Compulsive Disorder: a Comprehensive Meta-Analysis of Genetic Association Studies

ORIGINAL ARTICLE Molecular genetics of obsessive--compulsive disorder: a comprehensive meta-analysis of genetic association studies

S Taylor

Twin studies indicate that obsessive--compulsive disorder (OCD) is strongly influenced by additive genetic factors. Yet, molecular genetic association studies have yielded inconsistent results, possibly because of differences across studies in statistical power. Meta-analysis can yield greater power. This study reports the first comprehensive meta-analysis of the relationship between OCD and all previously examined polymorphisms for which there was sufficient information in the source studies to compute odds ratios (ORs). A total of 230 polymorphisms from 113 genetic association studies were identified. A full meta-analysis was conducted for 20 polymorphisms that were examined in 5 or more data sets, and a secondary meta-analysis (limited to the computation of mean effect sizes) was conducted for 210 polymorphisms that were examined in fewer than 5 data sets. In the main meta-analysis, OCD was associated with serotonin-related polymorphisms (5-HTTLPR and HTR2A) and, in males only, with polymorphisms involved in catecholamine modulation (COMT and MAOA). Nonsignificant trends were identified for two dopamine-related polymorphisms (DAT1 and DRD3) and a glutamate-related polymorphism (rs3087879). The secondary meta-analysis identified another 18 polymorphisms with significant ORs that merit further investigation. This study demonstrates that OCD is associated with multiple genes, with most having a modest association with OCD. This suggests a polygenic model of OCD, consistent with twin studies, in which multiple genes make small, incremental contributions to the risk of developing the disorder. Future studies, with sufficient power to detect small effects, are needed to investigate the genetic basis of OCD subtypes, such as early vs late onset OCD.

Molecular Psychiatry (2013) 18, 799--805; doi:10.1038/mp.2012.76; published online 5 June 2012 Keywords: association studies; genetics; meta-analysis; obsessive--compulsive disorder

INTRODUCTION problematic when genes with small effect sizes are being investi- Obsessive--compulsive disorder (OCD) is characterized by distre- gated. Meta-analysis, compared with the individual studies ssing, time-consuming obsessions and compulsions. Obsessions included in a meta-analysis, can be a more powerful method of 7 are unwanted thoughts, images or urges. Compulsions are repeti- evaluating effect sizes. Inconsistent findings across studies also tive behaviors or mental acts that the person feels compelled to might be an indication of the etiologic heterogeneity of OCD; perform, typically with a desire to resist.1 The exact etiology of there is evidence of sex differences and evidence of distinct 8 OCD is unknown, although evidence suggests that the disorder subtypes of the disorder. Different subtypes may be etiologically arises from complex combination of biopsychosocial factors, different from one another, and the genes involved in OCD might including genetic and environmental factors.2 A recent meta- be different for males compared with females. Meta-analysis analysis of 37 twin samples suggests that obsessions and com- can be used to investigate this issue by means of moderator pulsions arise from a combination of additive genetic factors and (subgroup) analyses. nonshared environment.3 As with other forms of psychopathol- The purpose of this study was to conduct the first comprehen- ogy,4 OCD might be shaped by a large number of genes of sive meta-analysis of genetic association studies of OCD, includ- modest impact, which additively combine to influence the risk for ing, where possible, data on all polymorphisms that have been developing obsessive--compulsive symptoms or disorder. studied so far. There have been over 100 OCD genetic association One of the leading biological models of OCD is the frontal-- studies, and so a comprehensive meta-analysis of this substantial striatal--thalamic model, which emphasizes the role of aberrant literature is warranted. Four previous meta-analyses have been modulation of brain circuits involving the prefrontal cortex, published, but each was limited to only a single polymorphism. regions of the basal ganglia such as the striatum and globus Azzam and Mathews9 meta-analyzed a small number of case-- pallidus, and the thalamus.5 Aberrant modulation could be due to control (CC) and family-based (FB) studies of COMT. They found no structural abnormalities and/or dysregulations in the neuromodu- association between either the Met or Val polymorphisms and lators or neurotransmitters (for example, serotonin, glutamate and OCD. Pooley et al.10 conducted a meta-analysis of COMT and dopamine) involved in these circuits. found significant sex differences in terms of allele distribution and There have been many molecular genetic studies of OCD but risk of OCD. Their study was limited because they included only CC relatively few consistent findings.6 Inconsistencies might have studies, which are prone to sample stratification effects.11 Both CC been due to differences across studies in statistical power, which is and FB studies have their strengths and weaknesses.12 Lin13 and

Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada. Correspondence: Professor S Taylor, Department of Psychiatry, University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC V6T 2A1, Canada. E-mail: [email protected] Received 17 January 2012; revised 11 April 2012; accepted 2 May 2012; published online 5 June 2012 Genetics of obsessive--compulsive disorder S Taylor 800 Bloch et al.14 meta-analyzed studies on the L and S polymorphisms etiologically heterogeneous.8 Effect sizes might vary as a function of a of 5-HTTLPR and found no association between any polymorphism range of variables, including study design (CC vs FB designs) and and OCD. A limitation of both meta-analyses was that there are 3, demographic variables such as sex and racial background. not 2, relatively common polymorphisms of 5-HTTLPR; La, Lg and Given the number of statistical analyses conducted in this study, the a S. Lg biologically acts like S, and so the question arises as to level for statistical significance was set at 0.01 (two-tailed) instead of the whether OCD is associated with La. (There are also two forms of S: conventional 0.05, in order to reduce type I error without unduly inflating 15,16 Sa and Sg. The latter is very rare compared with Sa, La and Lg). type II error. (With regard to type I and II errors when multiple tests are Until recently, most OCD studies had treated La and Lg as if they conducted, a stringent correction in type I error (for example, a Bonferroni were identical to one another. This study sought to address these correction) increases the number of type II errors. This is of particular limitations and to extend the investigation by meta-analytically concern when small effects are being investigated because statistical examining the association between OCD and many other power is reduced when type II error is increased. Some investigators have polymorphisms that have not been previously meta-analyzed. argued against the use of Bonferroni and related corrections, because of This study is the first meta-analysis to examine all polymorphisms their effects on inflating type II error.19,20 Lieberman and Cunningham21 that have been studied so far in relation to OCD for studies in argued for a more liberal a level than that imposed by a Bonferroni which effect sizes (odds ratios; ORs) could be computed. In correction because ‘type I errors are self-erasing because they will not addition to presenting meta-analytic findings, this study also replicate’ (p. 423). But an a level of 0.05 would seem unduly liberal given sought to identify important gaps or limitations in the research that 20 polymorphisms were examined in the main meta-analysis in this literature. If OCD is likely to be etiologically heterogeneous and article. A commonly used alternative is to set a at 0.01,22,23 which in this associated with genes that have small effects, then the question study lies between a Bonferroni-corrected a for the 20 polymorphisms arises as to whether the research literature adequately addresses (0.003) and 0.05. For the tests of mean ORs of these polymorphisms, this these issues. This involves questions of whether genetic associa- approach was supplemented by comparing the obtained P-values with tion studies have had sufficient statistical power to detect small cutoff values computed from the Holm--Bonferroni method,24,25 which effects, and whether these studies have adequately investigated controls type I error (at a ¼ 0.05) without inflating type II error as much as the question of whether genetic findings vary as a function of the Bonferroni method. Holm--Bonferroni corrections did not alter the moderator variables, such as OCD subtypes (for example, early vs main conclusions in this article.) late onset OCD, where the former is more prevalent in males)8 and Publication bias---the selective publication of significant results---was other potential moderators, such as particular symptom profiles. assessed by Egger’s test,26 for which significant t-values indicate that the obtained results are biased or unrepresentative of the universe of possible studies. Publication bias was examined only for polymorphisms in which MATERIALS AND METHODS the weighted mean OR was significantly different from 1. For each Relevant studies were identified by systematically searching, up to 1 March polymorphism, heterogeneity of ORs was assessed by I2, which represents 2012, MEDLINE, PsychINFO and EMBASE. All three databases were the percentage of variability in effect sizes that is due to true heterogeneity searched because they are not entirely overlapping in content.17 Search (that is, in excess of that due to random error). terms were (obsessive--compulsive or OCD) combined with (gene, genes, According to current guidelines,7 a full random effects meta-analysis is genetic, genotype, allele* or polymorphism*). Asterisks denote the use of recommended only when there are five or more data sets per effect size wild cards. References cited in all identified articles, and references cited in (that is, five or more data sets per polymorphism). Accordingly, a full meta- relevant review articles and book chapters, were also examined. For all analysis (for example, effect size analysis, Egger’s test, I2, mixed effects journals that had published genetic association studies of OCD, their moderator analyses and other analyses reported in the appendix of on-line ‘in press’ (or ‘online first’) publications were also inspected for Supplementary Information) was conducted only for polymorphisms for potentially suitable studies. which there were five or more data sets. Moderator analyses were limited A total of 179 potentially relevant studies were located, yielding 113 by the information provided in the source studies. These analyses were studies that were suitable for meta-analysis. A complete list of included confined to the analysis of effects of design (CC vs FB), sex, race (Asian and excluded studies appears in the appendix of Supplementary Materials. vs Caucasian) and sample age (child--adolescent (o17 years) vs adult Studies were included if they used either CC or FB association designs in (17 or older)). which cases (probands) met DSM-III, DSM-III-R or DSM-IV criteria for OCD. Sample age is a potentially important moderator variable because it can Studies were included only if it was possible to compute an effect size (OR) be used as a proxy measure of age of onset of OCD. (Too few studies for allele frequency for a given polymorphism. Studies were excluded if reported age of onset for inclusion of this variable in the meta-analysis). their samples were subsumed within other, larger studies included in the Early vs later onset OCD are empirically defined subtypes of the disorder.8 meta-analysis, or if the sample consisted of form of OCD that may not be Child--adolescent samples consist of early onset cases whereas adult representative of OCD in general (for example, OCD studied exclusively in samples likely consist of a mix of early vs later onset. The age cutoff of 17 people with Velocardiofacial syndrome). Samples consisting entirely of years, which was dictated by the nature of the age groups in the probands with hoarding symptoms were excluded from meta-analysis. This association studies, comes close to the cutoff of 21 years, which is the was to limit the number of probands who would be diagnosed with empirically defined optimal cutoff for distinguishing early from late onset hoarding disorder (as currently proposed for DSM-V; www.dsm5.org) rather OCD.8 than diagnosed with OCD. As currently proposed for DSM-V, people with For polymorphisms that were investigated in fewer than five data sets, a prominent hoarding symptoms would be diagnosed as having hoarding secondary meta-analysis was conducted, limited to the computation of disorder. OCD would be diagnosed when a person has hoarding symptoms mean ORs for each polymorphism. This can provide useful preliminary that do not dominate the clinical picture; that is, when hoarding co-occurs information about whether a given polymorphism is a promising with prototypic obsessive--compulsive symptoms (for example, checking, candidate for further investigation. washing) and hoarding is not the primary symptom in terms of severity. Analyses were conducted using the Comprehensive Meta-Analysis program, version 2.2050.18 ORs from individual studies were weighted according to the inverse variance method, in which more precise studies RESULTS (that is, those with smaller variances and typically larger sample sizes) Characteristics of probands included in the meta-analyses received greater weighting.7 Random effects modeling was used to For the studies included in the main and secondary meta-analyses, compute mean ORs because it was unclear whether the true effect size for the mean number of OCD probands was 113 (range 9--459). a given polymorphism is the same across all studies or subgroups. This Regarding the descriptive features of the probands, the following type of analysis was indicated, given the evidence suggesting that OCD is weighted means were computed (weighted by sample size) for

Molecular Psychiatry (2013), 799 -- 805 & 2013 Macmillan Publishers Limited Genetics of obsessive--compulsive disorder S Taylor 801 those studies presenting relevant data: males ¼ 52%, age at and COMT. Table 1 also shows nonsignificant trends for two assessment ¼ 33 years, age at OCD onset ¼ 17 years, lifetime dopamine-related polymorphisms (DAT1 and DRD3) and a history of a tic disorder ¼ 17%, prevalence of OCD among first- glutamate-related polymorphism (rs3087879). degree relatives of probands ¼ 25%, mean score of probands at Forest plots of ORs for triallelic 5-HTTLPR and HTR2A appear in the time of assessment on the Yale--Brown Obsessive--Compulsive Figures 1 and 2, respectively. The size of the squares corresponds Scale ¼ 24 (indicating moderate-to-severe symptoms). The pro- to the weighting assigned to each study and the width of the portion of probands reporting particular obsessive--compulsive diamonds corresponds to the 99th percentile confidence interval symptoms was as follows: checking ¼ 69%, contamination/ of the weighted mean OR. Egger’s test was nonsignificant for the cleaning ¼ 46%, symmetry/ordering ¼ 42%, hoarding ¼ 18% (a triallelic 5-HTTLPR, t(6) ¼ 0.39, P40.10, and for HTR2A, t(17) ¼ 0.86, given proband may have had more than one symptom). P40.10. This suggests that it was unlikely that the mean ORs for these polymorphisms were biased by the selective publication Mean effect sizes of studies obtaining significant results. Egger’s tests for COMT Most (94%) controls in CC studies in the main and secondary are reported later in this article, with regard to the analyses of meta-analyses were in Hardy--Weinberg equilibrium, and the significant sex differences. pattern of results did not change when studies not in equilibrium To facilitate the interpretation of the ORs in Table 1, they were converted to Cohen’s d, where values of 0.2, 0.5 and 0.8 represent were excluded (see Appendix). Twenty polymorphisms were 28 examined in the main meta-analysis (Table 1). These were related small, medium and large effect sizes, respectively. These values to the regulation of serotonin (5-HTT, 5-HTTLPR, HTR1B, HTR2A of d correspond to ORs of 1.437, 2.477 and 4.268. Table 1 shows and HTR2C), glutamate (SLC1A1), dopamine (DAT1, DRD2, DRD3 that, in terms of d, all effects were small, even those that attained and DRD4), catecholamines (COMT and MAOA) and neurotrophin statistical significance. With a greater number of studies, and/or (BDNF). For HTR2A, the meta-analysis combined data from larger sample sizes in the studies, more of the mean ORs in Table 1 two polymorphisms (rs6311 and rs6313). These were combined may have reached statistical significance. However, these would because they are in complete linkage disequilibrium with one have represented very small effects. another,27 which means that the findings for one polymorphism are identical to those of the other. The weighted mean ORs for Moderator (subgroup) analyses rs6311 and rs6313 did not significantly differ from one another; The values of I2 (Table 1) suggests that for each polymorphism w2(df ¼ 1) ¼ 2.13, P40.10. there was a good deal of heterogeneity in ORs, which raises Table 1 shows that the mean ORs were significant for three the question of whether ORs significantly varied as a function polymorphisms; 5-HTTLPR (coded as triallelic; La vs Lg þ S), HTR2A of moderator variables. Moderator (subgroup) analyses were

Table 1. Main meta-analysis: weighted mean ORs signiﬁcantly 41 (highlighted in bold) indicate that the target allele was associated with obsessive-- compulsive disorder

No. of Mean OR (and 99th Mean OR Target allele vs data percentile conﬁdence Obtained P-value Holm- Bonferroni expressed as I2 Gene Polymorphism other allele(s) sets interval) for mean OR critical P-value Cohen’s d (%)

5-HTT STin2 VNTR 12 vs non-12 11 1.052 (0.845--1.309) 0.554 0.006 0.028 38 5- Coded as L vs S 34 1.051 (0.937--1.179) 0.266 0.005 0.027 32 HTTLPR biallelic 5- Coded as La vs (Lg+S)81.251 (1.048--1.492) 0.001 0.003 0.123 21 HTTLPR trialleic BDNF rs6265 Met vs Val 12 1.013 (0.765--1.342) 0.904 0.017 0.007 56 COMT rs4680 Met vs Val 25 1.200 (1.001--1.438) 0.010 0.003 0.101 44 DAT1 VNTR 9 vs non-9 8 1.260 (0.894--1.775) 0.082 0.003 0.127 24 repeats DRD2 rs1800497 C vs T 7 0.801 (0.535--1.198) 0.156 0.004 0.122 45 DRD3 rs6280 T vs C 7 1.388 (0.901--2.139) 0.051 0.003 0.181 61 DRD4 VNTR 2 vs non-2 10 0.837 (0.440--1.592) 0.476 0.005 0.098 60 repeats DRD4 VNTR 4 vs non-4 10 1.021 (0.639--1.631) 0.910 0.025 0.011 78 repeats DRD4 VNTR 7 vs non-7 10 1.041 (0.680--1.596) 0.807 0.008 0.022 58 repeats HTR1B rs6296 G vs C 11 1.139 (0.860--1.509) 0.232 0.004 0.072 40 HTR2A rs6311 or A vs G ( ¼ T vs 19 1.219 (1.037--1.433) 0.002 0.003 0.109 24 rs6313 C) HTR2C rs6318 Cys vs Ser 6 0.956 (0.533--1.716) 0.843 0.010 0.025 50 MAOA EcoRV T vs C 6 1.281 (0.516--3.182) 0.483 0.007 0.137 82 SLC1A1 rs301430 T vs C 8 1.001 (0.771--1.301) 0.989 0.050 0.001 23 SLC1A1 rs301434 A vs G 7 0.818 (0.492--1.359) 0.308 0.004 0.111 58 SLC1A1 rs301979 C vs G 6 0.958 (0.548--1.675) 0.844 0.013 0.024 34 SLC1A1 rs3087879 G vs C 5 1.600 (0.918--2.788) 0.029 0.003 0.259 45 SLC1A1 rs3780412 A vs G 7 1.095 (0.633--1.810) 0.641 0.006 0.050 58 Abbreviations: OR, odds ratio; VNTR, variable number tandem repeats. Signiﬁcant results are also indicated by P-values for mean ORs that were larger than their corresponding Holm--Bonferroni P-values. The Holm--Bonferroni method is a sequential method of testing P-values (tested from smallest to largest) that maintains the family-wise error rate (that is, across the 20 ORs) at a ¼ 0.05.

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 799 -- 805 Genetics of obsessive--compulsive disorder S Taylor 802

15,16,34--36 Figure 1. 5-HTTLPR, La vs (Lg þ S): forest plot of odds ratios (ORs) and 99th percentile conﬁdence intervals. F, female; M, male.

Figure 2. HTR2A, A vs G (equivalent to T vs C): forest plot of odds ratios (ORs) and 99th percentile conﬁdence intervals.20,37--49 F, female; M, male.

conducted for each polymorphism in the main meta-analysis. list). Of these, 18 were significant (Po0.01). Polymorphisms Method effects (CC vs FB designs) were nonsignificant for all 20 significantly associated with OCD were those related to trophic polymorphisms; w2(df ¼ 1)o6.19, P40.01. Sample age was not factors (BDNF polymorphisms apart from the one examined in the significantly related to ORs for any polymorphism, although there main meta-analysis, as well as NGFR and NTRK2), GABA (GABRB3), were two nonsignificant trends: for HTR1B, there was a trend glutamate (GRIK2), serotonin (HTR2A C516T), bradykinin (BDKRB2), (P ¼ 0.03) for ORs of adults (1.410) to be larger than those of acetylcholine (CHMR5, CHRNA1), glycine (GLRB), ubiquitin (involved children and adolescents (0.652). For HTR2C, there was a trend in the normal functioning of cells; UBE3A), immunologic factors (P ¼ 0.05) for ORs of children and adolescents (1.550) to be larger (TNFA) and myelinization (OLIG). than those of adults (1.087). For all 20 polymorphisms, there were Mean ORs (and 99th percentile confidence intervals) for the 18 no significant differences between White and Asian samples; significant polymorphisms were as follows: BDKRB2 (rs8016905): w2(df ¼ 1)o1.00, P40.10. 1.420 (1.004--2.011); BDNF (C11756G): 2.060 (1.194--3.557); BDNF Significant sex effects in ORs were obtained for COMT (rs2049046): 1.477 (1.037--2.103); CHMR5 (rs2702285): 1.622 (w2(df ¼ 1) ¼ 9.40, Po0.002) and for MAOA (w2(df ¼ 1) ¼ 24.17, (1.008--2.611); CHRNA1 (rs3755485): 1.745 (1.181--2.581); GABRB3 Po0.001). The COMT Met allele was associated with OCD only in (rs4304994): 1.426 (1.049--1.937); GLRB (rs11930311): 1.533 (1.070-- males (Figure 3) and the MAOA T allele was associated with OCD 2.198); GRIK2 (rs1556995): 4.364 (1.033--18.434); HTR2A (C516T): only in males (Figure 4). In terms of Cohen’s d, the effect size in 3.247 (1.464--7.200); NGFR (rs3785931): 1.429 (1.029--1.984); NTRK2 males was small for COMT (0.241) and large for MAOA (0.582). For (rs2378672): 4.215 (1.456--12.202); OLIG (rs1059004): 3.245 (1.074-- COMT for males, Egger’s test was nonsignificant; t(7) ¼ 0.33, 9.798); OLIG (rs762178): 4.944 (1.567--15.597); OLIG (rs9653711): P40.10. For MAOA for males, Egger’s test was also nonsignificant; 4.510 (1.153--17.648); TNFA (rs361525): 2.980 (1.299--6.838); UBE3A t(1) ¼ 0.26, P40.10. (rs12899875): 1.705 (1.118--2.598); UBE3A (rs2526025): 1.619 (1.094--2.395); UBE3A (rs7175651): 1.800 (1.171--2.766). These findings may serve as useful leads for future investigation, Secondary meta-analysis although it should be cautioned that most of these results were Mean ORs were computed for 210 polymorphisms that were based on only a single study, and so the reliability (replicability) of examined in fewer than five data set (see Appendix for a complete the findings remains to be determined.

Molecular Psychiatry (2013), 799 -- 805 & 2013 Macmillan Publishers Limited Genetics of obsessive--compulsive disorder S Taylor 803

Figure 3. COMT, Met vs Val: forest plot of odds ratios (ORs) and 99th percentile conﬁdence intervals for each sex.10,22,42,50--55

Figure 4. MAOA, T vs C: forest plot of odds ratios (ORs) and 99th percentile conﬁdence intervals for each sex.22,56,57

DISCUSSION likely consisted of a mix of early and late onset OCD, whereas OCD has been the subject of over 100 genetic association studies, child--adolescent samples consisted of early onset OCD. Sample involving the investigation of 4200 polymorphisms. The present age was a nonsignificant moderator variable. However, there were study is the first comprehensive meta-analysis of this substantial trends for HTR1B and HTR2B, which merit further investigation to body of research. Findings indicated that OCD is associated with determine whether they reach statistical significant if a larger multiple genes, which is consistent with twin studies showing that number of studies are included. The secondary meta-analysis, OCD is shaped by additive genetic factors; that is, by multiple which focused on polymorphisms examined in fewer than five genes that incrementally increase the odds of developing the data sets, found significant results for 18/204 polymorphisms. disorder.3 This study showed that OCD is associated with polymor- Such findings offer potentially useful leads for further investiga- phisms involved in serotonin modulation (HTTLPR and HTR2A) and, tion. for males, polymorphisms involved in catecholamine regulation Data from the main and secondary meta-analyses provided the (COMT and MAOA). Sex differences for COMT is consistent with opportunity for evaluating the statistical power of OCD genetic other research showing that the expression of this polymorphism association studies. The average study, with a mean of 113 OCD is influenced by estrogens.10 Karayiorgou et al.29 speculated that probands, had insufficient power to detect small effects (that is, MAOA may be associated with X-linked markers, which might ORs in the vicinity of 1.437). The power of the average study to account for the sex differences of MAOA and OCD. Three other detect such effects was o0.45. In association studies of psychiatric polymorphisms had nonsignificant trends toward significance; or general medical conditions, ORs linking a disorder and DAT1, DRD3 and SLC1A1 (rs3087879). These results were based on polymorphic locus typically range between 1.100 and 1.500.30 6--8 data sets, which may have been insufficient for detecting The average study included in the present meta-analyses lacked small effects. Such findings merit further investigation to sufficient power to detect such effects. In future research, studies determine whether they are reliably associated with OCD. should be sufficiently powered to detect such small effects (for For the main meta-analysis, sample age (adults vs children and example, ORs as small as 1.100). The continued publication of adolescents) was used as a proxy for age of onset; that is, adults studies underpowered to detect small effects may hamper efforts

& 2013 Macmillan Publishers Limited Molecular Psychiatry (2013), 799 -- 805 Genetics of obsessive--compulsive disorder S Taylor 804 to understand the genetic basis of OCD. That is, null results from Hemmings, Humberto Nicolini, Dan J Stein, Jeremy M Veenstra-VanderWeele and underpowered studies of a given polymorphism may dissuade Susanne Walitza. researchers from further investigating that polymorphism, thereby leading to the failure to detect genes that make small, incremental contributions to the risk of developing OCD. REFERENCES This study identified a number of important gaps in the research literature. For the main meta-analysis, there was evidence 1 American Psychiatric Association. Diagnostic and Statistical Manual of Mental of substantial heterogeneity of effect sizes, which was not attri- Disorders,, 4th edn, text rev edn. Author: Washington, DC, 2000. 2 Taylor S, Jang KL, Asmundson GJG. 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