation on top of that, it could push an individual over the edge. So
for many families, the interplay between common and spontaneous genetic
factors could be the underlying genetic architecture of the disorder."
Current studies have not been large enough to reveal the many common
genetic variants that increase the risk of autism. On their own, none of
these common variants will have sufficient impact to cause autism.
"Our group in Pittsburgh is working to develop a model that predicts
the genetic risk for a family based on a myriad of small effects. Such a
score could provide clinical benefit to families," Roeder said.
Journal Reference:
- Trent Gaugler, Lambertus Klei, Stephan J Sanders, Corneliu A Bodea, Arthur P Goldberg, Ann B Lee, Milind Mahajan, Dina Manaa, Yudi Pawitan, Jennifer Reichert, Stephan Ripke, Sven Sandin, Pamela Sklar, Oscar Svantesson, Abraham Reichenberg, Christina M Hultman, Bernie Devlin, Kathryn Roeder, Joseph D Buxbaum. Most genetic risk for autism resides with common variation. Nature Genetics, 2014; DOI: 10.1038/ng.3039
Courtesy: ScienceDaily
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