What we learn from linking data

The NIH has launched the new Autism Data Science Initiative: https://dpcpsi.nih.gov/autism-data-science-initiative/funding-opportunities#section1, which brings questions about why linking different data sets is important. It can be done without including personal identifying information, and it should be done following ethical guidelines. If done correctly, using large datasets can answer questions relating to treatment, cause, better identification and personalized medicine for those on the spectrum. So what has linking data done for families? This week’s podcast summarizes longitudinal research that follows individuals across time, linking their information across different ages to look at factors that predict outcomes, environmental factors, and how to best support those on the spectrum.

https://pubmed.ncbi.nlm.nih.gov/40420626

https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-025-02739-4

https://pubmed.ncbi.nlm.nih.gov/40391067

https://pubmed.ncbi.nlm.nih.gov/40309015

https://pubmed.ncbi.nlm.nih.gov/40401338

attention attention…this is the INSAR 2023 summary

Last week in Stockholm, Sweden, 2200 researchers and scientists working to understand and help those on the spectrum, met to share their most recent findings and exchange ideas. What were the main takeaways as ASF saw them? We cover why some autistic people don’t want genetics to be studied, how to better engage families with IDD and who are non-speaking, females, adults, international studies and yes, diversity. The program book was released a day before the meeting and can be found here: https://cdn.ymaws.com/www.autism-insar.org/resource/resmgr/docs/annualmeeting/insar2023_program_book.pdf