Association between anxiety and non-coding genetic variants of the galanin neuropeptide.

BACKGROUND: Galanin, an inhibitory neuropeptide and cotransmitter has long been known to co-localize with noradrenaline and serotonin in the central nervous system. Several human studies demonstrated altered galanin expression levels in major depressive disorder and anxiety. Pharmacological modulation of galanin signaling and transgenic strategies provide further proof for the involvement of the galanin system in the pathophysiology of mood disorders. Little is known, however, on the dynamic regulation of galanin expression at the transcriptional level. The aim of the present study was to seek genetic association of non-coding single nucleotide variations in the galanin gene with anxiety and depression.
METHODS: Six single nucleotide polymorphisms (SNP) occurring either in the regulatory 5' or 3' flanking regions or within intronic sequences of the galanin gene have been genotyped with a high-throughput TaqMan OpenArray qPCR system in 526 healthy students (40% males). Depression and anxiety scores were obtained by filling in the Hospital Anxiety and Depression Scale (HADS) questionnaire. Data were analyzed by ANCOVA and Bonferroni correction was applied for multiple testing. Linkage disequilibrium (LD) analysis was used to map two haploblocks in the analyzed region. RESULTS AND
CONCLUSIONS: A single-locus and a haplotype genetic association proved to be statistically significant. In single-marker analysis, the T allele of the rs1042577 SNP within the 3' untranslated region of the galanin gene associated with greater levels of anxiety (HADS scores were 7.05±4.0 vs 6.15±.15; p = 0.000407). Haplotype analysis revealed an association of the rs948854 C_rs4432027_C allele combination with anxiety [F(1,1046) = 4.140, p = 0.042141, η2 = 0.004, power = 0.529]. Neither of these associations turned out to be gender-specific. These promoter polymorphisms are supposed to participate in epigenetic regulation of galanin expression by creating potentially methylatable CpG dinucleotides. The functional importance of the rs1042577_T allele remains to be elucidated.

Introduction

Common affective disorders such as depression and anxiety emerge against the background of perturbed monoaminergic neurotransmission. Beyond the well-substantiated role of classical neurotransmitters such as norepinephrin and serotonin in the pathogenesis of mood disorders, a number of recent studies implicated coexpressed neuropeptides such as galanin, a 29 amino acid long inhibitory neurotransmitter and trophic factor [1], in anxiety and depression [2]. A Bayesian multivariate analysis of gene factors revealed that the galanin signaling system consisting of the stress-inducible galanin gene and three heptahelical galanin receptors seems to play a seminal role in the development of depression by enhancing the vulnerability to environmental stressors [3].

However, the exact function of galanin in depression still remains elusive. Data gained from animal studies suggest that galanin mediates depression-like behaviour [4], while other authors emphasize its antidepressant-like effects [5, 6].

Experimental data argue that the effects of galanin on anxiety are brain region specific and all three galanin receptors seem to mediate its anxiety-like effects. Intracerebroventricular administration of galanin resulted in anxiolytic-like action in rats [7], while its microinjection in rodent amygdala produced both anxiogenic [8] and anxiolytic effects [9]. The anxiolytic action was more predominant when galanin was infused into the dorsal raphe nucleus in rats [10]. However, intra-dorsal hippocampal administration of galanin induced anxiogenic-like behaviours that could be attenuated with a type 2 galanin receptor antagonist [11].

Importantly, these seemingly contradictory findings could be reconciled by showing that type 1 and type 2 galanin receptors mediate opposite anxiety-like effects in the rat dorsal raphe nucleus [12]. The anxiolytic action of the type 2 galanin receptor is underscored by the fact that Gal2R knockout mice exhibit an anxiogenic-like phenotype [13], while type 3 galanin receptor knockout animals display increased anxiety [14]. Polymorphisms in the gene encoding galanin receptor 2 seem to mediate the effect of environmental stressors and gene-environment interactions [15].

Differential expression of galanin has been implicated in a broad spectrum of neuropsychiatric disorders including post-traumatic stress disorder [16] and Lewy body disorder [17]. Human studies revealed a direct correlation between plasma galanin levels and the severity of major depressive disorder [18]. In contrast, intravenous administration of galanin to depressed individuals exerted fast antidepressant activity [19]. Moreover, profound alterations in mRNA expression and DNA methylation have been found in the galanin system in postmortem brain samples of patients with major depressive disorder [20].

Though the regulation of galanin expression is far from being fully characterized, some transcription factors [21], medicine [22] and exercise [22, 23] have been shown to upregulate galanin transcription. Several lines of compelling evidence suggest that non-coding DNA variations affecting important 5’ and 3’ regulatory as well as intronic sequences are associated with central nervous system disorders such as panic disorder [24], depression and anxiety [25-28] via altering transcription factor or microRNA binding sites.

As described above, other authors have already demonstrated associations between GAL polymorphisms and mood disorders, but no studies have been done to date to test this possible association in a non-clinical, largely normal, healthy sample. Thus, our goal was to figure out whether any genetic association is detectable between a set of marker SNPs representing the entire regulatory landscape of the galanin gene and mood characteristics in an ostensibly normal sample consisting of university students with no psychiatric history.

Materials and methods

Subjects

To test possible genetic associations between GAL polymorphisms and anxiety and depression, DNA samples from a previous study on anxiety were genotyped for GAL polymorphisms [29]. Thus, participants of the present investigation largely overlap with those of an earlier genetic association study where the associations of glial cell derived neurotrophic factor (GDNF) polymorphisms with mood characteristics were tested [29]. The non-related Caucasian (Hungarian) subjects who participated on a voluntary basis were students from several educational institutions from Budapest, Hungary. They gave written informed consent, provided buccal cell samples and filled out the Hospital Anxiety and Depression Scale (HADS) questionnaire. The study protocol was designed in accordance with guidelines of the Declaration of Helsinki, and was approved by the Scientific and Research Ethics Committee of the Medical Research Council (ETT TUKEB). Inclusion criteria were as follows: no past or present psychiatric history (based on self-report), age between 18–35 years, valid GDNF SNP genotypes and valid self-report data for the HADS scales.

A total of 597 independent subjects were genotyped with a high-throughput system, and filled out the HADS self-report questionnaire. Of them, 589 had no previous psychiatric history and 526 subjects were between 18–35 years. Therefore, we analyzed data from 526 participants (40.7% males, 59.3% females; mean age: 22.01 ± 3.1 years).

Phenotype characteristics

As described in our previous study on anxiety [29], participants completed the Hungarian version [30] of the Hospital Anxiety and Depression Scale [31]. The HADS questionnaire measures anxiety and depression on 7–7 items, scoring on a 0 to 3 Likert scale. It was originally developed to assess anxiety and depression in case of non-psychiatric hospital patients [31]. However, a great deal of studies have shown that it is an adequate tool to measure mood characteristics on non-clinical samples as well [32]. The Cronbach Alpha values of the HADS scales were adequate (Cronbach Alpha = 0.775 for the anxiety and 0.715 for the depression scale, respectively). The inter-correlation of the two scales was high (r = 0.561, p < 0.001). The sample’s mean scores were 6.55 (± 3.7) on the anxiety scale and 2.80 (± 2.7) on the depression scale.

SNP selection criteria

Single nucleotide polymorphisms (SNPs) were selected for genotyping from the Single Nucleotide Polymorphism database of NCBI (dbSNP) with a minor allele frequency greater than 0.05. The pairwise tagging method using r2 threshold of 0.8 by Haploview was used to determine tagging SNPs based on HapMap data to obtain a proper coverage of the GAL gene resulting in a mean distance of 1721 bp between the selected SNPs. Polymorphisms with a reference from previous association studies concerning neuropsychiatric disorders were preferred.

DNA preparation and SNP genotyping

Genomic DNA samples were isolated from buccal swabs as described previously [29]. Genotypes were determined applying the TaqMan® OpenArray™ Genotyping System (Thermo Fisher Scientific, Waltham, Massachusetts) that is based on sequence-specific, fluorescent TaqMan probes in combination with a high-throughput PCR system using nanoliter-scale sample volume and post-PCR (endpoint) detection. Genotyping panels were obtained from the manufacturer as immobilized target specific primers and fluorescent probes in a low density array format. Reaction mixtures containing approximately 100 ng DNA (range: 30–150 ng) and the 1× master mix (each deoxyribonucleoside triphosphate and the AmpliTaq Gold DNA-polymerase, provided by the manufacturer) were prepared on a 384-well sample plate and then loaded on the genotyping plates by the OpenArray™ Autoloader. PCR amplification was performed in the GeneAmp® PCR System 9700 (Thermo Fisher Scientific, Waltham, Massachusetts) following the manufacturer's instruction. Endpoint imaging of the allele specific FAM and VIC fluorescent intensities was made by the OpenArray™ NT Imager. Raw data were evaluated by the TaqMan Genotyper v1.2 software.

2% of the DNA samples were repeatedly applied on the OpenArray system, demonstrating a reproducibility exceeding 98%. In addition, a subsample was re-genotyped for two SNPs with a 7300 Real-Time PCR System (Applied Biosystems, Foster City, CA) in triplicates for quality control.

Table 1 summarizes the main characteristics of six SNPs genotyped within the GAL gene. Genotype, chromosomal position, relative distances in the gene body and regional localisation for the tested GAL polymorphisms are presented for each SNP. Genotype frequencies, p values from the Hardy-Weinberg equilibrium (HWE) tests and call rate information are also presented. The rs694066 SNP exhibited an outstandingly small minor genotype frequency (0.8%), while the others vary between 6.5% and 13.1%. All genotypes were in Hardy-Weinberg equilibrium. Call rates exceeded 85% for each polymorphism.

Table 1

Main characteristics of the studied SNPs in the GAL gene.

dbSNP number		Position		Distance	Region	N	%	HWE	Call rate
rs948854	TT	g.68682735			5' flanking	260	50.0	P = 0.996	98.86%
	CT			-		216	41.5
	CC					44	8.5
rs2097042	TT	g.68682846			5' flanking	233	50.7	P = 0.999	87.26%
	CT			111		188	41.0
	CC					38	8.3
rs4432027	TT	g.68683779			5' flanking	251	51.3	P = 0.762	92.97%
	CT			933		194	39.7
	CC					44	9.0
rs694066	GG	g.68685517			intron 2	399	79.2	P = 0.682	95.82%
	AG			1738		101	20.0
	AA					4	0.8
rs3136540	CC	g.68688942			intron 5	260	56.7	P = 0.938	87.26%
	CT			3425		169	36.8
	TT					30	6.5
rs1042577	CC	g.68691002			3'-UTR	180	40.1	P = 0.983	85.36%
	CT			2060		210	46.8
	TT					59	13.1

HWE = Hardy-Weinberg equilibrium; UTR = untranslated region. Distance: distance between chromosomal positions of neighboring SNPs in base pairs.

Linkage disequilibrium analyses

Lewontin’s D’ as well as R2 values of linkage disequilibrium were determined using the HaploView 4.2 software [33]. Haplotypes were determined by the Phase programme [34-36]. Linkage disequilibrium values of the studied SNPs are displayed in Fig 1. Importantly, both Lewontin’s D’ and R2 analysis revealed two haplotype blocks. Haplotype block No. 1 encompasses rs948854, rs2097042, rs4432027 and rs694066 SNPs, while rs3136540 and rs1042577 belong to haplotype block No. 2.

Fig 1

Linkage disequilibrium plots for the studied GAL SNPs.

Lewontin’s D’ measure (panel A) and R2 values (panel B) of linkage disequilibrium. Larger figures and darker squares indicate stronger pairwise linkage disequilibrium between two loci.

Statistical analysis

Statistical analyses were carried out using SPSS 20.0 for Windows. Chi-square analysis was used to assess reliability of the measured genotype and allele frequencies. Lewontin’s D’ as well as R2 values of linkage disequilibrium were calculated using the HaploView 4.2 application [33]. Haplotypes were determined by the Phase program. To test gender differences, the Independent-Samples t-test was used. Correlation analyses were carried out to test the HADS scales relationship with age. One-way analyses of covariance (ANCOVA) was used to test genetic associations of the single and multiple marker analyses in an allele-wise design. Bonferroni correction for multiple testing was used to rule out false positive results [37]. The corrected level of significance was p < 0.00417, as the nominal p (threshold value 0.05) was divided by the number of analyses performed (6 SNPs x 2 HADS scales = 12). Two-way ANOVA was used for testing the effect of prior associations in males and females.

Results

Influence of age and gender on anxiety and depression scores

Testing for covariates included testing the relationships between age, gender and the measured phenotypes and genotypes. The HADS anxiety scale showed significant differences across males and females [t(524) = - 4.054; p<0.001]; namely, females showed a higher mean score (7.09) than males (5.78). The HADS depression scale did not differ across genders. For testing the relationship between age and the HADS scales, Pearson correlation was used. The anxiety scale significantly correlated with age (r = - 0.89, p = 0.042), while the depression scale showed no significant correlation. The genotype frequency differences in males and females were tested with Chi-square analyses and no significant differences were observed. The ANOVAs testing the genotype and age association did not show any significant association either. In summary, age and gender were used as covariates in all association analyses on account of their association with the phenotype.

Single-allele association analyses on mood characteristics with GAL polymorphisms

Table 2 summarizes the results obtained from the single-allele association analyses. Minor allele frequencies, anxiety and depression mean scores for the alleles of each tested SNPs are presented with the corresponding p values. Based on the one-way ANCOVAs, three nominally significant associations were found with the anxiety scale, and one with the depression scale. The results showed higher anxiety mean scores associated with the minor allele of rs948854 [F(1,136) = 3.865, p = 0.049572, η2 = 0.004, power = 0.502], rs4432027 [F(1,974) = 4.349, p = 0.037297, η2 = 0.004, power = 0.549] and rs1042577 [F(1,894) = 12.594, p = 0.000407, η2 = 0.014, power = 0.944]. The minor allele of rs1042577 associated with a higher mean score on the depression scale as well [F(1,894) = 5.718, p = 0.016996, η2 = 0.006, power = 0.666]. Bonferroni correction was applied to rule out possible false positive effects. After correcting for multiple testing, association of anxiety and rs1042577 remained significant. In the presence of the minor allele (T) of the rs1042577 the mean anxiety score was significantly higher (7.05±4.0) as compared to the major allele (G) carriers (6.15±3.5). The effect of this polymorphism explained 1.4% of the variability of anxiety. In this analysis, the covariate effect of gender but not that of age proved to be significant (p < 0.001).

Table 2

Association analyses between GAL polymorphisms and mood characteristics as measured by HADS questionnaire.

dbSNP number		MAF**	mMAF***	Anxiety	p		Depression	p
rs948854	C	0.319	0.292	6.91 (±4.1)	0.049572		2.95 (±3.0)	0.315956
	T			6.45 (±3.5)			2.76 (±2.5)
rs2097042	C	0.265	0.288	6.81 (±3.9)	0.073644		2.91 (±3.0)	0.424516
	T			6.36 (±3.5)			2.75 (±2.5)
rs4432027	C	0.321	0.288	6.86 (±4.1)	0.037297		2.93 (±3.0)	0.318117
	T			6.34 (±3.5)			2.74 (±2.5)
rs694066	A	0.136	0.109	6.58 (±4.4)	0.925477		2.83 (±2.9)	0.728726
	G			6.49 (±3.6)			2.76 (±2.6)
rs3136540	T	0.262	0.250	6.77 (±4.0)	0.188575		2.83 (±2.8)	0.602540
	C			6.44 (±3.6)			2.71 (±2.5)
rs1042577	T	0.373	0.358	7.05 (±4.0)	0.000407*		3.01 (±3.0)	0.016996
	C			6.15 (±3.5)			2.59 (±2.4)

p: level significance (ANOVA with age and sex as covariant).

*Significant after Bonferroni correction (12 tests: p<0.004167).

**MAF: minor allele frequency (based on data from the 1000 Genome project).

***mMAF: measured minor allele frequency. (Standard deviations are shown in parenthesis)

Haplotype analyses

As a next step, haplotype analyses were performed involving the three SNPs significantly associated with anxiety comparing the combined effects of the risk alleles versus non-risk alleles. To this end, bipartite and tripartite haplotypes were set up by pairing the most significantly associated rs1042577 3’ UTR SNP with one or both of the less significantly associated 5’ SNPs as shown in Table 3. Upon comparing haplotype frequencies, it is striking that two major haplotypes are represented with outstanding frequency in each category. For example, in case of the rs1042577—rs948854 haplotypes the non-risk-allele combination (rs1042577 C—rs948854 T) and the one containing both risk alleles (rs1042577 T—rs948854 C) occurred most frequently (0.692 and 0.254, respectively, as compared to 0.040 and 0.014 of the C-C and T-T haplotypes). Similarly, in case of the tripartite haplotype a few combinations were very rare (e.g. rs1042577 C, rs948854 C, rs4432027 T: 0.001) or even unrepresented in the present sample (e.g. C–T–C or T–C- T). In case of all three analyses, the two major haploalleles made up about 95% of all haplotypes. The low frequency of some haplotypes is probably due to the high linkage between the SNPs (see Fig 1).

Table 3

Haplotype frequencies in the studied population.

Haplotypes*	N	Frequency
rs1042577 C—rs948854 T	728	0.692
rs1042577 C—rs948854 C	42	0.040
rs1042577 T—rs948854 T	15	0.014
rs1042577 T—rs948854 C	267	0.254
rs1042577 C—rs4432027 T	729	0.693
rs1042577 C—rs4432027 C	41	0.039
rs1042577 T—rs4432027 T	14	0.013
rs1042577 T—rs4432027 C	268	0.255
rs1042577 C—rs948854 T–rs4432027 T	728	0.692
rs1042577 C—rs948854 C–rs4432027 T	1	0.001
rs1042577 C—rs948854 T–rs4432027 C		0.000
rs1042577 C—rs948854 C–rs4432027 C	41	0.039
rs1042577 T—rs948854 T–rs4432027 T	14	0.013
rs1042577 T—rs948854 T–rs4432027 C	1	0.001
rs1042577 T—rs948854 C–rs4432027 T		0.000
rs1042577 T—rs948854 C–rs4432027 C	267	0.254

*risk alleles in the haplotypes are displayed bold

Thus, the haplotype analyses were carried out between the two most frequent haplotypes. One-way ANCOVAs were applied to both mood dimensions with the haploalleles of the significant SNPs from haploblock 1 (rs948854—rs4432027) and from both haploblocks (rs1042577—rs948854, rs1042577—rs4432027, rs1042577- rs948854—rs4432027). Age and gender were also included as covariates. As it can be seen in Table 4, the haplotype with the risk alleles of both 5’ UTR SNPs (rs948854_C—rs4432027_C) showed significantly higher anxiety mean score than the haplotype with non-risk alleles [F(1,1046) = 4.140, p = 0.042141, η2 = 0.004, power = 0.529]. Unexpectedly, however, any bi- or tripartite haplotype comprising the risk allele of the 3’ UTR SNP (rs1042577) which associated significantly with anxiety even after correcting for multiple testing, did not prove to be associated either with anxiety or depression.

Table 4

Haplotype analysis of risk alleles.

Haplotypes*	N	Frequency	Anxiety	p	Depression	p
rs1042577 C _rs948854 T	728	0.692	6.41 (±3.54)	0.075066	2.76 (±2.52)	0.260648
rs1042577 T_rs948854 C	267	0.254	6.83 (±4.10)		2.99 (±3.11)
rs1042577 C_rs4432027 T	729	0.693	6.41 (±3.54)	0.059088	2.75 (±2.52)	0.226432
rs1042577 T_rs4432027 C	268	0.255	6.85 (±4.11)		3.00 (±3.11)
rs948854 T_rs4432027 T	742	1.000	6.42 (±3.52)	0.042141	2.74 (±2.51)	0.309043
rs948854 C_rs4432027 C	308	0.293	6.89 (±4.05)		2.93 (±3.02)
rs1042577 C_rs948854 T_rs4432027 T	728	0.692	6.41 (±3.54)	0.075066	2.76 (±2.52)	0.260648
rs1042577 T_rs948854 C_rs4432027 C	267	0.254	6.83 (±4.10)		2.99 (±3.11)

*risk alleles in the haplotypes are displayed bold. (Standard deviations are shown in parenthesis)

Gender-specific effects

The HADS anxiety scores differed across the genders, and the covariate effect of gender was also significant in the analysis of rs1042577 and anxiety. Thus, we raised the question whether the effect of this single-locus SNP was gender-specific. To address this issue, a two-way ANOVA was carried out to test whether the effect of rs1042577 in the single-locus analyses differed between males and females. Results are presented in Fig 2. The analysis revealed a significant GAL rs1042577 main effect [F(1,893) = 11.571, p = 0.0007, η2 = 0.013, power = 0.925], and a significant gender main effect [F(1,893) = 21.253, p < 0.001, η2 = 0.023, power = 0.996]. However, their interaction was not significant. According to these results, the risk effect of the T allele of the GAL rs1042577 SNP for higher anxiety scores was present in both genders. Males with the T allele showed a mean anxiety score of 6.21 (±3.9) and the females’ mean anxiety score with this allele was 7.65 (±3.9) as compared to the 5.48 (±3.6) and 6.61 (±3.4) mean scores with the C allele in males and females. The significant gender main effect is in accordance with literary data [38], suggesting that females in general show higher anxiety scores than males.

Fig 2

Effect of GAL rs1042577 alleles on anxiety in males and females.

Mean HADS anxiety scores in males and females as a function of GAL rs1042577 alleles. Open symbols denote females; filled symbols stand for males. Error bars represent standard errors of the mean.

Furthermore, we also tested whether the association between the rs948854—rs4432027 haplotype and anxiety is gender specific. The two-way ANOVA showed a significant rs948854—rs4432027 haplotype main effect [F(1, 1046) = 4.449, p = 0.035, η2 = 0.004, power = 0.559], a significant gender main effect [F(1,893) = 25.603, p < 0.001, η2 = 0.024, power = 0.999], but the interaction between the rs948854—rs4432027 haplotype and gender was not significant. According to the results (Fig 3), the risk haplotype group showed a higher mean anxiety score both in males (6.24 ± 4.2) and females (7.36 ± 3.9), as compared to the non-risk haplotype groups of males (5.57 ± 3.4) and females (6.98 ±3.5).

Fig 3

Effect of the GAL rs948854—rs4432027 haplotype on anxiety in males and females.

Mean HADS anxiety scores in males and females as a function of GAL rs948854—rs4432027 haplotypes. Open symbols denote females; filled ones stand for males. Error bars represent standard errors of the mean.

Discussion

Galanin has been shown to co-localize with and modulate the release of norepinephrine and serotonin, principal neurotransmitters in depression and anxiety. In contrast to former research aimed to find genetic associations between GAL gene variants and mood characteristics in subjects with clinical anxiety and depression [, the novelty of the present study is that it was performed on a cohort of apparently normal, healthy volunteers. Candidate single nucleotide polymorphisms were carefully selected to cover 5’ and 3’ regulatory as well as intronic sequences of the gene, and polymorphisms with previous association data were preferred. Genetic association analyses of six GAL single nucleotide polymorphisms with anxiety and depression have been carried out with one-way analyses of covariance in an allele-wise method. Allele frequencies calculated from our population corresponded very well to those available from the 1000 Genomes project. Four nominally significant single-locus associations have been observed in the present study. While GAL rs948854 and rs4432027 SNPs were found to associate with anxiety, the rs1042577 SNP was significantly associated with both anxiety and depression. The association between rs1042577 and anxiety remained significant following correction for multiple testing. The minor allele of this polymorphism is coupled with higher anxiety mean score (T) as compared to the major allele (C). This association was observable in both females and males.

Recent studies conducted on healthy samples also found that HADS anxiety and depression scores varied a lot among university students [39-41]. Importantly, our healthy sample was also quite stratified as 9.9% of the sample (n = 52) scored higher than 11 (mean score of 14.23 ± 2.278) and 11.4% of the sample (n = 60) scored lower than 3 (mean: 1.32 ± 0.673) on the anxiety scale. On the other hand, 9.7% of the sample (n = 51) scored higher than 6 (mean: 9.160 ± 1.902) and 11.6% scored 0 on the depression scale. These data imply that approximately 10% of our admittedly healthy sample had clinical anxiety and depression [32]. It is to note that the frequency of the rs1042577 risk T allele was significantly higher in the top 9.9% than in the bottom 11.4% anxiety groups (50.0% vs. 30.6%, p = 0.005, data not shown).

Haplotype analysis is a very effective tool to test possible allelic interactions. In the present study, comparing the risk allele of rs1042577 from haploblock 2 (see Fig 1) and the risk alleles of the other two SNPs from haploblock 1 (rs948854 and rs4432027) which showed nominally significant associations with anxiety did not yield any significant associations. However, significant association between haplotype rs948854 C_rs4432027_C and anxiety was observed suggesting a possible additive effect of the risk alleles in this haploblock.

The chromosomal distance between these SNPs is slightly more than 1 kb. Importantly, the C allele of each SNP is followed by a guanine nucleotide, creating CpG dinucleotides as potential DNA methylation sequences in the promoter [42]. One can therefore assume that their methylation might elicit anxiety via diminished galanin expression. High-resolution methylation mapping of the galanin promoter and functional studies are needed to clarify this assumption. Notably, the role of DNA methylation in the regulation of the galanin system was already suggested by Barde et al. [20].

To our best knowledge, this is the first study in the literature shedding light on the association of the rs1042577 single nucleotide variation with any phenotype. Though this polymorphism was analyzed in a study by Unschuld et al. [24], it was not found to be associated with panic disorder. Apart from psychiatric studies, Schäuble et al. [43] also tested this polymorphism, addressing the role of galanin in fat intake and early onset obesity but failed to find associations.

The rs1042577 SNP is localized to the 3’ untranslated region of the galanin gene, a sequence where miRNA binding sites are frequently found. In an attempt to ascribe a functional role to this polymorphism, we searched the online PolymiRTS Database 3.0 (http://compbio.uthsc.edu/miRSNP/) but it turned out that this polymorphism does not affect any known miRNA target sequences. It is also possible that this SNP affects mRNA stability or half-life by allele-specific recruitment of RNA binding proteins but this assumption lacks yet experimental evidence. The rs1042577 SNP is found within a weak CTCF binding site in the 3’UTR. This transcription factor plays multiple roles in transcriptional modulation and chromatin architecture [44]. The issue whether it really binds the 3’ UTR in the context of chromatin needs further investigation.

In summary, in this study we revealed two statistically significant associations between anxiety and the galanin rs948854_C–rs4432027_C haplotype and the rs1042577_T single-locus allele, respectively. These results should be corroborated using clinical samples and functional analyses should also be performed, addressing the role these sequence variants might play in governing galanin expression.

2 Sep 2019

PONE-D-19-16922

Association between anxiety and non-coding genetic variants of the galanin neuropeptide

PLOS ONE

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1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This a study of the association of “six single nucleotide polymorphisms (SNP) occurring either in the regulatory 5’ or 3’ flanking regions or within intronic sequences of the galanin gene” with anxiety and depression scores on the Hospital Anxiety and Depression Scale in 526 healthy students (41% men) ages 18-35 years. As such it is a straightforward correlative study between galanin gene-related SNPs and a psychometric measure of anxiety and depression in normal individuals with no psychiatric illness. A T allele of one SNP and a C-C combination of two other SNPs were associated with greater levels of anxiety in both men and women.

Not being a geneticist, I cannot comment on the methodology used in the genetic analyses; I must assume the analyses were done rigorously and interpreted correctly. The authors did appropriately correct their nominal significance levels for the multiple statistical tests they performed. My concerns are about the nature of the subjects studied vis-à-vis issues of anxiety and depression as psychiatric disorders, to which the authors give detailed attention, and the rating scale used to develop a “phenotype” (subjects with greater or lesser amounts of anxiety and/or depression on the HADS).

Concerning the HADS (ref 31 in the MS), it is a “self-assessment scale…found to be a reliable instrument for detecting states of depression and anxiety in the setting of an hospital medical outpatient clinic. The anxiety and depressive subscales are also valid measures of severity of the emotional disorder… The research was conducted in general medical outpatient clinics on adults of both sexes between the ages of 16 and 65 who suffered from a wide variety of complaints and illnesses.” The HADS thus was not designed to measure anxiety or depression in a sample of normal young adult college students with no complaints or current illnesses. The mean anxiety score (6.55 +/- 3.7 [which I assume is the standard deviation – not stated]) is in the lowest group of scores (Table 1 in ref 31), which consisted of 98% non-and doubtful-cases of clinical anxiety. As well, the mean depression score (2.80 +/- 2.7) was in the lowest group of scores (Table1 in ref 31), which again consisted of 98-99% non-and doubtful-cases of clinical depression. In short, the normal subjects’ scores were clustered near the low end of the HADS, providing little variance for correlational analysis with the genetics data – not surprising for the use of a hospital clinic-derived scale on normal subjects with no complaints or illnesses. More appropriate depression and anxiety scales should have been used to develop the subjects’ “phenotype.”

Given the use of an inappropriate rating scale on normal subjects, the lengthy discussions in the Introduction and Discussion sections of the relationship of galanin to psychiatric illnesses is of little relevance.

I suggest the authors severely shorten the MS and present it as straightforward correlative study between galanin gene-related SNPs and a psychometric measure of anxiety and depression in normal individuals with no psychiatric illness. The authors should provide one or two sentences as rationale for performing the study, limiting any comment about galanin and psychiatric illness to a short, suggestive statement about its relationship to classical neurotransmitters and that it has been found to be altered in certain psychiatric illnesses, and including the list of references.

Reviewer #2: The manuscript "Association between anxiety and non-coding genetic variants of the galanin neuropeptide" by Gergely Keszler and coworkers studies the genetic association of six non-coding single nucleotide variations in the GAL gene with anxiety and depression in healthy young students (mean age 22 years). From their results the authors conclude that only allele T of the rs 10442577 SNP and association of the rs948854C-rs4432027 allele combination are associated with greater lebels of anxiety. Neither association was obseved of other SNP in the GAL gene and depression. The experiments were carried out in an adeguate manner, respect the ethics or publication ethics, and the documentation of the results is satisfactory. Overall, the manuscript is nicely written, satisfies the PLOS ONE criteria for pubblication and is worth publishing. However, I have several comments about the choice of population and the results obtained from this study. The results aren't very interesting. The association between SNP in the GAL genes and anxiety is very low. It is very difficult to demonstrate this association in healthy young people. The works you cited show a strong correlation between SNPs of genes for GAL in anxious subjects, with major depression, panic disorders and multiple schlerosis. As you described in the conclusions, these differences could be ascribed to the fact that in those works they recruit patients with different psychiatric pathologies. You have excluded subjects with psychiatric history from your samples, but it would have been more interesting to study the polymorphisms for the GAL genes in these subjects or in people with family histories of psychiatric illnesses, to try to study the susceptibility of these people for anxiety, depression and other psychiatric disease

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Reviewer #1: Yes: Robert T. Rubin, MD, PhD

Reviewer #2: No

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Submitted filename: Manuscript Keszler.docx

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15 Oct 2019

Response to Reviewers

Fisrt of all, we would like to thank both anonymous Reviewers for thoroughly revising our paper, appreciating its merits and raising valuable concerns which prompted us to rethink several points and to amend the manuscript accordingly. Please find beneath our point-by-point response to your comments and criticism.

Importantly, a common major concern of both Reviewers was whether it is relevant to study association of GAL polymorphisms with anxiety and depression on a normal, healthy young population rather than on a clinical sample. We admit it should have been better explained in the original manuscript, and are grateful to you for having drawn our attention to our negligence.

Quotations from reviewers’ comments are written in italics, our responses are typed in normal letters and revised sections of the manuscript are highlighted bold.

Reviewer #2:

1. It is very difficult to demonstrate this association in healthy young people. The works you cited show a strong correlation between SNPs of genes for GAL in anxious subjects, with major depression, panic disorders and multiple schlerosis. As you described in the conclusions, these differences could be ascribed to the fact that in those works they recruit patients with different psychiatric pathologies. You have excluded subjects with psychiatric history from your samples, but it would have been more interesting to study the polymorphisms for the GAL genes in these subjects or in people with family histories of psychiatric illnesses, to try to study the susceptibility of these people for anxiety, depression and other psychiatric disease

As cited in the Introduction of the manuscript, numerous studies found firm genetic association between GAL gene polymorphisms and depression, anxiety, alcohol dependence and panic disorder in psychiatric in- or outpatients. In our study, however, we have intentionally chosen a non-clinical, healthy population to extend the findings of others, that is, to study whether the effect of GAL polymorphisms could be observed on the mood characteristics of a normal cohort. Notably, the anxiogenic effect of a single SNP proved to be significant even in this context, and this effect has never been described before even on a clinical population. This prompts us to check whether the rs1042577 T allele and the rs948854_C_rs4432027_C haplotype as predilection factors are enriched in a clinical sample with anxiety too.

Psychiatric disorders are known to have a strong polygenic genetic background and a lot of environmental stressors (life events) might precipitate the development of symptoms. We chose a young healthy population as the prevalence of negative life events (such as getting divorced, unemployed, widowed, bereaved, having low socio-economic status or afflicted by severe diseases) is far less among these people, making the genetic components more exposed and identifiable. On the other hand, our randomly selected non-clinical population is genetically heterogeneous, i.e. represents a continuous spectrum of mood dimensions, and might comprise subjects with milder (subclinical) forms of anxiety and depression such as GAD (generalized anxiety disorder) or PDD (persistent depressive disorder) as indicated by higher HADS scores on the corresponding scales. Recent studies conducted on healthy samples also found that HADS anxiety and depression scores vary a lot among university students (Andrews et al., 2006; Kebede et al., 2019; Gan and Yuen Ling, 2019).

To emphasize the above considerations, the bold-marked text above was incorporated in the Discussion and the following paragraph has been inserted in the Introduction:

“As described above, other authors have already demonstrated associations between GAL polymorphisms and mood disorders, but no studies have been done to date to test this possible association in a non-clinical, normal healthy sample. Thus, our goal was to figure out whether any genetic association is detectable between a set of marker SNPs representing the entire regulatory landscape of the galanin gene and mood characteristics on the normal spectrum as well.”

2. The results aren't very interesting. The association between SNP in the GAL genes and anxiety is very low. It is very difficult to demonstrate this association in healthy young people.

The Reviewer is right in saying that differences between the HADS scores of cohorts with different genotypes are quite low. However, due to the polygenic nature of psychological traits, a single non-coding polymorphism being even in candidate genes typically does not account for greater effects. For comparison, we refer to a paper by de Moor et al. (2012) who performed a meta-analysis on genome-wide association studies for personality traits on a 17,375-strong sample. Despite that large sample size, the variance did not exceed 0.2%. It is of note that in a previous genetic association study (Kótyuk et al., 2013) performed on polymorphisms of the GDNF gene we have got differences commensurable to those in the present manuscript which also proved statistically significant.

As far as the enrollment of healthy, young people is concerned, we refer to the explanation above.

Reviewer #1

1. My concerns are about the nature of the subjects studied vis-à-vis issues of anxiety and depression as psychiatric disorders, to which the authors give detailed attention, and the rating scale used to develop a “phenotype” (subjects with greater or lesser amounts of anxiety and/or depression on the HADS).

Concerning the HADS (ref 31 in the MS), it is a “self-assessment scale…found to be a reliable instrument for detecting states of depression and anxiety in the setting of an hospital medical outpatient clinic. The anxiety and depressive subscales are also valid measures of severity of the emotional disorder… The research was conducted in general medical outpatient clinics on adults of both sexes between the ages of 16 and 65 who suffered from a wide variety of complaints and illnesses.” The HADS thus was not designed to measure anxiety or depression in a sample of normal young adult college students with no complaints or current illnesses.

The Hospital Anxiety and Depression Score (HADS), a psychometric tool was originally developed and has since been widely used to detect depression and anxiety in patients with physical health problems (Zigmond and Snaith, 1983). Over the subsequent decades the test has attained an established role in quantitative psychometrics with almost 5,000 scientific references to date, and it also underwent several re-evaluations and its scope was extended several times.

By reviewing the literature in 2002, Bjelland et al. concluded that it is an adequate tool to assess mood characteristics in the general population too. One of the founding fathers of the test proposed that the questionnaire was valid when used in community settings too (Snaith, 2003). Finally, the intriguing question whether the HADS could measure anxiety and depression in healthy subjects was addressed by Caci et co-workers (2003). Their landmark study concluded that the HADS inquiry battery is sensitive enough to discriminate between two levels of anxiety in a non-clinical, healthy population. They identified these constructs as ‘anxiety’ and ‘restlessness’ (inner tension), the latter interpreted as low-intensity anxiety with lower scores on the HADS-A scale. Their work has paved the way for dozens of recent analyses deploying HADS to quantitate anxiety and depression in normal healthy subjects, especially in cohorts of university students from all over the world with statistically firm data and conclusions (Andrews et al., 2006; Andrews and Wilding, 2004; Gan and Yuen Ling, 2019; Kebede et al., 2019; Lee et al., 2016; Liu et al., 2009; Moreira de Sousa et al., 2018; Sadeghi et al., 2019; Silva and Figueiredo-Braga, 2018). As it is based on a healthy cohort, our manuscript blends well in this series of investigations, being one of a few recent genetic association studies using HADS scores in healthy populations (Jiménez et al., 2018; Loja-Chango et al., 2016; Kotyuk et al., 2013). The latter is actually a former project of ours that analyzed the same healthy population with HADS to set up associations between non-coding genetic polymorphisms in the GDNF gene and anxiety. Thus, the current manuscript is a direct corollary of that one.

To briefly reflect the above, the following paragraph has been incorporated to the Phenotype characteristics section of the manuscript: “The HADS questionnaire measures anxiety and depression on 7-7 items, scoring on a 0 to 3 Likert scale. It was originally developed to assess anxiety and depression in case of non-psychiatric hospital patients [31]. However, a great deal of studies have shown that it is an adequate tool to measure mood characteristics on non-clinical samples as well (Caci et al., 2003).”

2. The mean anxiety score (6.55 +/- 3.7 [which I assume is the standard deviation – not stated]) is in the lowest group of scores (Table 1 in ref 31), which consisted of 98% non-and doubtful-cases of clinical anxiety. As well, the mean depression score (2.80 +/- 2.7) was in the lowest group of scores (Table1 in ref 31), which again consisted of 98-99% non-and doubtful-cases of clinical depression. In short, the normal subjects’ scores were clustered near the low end of the HADS, providing little variance for correlational analysis with the genetics data – not surprising for the use of a hospital clinic-derived scale on normal subjects with no complaints or illnesses. More appropriate depression and anxiety scales should have been used to develop the subjects’ “phenotype.”

Yes, in scores like 6.55 � 3.7, the � value denotes the standard deviation. Thank you for your comment, we indicated it in every table of the manuscript.

Well, it is obviously true that the mean scores on the two subscales are near the lower end of the scale in our sample – especially in case of the depression subscale, which is ‘normal’ considering the nature of the data. However, in the context of our sample size and using the same statistical toolbox which most studies did as quoted above – especially ANOVA that focuses on the variability of the dependent variable - , we got statistically significant correlation data even after Bonferroni’s correction for multiple setting. While maximally respecting the opinion of the Reviewer, we take the liberty of hinting that one might not directly compare the HADS scores and cut-off values from the initial study of Zigmond and Snaith conducted on a clinical sample back in 1983 to those measured in our normal, healthy Central European population that differs from theirs in so many respects.

3. Given the use of an inappropriate rating scale on normal subjects, the lengthy discussions in the Introduction and Discussion sections of the relationship of galanin to psychiatric illnesses is of little relevance. I suggest the authors severely shorten the MS and present it as straightforward correlative study between galanin gene-related SNPs and a psychometric measure of anxiety and depression in normal individuals with no psychiatric illness. The authors should provide one or two sentences as rationale for performing the study, limiting any comment about galanin and psychiatric illness to a short, suggestive statement about its relationship to classical neurotransmitters and that it has been found to be altered in certain psychiatric illnesses, and including the list of references.

As it is a psychiatric genetic study addressing both molecular geneticists, psychologists and psychiatrists, we deemed it important to review and discuss the available literature on galanin and its polymorphisms in sufficient detail to make it understandable for all readers. However, accepting the argumentation of the Reviewer, we have streamlined the Introduction as you suggested regarding correlation between galanin and psychiatric illnesses (see the revised version of the manuscript).

As far as the shortening of the Discussion is concerned, we assume it is important to compare our findings observed in our healthy population to those obtained in transcriptional studies, cell and animal models as well as people with psychiatric problems in order to provide our Readers a comprehensive insight into the relevance of our data in the broader context too. In our opinion, cutting parts of the Discussion would impair the integrity of the paper to a large extent, so we decided not to modify it.

References

Andrews B, Hejdenberg J, Wilding J. Student anxiety and depression: comparison of questionnaire and interview assessments. J Affect Disord. 2006 Oct;95(1-3):29-34. Epub 2006 Jun 9.

Andrews B, Wilding JM. The relation of depression and anxiety to life-stress and achievement in students. Br J Psychol. 2004 Nov;95(Pt 4):509-21.

Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res. 2002 Feb;52(2):69-77.

Caci H, Baylé FJ, Mattei V, Dossios C, Robert P, Boyer P. How does the Hospital and Anxiety and Depression Scale measure anxiety and depression in healthy subjects? Psychiatry Res. 2003 May 1;118(1):89-99.

de Moor MH, Costa PT, Terracciano A, Krueger RF, de Geus EJ, Toshiko T, Penninx BW, Esko T, Madden PA, Derringer J, Amin N, Willemsen G, Hottenga JJ, Distel MA, Uda M, Sanna S, Spinhoven P, Hartman CA, Sullivan P, Realo A, Allik J, Heath AC, Pergadia ML, Agrawal A, Lin P, Grucza R, Nutile T, Ciullo M, Rujescu D, Giegling I, Konte B, Widen E, Cousminer DL, Eriksson JG, Palotie A, Peltonen L, Luciano M, Tenesa A, Davies G, Lopez LM, Hansell NK, Medland SE, Ferrucci L, Schlessinger D, Montgomery GW, Wright MJ, Aulchenko YS, Janssens AC, Oostra BA, Metspalu A, Abecasis GR, Deary IJ, Räikkönen K, Bierut LJ, Martin NG, van Duijn CM, Boomsma DI. Meta-analysis of genome-wide association studies for personality. Mol Psychiatry. 2012 Mar;17(3):337-49. doi: 10.1038/mp.2010.128. Epub 2010 Dec 21.

Gan GG, Yuen Ling H. Anxiety, depression and quality of life of medical students in Malaysia. Med J Malaysia. 2019 Feb;74(1):57-61.

Jiménez KM, Pereira-Morales AJ, Adan A, Lopez-Leon S, Forero DA. Depressive symptoms are associated with a functional polymorphism in a miR-433 binding site in the FGF20 gene. Mol Brain. 2018 Sep 21;11(1):53. doi: 10.1186/s13041-018-0397-0.

Kebede MA, Anbessie B, Ayano G. Prevalence and predictors of depression and anxiety among medical students in Addis Ababa, Ethiopia. Int J Ment Health Syst. 2019 May 6;13:30. doi: 10.1186/s13033-019-0287-6. eCollection 2019.

Kotyuk E, Keszler G, Nemeth N, Ronai Z, Sasvari-Szekely M, Szekely A. Glial cell line-derived neurotrophic factor (GDNF) as a novel candidate gene of anxiety. PLoS One. 2013 Dec 6;8(12):e80613. doi: 10.1371/journal.pone.0080613. eCollection 2013.

Lee SJ, Park CS, Kim BJ, Lee CS, Cha B, Lee YJ, Soh M, Park JA, Young PS, Song EH. Association between morningness and resilience in Korean college students. Chronobiol Int. 2016;33(10):1391-1399. Epub 2016 Aug 30.

Liu Q, Shono M, Kitamura T. Psychological well-being, depression, and anxiety in Japanese university students. Depress Anxiety. 2009;26(8):E99-105. doi: 10.1002/da.20455.

Loja-Chango R, Pérez-López FR, Simoncini T, Escobar GS, Chedraui P. Increased mood symptoms in postmenopausal women related to the polymorphism rs743572 of the CYP17 A1 gene. Gynecol Endocrinol. 2016 Oct;32(10):827-830. Epub 2016 Apr 27.

Moreira de Sousa J, Moreira CA, Telles-Correia D. Anxiety, Depression and Academic Performance: A Study Amongst Portuguese Medical Students Versus Non-Medical Students. Acta Med Port. 2018 Sep 28;31(9):454-462. doi: 10.20344/amp.9996. Epub 2018 Sep 28.

Sadeghi O, Keshteli AH, Afshar H, Esmaillzadeh A, Adibi P. Adherence to Mediterranean dietary pattern is inversely associated with depression, anxiety and psychological distress. Nutr Neurosci. 2019 Jun 11:1-12. doi: 10.1080/1028415X.2019.1620425.

Silva RG, Figueiredo-Braga M. Evaluation of the relationships among happiness, stress, anxiety, and depression in pharmacy students. Curr Pharm Teach Learn. 2018 Jul;10(7):903-910. doi: 10.1016/j.cptl.2018.04.002.

Snaith RP. The Hospital Anxiety And Depression Scale. Health Qual Life Outcomes. 2003 Aug 1;1:29.

Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983 Jun;67(6):361-70.

Submitted filename: Response to reviewers.docx

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24 Oct 2019

PONE-D-19-16922R1

Association between anxiety and non-coding genetic variants of the galanin neuropeptide

PLOS ONE

Dear Dr Keszler,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Review of PONE-D-19-16922_R1: The authors have considered the comments of the reviewers on their original MS and have addressed them accordingly. With regard to my comments on the original MS, I still have concerns about the use of the HADS in the sample of students recruited for this study. I do not disagree that the HADS can detect anxiety and depressive symptoms in an ostensibly normal subject sample, such as students, because a large sample will have some clinically anxious and depressed individuals included. And some likely were in the 526 healthy students included in this study. But the data indicate that there were relatively few such students, because, as I noted in my earlier review, the mean anxiety and depression scores were quite low, with small standard deviations. Nevertheless, the phenotypic data are derived from the HADS, and that’s the reality of the situation. I will not argue this point any further, except to say that the authors might emphasize this a bit more, focusing on the unique aspects of their study of galanin genotypes in a largely normal subject sample.

I am less sanguine about the authors’ rationale of not changing their Discussion, other than adding a paragraph (p 18, lines 312-321) that is a bit fuzzy in its reasoning. For example, the first sentence (“Psychiatric disorders…”) is irrelevant to the study. The second sentence (“We chose…”) does not make sense to me; choosing a young healthy “population” (really a sample, not a population) having few negative life events in order to make “genetic components more exposed and identifiable” is illogical – genetic components of what? Young age and health? The next sentence is speculative (“On the other hand, our randomly selected non-clinical population [again, sample, not population]…might comprise subjects with milder…forms of anxiety and depression.”). Yes it might, but it also might not. Why not test this speculation by comparing the top 10% of the sample with the bottom 10%, both in HADS scores and in genetic characteristics? While I usually am against converting continuous data to categorical data, because of the large loss of information, it would be of interest to see if the top 10% of the subjects had HADS scores in the clinical range. (One could get a sense of this as well from the mean scores + 2 standard deviations.) Absent further analysis, the sentence remains speculative and conveys no useful information.

As well, the second sentence of the next paragraph (“It is possible that the association…”) is speculative and non-informative. Yes, anything is possible if the data were different. But they are not.

The above comments on the Discussion section can be summarized by my comment about the MS in my original review: I suggest the authors severely shorten the MS. This particularly includes the Discussion, with elimination of the non-informative aspects and those aspects not directly related to this study.

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Reviewer #1: Yes: Robert T. Rubin MD, PhD

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13 Nov 2019

Authors’ responses to Reviewer 1

Dear Professor Rubin,

Thank you very much for your careful re-evaluation of our revised manuscript. We are very grateful for your valuable suggestions on how to substantiate our largely speculative allegations in the Discussion.

1. We totally agree with your remarks on the use of the HADS questionnaire in a seemingly normal sample of students recruited for this study. To emphasize better that our study differs in this respect from other studies using clinical samples for association studies, the following sentence has been inserted into the introductory section of the manuscript: (association was tested) “in an ostensibly normal sample consisting of university students with no psychiatric history”, and it is highlighted again in the second sentence the Discussion chapter: “In contrast to former research aimed to find genetic associations between GAL gene variants and mood characteristics in subjects with clinical anxiety and depression, the novelty of the present study is that it was performed in a cohort of apparently normal, healthy volunteers.”

2. To expel your concerns regarding our speculative assumption on the potentially marked stratification of our (seemingly) normal sample (students without psychiatric history), we tested whether the HADS scores of the top 10% cohorts of students reach the clinical range on the depression and anxiety subscales – as you suggested.

As described in the ‘Phenotype characteristics’ paragraph of the ‘Materials and methods’ section, the mean anxiety score in the total sample was 6.55 (± 3.7 standard deviation) and the mean depression score was 2.80 (± 2.7). Upon setting up the “top 10%” and “bottom 10%” cohorts, it turned out that 11.4% of the sample (n=60 individuals) scored lower than 3 and 9.9% of the sample (n=52) scored higher than 11 on the anxiety scale. 9.7% of the sample (n=51) scored higher than 6 and 11.6% of students (n=61) scored 0 on the depression scale.

Descriptive statistics for these cohorts are as follows. Anxiety mean score ± standard deviation for the anxiety bottom 11.4%: 1.32 ± 0.673; and for the top 9.9%: 14.23 ± 2.278. Depression mean score ± standard deviation for the depression bottom 11.6%: 0 (all depression scores were 0 for all members of this cohort); and for the top 9.7%: 9.160 ± 1.902. Hermann et al. (1995) and Caci et al. (2003) found that the cut-off values for “abnormal”, i.e. clinical depression and anxiety were 11 and 9 HADS scores, respectively. These data corroborate our assumption that a significant portion of our healthy, non-clinical sample had clinical anxiety and depression indeed.

These findings prompted us to perform genetic association analyses on these cohorts as well. Results of these tests can be seen in the table beneath. The Chi square analysis of allele frequencies in the top versus bottom 10% cohorts revealed statistically significant association of the rs1042577 SNP with anxiety and depression. However, the association between GAL rs948854 and rs4432027 with anxiety was not observable in this context, possibly due to low cohort sizes.

dbSNP

number Anxiety Depression

low- anxiety cohort

(n=60) high- anxiety cohort

(n=52) p low- depression cohort

(n=61) High- depression scores

(n=51) p

rs948854 C 31.4% 39.4% 0.209 36.7% 39.2% 0.696

T 68.6% 60.6% 63.3% 60.8%

rs2097042 C 29.6% 37.0% 0.272 37.7% 40.2% 0.726

T 70.4% 63.0% 62.3% 59.8%

rs4432027 C 30.2% 39.6% 0.151 36.8% 39.1% 0.736

T 69.8% 60.4% 63.2% 60.9%

rs694066 A 14.4% 14.7% 0.950 10.2% 15.2% 0.270

G 85.6% 85.3% 89.8% 84.8%

rs3136540 T 27.3% 33.7% 0.322 32.1% 31.7% 0.957

C 72.7% 66.3% 67.9% 68.3%

rs1042577 T 30.6% 50.0% 0.005 36.8% 51.2% 0.048

C 69.4% 50.0% 63.2% 48.8%

We decided to mention these interesting data in the Discussion section to provide further evidence for the association described between the rs1042577 T allele and anxiety from a different approach and to underpin our speculative sentences with statistical data. The Discussion has been shortened and tautened by removing non-relevant or lengthy speculative sentences, according to your suggestions.

Thank you again for your inspiring comments that made us rethink the concept by obtaining further data in support of the biological relevance of GAL polymorphism in anxiety and depression.

Sincerely yours,

Gergely Keszler

corresponding author

Submitted filename: Answers To Reviewer 1.docx

Click here for additional data file.

22 Nov 2019

Association between anxiety and non-coding genetic variants of the galanin neuropeptide

PONE-D-19-16922R2

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18 Dec 2019

PONE-D-19-16922R2

Association between anxiety and non-coding genetic variants of the galanin neuropeptide

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