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Keywords:

  • neuregulin-1;
  • gene;
  • psychosis;
  • longitudinal;
  • depression;
  • primary care

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

A better understanding of the factors associated with psychotic symptoms could aid early identification and treatment of psychotic disorders. Previous studies have typically utilized cross-sectional study designs and have focused on individuals with psychotic disorders. Thus, examination of promising correlates of psychotic symptoms using longitudinal designs among more broadly defined populations is warranted. Two such correlates are neuregulin-1 (NRG1) genotypic variation and depression symptom severity. Both NRG1 and depression symptom severity have cross-sectional evidence for an association with psychosis but their affect on longitudinal patterns of psychotic symptoms and their potential interaction effects are less clear. Using repeated measures analysis of variance and covariance we modeled the main and interaction effects of NRG1 genotypic variation and depressive symptom severity on longitudinal psychotic symptom patterns in 301 primary care attendees assessed annually over 4 years. One-fifth (19.9%) of the participants reported one or more psychotic symptoms over the 4-year assessment period. We observed a curvilinear (i.e., cubic) association between depression symptom severity at baseline and longitudinal patterns of psychotic symptoms but did not observe a main effect for NRG1 genotypic variation on psychotic symptom patterns. However, NRG1 rs6994992 genotype moderated the curvilinear association between depression symptom severity and psychotic symptom patterns. Specifically, depression symptom severity had less of an effect on longitudinal psychotic symptoms among carriers of the rs6994992 TT genotype compared to CC and CT carriers. Our findings suggest a curvilinear association between depression symptom severity and longitudinal patterns of psychotic symptoms that is moderated by NRG1 genotype. © 2013 Wiley Periodicals, Inc.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

The expression of psychotic symptoms/experiences such as delusions and hallucinations are dynamic phenomena that fluctuate in intensity, severity, and duration within individuals over time [van Os and Murray, 2013]. However, studies examining factors associated with psychosis and/or psychotic symptoms typically utilize cross-sectional designs. Although these studies have identified promising correlates of psychotic symptoms, few of these correlates have been examined in longitudinal studies. Two examples are neuregulin-1 (NRG1) genetic variation and depression symptom severity.

NRG1 is one of the most promising genetic factors for both affective and non-affective psychosis [Blackwood et al., 2007]. Numerous genetic variants at both the 5′ and 3′ ends of the gene have been associated with psychosis onset [Hall et al., 2006; Keri et al., 2009; Bousman et al., 2013] and established psychotic disorders such as schizophrenia and bipolar disorder [Stefansson et al., 2002, 2003; Yang et al., 2003; Harrison and Law, 2006; Lachman et al., 2006; Thomson et al., 2007]. Likewise, major depressive disorder or depressive symptoms are commonly observed among individuals with psychotic disorders and a recent systematic review of the literature has suggested a strong link between depression and clinical and sub-clinical psychotic experiences [Hartley et al., 2013].

However, we lack evidence about the effect NRG1 genotypic variation and depression symptom severity have on longitudinal patterns of psychotic symptoms. It is also unclear whether NRG1 moderates the association commonly observed between depression and psychotic symptoms. Thus, the current study sought to address three questions: (1) Are NRG1 genotypic variants associated with longitudinal psychotic symptom patterns?; (2) Is depression symptom severity associated with longitudinal psychotic symptom patterns?; and (3) Does NRG1 genotype moderate the association between depression symptom severity and longitudinal psychotic symptom patterns?

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

Study Population

All participants were enrolled in the Diagnosis, Management and Outcomes of Depression in Primary Care (diamond) study, an ongoing longitudinal cohort that commenced in 2005 with an aim to document the experiences, health outcomes, treatment, and service use of primary care patients identified as having probable depression at screening [Gunn et al., 2008]. Full details of the study methods have been published elsewhere [Gunn et al., 2008, 2013; Potiriadis et al., 2008]. Briefly, primary care patients were eligible for the diamond cohort if they were: (a) aged 18–75 years, (b) able to read English, (c) not terminally ill, (d) did not reside in a nursing home, and (e) scored 16 or higher on the Center for Epidemiologic Studies Depression Scale [CES-D; Radloff, 1977]. Participants were assessed annually using postal surveys and/or computer-assisted telephone interviews. In 2007 (cohort year 3), assessment of psychotic symptoms commenced. In 2011 (cohort year 6), participants enrolled in the cohort were invited to provide a saliva sample for DNA extraction and genotyping. All procedures were conducted in accord with principles expressed in the Declaration of Helsinki and obtained approval from the University of Melbourne Human Research Ethics Committee.

Measures

Psychotic symptoms

The Psychosis Screening Questionnaire [PSQ; Bebbington and Nayani, 1995] was used to assess 12-month self-report psychotic symptoms (i.e., thought interference, paranoia, strange experiences, and hallucinations) in 2007 (T1), 2008 (T2), 2009 (T3), and 2010 (T4). In addition to examining each of the four symptoms, we created a binary variable (“any psychotic symptom”) that reflected the “presence” or “absence” of one or more psychotic symptoms at each assessment per procedures reported elsewhere [Johns et al., 2004]. A summary variable was also created that reflected an affirmative report of a psychotic symptom at any assessment (T1–T4).

Depression symptom severity

There is no agreed upon gold standard for measuring depression symptom severity in primary care settings. As such, depression symptom severity was measured at T1 using two measures: (1) Primary Care Evaluation of Mental Disorders Patient Health Questionnaire-9 (PHQ-9) [Kroenke et al., 2001], and (2) Center for Epidemiologic Studies Depression Scale (CESD) [Radloff, 1977]. Both measures assess depressive symptoms but do so over different time intervals (CESD: 1 week; PHQ-9: 2 weeks) and have different scoring ranges (CESD: 0–60; PHQ-9: 0–27). In addition, DSM–IV criteria for MDD was assessed at baseline using the Composite International Diagnostic Interview (CIDI) Auto version 2.1 [WHO, 1997] by a trained research assistant.

Potential confounding variables

Age, sex, highest level of completed education, age of depression onset, and use of antidepressants, anxiolytics, mood stabilizers, and antipsychotics were collected at T1.

Polymorphism Selection and Genotyping

We selected two non-synonymous NRG1 polymorphisms [rs6994992 (SNP8NRG243177) and rs10503929 (T973C; Met294Thr)] based on reports of consistent association with schizophrenia [Stefansson et al., 2002, 2003; Yang et al., 2003; Harrison and Law, 2006; Lachman et al., 2006; Thomson et al., 2007; Allen et al., 2008] and evidence of putative functional relevance from previous studies [Law et al., 2006; Yokley et al., 2012]. These two polymorphisms are located in the HapICE schizophrenia-risk haplotype and 5′ regions of NRG1, respectively; regions associated with schizophrenia [Mei and Xiong, 2008]. Although non-synonymous, rs6994992 has been associated with psychosis onset [Hall et al., 2006; Keri et al., 2009] and increased NRG1 type III expression [Law et al., 2006]; whereas rs10503929 has been associated with cognitive functioning [Yokley et al., 2012] and was the only NRG1 polymorphism of 13 assessed that was associated with schizophrenia in a recent meta-analysis [Allen et al., 2008].

DNA was recovered from stabilized saliva samples using the manual prepIT system according to manufacturer's instructions (Oragene DNA (OG-500); DNA Genotek Inc, Ontario, Canada). Genotyping was performed using standard procedures by the Australian Genome Research Facility, Ltd.

Statistical Analysis

The CubeX program [Gaunt et al., 2007] was applied to detect departures from Hardy Weinberg Equilibrium (HWE), determine minor allele frequency (MAF), and estimate pairwise linkage disequilibrium (LD) measures r2 and D′. To estimate the presence of population stratification, MAFs from the three HapMap phase III populations (Northern/Western European, CEU; Han Chinese, CHB; Yoruba in Nigeria, YRI) were extracted for both of the NRG1 SNPs and compared to the observed MAFs using chi-square analysis. Comparison of categorical and continuous baseline characteristics by genotypes was done using chi-square and analysis of variance (ANOVA), respectively. Repeated measures ANOVAs and ANCOVAs were used to model the main and interaction (i.e., moderation) effects of NRG1 and depressive symptom severity on longitudinal psychotic symptom patterns. All analyses were performed using PASW Statistics 18.0.2 (IBM, Armonk, NY).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

Of the 789 participants enrolled in the diamond cohort, 498 were enrolled at the time of DNA collection (cohort year 6) and 342 (69%) participants consented and returned a DNA sample. We excluded 38 (11%) individuals that returned their sample after genotyping had been completed and an additional three individuals who were missing genotype data for the two NRG1 SNPs. This resulted in 301 individuals included in the analysis (Table I).

Table I. Participant Characteristics at T1 (N = 301)
  1. MDD, major depressive disorder. CES-D, Center for Epidemiologic Studies Depression Scale. PHQ-9, Patient Health Questionnaire-9.

Age, mean (SD) years49.7 (12.1)
Sex, % (n) female68.8 (207)
Education, % (n) tertiary24.6 (74)
Medication use, % (n)
Antidepressant59.1 (178)
Anxiolytic24.9 (75)
Antipsychotic9.0 (27)
Mood stabilizer1.7 (5)
Depression measures
MDD diagnosis, % (n)49.2 (148)
CES-D score, mean (SD)19.5 (12.8)
PHQ-9 score, mean (SD)8.1 (6.0)
Depression age of onset, mean (SD)17.1 (19.9)
rs6994992, % (n)
CC34.9 (105)
CT48.8 (147)
TT16.3 (49)
rs10503929, % (n)
TT66.8 (201)
TC30.2 (91)
CC3.0 (9)

Both NRG1 SNPs were in HWE (P > 0.05), MAF ≥ 15% and were not in LD (r2 = 0.01 and D′ = 0.20). Comparison of MAFs from the HapMap phase III populations and the current sample showed MAFs for both SNPs examined did not differ from the HapMap CEU population (P-values >0.85) but did differ compared to CHB (P-values <0.001) and YRI (P-values <0.001) populations; suggesting the current sample is predominately of Northern/Western European descent (Supplementary Table I).

Sixty (19.9%) of the 301 participants reported one or more psychotic symptoms during the 4-year study period. The mean 12-month prevalence rate was 8.9% (standard error (SE) = 1.7%) with T1, T2, T3, and T4 prevalence rates of 9.0% (SE = 1.7%), 8.3% (SE = 1.6%), 10.3% (SE = 1.8%), and 8.3% (SE = 1.6%), respectively (Fig. 1).

image

Figure 1. Longitudinal patterns of psychotic symptoms. Bars represent the standard error of the mean.

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Are NRG1 Genotypic Variants Associated with Longitudinal Psychotic Symptom Patterns?

Psychotic symptom patterns did not differ by rs10503929 (F = 0.02, df = 1,299, P = 0.899) or rs6994992 (F = 0.95, df = 2,298, P = 0.387) (Supplementary Fig. 1). Additionally, individual PSQ psychotic symptom patterns did not differ by rs10503929 (thought interference: F = 0.67, df = 1,299, P = 0.415; paranoia: F = 0.32, df = 1,299, P = 0.573; strange experiences: F = 0.06, df = 1,299, P = 0.805; hallucinations: F = 0.73, df = 1,299, P = 0.394) or rs6994992 (thought interference: F = 1.14, df = 2,298, P = 0.321; paranoia: F = 0.57, df = 2,298, P = 0.562; strange experiences: F = 0.72, df = 2,298, P = 0.489; hallucinations: F = 0.23, df = 2,298, P = 0.794) genotype. Demographic and clinical characteristics by rs10503929 and rs6994992 genotypes showed no differences, with exception that rs10503929 CC/CT carriers were more likely to report use of a mood stabilizer and rs6994992 TT carriers were less likely to have a tertiary level of education (Supplementary Table II).

Is Depression Symptom Severity Associated with Longitudinal Psychotic Symptom Patterns?

A curvilinear association between depression symptom severity at T1 and psychotic symptom patterns was observed for both the CESD (Fcubic = 2.33, df = 51,249, P < 0.001; R2 = 0.63) and PHQ-9 (Fcubic = 2.03, df = 27,273, P = 0.002; R2 = 0.52) (Fig. 2). These observed associations remained after adjustment for age, sex, highest level of completed education, age of depression onset, and use of antidepressants, anxiolytics, mood stabilizers and antipsychotics (CESD: Fcubic = 2.19, df = 51,241, P < 0.001; PHQ-9: Fcubic = 1.95, df = 27,265, P = 0.004). Examination of depression symptom severity and individual psychotic symptoms showed similar trends for both CESD (thought interference: Fcubic = 1.75, df = 51,249, P = 0.003; paranoia: Fcubic = 2.68, df = 51,249, P < 0.001; strange experiences: Fcubic = 2.46, df = 51,249, P < 0.001; hallucinations: Fcubic = 1.76, df = 51,249, P = 0.002) and PHQ-9 (thought interference: Fcubic = 3.26, df = 27,273, P < 0.001; paranoia: Fcubic = 1.32, df = 27,273, P = 0.142; strange experiences: Fcubic = 2.21, df = 27,273, P = 0.001; hallucinations: Fcubic = 7.32, df = 27,273, P < 0.001).

image

Figure 2. Association between depression symptom severity using the (A) CESD and (B) PHQ-9 at assessment time point 1 (T1) and the proportion of the four annual assessments (T1–T4) where a psychotic symptom was endorsed. The fitted curvilinear (cubic method) line is solid and the 95% confidence intervals are represented by dashed lines.

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Does NRG1 Genotype Moderate the Association between Depression Symptom Severity and Longitudinal Psychotic Symptom Patterns?

NRG1 rs6994992 moderated the curvilinear association between CESD symptom severity and longitudinal psychotic symptom patterns (F = 1.50, df = 150,543, P < 0.001). Stratified analysis showed significant curvilinear associations for all rs6994992 genotypes (CC: F = 1.63, df = 123,189, P = 0.002, R2 = 0.38; CT: F = 1.87, df = 144,294, P < 0.001, R2 = 0.58; TT: F = 2.04, df = 84,60, P = 0.006, R2 = 0.22). However, only the carriers of the CC and CT genotypes resembled the curvilinear association observed in the full sample (Fig. 3). No other moderating effects were observed.

image

Figure 3. Association between depression symptom severity using the CESD at assessment time point 1 (T1) and the proportion of the four annual assessments (T1–T4) where a psychotic symptom was endorsed by NRG1 rs6994992 genotype. Lines represent the fitted curvilinear (cubic method) lines by genotype.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

We observed a curvilinear association between the two measures (CESD and PHQ-9) of depression symptom severity and longitudinal patterns of psychotic symptoms. No association between NRG1 genetic variation and longitudinal psychotic symptom patterns was observed but we did find rs6994992 genotype moderated the curvilinear association between CESD depression symptom severity and longitudinal psychotic symptom patterns.

The robust curvilinear association between depression symptom severity and psychotic symptom patterns that we observed is in concordance with numerous cross-sectional studies that have demonstrated consistent correlations between depression and psychotic symptom prevalence [Hartley et al., 2013]. Unlike previous studies, we show for the first time to our knowledge that depression symptom severity measured using two different depression scales explained a significant amount of the variance (R2 = 0.52–0.63) in longitudinal patterns of psychotic symptoms. If replicated, these findings suggest therapeutic interventions aimed at reducing depression symptom severity may also reduce the prevalence of psychotic symptoms via attenuating the risk for psychotic symptom development.

We did not detect an association between NRG1 genotype and psychotic symptom patterns. However, we did show that rs6994992 genotype moderated the curvilinear relationship observed between CESD depression symptom severity and psychotic symptom patterns. Specifically, our results suggest that among carriers of the TT genotype the curvilinear association observed in the full sample (Fig. 2) was absent. Previous studies have implicated the rs6994992 TT genotype with schizophrenia [Stefansson et al., 2002, 2003; Yang et al., 2003; Harrison and Law, 2006; Lachman et al., 2006; Thomson et al., 2007] and psychosis onset [Hall et al., 2006; Keri et al., 2009]; suggesting carriers of the TT genotype may be more susceptible to psychotic experiences regardless of their depression symptom profile. Importantly, no study to our knowledge has examined the potential moderating effects of any NRG1 variant on the association between depression and psychosis phenotypes. As such, replication of this finding is necessary before firm conclusion can be made.

A major strength of the study is that we assessed psychotic symptoms longitudinally within the primary care setting, a novel study design. However, two primary caveats of the current study should be considered. First, psychotic symptoms were measured using a self-report questionnaire developed with the purpose of screening individuals for psychotic conditions [Bebbington and Nayani, 1995]. Other studies have commonly used the 10 psychosis items from the Mini International Psychiatric Interview or the 17 core psychosis items from the CIDI [WHO, 1997], which are more comprehensive and more likely to detect psychotic symptoms compared to the PSQ. Thus, the sensitivity to detect an effect of NRG1 on psychotic symptom patterns was limited and our negative finding could represent a Type II error. Furthermore, clinically trained assessors did not interview participants and as such we were unable to determine the validity of the psychotic symptoms reported and/or the proportion of our sample with a psychotic disorder diagnosis. Second, we only examined two NRG1 polymorphisms and therefore cannot rule out the possibility that other polymorphisms in NRG1 are associated with psychotic symptom patterns. In fact, meta-analyses [Li et al., 2006; Munafo et al., 2006, 2008; Gong et al., 2009] suggest that specific NRG1 risk alleles are likely to vary between populations and more recently it has been suggested that the risk conveyed by sequence variation within NRG1 is likely not to be driven by one polymorphism but a diverse accumulation of nucleotide changes [Weickert et al., 2012].

Our findings provide an important extension to previous research by suggesting the longitudinal relationship between depression and psychosis symptoms is curvilinear and may be moderated by NRG1 genotype. These findings warrant further follow-up within independent longitudinal studies that employ clinically standardised measures of psychotic symptoms and adequately assess genetic variation across the entire NRG1 gene.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

The named authors submit this publication on behalf of the diamond study investigators which include: Prof. Jane Gunn, Prof. Helen Herrman, Prof. Mike Kyrios, A/Prof. Kelsey Hegarty, Prof. Christopher Dowrick, Dr. Gail Gilchrist, A/Prof. Grant Blashki, Prof. Dimity Pond, Dr. Patty Chondros, A/Prof. Renata Kokanovic and Dr. Victoria Palmer. The diamond study was initiated with pilot funding from the beyondblue Victorian Centre of Excellence and the main cohort has received project grant funding from the National Health and Medical Research Council (ID 299869, 454463, 566511 & 1002908). The collection of DNA and genotyping was funded by the LEW Carty Chartable Fund (ID 7284). No funding body had a role in study design; the collection, analysis, and interpretation of data; the writing of the manuscript; or the decision to submit this manuscript for publication. We acknowledge the 30 dedicated GPs, their patients and practice staff for making this research possible. We thank the cohort participants for their ongoing involvement in the study. We also thank the diamond project team and associate investigators involved in the study: A/Prof. Lena Sanci, A/Prof. Catherine Mihalopoulos, Ms. Maria Potiriadis, Ms. Konstancja Densley, Ms. Aves Middleton and the casual research staff.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  9. Supporting Information

Additional supporting information may be found in the online version of this article at the publisher's web-site.

FilenameFormatSizeDescription
ajmgb32206-sm-0001-SupFig-S1.tiff58KFigure S1 Longitudinal patterns of psychotic symptoms by (A) rs10503929 and (B) rs6994992 genotype. Bars represent standard error of the mean.
ajmgb32206-sm-0002-SupTab-S1.docx56K

Table S1 NRG1 minor allele frequencies and pairwise linkage disequilibrium.

Table S2 Participant characteristics by NRG1 rs10503929 and rs6994992.

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