Elsevier

Schizophrenia Research

Volume 198, August 2018, Pages 6-15
Schizophrenia Research

Deficient prepulse inhibition in schizophrenia in a multi-site cohort: Internal replication and extension

https://doi.org/10.1016/j.schres.2017.05.013Get rights and content

Abstract

Background

The Consortium on the Genetics of Schizophrenia (COGS) collected case-control endophenotype and genetic information from 2457 patients and healthy subjects (HS) across 5 test sites over 3.5 years. Analysis of the first “wave” (W1) of 1400 subjects identified prepulse inhibition (PPI) deficits in patients vs. HS. Data from the second COGS “wave” (W2), and the combined W(1 + 2), were used to assess: 1) the replicability of PPI deficits in this design; 2) the impact of response criteria on PPI deficits; and 3) PPI in a large cohort of antipsychotic-free patients.

Methods

PPI in W2 HS (n = 315) and schizophrenia patients (n = 326) was compared to findings from W1; planned analyses assessed the impact of diagnosis, “wave” (1 vs. 2), and startle magnitude criteria. Combining waves allowed us to assess PPI in 120 antipsychotic-free patients, including many in the early course of illness.

Results

ANOVA of all W(1 + 2) subjects revealed robust PPI deficits in patients across “waves” (p < 0.0004). Strict response criteria excluded almost 39% of all subjects, disproportionately impacting specific subgroups; ANOVA in this smaller cohort confirmed no significant effect of “wave” or “wave x diagnosis” interaction, and a significant effect of diagnosis (p < 0.002). Antipsychotic-free, early-illness patients had particularly robust PPI deficits.

Discussion

Schizophrenia-linked PPI deficits were replicable across two multi-site “waves” of subjects collected over 3.5 years. Strict response criteria disproportionately excluded older, male, non-Caucasian patients with low-normal hearing acuity. These findings set the stage for genetic analyses of PPI using the combined COGS wave 1 and 2 cohorts.

Introduction

Prepulse inhibition (PPI) of startle is a reliable, quantitative operational measure of sensorimotor gating that is deficient in several neuropsychiatric disorders, including schizophrenia (SZ) (Braff et al., 1978, Swerdlow et al., 2008). PPI deficits in SZ patients have been reported from a large number of laboratories in many different countries, using a variety of stimuli to elicit and inhibit startle, both within and across stimulus modalities (Aggernaes et al., 2010, Braff et al., 1978, Braff et al., 1999, Braff et al., 2001, Csomor et al., 2009, Hammer et al., 2011, Hammer et al., 2013, Hong et al., 2007, Kishi et al., 2012, Kumari et al., 1999, Kumari et al., 2007, Kunugi et al., 2007, Light et al., 2012, Ludewig et al., 2003, Mackeprang et al., 2002, Martinez-Gras et al., 2009, Meincke et al., 2004, Molina et al., 2011, Moriwaki et al., 2009, Oranje and Glenthøj, 2013, Preuss et al., 2011, Quednow et al., 2006, Rabin et al., 2009, Takahashi et al., 2008, Wang et al., 2013, Weike et al., 2000, Xue et al., 2012). PPI has robust heritability (Greenwood et al., 2007), and genes associated with PPI in SZ patients and healthy comparison subjects (HS) have been identified (Hong et al., 2008a, Petrovsky et al., 2010, Quednow et al., 2011, Greenwood et al., 2011, Greenwood et al., 2012, Roussos et al., 2016).

The Consortium on the Genetics of Schizophrenia (COGS) was designed to identify genes associated with SZ endophenotypes, using five geographically dispersed data collection sites. From July 2010, to February 2014, neurocognitive and neurophysiological endophenotypes as well as genetic material were collected from 1405 carefully characterized SZ patients and 1052 HS. Despite significant efforts in quality control and equipment and procedural standardization, this large, multi-site study presented challenges not faced in smaller, single-site studies of PPI in SZ, including site-based differences in sample demographics, methodologies and test conditions. Our quality assurance plan included an interim (circa January 2013) analysis of PPI data from the “first wave” of 1400 COGS subjects.

The results of the “first wave” (W1) analysis of PPI (Swerdlow et al., 2014) confirmed significant deficits in PPI in SZ patients. These deficits were sensitive to several moderating variables as previously reported in numerous “single site” PPI studies (e.g. Hong et al., 2008a, Hong et al., 2008b, Kumari et al., 1999, Kumari et al., 2004, Swerdlow et al., 2006a, Weike et al., 2000), including prepulse interval (deficits at 60 ms, but not 30 or 120 ms) and medications (deficits blunted by antipsychotics (“APs”)). We discussed opportunities and challenges created by PPI assessment in this multi-site platform. For example, embedded within this multi-site sample was the largest subgroup of AP-free SZ patients in which PPI had been tested, providing the opportunity for potentially novel insights into the nature of SZ-linked PPI deficits independent of drugs that are known to alter PPI. We also reported differences in the magnitude of PPI and SZ-linked PPI deficits across the 5 COGS sites, which created interpretative challenges, and at least in part may have reflected site-specific patterns of racial stratification.

Another challenge emerged from this W1 analysis: the use of strict response inclusion criteria (a “non-responder” defined as reflex magnitude < 10 units (1.31 μV/digital unit)) for either of the two trial blocks during which PPI was analyzed) resulted in the exclusion of over 40% of the test subjects. While PPI deficits were evident with or without the use of these exclusion criteria based on a minimal startle response magnitude, this large attrition rate became important in subsequent COGS analyses, when multiple endophenotypes were integrated across subjects to identify endophenotype “factors” or “pathways” (Seidman et al., 2015, Millard et al., 2016, Thomas et al., 2017). Conceivably, this substantive loss of subjects may also negatively impact the design and interpretation of upcoming COGS genetic analyses, in which PPI data will be used, together with results from all other COGS endophenotypes.

Multi-site PPI assessment in the COGS “second wave” (W2) was completed in February 2014. Here, we present the results of the inclusive W1 and W2 PPI assessments, with three goals: 1. To assess the replicability, over time, of SZ-linked PPI deficits within a multi-site study; 2. To assess the impact of reflex response magnitude exclusion criteria on usable sample size and predicted patterns of PPI; 3. Absent evidence of significant W1 vs. W2 differences, to combine W(1 + 2) samples to achieve adequate power to conduct informative analyses of moderating variables in larger subgroups of potential interest, including patients who were unmedicated and early in their illness.

Section snippets

Methods

Other than collection date, methods and procedures for W2 subject ascertainment and collection of W2 data were identical to that for W1. As described previously, COGS participants were recruited and tested at 5 sites: Mount Sinai School of Medicine, University of California Los Angeles, University of California San Diego, University of Pennsylvania and University of Washington. Participants were 18–65 years old and fluent in English. Inclusion and exclusion criteria for W2 subjects were

W1 vs. W2 subject characteristics

Demographic and clinical characteristics of COGS W1 vs. W2 subjects are seen in Table 1. W1 and W2 were comparable in proportions of patients vs. HS and men vs. women; subject age, patient age at illness onset and racial distributions were also comparable in W1 and W2. Across a number of metrics (number of hospitalization, SANS and SAPS), W2 patients were slightly but significantly more impaired, compared to W1 patients. The proportions of subjects tested at each of the 5 sites also differed

Discussion

The relative loss of sensorimotor gating in SZ patients vs. HS, as reflected by deficient PPI, has been detected in several dozen studies since the original observation by Braff et al. (1978) in Callaway's research group (e.g. Aggernaes et al., 2010, Braff et al., 1999, Braff et al., 2001, Braff et al., 2005, Csomor et al., 2009, Hammer et al., 2011, Hammer et al., 2013, Hong et al., 2007, Kishi et al., 2012, Kumari et al., 1999, Kumari et al., 2007, Kunugi et al., 2007, Light et al., 2012,

Conflict of interest

Drs. Braff, Calkins, Greenwood, RE Gur, RC Gur, Lazzeroni, Light, Radant, Seidman, Siever, Silverman, Stone, Sugar, Swerdlow, DW Tsuang, MT Tsuang and Turetsky report no financial relationships with commercial interests. Dr. Green reports having been a consultant to Abbott laboratories (AbbVie), Biogen, and Roche, he is a member of the scientific board for Mnemosyne, and he has received research funds from Amgen. Dr. Nuectherlein has received unrelated research support from Janssen Scientific

Contributors

Dr. Swerdlow supervised 5-site quality assurance for PPI measures, completed all statistical analyses and wrote the first draft of this manuscript. Joyce Sprock performed quality assurance for all data and coordinated database activities. All other authors participated in aspects of study design, including subject recruitment, phenotyping, and validation of the clinical and endophenotype data. All authors were responsible for reviewing and approving the final manuscript.

Role of funding source

Other than providing support, the NIH had no further role in this manuscript.

Acknowledgements

This study was supported by grants R01-MH065571, R01-MH065588, R01-MH065562, R01-MH065707, R01-MH065554, R01-MH065578, R01-MH065558, R01 MH86135, and K01-MH087889 from the National Institute of Mental Health.

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