- Identifying specific genetic links to addiction can improve treatment outcomes
- Big Red II+ supercomputer analyzed over 12 million genetic markers from 12,000 individuals
- Faster processing time allows geneticists to examine multiple traits
It’s no secret that substance abuse is on the rise in the United States. In 2016, more than 59,000 Americans died from drug overdoses, a 19 percent increase over 2015.
If researchers can identify the genetic traits that lead to addiction, health care experts could improve the chances of successful treatment.
But pinpointing these traits is not easy. There are over 20,000 to 25,000 protein-coding genes in the human genome. Finding the relevant gene can be as difficult as plucking the proverbial needle from the haystack.
This is where Big Red II+, Indiana University’s (IU) main system for high-performance parallel computing, comes into play. IU School of Medicine researcher Leah Wetherill used the supercomputer to perform a genetic analysis of 12,000 people to map genetic traits for addiction.
“High-performance computing gives us the ability to expand our analyses to include examining psychological disorders and behavioral traits that previously had to be ignored due to lack of computing power,” says Wetherill.
Wetherill and her team collected genetic information from three racial groups, including European Americans, African Americans, and a final group composed of Hispanics, Asians, Native Americans, and Pacific Islanders.
This large sample size created an enormous dataset to parse - in all, 12 million genetic markers were examined.
Using a supercomputer meant that the group ran analyses on the data much faster than when using other machines. They were able to inspect 10 traits in all three groups in a matter of days, instead of waiting for an entire month.
“I can submit jobs for the set of traits I want to analyze for the week, for all three racial groups. They all finish within days, and all jobs complete with no incomplete output files and no failed jobs,” says Wetherill. “This has literally changed our computing life!”
Big Red II+’s computational powers allow Wetherill to review several genetic markers potentially related to biological measures of alcohol use, such as tolerance, withdrawal, incidence of seizures, flushing, and craving alcohol when one can’t drink.
“Now that we can reliably run these analyses, and run them faster, we can expand our repertoire of traits of interest, especially for the psychological and behavioral traits which we previously did not consider,” says Wetherill.
Wetherill and her team now aim to run further surveys in the goal of pinpointing the exact genetic traits for addiction.
“We already have a growing list of additional aspects that our colleagues would like to have analyzed, and we plan to continue these analyses in the months to come,” says Wetherill.
Addiction is a complex trait which likely involves multiple genes. But with more Americans suffering from substance abuse every day, and millions more affected by the addiction of a family member, identifying specific parts of the human genome that contribute to addiction is more important than ever.
This epidemic of addiction is not limited to the US—research shows that addiction rates are rising and devastating communities worldwide. Thanks to Wetherill and her group’s research, health practitioners are one step closer to combating this deadly trend.