| Literature DB >> 32778826 |
Yuan Luo1,2,3,4, Alal Eran5,6,7, Nathan Palmer6, Paul Avillach6, Ami Levy-Moonshine8, Peter Szolovits9, Isaac S Kohane10.
Abstract
The promise of precision medicine lies in data diversity. More than the sheer size of biomedical data, it is the layering of multiple data modalities, offering complementary perspectives, that is thought to enable the identification of patient subgroups with shared pathophysiology. In the present study, we use autism to test this notion. By combining healthcare claims, electronic health records, familial whole-exome sequences and neurodevelopmental gene expression patterns, we identified a subgroup of patients with dyslipidemia-associated autism.Entities:
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Year: 2020 PMID： 32778826 DOI： 10.1038/s41591-020-1007-0
Source DB: PubMed Journal: Nat Med ISSN： 1078-8956 Impact factor: 53.440