Autism is widely believed to be caused by an interplay of genetics and other factors. However, scientists have not reached a consensus on how much of an influence genes have on autism risk.
Recent evidence has suggested that the genomes of people who have autism are more likely to include de novo mutations - rare and spontaneous mutations with significant effects that are thought to account for particular cases of autism.
"Many people have been focusing on de novo mutations, such as the ones that can occur in the sperm of an older father," explains Joseph D. Buxbaum, PhD, the study's lead investigator and director of the Seaver Autism Center for Research and Treatment and professor of psychiatry, neuroscience and genetics and genomic sciences at the Icahn School of Medicine at Mount Sinai.
"While we find these mutations are also key contributors, it is important to know that there is underlying risk in the family genetic architecture itself."
By conducting a "rigorous analysis" of DNA sequence variations as part of the Population-Based Autism Genetics and Environment Study (PAGES) Consortium, Dr. Buxbaum's team found that about 52.4% of autism cases can be traced back to both common and rare inherited variations. By contrast, spontaneous mutations were found to account for just 2.6% of total autism risk.
"We show very clearly that inherited common variants comprise the bulk of the risk that sets up susceptibility to autism," Dr. Buxbaum says. "But while families can be genetically loaded for autism risk, it may take additional rare genetic factors to actually produce the disorder in a particular family member."
The study used data from Sweden's universal health registry to compare about 3,000 participants, including autistic subjects and a control group. The researchers say that PAGES is the largest study of its kind to date.
New statistical methods promise 'more reliable results'
Limitations in sample size have previously made it difficult to ascertain the relative influence of common, rare inherited and rare spontaneous variations. Differences in the statistical models and methods used across studies have also presented challenges in obtaining a consensus view, with estimates of autism heritability varying from 17-50%.
In PAGES, new statistical methods - such as "machine learning techniques and dimension reduction tools" - were deployed, which the researchers claim allowed a more reliable method for assessing heritability.
The researchers were also able to access data from a parallel study of Swedish families that looked at twins, cousins, age of the father at birth and the psychiatric history of the parents.
Thomas Lehner, chief of the National Institute of Mental Health's Genomics Research Branch, says:
"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."
【News Source：2014.7.21 MNT】