Machine learning in schizophrenia genomics, a case-control study using 5,090 exomes.

Our hypothesis is that machine learning (ML) analysis of whole exome sequencing (WES) data can be used to identify individuals at high risk for schizophrenia (SCZ). This study applies ML to WES data from 2,545 individuals with SCZ and 2,545 unaffected individuals, accessed via the database of genotypes and phenotypes (dbGaP). Single nucleotide variants and small insertions and deletions were annotated by ANNOVAR using the reference genome hg19/GRCh37.

Prevalence of four Mendelian disorders associated with autism in 2392 affected families.

Autism spectrum disorder (ASD) is a neurobehavioral disorder with a heterogeneous genetic etiology. Based on the literature, several single-gene disorders, including Rett syndrome, Smith-Lemli-Opitz syndrome, PTEN hamartoma tumor syndrome and tuberous sclerosis, are associated with a high prevalence of ASD. We estimated the prevalence of these four conditions in a large cohort of patients using whole-exome sequencing data from 2392 families (1800 quads and 592 trios) with ASD from the National Database for Autism Research.

Inborn errors of metabolism associated with psychosis: literature review and case-control study using exome data from 5090 adult individuals.

A literature review was conducted, using the computerized "Online Mendelian Inheritance in Man" (OMIM) and PubMed, to identify inborn errors of metabolism (IEM) in which psychosis may be a predominant feature or the initial presenting symptom. Different combinations of the following keywords were searched using OMIM: "psychosis", "schizophrenia", or "hallucinations" and "metabolic", "inborn error of metabolism", "inborn errors of metabolism", "biochemical genetics", or "metabolic genetics". The OMIM search generated 126 OMIM entries, 40 of which were well known IEM.