The figures speak for themselves. They show that around 10\u201315 per cent of all strokes occur in people under 50, with a higher prevalence among young women. Above all, in terms of trends, studies are confirming that ischaemic stroke in young adults is on the rise due to increased exposure to classic risk factors such as high blood pressure, dyslipidaemia, diabetes, smoking and being overweight. But the more research progresses, the more important it becomes to understand that we need to look beyond these factors \u2013 including the impact of alcohol and illicit drugs \u2013 to grasp the extent to which, and the ways in which, genetic predisposition plays a role, by combining an individual\u2019s DNA information with lifestyle factors and other variables. Artificial Intelligence is needed to bring all these elements together.<\/p>\n
And it is precisely an AI model tailored to this issue (starting with the genetic component) that experts at the University of Technology Sydney have developed, presenting their work in Computer Methods and Programs in Biomedicine (first author Yue (Eric) Yang). The system analyses a person\u2019s DNA to identify genetic risk factors for stroke with greater accuracy, paving the way for risk assessments tailored to each individual, partly by combining this data with traditional risk factors.<\/p>\n
The variants under consideration<\/p>\n
According to Yang, this is a unique AI algorithm because \u201cit not only identifies genetic variants linked to stroke, but also takes into account their location in the genome and possible interactions \u2013 as the researcher states in a note from the Australian university \u2013\u201d. For the record, the prototype was tested using genetic and health data from the UK Biobank database, comparing it with medical records from a large US database (All-of-Us). It proved to be more accurate than previous genetic risk assessment tools in distinguishing between people who had suffered a stroke and those who were healthy. In particular, the analysis identified 18 different genetic variants associated with ischaemic stroke. It was found that those with a higher genetic risk score were 22 per cent more likely to suffer a stroke than the control group. In particular, there appears to be a gene in the cerebral cortex that represents a key factor in susceptibility to ischaemic stroke. It is called EDEM2 and could provide a specific target for further biological research into the causes of stroke. For the record, the Australian experts used the same technology that underpins large-scale language models such as ChatGPT to train the model on thousands of genetic variants and identify links with ischaemic stroke.<\/p>\n
Ictus, rischia 1 persona su 4. Ecco i sintomi e cosa fare<\/p>\n
Predictive medicine<\/p>\n
We would like to reiterate this. Genetics is only one part of the risk profile. This is why the ability to combine a genetic score with clinical and lifestyle information \u2013 including known risk factors such as blood pressure, age, atrial fibrillation, type 2 diabetes and cholesterol \u2013 could improve monitoring and prevention by designing a personalised pathway, and not just for young people. And this is precisely the aim of the research, with experts turning to AI to identify associations between genes and diseases and to develop personalised risk assessments for targeted prevention. The aim is therefore to develop a multimodal tool based on artificial intelligence capable of combining a genetic risk assessment with other types of data, including health and lifestyle questionnaires, scans and diagnostic images.<\/p>\n
The future? As reported by Kairui Guo, who collaborated with the dedicated unit at Liverpool Hospital in Sydney on the analysis of genomic data and the application of artificial intelligence to the management of acute stroke, alongside Dennis Cordato, AI will help to understand the actual risk faced by the relatives of stroke patients, particularly those who suffer a stroke at a young age. \u201cWe have a proposal for a preventive clinical trial,\u201d says Guo. \u201cThe aim is to recruit the first cohort of patients, sequence their genomes and analyse their risk of stroke. We are also interested in gender differences in stroke risk between men and women.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"The figures speak for themselves. They show that around 10\u201315 per cent of all strokes occur in people…\n","protected":false},"author":2,"featured_media":894415,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50],"tags":[200,79],"class_list":["post-894414","post","type-post","status-publish","format-standard","has-post-thumbnail","category-genetics","tag-genetics","tag-science"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/894414","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=894414"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/894414\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/894415"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=894414"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=894414"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=894414"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}