The interaction of GSK3B and FXR1 genotypes may influence the

mania and depression dimensions in mood disorders

Running title : GSK3B - FXR1 genotypes and mood disorder

Alexandre Bureaua,b,*, Jean Martin Beaulieua,c,d, Thomas Paccaleta, Yvon C. Chagnona,c and

Michel Maziadea,c

a Centre de recherche de l’Institut universitaire en santé mentale de Québec du Centre

intégré universitaire en santé et services sociaux de la Capitale-Nationale, Québec, Canada; b

Département de médecine sociale et préventive, Université Laval, and c Département de

psychiatrie et neurosciences, Université Laval, Québec, Canada

d Department of Pharmacology and toxicology, University of Toronto, Toronto, Ontario,

Canada.

* Correspondence:

Alexandre Bureau, Département de médecine sociale et préventive, Université Laval,

Pavillon Ferdinand-Vandry, 1050, avenue de la Médecine, Room 2457, Quebec City, Quebec,

G1V 0A6, Canada.

Phone : 1-418-656-2131 ext. 3342

Fax : 1-418-656-5491

Email: alexandre.bureau@msp.ulaval.ca

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Abstract

Background: Previous evidence in healthy subjects suggested that functional

polymorphisms GSK3B rs12630592 and FXR1 rs496250 interact in regulating mood and

emotional processing. We attempted to replicate this interaction primarily on manic and

depressive dimensions in mood disorder patients, and secondarily on schizophrenia

patients, diagnosis itself and age of onset.

Methods: Symptom dimensions were derived from the Comprehensive Assessment of

Symptoms and History 82 items rated lifetime in acute episodes and stabilized interepisode

intervals in 384 patients from the Schizophrenia and Bipolar Disorder Eastern Quebec

Kindred Study. Linear mixed effect models of symptom dimensions included rs12630592-

rs496250 main and interaction fixed effects (obtained from TaqMan genotypes), and a

polygenic random effect. The distribution of lifetime best-estimate DSM-IV diagnosis of 855

kindred members was studied versus genotype under a polytomous logistic model.

Results: In mood disorder patients, the level of mania (in both acute and stabilized periods)

and depression in stabilized periods was positively associated with GSK3B rs12630592 T

only in FXR1 rs496250 A-allele carriers (Bonferroni-corrected interaction p=0.024, 0.052

and 0.017 respectively). The two polymorphisms explained 11% of mania variance and 5%

of interepisode depression variance. The association was observed neither in schizophrenia

patients nor with the psychotic dimension in mood disorder patients. Interaction with the

diagnosis distribution (p=0.03) was driven by the decreasing prevalence of recurrent major

depression with rs12630592 T also only in carriers of rs496250 A.

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Limitations: Sample size was limited, but power was sufficient to detect the tested

interaction effect in this replication sample.

Conclusions: We replicate in affective patients an interaction between the FXR1 rs496250

and GSK3B rs12630592 polymorphisms in regulating mood dimensions.

Word count: 250

Key words: age of onset; bipolar disorder; epistasis, genetic; Fragile X autosomal homolog

1, Glycogen Synthase Kinase 3; lithium

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Introduction1

Genome wide association studies have identified numerous genetic risk alleles for mental

illnesses like bipolar disorder (BD) and schizophrenia (SZ) (Hou et al., 2016; Schizophrenia

Working Group of the Psychiatric Genomics, 2014). However, individual allelic variations

explain only a very small proportion of risk and established risk indicators individually

showed weak odds ratios (ORs) to predict the development of the illness (Paccalet et al.,

2016). The investigation of functional interactions between genetic factors becomes an

imperative step to further understand individual risk and increase power to develop

translational applications in the clinic (Beaulieu, 2012; Paccalet et al., 2016). Another area

of new inquiry focuses on symptom dimensions as alternative phenotypes to diagnoses that

may also accelerate our understanding of the genetic underpinning of major psychoses

(Labbe et al., 2012).

Functional interaction between the glycogen synthase kinase 3 (GSK3B) and Fragile X

mental retardation homolog 1 (FXR1) genes is suggested by previous findings (Del'Guidice

et al., 2015). Inhibition of glycogen kinase 3 (GSK3) is a potential component of the

mechanism underlying the clinical effectiveness of mood stabilizers (Beaulieu et al., 2009;

Beaulieu et al., 2008a; Klein and Melton, 1996). GSK3 is a serine threonine kinase existing

under two isoforms respectively encoded by the GSK3A and GSK3B genes (Woodgett, 2001).

Several studies in animal models also support a central role for GSK3 activity in regulating

1 Abbreviations BD: Bipolar disorder; FXR1: Fragile X autosomal homolog 1; GEE: generalized estimating equation; GSK3B: glycogen synthase kinase 3; NAAR: non-affected adult relative; OR: Odds ratio; RMDD: recurrent major depressive disorder; SAD: Schizoaffective disorder; SNP: single nucleotide polymorphism; SZ: Schizophrenia.

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different behavioural dimensions including mood, cognition and social processes (Beaulieu

et al., 2008b; Jope, 2011). However, how GSK3 activity can contribute to clinical symptoms

and drug responsiveness in human populations with heterogeneous genetic makeups

remains poorly understood.

The Fragile X mental retardation homolog 1 (FXR1) is an RNA binding proteins that was

identified as a substrate of GSK3. A previous study has shown that FXR1 levels are

upregulated by chronic treatment with mood stabilisers, lithium, valproic acid or

lamotrigine in rodents (Del'Guidice et al., 2015). Elevated levels of FXR1 also replicate

behavioral responses to mood stabilizers in mice.

Functional polymorphisms GSK3B rs12630592 and FXR1 rs496250 have been shown to

interact in regulating mood and emotional processing in healthy humans (Del'Guidice et al.,

2015) but no study yet has approached the question in patients with mood disorders.

Furthermore, genetic variants of FXR1 have been associated to risk of SZ in a large genome

wide association study and functional evidences support an involvement for FXR1 in

regulating behavioural dimensions in this illness (Del'Guidice et al., 2015; Hauberg et al.,

2016; Schizophrenia Working Group of the Psychiatric Genomics, 2014; Stepniak et al.,

2015).

Here, we examined in mood disorder patients the interaction between GSK3B rs12630592

and FXR1 rs496250 genotypes by focusing on the manic and depressive symptom

dimensions in an Eastern Quebec kindred sample densely affected by major psychosis

disorders (Maziade et al., 2005). As secondary objectives, we examined the same

interaction in relation to the diagnosis distribution and age of onset in the kindred sample.

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Furthermore, given that mood stabilizers inhibit GSK3 activity and increase levels of FXR1,

we explored the relationship between GSK3B and FXR1 genotypes, medication and

symptom dimensions.

Methods

Study subjects and phenotype definition

The kindred sample consisted of 855 members of 48 multigenerational families from the

Eastern Quebec population. All subjects were Caucasian of French-Canadian ancestry. A

lifetime best-estimate DSM-IV diagnosis was stringently made using personal interview,

information from relatives and the review of lifetime in- and out-patient medical records

according to a method extensively detailed previously (Maziade et al., 1992; Roy et al.,

1997). In brief, four research psychiatrists reviewed blindly all available information across

lifetime from different sources (all medical records, family informant interviews, personal

structured interview). We considered the following major psychosis diagnoses: Mood

disorders including BD I, BD II and recurrent major depressive disorder (RMDD); a broad

definition of SZ including SZ per se, schizophreniform disorder and schizotypal personality;

and schizoaffective disorder (SAD). We formed a comparison group with the genotyped

non-affected family members satisfying the following criteria: A) absence of the above

diagnoses, B) age greater or equal to 25 years and C) not the parent of a patient, and these

subjects were referred to as non-affected adult relatives (NAARs). Age of onset was defined

as the age of the first probable episode of the disorder. If unavailable, the age of the first

definitive episode was used. The number of subjects in each diagnosis category is in Table

1.

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Ethics

The study was explained to each family member, unrelated cases and controls, and a signed

consent was obtained, as reviewed by our University Ethics Committee.

Lifetime symptoms assessment

The lifetime presence and severity of psychotic, manic and depressive symptoms was

evaluated on a six-point rating scale (each point corresponding to an operational definition

of severity adapted for each symptom - 0: None, 1: Questionable, 2: Mild, 3: Moderate, 4:

Marked, 5: Severe) on the 82 items of the Comprehensive Assessment of Symptoms and

History (CASH) instrument (Andreasen et al., 1992). Items cover 11 dimensions: Delusion,

Hallucination, Bizarre behavior, Catatonia, Thought disorder, Alogia, Anhedonia, Apathy,

Affective blunting, Mania and Depression. Item-specific ratings were averaged for each

dimension. Catatonia was excluded as it exhibited very limited variability across subjects.

The differences from the original CASH assessment scale were: 1) the rating was based not

only on interviews, but also on an estimate of the lifetime presence (across the whole

duration of illness) and severity of each symptom that was based on all available sources

used for making the best-estimate diagnosis (i.e., the SCID personal interview, family

history interviews from several family informants, and all available medical records whose

access is made possible by the universal public health system of Québec, Canada ), and 2)

symptoms were rated separately for two time frames: lifetime acute episodes and lifetime

stabilized interepisode intervals. The reliability and details of the procedure are provided in

Maziade et al. (Maziade et al., 1995).

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Medication

Information on lifetime medication for all patients was extracted from all available medical

records. We defined indicator variables of having ever taken three types of medications:

lithium, anti-depressors and neuroleptics. Other types of medication were taken by few

subjects and were not considered.

Genotyping

Genotyping of GSK3B rs12630592 and FXR1 rs496250 was done on a realtime PCR

(Lightcycler 480 ; Roche) using the specific 5’_ nuclease Taq Man assays C_1029492_10 for

FXR1 and C_ 1849026_20 for GSK3B (proprietary sequences Life Technologies). For both

SNPs, PCR was made using 0.5 ul of 10X PCR MasterMix (Roche), 0.25 ul 40X TaqMan assay,

50 ng DNA in a final volume of 5 ul. PCR run included a denaturing step of 10 min at 95°C

followed by 35 PCR cycles (1 min 95°C, 1 min 55°C, 1 min 72°C). Mendelian inheritance was

checked using the computer software PedCheck (O'Connell and Weeks, 1998), and 10%

blind replicates were included for genotyping quality control.

Statistical analysis

Given the low frequency of the FXR1 rs496250 A allele, we followed Del’Guidice et al.

(Del'Guidice et al., 2015) in combining the AG and AA genotypes into the “A carrier”

category (dominant coding). For GSK3B rs12630592, we adopted an additive model of the

number of T alleles based on the phenotype-genotype relationship observed in healthy

subjects (Del'Guidice et al., 2015). Association between symptom dimensions and genotypic

variables was studied using linear mixed effect models with the genotypic variables and

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their interaction term as fixed effects and a polygenic random effect to capture residual

familial correlation. The proportion of total variance (additive genetic plus residual

variance) explained by the genotypic variables was estimated by taking the difference of the

total variance of the null model and the total variance of the model with genotypic

variables. Association between the diagnosis distribution (RMDD, BD, SAD, SZ vs. NAARs)

and genotypic variables was studied using a polytomous logistic model estimated using

generalized estimating equations (GEEs) with an independence working correlation

structure between the subjects in the same family and an empirical standard error estimate

robust to intra-familial correlation (Zeger et al., 1988). All analyses were redone with age

and sex as covariates in the models. Since results were very similar with and without

adjusting for age and sex, we report the unadjusted results only. Association between the

prevalence of each type of medication and genotypic variables was evaluated using log

binomial models fitted using Poisson GEEs with robust standard error estimates.

Multiple testing corrections

Our primary objective was based on the apriori hypothesis that the genetic interactions

would be in relation with two symptom dimensions (mania and depression) given GSK3B

rs12630592 and FXR1 rs496250 have been shown to interact in regulating mood and

emotional processing in healthy humans. Since these two dimensions were assessed in two

states (acute episodes and stabilized interepisode intervals), we applied a Bonferroni

correction to the interaction p-values of these four analyses. The analyses of the eight other

symptom dimensions in mood disorder patients and of all ten symptom dimensions in SZ

patients, all in two states, were secondary analyses to test the specificity of the interactions

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with the two former dimensions. A Bonferroni correction for 36 tests was applied to these

secondary analyses. Our secondary objectives of testing genetic interaction with the

diagnosis distribution and with age of onset involved a single analysis each, and our

analysis of medication was exploratory, so no multiple testing correction was applied on

the interaction tests for these additional analyses. A correction for testing association to

GSK3B rs12630592 within the two genotype categories of FXR1 rs496250 was applied

throughout.

Results

GSK3B - FXR1 interaction on mania and depression

In mood disorder patients we detected a statistically significant interaction between the T

allele of GSK3B rs12630592 and the A allele of FXR1 rs496250 in association with the

severity level of the mania symptom dimension in acute episodes, and a nearly statistically

significant one in stabilized interepisode intervals (Figure 1A and B). We also detected the

same interaction in association with the level of the depression dimension in stabilized

intervals but not in acute episodes (Figure 1C and D). The interaction pattern was the same

for the mania or the depression dimension in stabilized intervals: the severity level of the

symptom dimension increased with the number of GSK3B rs12630592 T alleles only in

carriers of the A allele of FXR1 rs496250, such that the subjects who are homozygote TT for

GSK3B rs12630592 and carriers of the A allele of FXR1 rs496250 had the highest severity of

symptoms. By contrast, subjects carrying GSK3B rs12630592 T alleles with the FXR1

rs496250 GG genotype, or carrying the FXR1 rs496250 A allele with the GSK3B rs12630592

GG genotype, had symptom severities similar to subjects with the reference GSK3B

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rs12630592 GG - FXR1 rs496250 GG genotype. The SNPs rs12630592 and rs496250 and

their interaction explained 11% of the total variance of the manic symptom dimension (in

acute and in stabilized periods) and 5% of the total variance of the depression symptom

dimension in stabilized periods.

Specificity of the GSK3B - FXR1 interaction

To check the specificity of the interaction effect on the mania and the depression

dimensions, we examined in the mood disorder patients the relation with psychotic

symptom dimensions, and found no significant interaction between the combinations of

GSK3B rs12630592 and FXR1 rs496250 genotypes, whether in acute (Figure S1) or

stabilized periods (Figure S2). We did the same in the SZ patients and we observed no

significant interaction of the combinations of GSK3B rs12630592 and FXR1 rs496250

genotypes in relation with either the manic, depressive or psychotic symptom dimensions,

whether in acute (Figure S3) or stabilized periods (Figures S4).

GSK3B - FXR1 interaction on diagnosis distribution

Another way to examine the interacting effects of GSK3B and FXR1 is to consider the

prevalence of various major psychosis diagnoses as a function of GSK3B rs12630592 and

FXR1 rs496250 genotypes. A statistically significant interaction between the T allele of

GSK3B rs12630592 and the A allele of FXR1 rs496250 was then detected in relation to the

diagnosis distribution in the sample (p interaction = 0.04). The T allele of GSK3B

rs12630592 was associated with the diagnosis distribution only in FXR1 rs496250 A

carriers (p = 0.03, Figure 2 and Table 1). This association was driven mainly by the

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decreasing prevalence of RMDD with the number of GSK3B rs12630592 T alleles, to the

point that no RMDD case was observed among the 30 GSK3B rs12630592 TT homozygotes

who are also FXR1 rs496250 A carriers. By contrast, the diagnosis distribution in carriers of

GSK3B rs12630592 T alleles with the FXR1 rs496250 GG genotype, or in carriers of the

FXR1 rs496250 A allele with the GSK3B rs12630592 GG genotype was similar to the

distribution in subjects with the reference GSK3B rs12630592 GG - FXR1 rs496250 GG

genotype.

Impact of the GSK3B - FXR1 interaction on age of onset

Given previous evidence that symptoms severity may be related to younger age of illness

onset (Propper et al., 2015; Suominen et al., 2007), we also considered a potential relation

of the interaction with onset age. In our sample, the mania dimension severity was

negatively correlated with age of onset of mood disorder (r = -0.23 in acute episodes, r = -

0.12 in stabilized interepisode intervals). In contrast, correlation between depression

severity and age of onset of mood disorder was negligible (r = -0.05 in acute episodes, r = -

0.02 in stabilized interepisode intervals). When we fitted a linear mixed model with FXR1

rs496250 and GSK3B rs12630592 genotypic variables to age of onset of mood disorder (BD

or RMDD), subjects who are homozygote TT for GSK3B rs12630592 and carriers of the A

allele of FXR1 rs496250 had an estimated mean age of onset of 21.5 years (nominal 95% CI:

[13.8, 29.1]), 13 years younger than the estimated mean age of onset of 34.4 years (nominal

95% CI: [31.4, 37.3]) for subjects who are homozygote GG for GSK3B rs12630592 and non-

carriers of the A allele of FXR1 rs496250 (Figure S5). Contrary to the mania symptom

dimensions, other genotypes had intermediate mean ages of onset between these two

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extremes, so the interaction term was not statistically significant (nominal p = 0.19). No

association between FXR1 rs496250 and GSK3B rs12630592 genotypic variables and age of

onset of SZ was detected (results not shown).

Association between GSK3B - FXR1 genotype and lithium intake

The prevalence of lithium intake among mood disorder patients was associated with FXR1

rs496250 and GSK3B rs12630592 genotypes, the prevalence tending to decrease with the

number of GSK3B rs12630592 T alleles in FXR1 rs496250 GG subjects and to increase with

the number of GSK3B rs12630592 T alleles in FXR1 rs496250 A carriers (Table S1). To the

contrary, the intake of neuroleptic and anti-depressive medications was not associated with

FXR1 rs496250 and GSK3B rs12630592 genotypes (results not shown).

In order to assess the association between symptom dimensions and FXR1 and GSK3B in

patients with exposure to lithium, we repeated the analysis in the subset of 127 mood

disorder patients having taken lithium. Although lithium intake was highly prevalent among

BD patients, lithium intake did not equate BD diagnosis, as a sizable proportion of RMDD

patients also had lithium (Table S2). The pattern of association to the genotypes was

similar, with some attenuation of the slope of the symptoms with the number of GSK3B

rs12630592 T alleles and wider confidence intervals given reduced sample size compared

to Figure 1 (slope and 95% CI: 0. 50 [-0.18, 1.17] for mania in acute episodes; 0.28 [-0.21,

0.78] for mania in stabilized interepisode intervals and 0.35 [-0.18, 0.88] for depression in

stabilized intervals).

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Discussion

Our findings support our a priori hypothesis of a possible interaction between GSK3B

(rs12630592 T allele) and FXR1 (rs496250 A allele) in mood disorder patients. A previous

study had indeed found this gene-gene interaction in healthy subjects on mood stability

(Del'Guidice et al., 2015).

Our analysis of mood disorder patients’ manic and depressive symptom dimensions, as

assessed in lifetime acute episodes and stabilized interepisode intervals, in densely affected

kindreds in relation to GSK3B and FXR1 functional SNP genotypes revealed an interaction

pattern related to the severity of mania (in both acute and stabilized periods) and of

depression symptoms in stabilized periods. The GSK3B rs12630592 T allele was associated

with higher dimension severity only in carriers of the A allele of FXR1 rs496250. The

highest levels of these symptom dimensions were thus observed in subjects who were

homozygote TT for GSK3B rs12630592 and carriers of the A allele of FXR1 rs496250. The

sizeable proportion of variance explained by the SNPs rs12630592 and rs496250 and their

interaction (11% for mania, 5% for depression in stabilized periods) attest the value of

testing biologically driven hypotheses on relevant alternative phenotypes to identify

genetic factors for mental illness. The pattern was found specific to manic and depressive

symptom dimensions in mood disorder patients. Given the higher level of manic symptoms

in BD patients, the decrease in prevalence of RMDD with the number of GSK3B rs12630592

T alleles only in carriers of the A allele of FXR1 rs496250 is congruent with the association

of this allelic combination with higher levels of mania.

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Noteworthily, we had reported suggestive evidence of linkage to BD at D3S3023, a marker

close to GSK3B, in a subset of the families analyzed here (Maziade et al., 2005). The need to

take into account epistasis with FXR1 and examining symptom dimensions may explain the

previous difficulty in reproducing this linkage signal and detecting one at FXR1.

The meaning of our findings is enhanced by previous studies. Our data further support the

observation of a functional interaction between these two SNPs and mood regulation in

healthy subjects (Del'Guidice et al., 2015). The FXR1 rs496250 A allele has already been

found associated to greater expression of FXR1 and GSK3B rs12630592 T associated to a

reduced expression of GSK3B in the pre-frontal cortex of healthy human subjects (Blasi et

al., 2013; Colantuoni et al., 2011; Del'Guidice et al., 2015). Furthermore, control subjects

carrying the FXR1 rs496250 A allele display greater emotional stability, a potential

protective effect against mood disorder only observed in GSK3B rs12630592 T carriers

(Del'Guidice et al., 2015). Our present observations in medicated BD patients may appear

contradictory since the combination of FXR1 rs496250 A and GSK3B rs12630592 T alleles

would be associated with greater severity of mania and earlier age of onset. A similar

paradox has been described for other risk alleles such as DRD2 rs2514218 T which exhibit a

level of protection against SZ (Schizophrenia Working Group of the Psychiatric Genomics,

2014) and yet, in first episode psychosis, would be associated with more severe symptoms,

poorer responsiveness to treatment and greater side effects (Zhang et al., 2015). In light of

this, it might then be possible that, while being protective in controls, the FXR1 rs496250 A

- GSK3B rs12630592 T allele combination would foster treatment resistance for some

dimensions of symptoms in subjects with mood disorder. Further studies need to address

treatment responsiveness for mania in testing this gene-gene interaction.

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In line with previous studies showing more severe mania in patients with younger age of

illness onset, subjects of our sample who were homozygote TT for GSK3B rs12630592 and

carriers of the A allele of FXR1 rs496250 were diagnosed with BD at a substantially younger

age on average (21.5 years vs 34.4 years) than subjects with the reference GSK3B

rs12630592 GG - FXR1 rs496250 GG genotype were diagnosed with mood disorder (BD or

RMDD). Our findings in patients need replication but our data nonetheless suggest that the

BD patients who carry the variant allele in the two genes would suffer a greater impact of

illness on their life course because they would develop the disorder earlier. Congruent with

our findings regarding the mania and depression dimensions, the interaction effect with age

of onset was observed only in mood disorder patients, not in SZ patients. When replicated,

this finding could have future implications in the clinic such as the possibility of testing

young patients at entry into illness and inducing particular forms of management and

surveillance depending on genotype.

Our study has strengths and limitations. A first strength resides in our symptom ratings

based on a lifetime assessment of the patients’ records and our measurements of manic,

depression and psychotic symptoms on all patients in the study regardless of their

diagnosis. Second, the kindred sample comes from a population where we previously

demonstrated that population stratification confounding is negligible (Bureau et al., 2013),

so adjustment for such stratification was unnecessary. Lastly, the relatedness of the kindred

members was taken into account by polygenic random effect in linear mixed models for

quantitative outcomes and by the use of generalized estimating equations for categorical

outcomes. Limitations reside first in the limited sample size resulting in a small number of

subjects who were homozygote TT for GSK3B rs12630592 and carriers of the A allele of

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FXR1 rs496250, although we had sufficient power to detect the interaction effect assuming

effects of the GSK3B rs12630592 T allele are additive, as suggested in healthy individuals

(Del'Guidice et al., 2015). Second, generalization of our findings to all BD patients may be

limited by the fact that the present sample was made of familial patients, although we have

already shown that most phenotypic, endophenotypic and genetic characteristics we

previously reported in this familial sample were very much alike those observed in studies

of sporadic patients (Maziade and Paccalet, 2013).

In conclusion, our study confirms previous observations of an interaction between FXR1

rs496250 and GSK3B rs12630592 genetic variants in regulating mood related behavioural

dimensions in humans (Del'Guidice et al., 2015). It also suggests that this allelic

combination may impact disease severity and age of onset in people with mood disorder.

Acknowledgements

We thank Chantal Mérette (Université Laval) for her comments to improve the study and

manuscript. We are grateful to our professional research assistants: Louise Bélanger, Marie-

Claude Boisvert, Linda René, Lisette Gagnon, Claudie Poirier, Nicole Leclerc, Julie Lamarche,

Pierrette Boutin, Lise St-Germain, Mélanie Mercier, Jordie Croteau, Alain Fournier, Claudia

Émond and Isabel Moreau, and to the family members, adults and children, who

participated in this study.

Funding

This work was supported by the Canadian Institutes of Health research (CIHR, grants MOP-

74430, MOP-119408 and MOP-114988) and by a Canada Research Chair (# 950-200810) in

the genetics of neuropsychiatric disorders of which M. Maziade is the Chair. The data

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management system was supported by the Canada Foundation for Innovation Leadership

Opportunity Fund (grant 27592). J.-M. Beaulieu holds a Canada Research Chair in Molecular

Psychiatry and is an International Mental Health Organization Rising Star Awardee.

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Figure legends

Figure 1 Distribution of manic and depressive symptom dimensions in mood disorder

patients of the Eastern Quebec kindred study by GSK3B rs12630592 and FXR1 rs496250

genotypes. Interaction p-values are Bonferroni-corrected for testing 4 dimensions. The

slopes of the relationships between mean symptom levels and the number of GSK3B

rs12630592 T alleles, in FXR1 rs496250 GG subjects and in A carriers (A*), are shown

below the interaction p-values, with simultaneous 95% confidence intervals for two

genotypes and four symptom dimensions, obtained using the Bonferroni method. In box

plots, center lines are the median, bottom and top lines are the 1st and 3rd quartiles and the

whiskers extend to 1.5x the interquartile range. N : number of subjects with given genotype.

Figure 2 Distribution of major psychosis diagnoses by GSK3B rs12630592 and FXR1

rs496250 genotypes in the Eastern Quebec kindred study.

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Table

Table 1 : Association of the GSK3B rs12630592 T allele with major psychosis diagnosis

distribution stratified by FXR1 rs496250 genotype in the Eastern Quebec kindred study.

FXR1 rs496250 GG FXR1 rs496250 A carrier

GSK3B rs12630592 T

allele

GSK3B rs12630592 T allele

Diagnosis N OR (95% CI)* P† OR (95% CI)* P†

RMDD 86 0.94 (0.58, 1.53) 0.13 (0.02, 0.89)

BD 128 0.92 (0.58, 1.45) 0.81 (0.34, 1.96)

SAD 48 1.26 (0.65, 2.44) 1.76 (0.58, 5.31)

SZ 122 0.84 (0.50, 1.40) 1.39 (0.77, 2.50)

NAAR 471 1 (reference) 1.0 1 (reference) 0.03

RMDD: recurrent major depressive disorder; BD: bipolar disorder; SAD: schizoaffective

disorder; SZ: schizophrenia; NAAR: non-affected adult relative

* Odds ratio of diagnosis compared to non-affected category for an additional copy of the

GSK3B rs12630592 T allele, with simultaneous 95% confidence interval for two genotypes

and four diagnoses.

† P-value for global test of association of GSK3B rs12630592 T with diagnosis, Bonferroni

corrected for two genotypes.

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