A multidimensional precision medicine approach identifies an autism subtype characterized by dyslipidemia

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. Integration of large datasets of familial whole-exome sequencing, neurodevelopmental gene expression, electronic health records and healthcare claims led to the identification of a subtype of autism spectrum disorder that is associated with lipid dysregulation.