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

Yuan Luo; Alal Eran; Nathan Palmer; Paul Avillach; Ami Levy-Moonshine; Peter Szolovits; Isaac S. Kohane

doi:10.1038/s41591-020-1007-0

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

Yuan Luo, Alal Eran, Nathan Palmer, Paul Avillach, Ami Levy-Moonshine, Peter Szolovits, Isaac S. Kohane

Department of Life Sciences

Research output: Contribution to journal › Article › peer-review

55 Scopus citations

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.

Original language	English
Pages (from-to)	1375-1379
Number of pages	5
Journal	Nature Medicine
Volume	26
Issue number	9
DOIs	https://doi.org/10.1038/s41591-020-1007-0
State	Published - 1 Sep 2020

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology

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AU - Kohane, Isaac S.

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

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