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Environmental Factor

Environmental Factor

Your Online Source for NIEHS News

June 2016

Bioinformatics Sheds Light on the Genetics of Autism

Two researchers from the Simons Foundation discussed their work with big data to study the genetics underlying autism spectrum disorder.

Two researchers who use big data to study the genetics underlying the autism spectrum disorder (ASD) discussed their work May 9 as part of the NIEHS Keystone Science Lecture Seminar Series.

Alex Lash, M.D., chief informatics officer at the Simons Foundation, discussed the Simons Foundation Autism Research Initiative (SFARI), which works to improve understanding, diagnosis, and treatment of ASD. Olga Troyanskaya, Ph.D., deputy director for genomics at the Simons Center for Data Analysis and professor at Princeton University, presented a talk called, “Tissue-specific View of Human Disease.”

Cindy Lawler, Ph.D., head of the NIEHS Genes, Environment, and Health Branch, hosted the talk. “Autism is a complex condition, and we are learning a lot about the intricate connections between genetic and environmental factors,” said Lawler, who oversees grants on autism-related research. “The data-focused approaches being used by the Simons Foundation may be what’s needed to clarify some of those relationships.”

Autism cohorts

In his talk, “Overview of Data in Simons Foundation Autism Cohorts,” Lash described the Simons Simplex Collection (SSC), a core project of SFARI. The collection includes data from 2,600 families, each with a single child affected by ASD, as well as their unaffected parents and siblings. Using clinical visits, questionnaires, and genetic samples collected from the affected children, researchers were able to precisely characterize, or phenotype, the children.

According to Lash, this approach has identified 71 autism-risk loci, or specific DNA sequences. “It has also allowed for an estimate of the total number of autism-risk genes, [which is] in the mid to high hundreds, and even up to the thousands.” The genome-wide data sets generated by this work are available for use by other researchers through the SFARI website.

He also discussed the Simons Foundation Powering Autism Research for Knowledge (SPARK), a new SFARI research initiative working to recruit, phenotype, and genetically characterize 50,000 autistic individuals and their family members. This project includes collaboration with 21 university-affiliated research clinics in 18 states.

One of the key challenges is how access to such genetic and phenotype collections can be used to identify environmental risks. “We know about 60 percent of autism risk is genetic,” Lash said. “We want to better identify the environmental conditions that contribute [to the other 40 percent].”

Bioinformatic approaches

Troyanskaya uses computer science, statistical methods, and molecular biology to develop novel computational algorithms and systems to address important disease questions. She and her colleagues hope that understanding gene function and regulation in biological networks, in a cell-lineage and tissue-specific context, can lead to better understanding of complex human disease.

For example, she can combine a brain-specific functional network with known autism-associated genes to predict new ASD-gene associations, even for genes that have never before been detected in sequencing studies. Troyanskaya suggested that such associations may help direct future resequencing efforts, or analysis of whole-genome ASD data.

The computational analysis she performs to evaluate hypertension-associated genes combines a kidney-specific functional signal network with hypertension genome-wide association studies (GWAS). The technique is called Network-guided association study (NetWAS). “If you put functional genomics together with computational genetics, you can identify disease-associated genes a lot more accurately than if you use each by itself,” Troyanskaya said.

The approach can be applied to any GWAS, and more importantly, retains the unbiased nature of GWAS. Troyanskaya characterized NetWAS as discovery-driven, and because it does not depend on known disease-gene associations, it permits discovery of novel associations. “So it can be used with rare diseases or genetically undercharacterized processes, like, for example, environmental factors,” she said.

Environmental factors are, of course, of key interest to scientists at NIEHS, and teasing out the relative roles of exposures and genetics concerns both in-house scientists and grantees of the institute.

Citation: Greene CS, Krishnan A, Wong AK, Ricciotti E, Zelaya RA, Himmelstein DS, Zhang R, Hartmann BM, Zaslavsky E, Sealfon SC, Chasman DI, FitzGerald GA, Dolinski K, Grosser T, Troyanskaya OG. 2015. Understanding multicellular function and disease with human tissue-specific networks. Nat Genet. 47:569-576.

(Tara Ann Cartwright, Ph.D., is a former postdoctoral fellow in the NIEHS Intracellular Regulation Group).

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