Association of SLC1A1 gene polymorphism with obsessive compulsive disorder in a sample from southern India.

Acknowledgement: Biju Viswanath, Meera Purushottam, Gerald Nestadt, Y. C. Janardhan Reddy, and Sanjeev Jain conceived and designed the study. Tulika Shukla and Reshma Jabeen Taj M. J. were involved in recruitment and data collection. Tulika Shukla, Reshma Jabeen Taj M. J., Ravi Kumar Nadella, and Suhas Ganesh are involved with data analysis. Tulika Shukla, Ravi Kumar Nadella, and Suhas Ganesh have prepared the manuscript. All authors read and approved the final manuscript. The work was funded by the Indian Council of Medical Research (Grant GIA/38/2014-DHR), Government of India. Reshma Jabeen Taj M. J. was funded by Sun Pharmaceutical Industries Limited as a PhD scholar under Y. C. Janardhan Reddy in the Molecular Genetics Laboratory. Ravi Kumar Nadella is funded by the Accelerator program for Discovery in Brain disorders using Stem cells (ADBS), a program funded by the department of Biotechnology, Government of India and the Pratiksha trust.

Obsessive-compulsive disorder (OCD) is a major psychiatric illness with lifetime prevalence of 1–3% in the general population (Kessler et al., 2005; Ruscio, Stein, Chiu, & Kessler, 2010). Family and twin studies have estimated the heritability of OCD as 26–61% (Bloch & Pittenger, 2010; Hanna, Himle, Curtis, & Gillespie, 2005), suggestive of a genetic involvement in the pathophysiology of OCD.

Evidence from neuroimaging, genetics, neurochemical investigations and insights from animal models suggests that glutamatergic signaling is dysregulated in OCD (Pittenger, Bloch, & Williams, 2011). Many genes in the glutamatergic system like GRIN2B, SAPAP3, and SLC1A1 have been associated with OCD (Pauls, 2010). Pharmacologic agents modulating glutamatergic transmission such as memantine, topiramate and riluzole have been found to be useful in treating OCD (Grados, Specht, Sung, & Fortune, 2013). Studies show that serotonin reuptake inhibitors (SRI), which are first line treatment for OCD, have effect on glutamatergic function in the neuro-glia complex. In an in vitro study using human platelets, sertraline significantly reduced glutamate uptake after treatment (Rodrigues, Bristot, Klamt, & Frizzo, 2015). In another study performed on HEK293T cells, sertraline and fluoxetine reduced glutamate uptake by astroglial Kir4.1 channels (Ohno, Hibino, Lossin, Inanobe, & Kurachi, 2007).

The SLC1A1 gene encodes the primary neuronal glutamate transporter EAAT3 located at the 9p24 locus. Linkage studies have reported a signal for OCD in this region (Hanna et al., 2005; Willour et al., 2004). Several studies using family or case control design have shown association of various single nucleotide polymorphisms (SNP) in the SLC1A1 gene with OCD (Abdolhosseinzadeh, Sina, Ahmadiani, Asadi, & Shams, 2019; Arnold, Sicard, Burroughs, Richter, & Kennedy, 2006; de Salles Andrade et al., 2019; Dickel et al., 2006; Samuels et al., 2011; Shugart et al., 2009; Stewart et al., 2007; Wang et al., 2010; Zhang et al., 2015). The most consistently implicated SNP in the above-mentioned studies is a 3′ polymorphism rs3780412 (Dickel et al., 2006; Stewart et al., 2007), but no specific SNPs or haplotypes associated with OCD risk have been consistently reproduced across these studies. However, a meta-analysis comprising 815 trios, 306 patients with OCD, and 634 controls found no significant correlations between nine SNPs in the SLC1A1 gene and risk of OCD (Stewart et al., 2013). SLC1A1 is also shown to have a role in antipsychotic treatment induced OC symptoms in schizophrenia patients, and in those with OCD-related hoarding symptoms (Kwon et al., 2009). Studies have also shown an association of polymorphisms in the SLC1A1 gene with SRI treatment response in OCD (Abdolhosseinzadeh et al., 2019; Zhang et al., 2015).

In this study, we examine the association of the SLC1A1 rs3056 polymorphism in patients with OCD. This polymorphism has previously shown to be associated with thalamic volume in pediatric OCD (Arnold et al., 2009). In addition, we also examine the association of this SNP with clinical variables such as age of onset, disease severity, insight, factor-analyzed symptom dimensions of OCD, and treatment response.

Three hundred seventy seven patients fulfilling the DSM–IV criteria for OCD (APA, 1994) aged between 18 to 60 years without comorbid psychosis, bipolar disorder, mental retardation, and neurological disorders were recruited from the specialty OCD clinic at the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India. The study is part of ongoing work on genetics of OCD in the institute. Information was collected using the standard clinical proforma, which includes sociodemographic data, age of onset of OCD, duration of illness, duration of untreated illness, detailed history of present illness, presence of common comorbid disorders—including mood disorders, anxiety disorders, tic disorders, and other OC-spectrum disorders, family history of OCD and major psychiatric disorders, and detailed treatment history. Presence of OCD and other comorbid diagnoses were confirmed using Mini-International Neuropsychiatric Interview–Plus (MINI-Plus; Sheehan et al., 1998). Patients were additionally assessed on the Yale Brown Obsessive Compulsive Scale (YBOCS; Goodman et al., 1989), and the Clinical Global Impression scale (CGI; Guy, 1976). Insight was measured using YBOCS Item 11 (Goodman et al., 1989).

As a routine clinical follow-up in the OCD clinic, patients were reassessed with the YBOCS and CGI to monitor improvement. The usual follow-up duration is once in a month or 2 months. To study extreme phenotypes in serotonin reuptake inhibitor (SRI) treatment response, we included patients who are full responders (≥35% reduction in the YBOCS and the CGI-I score of 1 or 2; n = 187) and nonresponders (<25% reduction in the YBOCS and the CGI-I score >4; n = 91) after adequate trial of at least two SRIs for a duration of 12 weeks (Mataix-Cols et al., 2016; Pallanti & Quercioli, 2006). Patients who were on the adjuvant benzodiazepines or on other augmenting treatments and who had not received two adequate trials were excluded from SRI treatment response analysis.

The control population (n = 333) consisted of healthy individuals who were recruited by word of mouth and did not have any major psychiatric illnesses as per the MINI plus, and no family history of OCD in at least two previous generations. Patients and controls had all four grandparents originating from the southern Indian region. The study was conducted in keeping with the Code of Ethics of the World Medical Association (Declaration of Helsinki) and was approved by the ethics committee of the institute. Written informed consent was obtained from all study subjects.

Genomic DNA was extracted from peripheral blood leukocytes by NaCl precipitation (Miller, Dykes, & Polesky, 1988) and genotyping at rs3056 was performed by TaqMan genotyping assay (Assay id #C_797985_10) from Thermo Fisher scientific using Applied Biosystems 7500 Real-Time PCR Systems.

Deviation from the Hardy-Weinberg equilibrium (HWE) was tested with the χ2 test. Allelic and genotypic distributions were compared using the χ2 test. Normality of the data was checked using Shapiro-Wilk test. For generation of the factors (symptom dimensions), the 14 lifetime symptom categories from the YBOCS symptom checklist were used (excluding all miscellaneous symptoms except mental rituals). Symptom dimensions were made using principle component analysis using Varimax rotation and eigenvalue of greater than 1. Factor loading of greater than 0.5 was considered as robust. Ascertaining a non-normal distribution across genotypes, clinical variables were tested for genotype association using Mann–Whitney U test. Significant p value was considered as <0.006 after Bonferroni correction for genetic association with clinical variables, <0.05 for case control analysis and genetic association with treatment response.

The clinical and demographic details of the patients (n = 377) are represented in Table 1. The mean age of the patients in our sample was 29.2 (SD = 9.5) years, which is significantly different from the control group 36.16 (SD = 16.5; t = −6.76, p < .0001). The gender ratio (M %) of cases is 61%, which is significantly different from controls 50.8% (χ2 = 7.55/p = .005). Factor analysis yielded five factor solution as the best fit for the data explaining 65% of the variance as follows—Factor 1 (hoarding) with robust loading on hoarding obsession (.891) and collecting compulsions (.913); Factor 2 (symmetry and orderliness) with obsessions of need for symmetry (.821) and ordering compulsions (.864); Factor 3 (doubts and checking) with pathological doubts obsessions (.824) and checking compulsions (.819); Factor 4 (forbidden thoughts) with sexual (.680), religious (.655), and aggressive obsessions (.554), mental rituals compulsions (.630); and Factor 5 (contamination) with contamination obsessions (.919) and washing compulsions (.893).

Genotype frequencies showed no significant deviation from Hardy Weinberg equilibrium. Genotype “GG” was significantly more frequent in cases than the controls and found to be modestly associated with OCD. The allele “A” was found to be more frequent in controls than the cases (see Table 2). No statistical association was found between the genotype or allele frequency and the age of onset, symptom severity or any of the symptom dimensions (Supplementary Table S1 in the online supplemental materials).

The sample characteristics between the responders and nonresponders to SRI treatment are similar except for the mean duration of the illness, which is longer in nonresponders (9.1 years) compared to responders (6.6 years; p = .004). Illness severity is significantly higher at baseline in nonresponders (YBOCS = 26.6; CGI = 4.6) compared to responders (YBOCS = 24.2; CGI = 4.4; p = .002 and p = .08, respectively; data not shown).

Genotype frequencies were in accordance with the prediction by Hardy Weinberg equilibrium. The frequent genotype in the sample is AA (56.5%), followed by AG (36.7%), and GG (6.8%). Chi-square analysis done using the genotype frequency (χ2 = 1.34/p = .5) and allele frequency (χ2 = 0.00/p = 1.0) between the responders and responders showed no significant association (Supplementary Table S2 in the online supplemental materials).

We observed a marginally significant association between rs3056 polymorphism of SLC1A1 and OCD in a southern Indian sample. This polymorphism has previously been reported to be associated with increased thalamic volumes in pediatric OCD (Arnold et al., 2009).

It is important to note that this specific SNP has not been associated with OCD in other populations. This could be due to variations in allele frequency. From the dbSNP database, the “A” allele frequency in south Asian population is 0.7, while it is 0.3 in Han Chinese population and 0.8 in European population (Sherry et al., 2001). This finding is consistent with other independent studies that have found associations with the SLC1A1 gene, but the specific SNPs are not replicated. A meta-analysis of 815 trios, 306 patients with OCD, and 634 controls had found that one SLC1A1 SNP was weakly associated with OCD (rs301443, p = .046; nonsignificant when corrected), and another SNP was modestly associated with OCD, but only in males (rs12682807; p = .012; nonsignificant when corrected; Stewart et al., 2013). Another study had found that six common SNPs of SLC1A1 did not contribute to the development of OCD, but instead contributed to trait empathy such as personal distress (Kim, Kang, Hwang, & Kim, 2018). These positive associations with the gene, but not with specific SNPs, suggests substantial allelic heterogeneity. This suggests that different variants within a single locus or gene could be contributing to disease risk, which in turn supports the hypothesis that different SNPs could be regulating the level of its expression to influence disease biology.

In the study, we did not detect an association of the rs3056 polymorphism with OCD symptom dimensions and other clinical variables, or with treatment response. We did not find any previous studies looking at association of the SLC1A1 gene with symptom dimensions in OCD. Studies in the Han Chinese population and Iranian population had found a significant influence of other SLC1A1 SNPs on fluoxetine and fluvoxamine response, respectively, in OCD patients (Abdolhosseinzadeh et al., 2019; Zhang et al., 2015). In another study, four SNPs across SLC1A1 were observed to be significantly associated with response to different SRI(s): citalopram, sertraline, and fluvoxamine (Zai, Brandl, Müller, Richter, & Kennedy, 2014). In another study looking at several SNPs in the SLC1A1 genomic regions in a sample of 238 OCD patients, rs308779 were found to be associated with increased risk of treatment resistance in OCD patients without life stress at the onset of illness, which indicates a complex gene environment interaction on treatment resistance (Real et al., 2013). In our study we did not assess the presence of life stressors at onset or other psychosocial factors affecting the presentation.

The use of structured instruments for phenotype characterization is a strength of the study. A limitation is the absence of any dimensional assessment for OC traits. Such an evaluation could enable us to examine the association of SLC1A1 gene polymorphism with obsessive traits. There were a higher number of male patients in our sample, which does not represent the gender distribution of OCD in the community. This could be due to the higher treatment-seeking behavior in male patients due to various psychosocial factors, which has been previously reported from our clinic (Cherian et al., 2014). The severity of OCD in our sample was moderate (mean baseline YBOCS = 24 and CGI = 4.4), which is comparable to other studies looking at treatment response.(Abdolhosseinzadeh et al., 2019; Kim et al., 2018; Real et al., 2013). Most of the studies have looked at association with specific SRI drug response; in our study we have grouped response to any SSRI that might be a potential limitation. However, such distinction for the specific SSRI response can have major impact when we examine pharmacokinetic properties such as effect of variation in cytochrome P450 (CYP) polymorphism and treatment response (Brandl, Müller, & Richter, 2012). Exclusion of the partial responders from the study design is another limitation of our study. In our secondary analysis including partial responders (n = 20) using YBOCS improvement as continuous phenotype using the Kruskal Wallis test, we did not find any significant association (χ2(2) = 1.12, p = .57; data not shown). As partial responders are few in number, removing partial responders from our analysis had no major effect on our findings.

To conclude, our study shows association of SLC1A1 polymorphism (rs3056) with OCD in a south Indian population. However, no association was observed with symptom dimensions or treatment response.

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Submitted: July 23, 2019 Revised: December 4, 2019 Accepted: December 4, 2019