Single molecule in situ hybridization reveals distinct localizations of schizophrenia risk-related transcripts SNX19 and AS3MT in human brain

Takahashi, Yōichirō; Maynard, Kristen R.; Tippani, Madhavi; Jaffe, Andrew E.; Martinowich, Keri; Kleinman, Joel E.; Weinberger, Daniel R.; Hyde, Thomas M.

doi:10.1038/s41380-021-01046-9

Cited by 6 publications

(1 citation statement)

References 44 publications

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“…Our Sherlock integrative analysis found 20 genes where expression changes may contribute to suicide risk, with nine of these genes having evidence of differential expression in psychiatric conditions, including schizophrenia (SCZ), autism spectrum disorder (ASD), depression, stress response, and neurodegeneration. Specifically, findings implicated variants associated with overexpression of SCZ-associated genes: SNX19 [ 55 – 58 ], CNN3 [ 59 , 60 ], BCAP29 (opposite direction of prior findings [ 61 ]), and IGF1R (opposite direction of prior findings [ 62 ]). ZNF501 was found to have diminished expression with the associated variant in this study, consistent with prior ASD [ 63 ] and depression studies [ 64 ].…”

Section: Discussionmentioning

confidence: 99%

Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes

Han,

DiBlasi,

Monson

et al. 2023

Mol Psychiatry

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Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e−06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.

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