A Gene-Based Analysis of Acoustic Startle Latency.

Alicia K Smith,Nicholas Massa,Samuel S Lee,Bruce Cuthbert,Varun Kilaru,Kerry J Ressler,Seth Davin Norrholm,Bekh Bradley,Tanja Jovanovic,Lauren Gensler,Adriana Lori,Erica Duncan

doi:10.3389/fpsyt.2017.00117

Abstract

Latency of the acoustic startle response is the time required from the presentation of startling auditory stimulus until the startle response is elicited and provides an index of neural processing speed. Latency is prolonged in subjects with schizophrenia compared to controls in some but not all studies and is 68–90% heritable in baseline startle trials. In order to determine the genetic association with latency as a potential inroad into genetically based vulnerability to psychosis, we conducted a gene-based study of latency followed by an independent replication study of significant gene findings with a single-nucleotide polymorphism (SNP)-based analysis of schizophrenia and control subjects. 313 subjects from an urban population of low socioeconomic status with mixed psychiatric diagnoses were included in the gene-based study. Startle testing was conducted using a Biopac M150 system according to our published methods. Genotyping was performed with the Omni-Quad 1M or the Omni Express BeadChip. The replication study was conducted on 154 schizophrenia subjects and 123 psychiatric controls. Genetic analyses were conducted with Illumina Human Omni1-Quad and OmniExpress BeadChips. Twenty-nine SNPs were selected from four genes that were significant in the gene-based analysis and also associated with startle and/or schizophrenia in the literature. Linear regressions on latency were conducted, controlling for age, race, and diagnosis as a dichotomous variable. In the gene-based study, 2,870 genes demonstrated the evidence of association after correction for multiple comparisons (false discovery rate < 0.05). Pathway analysis of these genes revealed enrichment for relevant biological processes including neural transmission (p = 0.0029), synaptic transmission (p = 0.0032), and neuronal development (p = 0.024). The subsequent SNP-based replication analysis revealed a strong association of onset latency with the SNP rs901561 on the neuregulin gene (NRG1) in an additive model (beta = 0.21, p = 0.001), indicating that subjects with the AA and AG genotypes had slower mean latency than subjects with GG genotype. In conclusion, startle latency, a highly heritable measure that is slowed in schizophrenia, may be a useful biological probe for genetic contributions to psychotic disorders. Our analyses in two independent populations point to a significant prediction of startle latency by genetic variation in NRG1.

Highlights

Schizophrenia is a psychiatric disorder associated with significant morbidity, mortality, and global burden of disease with a preva lence estimated at 1% of the general population [1, 2]
Independent Replication Sample of Veterans Affairs Subjects. We focused on these genes in a single-nucleotide polymorphism (SNP)-based replication study on the Atlanta Veterans Affairs Medical Center (VA) cohort, which consisted of 324 subjects, of whom 185 had schizophrenia and 139 were psychiatric controls
We conducted a SNP-based follow-up study on an independent sample targeting genes expressed in the pons, a region that mediates startle, and known from prior work to be associated with schizophrenia, schizophrenia endophenotypes, or acoustic startle

Summary

Introduction

Schizophrenia is a psychiatric disorder associated with significant morbidity, mortality, and global burden of disease with a preva lence estimated at 1% of the general population [1, 2]. Recent genome-wide association studies (GWAS) have made promising steps in identifying independent genomic loci that infer polygenic lifetime risk and heritability to schizophrenia [4,5,6], but challenges remain in fully deciphering the genetic component of the disease. The advantage of using endophenotypes to study psychopathology is threefold: first, it reduces the complexity of symptoms and multifaceted behaviors by using quantitative units of measurement; second, a quantitative approach allows more power to detect linkage and is ideal for quantitative trait linkage analysis; third, relatively simpler phenomena involve fewer genes to produce functional abnormalities as compared to psychiatric diagnoses such as schizophrenia. The association between the endophenotype and the genes in question should be stronger than the association to the illness itself when discovered by candidate gene analysis [7, 8]

Methods

Results

Conclusion