But Hussman, father to a 16-year-old boy with autism, applied the same statistical tools he uses to map out complex economic relationships to produce new research findings in a paper titled “A Noise-Reduction GWAS Analysis Implicates Altered Regulation of Neurite Outgrowth and Guidance in Autism,” which was published today in the journal Molecular Autism.
Hussman, who has been researching autism since his son was diagnosed more than a decade ago, has collaborated for about six years with Margaret A. Pericak-Vance, Ph.D., director of the John P. Hussman Institute for Human Genomics at the Miller School. Now the pair has further solidified their work in the paper in which Hussman is the lead author and Pericak-Vance is the senior author.
“Even though John isn’t a geneticist, the type of approach he takes to integrate information and make a cohesive judgment applies to genetics,” said Dr. Pericak-Vance. “He has an ability to look at multiple sources of data and integrate and interpret them.”
“One of the real challenges in human genetics today is extracting useful information from the oceans of data we can now generate,” said Dr. Jonathan Haines, director of the Center for Human Genetics Research at Vanderbilt University and a collaborator on the study. “John’s approach is a significant step forward in filtering the data so we can find the genetic signals more easily.”
Dr. Hussman, whose Ph.D. is in economics from Stanford University, explained that it’s all in the numbers.
“It doesn’t matter if it’s genetics or financial data, as long as you understand how the data is structured,” Hussman said. “The genetic data we examined involves hundreds of thousands of locations across the whole genome. It’s like a huge coin-flipping experiment where the coins aren’t completely independent. You’re trying to find out which coins are tossed to people with autism more often than by chance.”
For this paper, the research team, which also included Ren-Hua Chung, Ph.D., research assistant professor in the Dr. John T Macdonald Foundation Department of Human Genetics and director of the Division of Statistical Genetics, and Anthony J. Griswold, Ph.D., post-doctoral associate at the Hussman Institute, have found what they think is a significant method that can be applied not only to autism genetics, but other diseases and disorders as well.
“This research,” Hussman explained, “improves our ability to identify fairly weak genetic signals by taking account of genetic signals at nearby locations and in more than one data set.” “It improves our ability to find a needle in a haystack.”
In genetics, certain genes can give off strong or weak signals and be linked to a specific disorder or disease. Studies on genes involved in Alzheimer’s disease and multiple sclerosis have shown such strong signals that there is no question they are tied to those diseases. But autism is different. Most of the signals are weak and difficult to detect, making the relationship harder to identify.
Once the researchers figured out how to “reduce the noise,” the signals became easier to detect, producing a set of autism candidate genes. Further study revealed that a large number of them interact, controlling how nerve cells extend and navigate to create networks. The pathway is consistent with evidence suggesting that people with autism may have very subtle differences in how their brains are “wired.”
“The results embrace some previous genetic findings that seemed to be unrelated,” Hussman said. “Now we can put them into a pathway that makes sense.”
Dr. Pericak-Vance pointed out that while this paper’s discoveries are important, autism is still a difficult disorder to crack open. “We do not know exactly which variants are involved and their specific role in autism, but this research gives us the pipeline to investigate more.”
The next step is doing genetic sequencing in the locations that were identified in this paper to identify the functional variants in genes that may be involved.
“The symbol of autism is a puzzle piece,” Hussman said. “You can’t cure something unless you understand it first. This is a significant step. Once you understand the pathway that is involved, you can look for ways to rescue it.”
Dr. Pericak-Vance said that while this research is not a cure, she hopes that eventually it will lead to discoveries that will improve the quality of life for children with autism.
Other members of the research team include James M. Jaworski, M.S.; Daria Salyakina, Ph.D.; Deqiong Ma, Ph.D.; Ioanna Konidari, M.S.; Patrice L Whitehead, B.S.; Jeffery M. Vance, Ph.D., M.D.; Eden R Martin, Ph.D.; Michael L Cuccaro, Ph.D.; and John R Gilbert, Ph.D.
The research conducted for this study was supported by the Autism Genetic Resource Exchange, Autism Speaks, NIH grants, the Medical Research Council’s Autism Genome Project, and by a gift from the Hussman Foundation.