Summary: Using machine learning technology, researchers concluded the risk of genetic risk may outweigh age as a predictor of whether a person will develop Alzheimer's disease. Once adults reach age 65, the threshold age for the onset of Alzheimer's disease, the extent of their genetic risk may outweigh age as a predictor of whether they will develop the fatal brain disorder, a new study suggests. The study, published recently in the journal Scientific Reports, is the first to construct machine learning models with genetic risk scores, non-genetic information and electronic health record data from nearly half a million individuals to rank risk factors in order of how strong their association is with eventual development of Alzheimer's disease. Researchers used the models to rank predictive risk factors for two populations from the UK Biobank: White individuals aged 40 and older, and a subset of those adults who were 65 or older. Results showed that age – which constitutes one-third of total risk by age 85, according to the Alzheimer's Association – was the biggest risk factor for Alzheimer's in the entire population, but for the older adults, genetic risk as determined by a polygenic risk score was more predictive.

Once adults reach age 65, the threshold age for the onset of Alzheimer's disease, the extent of their genetic risk may outweigh age as a predictor of whether they will develop the fatal brain disorder, a new study suggests. The study, published recently in the journal Scientific Reports, is the first to construct machine learning models with genetic risk scores, non-genetic information and electronic health record data from nearly half a million individuals to rank risk factors in order of how strong their association is with eventual development of Alzheimer's disease. Researchers used the models to rank predictive risk factors for two populations from the UK Biobank: White individuals aged 40 and older, and a subset of those adults who were 65 or older. Results showed that age – which constitutes one-third of total risk by age 85, according to the Alzheimer's Association – was the biggest risk factor for Alzheimer's in the entire population, but for the older adults, genetic risk as determined by a polygenic risk score was more predictive. "We all know Alzheimer's disease is a later-onset disease, so we know age is an important risk factor. But when we consider risk only for people age 65 or older, then genetic information captured by a polygenic risk score ranks higher than age," said lead study author Xiaoyi Raymond Gao, associate professor of ophthalmology and visual sciences and of biomedical informatics in The Ohio State University College of Medicine.

Emerging technology has the potential to add efficiency and effectiveness to healthcare, according to Eric Topol, MD. Capabilities such as artificial intelligence, polygenic risk scores and digital health technology can equip physicians to improve and reduce the cost of care, while enabling them to better connect with patients, said Topol, the founder and director of The Scripps Research Institute. Much of care today is not based on provable facts, Topol noted at Liberation 2019, the annual meeting of Medecision, in Frisco, Texas. He cited an article by Hannah Fry, MD, published last month in The New Yorker, which detailed research that found that, of every 1,000 people taking statins for heart conditions over five years, only 18 will avoid a major heart attack or stroke. "Patients and clinicians exist in a world of insufficient data," Topol said.

Genes carry the information that make you you. So it's fitting that, when sequenced and stored in a computer, your genome takes up gobs of memory--up to 150 gigabytes. Multiply that across all the people who have gotten sequenced, and you're looking at some serious storage issues. If that's not enough, mining those genomes for useful insight means comparing them all to each other, to medical histories, and to the millions of scientific papers about genetics. Sorting all that out is a perfect task for artificial intelligence.

The genetic risk for autism exists in every person, scientists today revealed. As a result, the principal signs of autistic spectrum disorder (ASD) are seen in each individual - just to varying degrees. Those with the most severe symptoms are the proportion of the population officially diagnosed with ASD, the scientists from the University of Bristol, Harvard and MIT and Massachusetts General Hospital found. They set out to identifying if there is a genetic relationship between ASD and ASD-related traits in people not considered to have ASD. Their findings reveal the risk underlying ASD affects a range of behavioural and developmental traits in all people.