Biostatistics approach to genetics yields new clues to roots of autism

Biostatistics approach to genetics yields new clues to roots of autism

Researchers have developed a statistical method for genetic screens that improves the classic genome-wide association screen, and, applying to autism, have uncovered genes related to the disorder that had not been suggested in previous analyses. The scientists offer evidence that beginning treatment in infants at the first symptoms could change the course of the disease, possibly preventing the permanent “pruning” of neurons, which occurs during the first two years of life, from cementing autistic symptoms in place.

via Top Health News — ScienceDaily:

A study is only as good as the tools used to analyze it. One of those tools is statistics, and while biologists and chemists set up and run the experiments, statisticians are at work tinkering with the math that makes sense of all the data. Researchers at The Rockefeller University have recently developed a novel statistical method for genetic screens, which takes advantage of recent increases in computing power. Applying it to autism, they have uncovered genes that had not been suggested in previous analyses.By crunching data from the genomes of hundreds of individuals with various degrees of autism, the researchers identified several functionally related genetic variations that they say are likely to be linked to autism or to the underlying pathology of neuronal development that may cause it.The work suggests that beginning treatment in infants at the first symptoms, around the age of 12 months, could change the course of the disease. Catching the disorder early, the researchers say, could prevent the permanent “pruning” of neurons, which occurs during the first two years of life, from cementing autistic symptoms in place. The researchers also say that their data-scouring methodology may be used to help identify previously unknown genetic causes of other diseases, even in cases where data has already been exhaustively analyzed.The research, led by Knut Wittkowski, biostatistician in the Center for Clinical and Translational Science at The Rockefeller University Hospital, is a twist on a traditional data-mining technique known as a genome-wide association study. By comparing DNA from groups of people with a certain illness to those without it, the technique identifies genetic variations that are associated with the disease. Conventional analyses look for individual mutations called SNPs — single-nucleotide polymorphisms. But looking for individual blips in the genetic code did not prove a reliable way to identify risk factors for early-onset diseases like autism. Wittkowski’s method looks not just at individual SNPs, but at combinations of several SNPs — the equivalent of looking at whole words rather than just the single letters that form them.Wittkowski applied this “multivariate” approach to data from studies of autism as well as studies of childhood absence epilepsy, a condition that turns out to have a similar genetic profile.First, looking at a study of 185 cases of childhood epilepsy, Wittkowski’s team found that mutations in genes that control axonal guidance and calcium signaling — both of which are important early in the developing brain when neurons are forming the appropriate connections — led to increased chances of having the disorder. …

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Top Health News — ScienceDaily

Biostatistics approach to genetics yields new clues to roots of autism

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