{"paper_id":"c08e17f3-6f52-41ec-951d-9db340d3dff2","body_text":"Examining mitochondrial genetic variation in obsessive-compulsive disorder | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Examining mitochondrial genetic variation in obsessive-compulsive disorder Vanessa Goncalves, Fernanda Dos Santos, Stavroula Giannoulis, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6149169/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Obsessive-compulsive disorder (OCD) is a severe neuropsychiatric disorder with clear evidence of genetic vulnerability, although specific risk factors are not fully understood. Mitochondrial dysfunction has been implicated in other severe neuropsychiatric disorders, particularly through its role in oxidative stress, and thus merits exploration in OCD. Here we first examined the association of a set of 59 mitochondrial single nucleotide polymorphisms (SNPs) with OCD symptom severity. These SNPs are located inside 28 nuclear-encoded mitochondrial genes involved in oxidative phosphorylation, oxidative stress, mitochondrial biogenesis, inflammation, and apoptosis. We used linear regression to test for the association of this SNP set with symptom severity using the Yale-Brown Obsessive Compulsive Scale (YBOCS). We found a nominally significant association for rs3820189 in the 5’ of the MFN2 gene with YBOCS total score (N = 346; P uncorrected = 0.002). We also conducted gene-based and gene-set (pathway) analyses on nuclear-encoded mitochondrial genes and pathways with OCD risk using MAGMA. We found the gene ADCK1 to be associated with OCD (p = 0.00005, q = 0.05). No mitochondrial pathways were associated with OCD risk. To further examine mitochondrial genetic variation in OCD risk, we then examined mitochondrial (mt) DNA (mtDNA), the circular genome located inside each mitochondrion. We utilized the Toronto OCD sample (N = 215) and the 1000 Genome Project (N = 485) as healthy controls for discovery. For replication, we compared individual-level data from the Psychiatric Genomics Consortium (PGC) OCD Working Group release 2017 (N = 1691) with the Wellcome Trust sample (N = 2616) as controls. After data cleaning, 58 common mtDNA SNPs (minor allele frequency greater than 1%) were available for analysis. Meta-analysis across the significant mtDNA variants shared between both samples revealed five SNPs significantly associated with OCD risk which survived Nyholt correction: NC_012920.1:m.1719G > A (P = 1.489E-05), NC_012920.1:m.3010G > A (P = 2.423E-05), NC_012920.1:m.10398A > G (P = 3.172E-04), NC_012920.1:m.11914G > A (P = 6.085E-04) and NC_012920.1:m.6260G > A (P = 7.792E-04). To the best of our knowledge, this is the largest study to report the involvement of mitochondrial variants in OCD risk. Further investigations and validation of our findings are warranted. Biological sciences/Genetics Biological sciences/Molecular biology Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder characterized by the presence of (unwanted) obsessive thoughts and repetitive compulsive actions. OCD affects approximately 2% of the population worldwide [ 1 ]. Family and twin studies strongly support a genetic basis for OCD with estimates for heritability around 50% in adults[ 2 ], and between 45 and 65% in individuals with onset in childhood or adolescence[ 3 , 4 ]. Candidate gene and genome-wide association studies have mainly implicated serotonergic, dopaminergic, and glutamatergic systems to be involved in OCD[ 5 – 8 ] ( for a review see[ 9 ]). There have also been recent efforts to identify the role of rare variants[ 10 – 12 ] in OCD with limited findings to date[ 2 ]. Despite progress, the genetic basis of the illness remains far from well understood. Moreover, there is currently a significant gap between the degree of genetic risk suggested by segregation studies, and the modest risk conveyed by identified common variants to date, suggesting that other potential genetic mechanisms merit exploration. One target for brain disorders is the mitochondrial system, which produces most of the energy in the form of ATP used at the synapses for the maintenance of membrane resting potential, sustaining synaptic transmission and plasticity, regulating the release and uptake of neurotransmitters[ 13 ]. Mitochondria are also involved in the biosynthesis of macromolecules (such as glutamate), and maintenance of redox homeostasis through the production of reactive oxygen species (ROS). At normal physiological levels, ROS act as secondary messengers of synaptic activity and are also involved in learning and memory, while excessive ROS can cause oxidative stress leading to synapse loss [ 14 ]. Mitochondria also play a role in cellular processes such as cell death (apoptosis), calcium homeostasis (which serves as second messenger for neurotransmission and synaptic plasticity), as well as in cellular senescence[ 15 ] and inflammation[ 16 ]. Furthermore, these organelles play central roles in sensing, integrating, and transducing signals from endocrine, metabolic, and immune systems to coordinate effective response to acute stress[ 17 , 18 ]. To date, there has been limited exploration of mitochondrial dysfunction in OCD. For example, Kuloglu and colleagues[ 19 ] found higher levels of malondialdehyde (MDA), a marker of OS, in OCD cases. A genetic study[ 20 ] reported that the proportion of CC genotype in superoxide dismutase 2 (MnSOD) and DD genotype in uncoupling protein 2 (UCP2), two genes related to OS, were significantly higher in OCD cases in comparison with healthy controls, and levels of MDA were also found to be higher in the subset of individuals carrying the risk genotypes. Kang et al[ 21 ] showed that OCD cases have lower leukocyte mtDNA copy number (mtDNAcn) in comparison with healthy controls, and levels of mtDNAcn were associated with increased systemic inflammation (as indicated by interleukin 6 levels) in cases. Another supporting evidence includes studies of comorbidity between mitochondrial diseases and neuropsychiatric symptomatology [ 22 – 24 ], including a report of OCD occurring in patients with primary mitochondrial diseases [ 25 ]. Furthermore, a meta-analysis showed the use of N -acetylcysteine, a mitochondrial modulator, in combination with conventional treatment improves outcomes for OCD and OCD-related disorders[ 26 ]. These initial findings suggest a role for excess oxidative stress (OS)[ 14 , 19 , 27 , 28 ] in OCD, and support a need for larger-scale investigations of mitochondrial variants in OCD. In this study, we partially address this limitation by testing the hypothesis that variants in mitochondrial genes (both nuclear and mitochondrial DNA) are involved in OCD pathophysiology using one of the largest OCD samples available at the global Psychiatric Genomics Consortium (PGC). We developed an analytical pipeline for analyzing the association of mitochondrial variants with OCD risk and severity. 2. METHODS 2.1 S amples Toronto OCD sample Participants were recruited from referrals to the Anxiety Disorders Clinic at the Centre for Addiction and Mental Health (CAMH) and the Frederick W. Thompson Anxiety Disorders Centre at Sunnybrook Health Sciences Centre in Toronto, Canada. All participants were assessed using the Structured Clinical Interview for the DSM-IV (SCID-IV)[ 29 ] and the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) to determine the severity of their symptoms[ 30 ]. An experienced research assistant performed assessments and interviews and a research psychiatrist reviewed all diagnoses, which were assigned according to DSM-IV criteria. The Research Ethics Boards of CAMH and Sunnybrook Health Sciences Centre approved the recruitment and all subjects gave their written informed consent to participate. All participants met criteria for a DSM-IV diagnosis of OCD as their primary disorder. The exclusion criteria included any severe metabolic or chronic neurological diseases, schizophrenia, schizoaffective disorder, other psychotic disorders, bipolar disorder, or current substance dependence. Psychiatric Genetics Consortium (PGC) OCD Summary Statistics We used the summary association statistics available in the PGC dataset generated by the OCD working group (PGC-OCD) (released on August 2017, ocd_aug2017.gz). We used this data to perform analyses of the nuclear-encoded mitochondrial genes (autosomal). The original quality control (QC) steps for 2,688 OCD cases (European ancestry) and 7,037 healthy controls, and detailed association analyses of 8,693,187 autosomal SNPs are described elsewhere[ 31 ]. The 1000 Genomes Phase 3 (1000G) The dataset describes a total of 84,805,772 variant sites at 2,504 individuals. The mtDNA file was downloaded from 1000 Genomes[ 32 ] website, (ALL.chrMT.phase3_callmom-v0_4.20130502.genotypes.vcf.gz). Welcome Trust Case-Control Consortium (WTCCC) : We requested and were granted access to National Blood Donors (NBS) cohort, a non-psychiatric control sample from WTCCC2. Genetic data was downloaded from the online repository the European Genome-Phenome Archive (EGA), study \"WTCCC2 project control from the National Blood Donors (NBS) cohort (N = 2,619, access ID: EGAD00000000024)\". This sample was genotyped using Illumina 1.2M and used as “healthy controls” for the replication of our findings for mtDNA analysis. PGC-OCD (PGC-OCD) Individual-Genotype Data We used mtDNA individual-level genotyping data from the Psychiatric Genomics Consortium OCD working group (PGC-OCD, released in 2017)[ 31 ] with available data for n = 2,673 OCD cases. For details regarding this PGC-OCD sample, see[ 7 , 31 ]. 2.2 Data Quality Control 2.2.1 Nuclear-Encoded Mitochondrial Gene Selection and Quality Control for Analysis of OCD risk and Clinical Phenotypes For analysis of clinical phenotypes, we used our in-house Toronto OCD sample and a customized genotyping array of a select set of mitochondria-related SNPs from a previous study[ 33 ]. Briefly, we selected 28 genes involved in oxidative phosphorylation or involved in oxidative stress, mitochondrial biogenesis, inflammation, and apoptosis to test our mitochondrial hypothesis in our in-house samples[ 33 ]. Gene boundary windows were defined as 5kb in the 5’and 2kb in the 3’ UTR regions. Tag SNPs were selected using the HapMap database, phase2 + phase3, release #28, CEU population, build36 ( www.HAPMAP.org ) and Tagger in Haploview[ 34 ]. The threshold for minor allele frequency (MAF) was set at 0.05. In total, 64 SNPs were selected with linkage disequilibrium (LD, r 2 ≥ 0.8). Extra details regarding SNP selection criteria, data cleaning and their predicted functionality were described previously[ 33 ]. After QC[ 33 ], 59 SNPs were available for analysis with OCD risk and severity. We used the Yale-Brown Obsessive-Compulsive Scale (YBOCS) to evaluate a lifetime symptom severity score, for which clients were asked to focus on symptom severity during the period of most severe OCD. We had genetic and clinical data (YBOCS) available for N = 346 OCD cases from our Toronto OCD sample that survived quality control measures for inclusion. 2.2.2 PGC-OCD Genotyping Quality Control Genome-wide genotyping in 2,673 OCD samples was performed using the Illumina Human610-Quadv1_B SNP array. A total of 620,283 SNPs were available in the raw data and positions were updated for human genome build37 using the LiftOver tool[ 35 ]. We performed standard QC[ 36 , 37 ] measures in this PGC-OCD sample. Briefly, we removed individuals with more than 2% of missing genotyped. No duplicate or related individuals were found after we checked for cryptic relatedness. Mean heterozygosity was calculated and outliers (± 3 SD) were removed (N = 8). Principal Component Analysis (PCA) of the genotypes was used to check for population stratification, and outliers were removed through visual inspection of scatter plots and using the standard rule of “6 SDs from the mean” (6SD). SNP quality control included the removal of any markers less than 99% genotyped across all individuals, and SNPs were filtered out if the χ²-test for Hardy-Weinberg equilibrium was < 0.0000001. Thus, after individuals and markers QC, we had a total sample of 1,996 individuals and 556,922 markers. We carried out imputation with 1000 Genome Project data as reference using IMPUTE2 v2.3.2 with quality info score of < 0.9 were excluded and a final number of available SNPs (genotyped and imputed) was 5,912,464. We used this sample to select individuals that passed nuclear DNA quality control to be included in the mtDNA analysis. 2.2.3 PGC-OCD mtDNA Genotypes Data Cleaning and Merging Datasets Initially, a total of 135 mtDNA variants were available in the PGC-OCD. We performed QC by removing individuals with missing genotyping rate higher than 5%, SNPs with missing genotyping rate higher than 5%, and set minor allele frequency (MAF) to ≥ 1%. Following mtDNA QC, a total of 78 SNPs and 1,991 OCD cases remained for analysis. We further removed individuals with mtDNA background assigned for non-European haplogroups (85 removed; N = 1,906) since these individuals represented only 4.2% of our sample size. The same parameters were used to QC the control datasets (1000G and NBS). We divided the PGC-OCD data in 2 sub-samples: TO-PGC (N = 215, individuals in PGC that were from Toronto OCD sample, and remaining-PGC (N = 1,691) consisting of those from other collaborators from PGC. The TO-PGC was merged with 1000G (those with mtDNA assigned for one of the Europeans haplogroups; N = 485). A total of 58 SNPs passed QC and were shared between our sample and 1000G and 700 subjects were present on the merged dataset (“discovery sample”: 215 OCD cases and 485 healthy controls). The remaining-PGC was merged with NBS sample after removal of NBS individuals with non-European haplogroups. A total of 48 SNPs were available and n = 4,307 subjects were present in the merged dataset (“replication sample”: 1,691 OCD cases and 2,616 healthy controls). Mitochondrial haplogroups were assigned using HaploGrep2[ 38 ], with European haplogroups defined as H, HV, V, J, T, I, W, X and U(k). 2.3 Analysis for Mitochondrial Pathways in OCD The OCD-PGC GWAS summary stats file was downloaded from the PGC website at https://figshare.com/articles/dataset/ocd2018/14672103?file=28169544 and was used as the primary input data for MAGMA (v1.06). The 1000 Genomes Project Phase 3 (Build 37/European data only) was used as the reference panel (downloaded from https://ctg.cncr.nl/software/magma ). The MAGMA gene-based results (p-values) were then corrected for multiple testing hypotheses using the p.adjust function from the stats base R package ( Benjamini-Hochberg method) version 4.4.0. The MAGMA gene-set analysis was then performed to examine whether one or more of the seven mitochondrial pathways from MitoCarta3[ 39 ] were enriched in variants associated with OCD risk. Finally, to examine if the genes identified are expressed in the brain, genes with q-value (FDR) < 0.1 (i.e., top hits) were entered into the Genotype-Tissue Expression Project (GTEx) Portal ( \\www.gtexportal.org ; GTEx v7)[ 40 ], accessed on January 17, 2025. 2.4 Statistical Analyses Linear regression was used to test for association between Y-BOCS total score as the dependent variable, and genotypes as predictor variables. For this analysis, correction for multiple testing was performed using Single-Nucleotide Polymorphism Spectral Decomposition (SNPSpD) [ 41 ]. A power calculation was derived using Quanto 1.2.4 ( http://hydra.usc.edu/gxe ). The p-value for significance was set to 0.001 for the nuclear-encoded mitochondrial DNA analysis using Nyholt/Bonferroni correction approach when considering a type 1 error rate at 5%. Logistic regression was used to test the association of mtDNA variants with OCD risk for the each of the TO-PGC discovery sample and the remaining-PGC replication sample. We then used METAL[ 42 ] to perform a meta-analysis based on the effect sizes and standard errors of the logistic regressions performed for the discovery and replication samples. Nyholt corrected p-value threshold for the logistic regressions and meta-analysis was set to p = 0.00142, when considering a type 1 error rate at 5% (VeffLi = 36.101). 3. RESULTS Here we tested the hypothesis that genetic variants in the mitochondrial system (both autosomal and mtDNA) are associated with OCD risk and clinical severity using our in-house OCD sample (TO-OCD) and OCD sample available in the global PGC consortium (PGC-OCD). See Fig. 1 for study design. 3.1 Nuclear-Encoded Mitochondrial SNP-based Analysis with OCD Clinical Severity We investigated the role of nuclear-encoded mitochondrial SNPs in the severity of OCD symptoms based on YBOCS lifetime total score (See table 1 for top hits). The most significant finding was for the SNP rs3820189 in the 5’of the MFN2 gene with YBOCS total score (N = 346; P uncor = 0.002). This gene is ubiquitously expressed across all tissues in the body, including the brain[ 43 ] (Fig. 2 a). While it is highly expressed throughout all developmental stages, its expression peaks during late infancy and young adulthood (Fig. 2 b). Notably, MFN2 exhibits its highest expression levels in the frontal cortex (median TPM = 53.61) and basal ganglia tissues, particularly the nucleus accumbens (median TPM = 40.6). However, the findings from this analysis did not survive correction for multiple hypothesis testing. 3.2 Nuclear-Encoded Mitochondrial Gene-based Analysis with OCD risk We also investigated the hypothesis that variants in the nuclear-encoded mitochondrial genes are associated with risk for OCD. To test this hypothesis, we used publicly available PGC-OCD genome-wide association summary stats data to perform gene-based (individual mitochondrial gene p-values) and gene-set (pre-defined mitochondrial pathways) analyses in MAGMA. For gene-based analysis, we found the gene ADCK1 (aarF domain containing kinase 1; q-value = 0.05) showed the strongest association with OCD risk (see table 2 for top hits). ADCK1 is mildly expressed throughout all tissues in the body, including brain regions previously associated with OCD, such as the frontal cortex (median TPM = 6.45) and the nucleus accumbens (median TPM = 5.38) (Fig. 3 a and c). According to GTEx analysis, when examining expression across the brain, two of our other top hits of MTX2 and ALDH6A1 genes show the most significant expression levels in brain tissues, more specifically, MTX2 is highly expressed in the frontal cortex region (median TPM = 54.74) (Fig. 3 a) and ALDH6A1 is highly expressed in the anterior cingulate cortex (median TPM = 62.12), nucleus accumbens (median TPM = 59.04), frontal cortex (median TPM = 56.47), and caudate (median TPM = 56.48) (Fig. 3 a). Moreover, both MTX2 and ALDH6A1 seem to be important during different developmental stages, being MTX2 highly expressed across all stages, while ALDH6A1 seems to present a shift from low to high expression during late pre-natal stage. For the gene-set analysis, we included 7 mitochondrial pathways defined by MitoCarta3 database, but none of them were associated with OCD risk (Table 3). 3.3 Mitochondrial-DNA SNP-based Analysis with OCD risk We examined the hypothesis that variants in mtDNA were associated with OCD risk. We identified five SNPs significantly associated with OCD risk: m.1719G > A (p = 1.489E-05) and m.3010G > A (p = 2.423E-04) in the gene 16S ribosomal RNA ( MT-RNR2 ), m.10398A > G (p = 3.172E-04) in the NADH dehydrogenase subunit 3 gene ( MT-ND3 ), m.11914G > A (p = 6.085E-04) in the NADH dehydrogenase subunit 4 gene ( MT-ND4 ), and m.6260G > A (p = 7.792E-04) in the gene Cytochrome c oxidase subunit I ( MT-CO1 ) (Table 4 and Fig. 2 ). Three of them were presented in both datasets: m.1719G > A, m.3010G > A, and m.11914G > A. 4. DISCUSSION To the best of our knowledge, this is the first study to identify mitochondrial genetic variants associated with OCD risk. We first used a hypothesis-driven approach and we genotyped SNPs from a selected set of nuclear-encoded mitochondrial genes directly involved in or related to OXPHOS, and tested for association with OCD clinical severity as estimated by lifetime YBOCS total score. Thus, we tested our set of nuclear-encoded mitochondrial genes in the severity of clinical OCD symptoms (lifetime YBOCS total score). We found significant results for rs3820189 (P uncorrected = 0.002) located in the 5’ region of the mitofusin 2 ( MFN2 ) gene. This gene is located in the outer membrane of mitochondria and is involved in the mitochondrial dynamic process of fusion and fission, as well as contact with other organelles, particularly the endoplasmic reticulum[ 44 ]. Mitochondrial dynamic has been shown to play a role in the pathophysiology of several psychiatric disorders (for a review, see[ 45 ]). However, it is important to note that these individual-SNP findings were nominal and did not survive correction for multiple testing. As described above, MFN2 exhibits its highest expression levels in the frontal cortex and nucleus accumbens. These regions have been consistently associated with OCD in brain imaging studies[ 46 – 48 ]. The nucleus accumbens is one of the regions targeted by the deep brain stimulation (DBS)[ 49 ], an intervention that has been proven effective in treating OCD symptoms [ 50 , 51 ]. Mitochondrial dysfunction in the nucleus accumbens has been associated with anxiety in rats[ 52 ], and it may be one of the impaired neurobiological mechanisms targeted by the DBS treatment. DBS intervention, particularly in Parkinson’s disease, has been shown to promote mitochondrial recovery. This process is mediated by mitophagy, a crucial component of the mitochondrial quality control system, which involves proteins such as MFN2. Therefore, although our findings from this primary analysis did not withstand correction for multiple testing, the aforementioned biological evidence, together with our analysis, suggest that genetic variants in the MFN2 gene might play a role in OCD symptom severity and should be further investigated in independent samples. Our gene-based analysis revealed the aarF domain-containing kinase 1 ( ADCK1 ) gene to be significantly associated with OCD risk (table 3). This gene was previously associated with OCD in a large meta-analysis[ 53 ]. A study with drosophila reported that ADCK1 acts along YME1-like 1 ATPase (YME1L1) to control optic atrophy 1 (OPA1) and inner membrane mitochondrial protein (IMMT)[ 54 ]. YME1L1 pathway is known to play a critical role in the regulation of mitochondrial dynamics[ 55 ] and is also involved in the proteolytic regulation of respiratory chain biogenesis[ 56 ]. This finding along with MFN2 from above suggests the presence of variants in specific mitochondrial dynamic genes playing a role in OCD risk and severity of symptoms. In support to our findings, the mitochondrial dynamic pathway was not significantly associated with OCD risk (Table 3, p = 0.64). Analysis of mitochondrial pre-established MitoCarta gene-sets (pathways) did not show positive associations with OCD risk likely due to the high degree of genetic heterogeneity seen in psychiatric disorders. We suggest that more hypothesis-driven mitochondrial-related pathways or inclusion of only core subsets of genes may be targeted in future gene-set based studies for more informative findings. We then examined mtDNA common variants in the subgroup of the TO-OCD discovery sample obtained through the PGC, and in the PGC-OCD replication sample. The meta-analysis revealed five SNPs to be significantly associated with OCD risk after multiple testing correction (P < 0.00142) (Table 2). The SNP m.10398A > G is mapped to the MT-ND3 gene, and it is classified as non-synonymous, i.e. predicted to cause an amino acid substitution at position 114 of the ND3 protein (T114A). This allele substitution has a MutPred score of 0.17 (low risk). The gene MT-ND3 is responsible for coding a subunit of NADH dehydrogenase, a component of the respiratory chain Complex I. Complex I is essential for normal functioning of OXPHOS, and disturbances in it can severely impact energy metabolism and mitochondrial function. Moreover, MT-ND3 is ubiquitously expressed in the brain[ 57 ] ( https://www.proteinatlas.org ; accessed 10/17/2024) and variants within MT-ND3 have been previously associated with several phenotypes, such as schizophrenia[ 58 ], risk for neurodegenerative disorders including Parkinson’s disease [ 59 , 60 ] and Alzheimer’s disease[ 61 ], and many others disorders, such as breast cancer[ 62 ] and type 2 diabetes[ 63 ]. Moreover, Smullen et al[ 64 ] recently described the association of the locus m.10398A > G with increased heteroplasmy in a specific region of the mtDNA, the control region (CR) in dorsolateral prefrontal cortex (DLPFC) post-mortem brain of individuals with Alzheimer’s Disease. This increase in heteroplasmy in the CR was also correlated with reduced expression of the mitochondrial genes MT-ND3 and MT-ND4 [ 64 ]. These findings highlight the critical role of this locus in maintaining mtDNA integrity and regular mitochondrial function, and its potential contribution to brain diseases. The SNPs m.1719G > A and m.3010G > A, m.11914G > A and m.6260G > A, mapped within the genes MT-RNR2 , MT-ND4 , and MT-CO1 , respectively, were found to be associated with OCD risk (Table 4). Although these SNPs are synonymous with minimal functional impact expected[ 65 ], recent studies have been suggesting a more prominent role for this type of variants in diseases, such as in cancer by, for example, disrupting pre-mRNA splicing (for a review see [ 66 ]). For mtDNA, in particular, synonymous variants may impact codon-anticodon affinity and play a role in modulating traits, disease phenotypes and mitochondrial evolution[ 67 ]. Two of these SNPs (m.1719G > A and m.3010G > A) are located inside the gene MT-RNR2 , which primarily encodes the mitochondrial 16S ribosomal RNA (rRNA), but it also encodes humanin, a peptide with cytoprotective properties, playing a role in inflammation, neuroprotection and oxidative stress[ 68 ]. Humanin has been previously reported as a protective factor in Alzheimer’s disease, based on its role in supressing apoptosis in Aβ-induced neuron death in vitro[ 68 , 69 ]. MT-ND4 encodes for the NADH-ubiquinone oxidoreductase chain 4 protein, another core component of the mitochondrial OXPHOS complex I. Dysfunctions in this protein are known for severely impairing the energy supply to neurons, which is believed to contribute to an increasing list of neurodevelopmental and psychiatric disorders, such as schizophrenia[ 70 , 71 ], bipolar disorder[ 72 ], major depressive disorder[ 73 ], autism spectrum disorder[ 74 ], and Parkinson’s disease[ 75 ]. Finally, MT-CO1 encodes for the Cytochrome c oxidase subunit I, which plays a critical role in the OXPHOS complex IV pathway. Dysfunctions in this subunit have also been linked to psychiatric disorders, including schizophrenia[ 76 ] and autism spectrum disorder [ 77 ]. To the best of our knowledge, this is the first report of mtDNA variants associated with OCD risk. Taken together, the mtDNA variation in the genes reported here may contribute to OCD risk and highlight complex I as a site of variants in OCD. Complex I is a site for leaking electrons and variants in it may contribute to increased OS, an emerging hypothesis for OCD pathophysiology[ 78 , 79 ]. Limitations of this study include small sample size and lack of data for inclusion of other ancestry beyond Europeans. Another limitation particularly applicable for the OCD clinical severity analysis is the absence of genetic control for population stratification (participants are self-declared Europeans). Furthermore, healthy controls samples (1000G and NBS) were not screened for OCD or other psychiatric disorders. Our findings were also limited due to low coverage of SNPs available for analysis, and future studies should, use genotyping arrays with better coverage of mtDNA SNPs or use next-generation sequencing data. Another future direction would consider the examining of mtDNA variants influencing the nuclear epigenetics in OCD individuals. Presence of variants on mtDNA compromising its integrity may alter nuclear epigenetic patterns (such as methylation loci) compromising metabolism and contributing to development of complex diseases[ 80 ]. Our group has reported evidence for genetic and epigenetic factors influencing OCD risk and severity of symptoms[ 81 ] and this new perspective may help to clarify pieces of the illness pathophysiology. In the same direction, the interaction between nuclear SNPs and mitochondrial DNA variants is worth exploring in future studies. Finally, the use of more comprehensive clinical and demographic data will allow a better exploration of whether environmental factors would affect these findings. In conclusion, we have identified evidence that mitochondrial variants in both nuclear and mtDNA genes influence OCD risk. Validation of the findings in larger and independent samples is still warranted. Declarations Acknowledgements This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113, 085475 and 090355. This work was supported by research grants from the Ontario Mental Health Foundation and Canadian Institutes for Health Research (Drs. Richter and Kennedy) and private donations to the Frederick W. Thompson Anxiety Disorders Centre at Sunnybrook Health Sciences Centre (Dr. Richter). Funding VFG, JLK and CCZ are currently supported by the CAMH Foundation and Larry and Judy Tanenbaum Foundation. GZ was supported by the Academic Scholars Award from the Department of Psychiatry at the University of Toronto and is current supported by research funding from the Centre for Addiction and Mental Health, Physicians Services’ Incorporated Foundation, BBRF (NARSAD) Young Investigator Grant, and International OCD Foundation Young Investigator Grant. Conflict of interest JLK is a member of the Scientific Advisory Board of Myriad Neuroscience (paid). JLK, VFG and CCZ are authors on several patents relating to pharmacogenetic tests for psychiatric medications. Dr. Richter has received research support through a grant from Eli Lilly, an honorarium and expenses from Brainsway for participation in a positional board meeting, and speaker honoraria from Lundbeck. JLK and CCZ are authors on a patent on genetic biomarkers of suicide risk. The remaining authors have no conflicts of interest to declare. References Ruscio AM, Stein DJ, Chiu WT, Kessler RC. 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A rescue factor abolishing neuronal cell death by a wide spectrum of familial Alzheimer’s disease genes and Abeta. Proc Natl Acad Sci U S A. 2001;98:6336–6341. Gong Z, Tas E, Muzumdar R. Humanin and age-related diseases: a new link? Front Endocrinol (Lausanne). 2014;5:210. Martorell L, Segués T, Folch G, Valero J, Joven J, Labad A, et al. New variants in the mitochondrial genomes of schizophrenic patients. Eur J Hum Genet. 2006;14:520–528. Rollins B, Martin M V, Sequeira PA, Moon EA, Morgan LZ, Watson SJ, et al. Mitochondrial variants in schizophrenia, bipolar disorder, and major depressive disorder. PLoS One. 2009;4:e4913. Bodenstein DF, Kim HK, Brown NC, Navaid B, Young LT, Andreazza AC. Mitochondrial DNA content and oxidation in bipolar disorder and its role across brain regions. NPJ Schizophr. 2019;5:21. Liu L, Cheng S, Qi X, Meng P, Yang X, Pan C, et al. Mitochondria-wide association study observed significant interactions of mitochondrial respiratory and the inflammatory in the development of anxiety and depression. Transl Psychiatry. 2023;13:216. Frye RE, Rincon N, McCarty PJ, Brister D, Scheck AC, Rossignol DA. Biomarkers of mitochondrial dysfunction in autism spectrum disorder: A systematic review and meta-analysis. Neurobiol Dis. 2024;197:106520. Kösel S, Grasbon-Frodl EM, Mautsch U, Egensperger R, von Eitzen U, Frishman D, et al. Novel mutations of mitochondrial complex I in pathologically proven Parkinson disease. Neurogenetics. 1998;1:197–204. Li J, Tran OT, Crowley TB, Moore TM, Zackai EH, Emanuel BS, et al. Association of Mitochondrial Biogenesis With Variable Penetrance of Schizophrenia. JAMA Psychiatry. 2021;78:911–921. Avdjieva-Tzavella D, Mihailova S, Lukanov C, Naumova E, Simeonov E, Tincheva R, et al. Mitochondrial DNA mutations in two bulgarian children with autistic spectrum disorders. Balkan J Med Genet. 2012;15:47–54. Shrivastava A, Kar SK, Sharma E, Mahdi AA, Dalal PK. A study of oxidative stress biomarkers in obsessive compulsive disorder. J Obsessive Compuls Relat Disord. 2017;15:52–56. Behl A, Swami G, Sircar SS, Bhatia MS, Banerjee BD. Relationship of possible stress-related biochemical markers to oxidative/antioxidative status in obsessive-compulsive disorder. Neuropsychobiology. 2010;61:210–214. Morin AL, Win PW, Lin AZ, Castellani CA. Mitochondrial genomic integrity and the nuclear epigenome in health and disease. Front Endocrinol (Lausanne). 2022;13:1059085. Lisoway AJ, Zai CC, Zai G, Nair A, Ebrahimi S, Tiwari AK, et al. PT613. The Role of SKA2 Genetic and Epigenetic Variation in Obsessive-Compulsive Disorder. Int J Neuropsychopharmacol. 2016;19:25. Tables Table 1 to 4 are available in the Supplementary Files section. Additional Declarations Yes JLK is a member of the Scientific Advisory Board of Myriad Neuroscience (paid). JLK, VFG and CCZ are authors on several patents relating to pharmacogenetic tests for psychiatric medications. Dr. Richter has received research support through a grant from Eli Lilly, an honorarium and expenses from Brainsway for participation in a positional board meeting, and speaker honoraria from Lundbeck. JLK and CCZ are authors on a patent on genetic biomarkers of suicide risk. The remaining authors have no conflicts of interest to declare. Supplementary Files table1YBOCSanalysis.xlsx Table 1: Results of association testing between nuclear mitochondrial SNPs and YBOCS total scores. table2genebasedanalysis.xlsx Table 2: Top five nuclear mitochondrial genes associated with OCD risk from MAGMA Gene-based analysis. table3Pathwayanalysis.xls Table 3: Results for MAGMA gene-set analysis involving seven mitochondrial pathways. table4mtDNAmetaanalysis.xlsx Table 4. Results of association analyses and meta-analysis of mtDNA SNPs. Statistics of regressions are displayed for discovery sample (N=700; 2150 OCD and 485 controls), and for the replication sample (N=4,307; 1,691 OCD and 2,616 controls). The table displays the 5 SNPs significantly associated with OCD risk after Nyholt correction (Nyholt corrected p-value threshold set at P = 0.00142) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6149169\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":430640061,\"identity\":\"4a612eb5-90f4-4beb-b8da-d54d9c6659fc\",\"order_by\":0,\"name\":\"Vanessa Goncalves\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYPCDAiBmb2BgYGwgWosBEPMcIFmLRAJ+LQbHzx58+OOPHYO8e+/BDz8MDsvJz3z88NPNHQzy/Di0GZzJSzbmbUtmMDxzLlmyx+CwscHtNGPp3DMMhjMOYNci2ZBjJs3YwAxUkWPGwGOQlrhBOodBOreNIYEBl5b+N+Y/f/ypB2th/GOQVj9/5hnm3yAt8ji08EuADGc7zCAPZDDzGNgkMNzgYQPbYoBTyxtjad624zwGPGeMpWUMbAw3nEkzs85tkzDciEMLG3+O4ccff6rl5Nt7DD++qZCQl28//Ph2bpuNvBwOLTDAg+4MCfzqQUC+gbCaUTAKRsEoGKEAAJqVVKu8IfqSAAAAAElFTkSuQmCC\",\"orcid\":\"https://orcid.org/0000-0001-5619-8755\",\"institution\":\"Centre for Addiction and Mental Health\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Vanessa\",\"middleName\":\"\",\"lastName\":\"Goncalves\",\"suffix\":\"\"},{\"id\":430640062,\"identity\":\"3ca48ffd-07ba-4691-a968-c20f82dc1d4e\",\"order_by\":1,\"name\":\"Fernanda Dos Santos\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0002-4590-5722\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Fernanda\",\"middleName\":\"Dos\",\"lastName\":\"Santos\",\"suffix\":\"\"},{\"id\":430640063,\"identity\":\"d72316c0-58fb-424f-aba6-1b5fe13a9072\",\"order_by\":2,\"name\":\"Stavroula Giannoulis\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Stavroula\",\"middleName\":\"\",\"lastName\":\"Giannoulis\",\"suffix\":\"\"},{\"id\":430640064,\"identity\":\"2a92c169-456a-457a-b083-b478eee98c0d\",\"order_by\":3,\"name\":\"Amanda Lisoway\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Amanda\",\"middleName\":\"\",\"lastName\":\"Lisoway\",\"suffix\":\"\"},{\"id\":430640065,\"identity\":\"841f5b9a-61bb-4120-8170-488abf27d5c8\",\"order_by\":4,\"name\":\"Catrina Wong\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Catrina\",\"middleName\":\"\",\"lastName\":\"Wong\",\"suffix\":\"\"},{\"id\":430640066,\"identity\":\"ba5aa584-0311-4abf-89ee-da89fdcd805e\",\"order_by\":5,\"name\":\"Clement Zai\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0003-0496-7262\",\"institution\":\"Centre for Addiction \\u0026 Mental Health\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Clement\",\"middleName\":\"\",\"lastName\":\"Zai\",\"suffix\":\"\"},{\"id\":430640067,\"identity\":\"4b452633-60a9-4bae-ad57-64d41915e563\",\"order_by\":6,\"name\":\"Gwyneth Zai\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Centre for Addiction and Mental Health; University of Toronto\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Gwyneth\",\"middleName\":\"\",\"lastName\":\"Zai\",\"suffix\":\"\"},{\"id\":430640068,\"identity\":\"3027910c-8144-4a16-8f73-66a5719cab93\",\"order_by\":7,\"name\":\"James L. 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Created in https://BioRender.com.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"figure1feb11.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/f4692fba9c43b33bbe6a38d7.png\"},{\"id\":79388939,\"identity\":\"9f581686-16da-4106-b0d7-60950a84dc14\",\"added_by\":\"auto\",\"created_at\":\"2025-03-27 19:13:16\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1979868,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGene expression patterns of top hits from a nuclear-encoded mitochondrial SNP-based analysis.\\u003c/strong\\u003e (A) Heatmap displaying gene expression levels of nearby genes of the three top hits across 54 human tissues based on GTEx data (built with FUMA). (B) Heatmap illustrating the nearby genes expression of the three top hits across 11 distinct developmental stages (built with FUMA). 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(B) Heatmap illustrating the 5 top genes expression across 11 distinct developmental stages (built with FUMA). (C) Violin plot showing the expression distribution of the top hit gene across tissues, as derived from GTEx web platform.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"figure3panel.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/f2e4feb97a5cf146cbf9f14c.png\"},{\"id\":84687556,\"identity\":\"7b18db92-d681-40f9-af15-4ac5ce83cb19\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 09:10:02\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":6335800,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/8afddb19-d9ff-4534-8811-179413487a6f.pdf\"},{\"id\":79388484,\"identity\":\"16b65b4d-b3b1-4608-b4f6-bfad791f72fc\",\"added_by\":\"auto\",\"created_at\":\"2025-03-27 18:57:16\",\"extension\":\"xlsx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":37624,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 1: \\u003c/strong\\u003eResults of association testing between nuclear mitochondrial SNPs and YBOCS total scores.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"table1YBOCSanalysis.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/38d4848bd5af4a6b9359cba2.xlsx\"},{\"id\":79388489,\"identity\":\"04785f6a-d242-4a81-93d0-a036162c44ff\",\"added_by\":\"auto\",\"created_at\":\"2025-03-27 18:57:16\",\"extension\":\"xlsx\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":39211,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 2: \\u003c/strong\\u003eTop five nuclear mitochondrial genes associated with OCD risk from MAGMA Gene-based analysis.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"table2genebasedanalysis.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/2e39d8aeb139338a3bd24ac8.xlsx\"},{\"id\":79388600,\"identity\":\"e389e774-4710-48a7-b27a-501704da200c\",\"added_by\":\"auto\",\"created_at\":\"2025-03-27 19:05:16\",\"extension\":\"xls\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":28160,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 3: \\u003c/strong\\u003eResults for MAGMA gene-set analysis involving seven mitochondrial pathways.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"table3Pathwayanalysis.xls\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/cf3337f5e3bedbdc1564683d.xls\"},{\"id\":79388493,\"identity\":\"06bda05b-a1b5-4f9e-8a53-b3626afc1723\",\"added_by\":\"auto\",\"created_at\":\"2025-03-27 18:57:16\",\"extension\":\"xlsx\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":35701,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable 4. \\u003c/strong\\u003eResults of association analyses and meta-analysis of mtDNA SNPs. Statistics of regressions are displayed for discovery sample (N=700; 2150 OCD and 485 controls), and for the replication sample (N=4,307; 1,691 OCD and 2,616 controls). The table displays the 5 SNPs significantly associated with OCD risk after Nyholt correction (Nyholt corrected p-value threshold set at P = 0.00142)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"table4mtDNAmetaanalysis.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6149169/v1/654432d8f39beb85f3c3eb1c.xlsx\"}],\"financialInterests\":\"\\u003cb\\u003eYes\\u003c/b\\u003e\\nJLK is a member of the Scientific Advisory Board of Myriad Neuroscience (paid). JLK, VFG and CCZ are authors on several patents relating to pharmacogenetic tests for psychiatric medications. Dr. Richter has received research support through a grant from Eli Lilly, an honorarium and expenses from Brainsway for participation in a positional board meeting, and speaker honoraria from Lundbeck. JLK and CCZ are authors on a patent on genetic biomarkers of suicide risk. The remaining authors have no conflicts of interest to declare.\",\"formattedTitle\":\"Examining mitochondrial genetic variation in obsessive-compulsive disorder\",\"fulltext\":[{\"header\":\"1. INTRODUCTION\",\"content\":\"\\u003cp\\u003eObsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric disorder characterized by the presence of (unwanted) obsessive thoughts and repetitive compulsive actions. OCD affects approximately 2% of the population worldwide [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. Family and twin studies strongly support a genetic basis for OCD with estimates for heritability around 50% in adults[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], and between 45 and 65% in individuals with onset in childhood or adolescence[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Candidate gene and genome-wide association studies have mainly implicated serotonergic, dopaminergic, and glutamatergic systems to be involved in OCD[\\u003cspan additionalcitationids=\\\"CR6 CR7\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e] ( for a review see[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]). There have also been recent efforts to identify the role of rare variants[\\u003cspan additionalcitationids=\\\"CR11\\\" citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e] in OCD with limited findings to date[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Despite progress, the genetic basis of the illness remains far from well understood. Moreover, there is currently a significant gap between the degree of genetic risk suggested by segregation studies, and the modest risk conveyed by identified common variants to date, suggesting that other potential genetic mechanisms merit exploration.\\u003c/p\\u003e \\u003cp\\u003eOne target for brain disorders is the mitochondrial system, which produces most of the energy in the form of ATP used at the synapses for the maintenance of membrane resting potential, sustaining synaptic transmission and plasticity, regulating the release and uptake of neurotransmitters[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Mitochondria are also involved in the biosynthesis of macromolecules (such as glutamate), and maintenance of redox homeostasis through the production of reactive oxygen species (ROS). At normal physiological levels, ROS act as secondary messengers of synaptic activity and are also involved in learning and memory, while excessive ROS can cause oxidative stress leading to synapse loss [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. Mitochondria also play a role in cellular processes such as cell death (apoptosis), calcium homeostasis (which serves as second messenger for neurotransmission and synaptic plasticity), as well as in cellular senescence[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e] and inflammation[\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. Furthermore, these organelles play central roles in sensing, integrating, and transducing signals from endocrine, metabolic, and immune systems to coordinate effective response to acute stress[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eTo date, there has been limited exploration of mitochondrial dysfunction in OCD. For example, Kuloglu and colleagues[\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] found higher levels of malondialdehyde (MDA), a marker of OS, in OCD cases. A genetic study[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] reported that the proportion of CC genotype in superoxide dismutase 2 (MnSOD) and DD genotype in uncoupling protein 2 (UCP2), two genes related to OS, were significantly higher in OCD cases in comparison with healthy controls, and levels of MDA were also found to be higher in the subset of individuals carrying the risk genotypes. Kang et al[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] showed that OCD cases have lower leukocyte mtDNA copy number (mtDNAcn) in comparison with healthy controls, and levels of mtDNAcn were associated with increased systemic inflammation (as indicated by interleukin 6 levels) in cases. Another supporting evidence includes studies of comorbidity between mitochondrial diseases and neuropsychiatric symptomatology [\\u003cspan additionalcitationids=\\\"CR23\\\" citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e], including a report of OCD occurring in patients with primary mitochondrial diseases [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. Furthermore, a meta-analysis showed the use of \\u003cem\\u003eN\\u003c/em\\u003e-acetylcysteine, a mitochondrial modulator, in combination with conventional treatment improves outcomes for OCD and OCD-related disorders[\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. These initial findings suggest a role for excess oxidative stress (OS)[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e] in OCD, and support a need for larger-scale investigations of mitochondrial variants in OCD. In this study, we partially address this limitation by testing the hypothesis that variants in mitochondrial genes (both nuclear and mitochondrial DNA) are involved in OCD pathophysiology using one of the largest OCD samples available at the global Psychiatric Genomics Consortium (PGC). We developed an analytical pipeline for analyzing the association of mitochondrial variants with OCD risk and severity.\\u003c/p\\u003e\"},{\"header\":\"2. METHODS\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e\\u003cspan type=\\\"SmallCaps\\\" class=\\\"SmallCaps\\\" name=\\\"Emphasis\\\"\\u003e2.1 S\\u003c/span\\u003eamples\\u003c/h2\\u003e \\u003cp\\u003e \\u003cstrong\\u003eToronto OCD sample\\u003c/strong\\u003e \\u003cp\\u003eParticipants were recruited from referrals to the Anxiety Disorders Clinic at the Centre for Addiction and Mental Health (CAMH) and the Frederick W. Thompson Anxiety Disorders Centre at Sunnybrook Health Sciences Centre in Toronto, Canada. All participants were assessed using the Structured Clinical Interview for the DSM-IV (SCID-IV)[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] and the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) to determine the severity of their symptoms[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. An experienced research assistant performed assessments and interviews and a research psychiatrist reviewed all diagnoses, which were assigned according to DSM-IV criteria. The Research Ethics Boards of CAMH and Sunnybrook Health Sciences Centre approved the recruitment and all subjects gave their written informed consent to participate. All participants met criteria for a DSM-IV diagnosis of OCD as their primary disorder. The exclusion criteria included any severe metabolic or chronic neurological diseases, schizophrenia, schizoaffective disorder, other psychotic disorders, bipolar disorder, or current substance dependence.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003ePsychiatric Genetics Consortium (PGC) OCD Summary Statistics\\u003c/strong\\u003e \\u003cp\\u003eWe used the summary association statistics available in the PGC dataset generated by the OCD working group (PGC-OCD) (released on August 2017, ocd_aug2017.gz). We used this data to perform analyses of the nuclear-encoded mitochondrial genes (autosomal). The original quality control (QC) steps for 2,688 OCD cases (European ancestry) and 7,037 healthy controls, and detailed association analyses of 8,693,187 autosomal SNPs are described elsewhere[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eThe 1000 Genomes Phase 3 (1000G)\\u003c/strong\\u003e \\u003cp\\u003eThe dataset describes a total of 84,805,772 variant sites at 2,504 individuals. The mtDNA file was downloaded from 1000 Genomes[\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e] website, (ALL.chrMT.phase3_callmom-v0_4.20130502.genotypes.vcf.gz).\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eWelcome Trust Case-Control Consortium (WTCCC)\\u003c/b\\u003e: We requested and were granted access to National Blood Donors (NBS) cohort, a non-psychiatric control sample from WTCCC2. Genetic data was downloaded from the online repository the European Genome-Phenome Archive (EGA), study \\\"WTCCC2 project control from the National Blood Donors (NBS) cohort (N\\u0026thinsp;=\\u0026thinsp;2,619, access ID: EGAD00000000024)\\\". This sample was genotyped using Illumina 1.2M and used as \\u0026ldquo;healthy controls\\u0026rdquo; for the replication of our findings for mtDNA analysis.\\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003ePGC-OCD (PGC-OCD) Individual-Genotype Data\\u003c/strong\\u003e \\u003cp\\u003eWe used mtDNA individual-level genotyping data from the Psychiatric Genomics Consortium OCD working group (PGC-OCD, released in 2017)[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e] with available data for n\\u0026thinsp;=\\u0026thinsp;2,673 OCD cases. For details regarding this PGC-OCD sample, see[\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Data Quality Control\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.1 Nuclear-Encoded Mitochondrial Gene Selection and Quality Control for Analysis of OCD risk and Clinical Phenotypes\\u003c/h2\\u003e \\u003cp\\u003eFor analysis of clinical phenotypes, we used our in-house Toronto OCD sample and a customized genotyping array of a select set of mitochondria-related SNPs from a previous study[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Briefly, we selected 28 genes involved in oxidative phosphorylation or involved in oxidative stress, mitochondrial biogenesis, inflammation, and apoptosis to test our mitochondrial hypothesis in our in-house samples[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. Gene boundary windows were defined as 5kb in the 5\\u0026rsquo;and 2kb in the 3\\u0026rsquo; UTR regions. Tag SNPs were selected using the HapMap database, phase2\\u0026thinsp;+\\u0026thinsp;phase3, release #28, CEU population, build36 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ewww.HAPMAP.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.HAPMAP.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) and Tagger in Haploview[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. The threshold for minor allele frequency (MAF) was set at 0.05. In total, 64 SNPs were selected with linkage disequilibrium (LD, r\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;\\u0026ge;\\u0026thinsp;0.8). Extra details regarding SNP selection criteria, data cleaning and their predicted functionality were described previously[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. After QC[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e], 59 SNPs were available for analysis with OCD risk and severity. We used the Yale-Brown Obsessive-Compulsive Scale (YBOCS) to evaluate a lifetime symptom severity score, for which clients were asked to focus on symptom severity during the period of most severe OCD. We had genetic and clinical data (YBOCS) available for N\\u0026thinsp;=\\u0026thinsp;346 OCD cases from our Toronto OCD sample that survived quality control measures for inclusion.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.2 PGC-OCD Genotyping Quality Control\\u003c/h2\\u003e \\u003cp\\u003eGenome-wide genotyping in 2,673 OCD samples was performed using the Illumina Human610-Quadv1_B SNP array. A total of 620,283 SNPs were available in the raw data and positions were updated for human genome build37 using the LiftOver tool[\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. We performed standard QC[\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e] measures in this PGC-OCD sample. Briefly, we removed individuals with more than 2% of missing genotyped. No duplicate or related individuals were found after we checked for cryptic relatedness. Mean heterozygosity was calculated and outliers (\\u0026plusmn;\\u0026thinsp;3 SD) were removed (N\\u0026thinsp;=\\u0026thinsp;8). Principal Component Analysis (PCA) of the genotypes was used to check for population stratification, and outliers were removed through visual inspection of scatter plots and using the standard rule of \\u0026ldquo;6 SDs from the mean\\u0026rdquo; (6SD). SNP quality control included the removal of any markers less than 99% genotyped across all individuals, and SNPs were filtered out if the χ\\u0026sup2;-test for Hardy-Weinberg equilibrium was \\u0026lt;\\u0026thinsp;0.0000001. Thus, after individuals and markers QC, we had a total sample of 1,996 individuals and 556,922 markers. We carried out imputation with 1000 Genome Project data as reference using IMPUTE2 v2.3.2 with quality info score of \\u0026lt;\\u0026thinsp;0.9 were excluded and a final number of available SNPs (genotyped and imputed) was 5,912,464. We used this sample to select individuals that passed nuclear DNA quality control to be included in the mtDNA analysis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.3 PGC-OCD mtDNA Genotypes Data Cleaning and Merging Datasets\\u003c/h2\\u003e \\u003cp\\u003eInitially, a total of 135 mtDNA variants were available in the PGC-OCD. We performed QC by removing individuals with missing genotyping rate higher than 5%, SNPs with missing genotyping rate higher than 5%, and set minor allele frequency (MAF) to \\u0026ge;\\u0026thinsp;1%. Following mtDNA QC, a total of 78 SNPs and 1,991 OCD cases remained for analysis. We further removed individuals with mtDNA background assigned for non-European haplogroups (85 removed; N\\u0026thinsp;=\\u0026thinsp;1,906) since these individuals represented only 4.2% of our sample size. The same parameters were used to QC the control datasets (1000G and NBS).\\u003c/p\\u003e \\u003cp\\u003eWe divided the PGC-OCD data in 2 sub-samples: TO-PGC (N\\u0026thinsp;=\\u0026thinsp;215, individuals in PGC that were from Toronto OCD sample, and remaining-PGC (N\\u0026thinsp;=\\u0026thinsp;1,691) consisting of those from other collaborators from PGC. The TO-PGC was merged with 1000G (those with mtDNA assigned for one of the Europeans haplogroups; N\\u0026thinsp;=\\u0026thinsp;485). A total of 58 SNPs passed QC and were shared between our sample and 1000G and 700 subjects were present on the merged dataset (\\u0026ldquo;discovery sample\\u0026rdquo;: 215 OCD cases and 485 healthy controls). The remaining-PGC was merged with NBS sample after removal of NBS individuals with non-European haplogroups. A total of 48 SNPs were available and n\\u0026thinsp;=\\u0026thinsp;4,307 subjects were present in the merged dataset (\\u0026ldquo;replication sample\\u0026rdquo;: 1,691 OCD cases and 2,616 healthy controls). Mitochondrial haplogroups were assigned using HaploGrep2[\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e], with European haplogroups defined as H, HV, V, J, T, I, W, X and U(k).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Analysis for Mitochondrial Pathways in OCD\\u003c/h2\\u003e \\u003cp\\u003eThe OCD-PGC GWAS summary stats file was downloaded from the PGC website at \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://figshare.com/articles/dataset/ocd2018/14672103?file=28169544\\u003c/span\\u003e\\u003cspan address=\\\"https://figshare.com/articles/dataset/ocd2018/14672103?file=28169544\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e and was used as the primary input data for MAGMA (v1.06). The 1000 Genomes Project Phase 3 (Build 37/European data only) was used as the reference panel (downloaded from \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://ctg.cncr.nl/software/magma\\u003c/span\\u003e\\u003cspan address=\\\"https://ctg.cncr.nl/software/magma\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). The MAGMA gene-based results (p-values) were then corrected for multiple testing hypotheses using the p.adjust function from the stats base R package \\u003cb\\u003e(\\u003c/b\\u003eBenjamini-Hochberg method) version 4.4.0. The MAGMA gene-set analysis was then performed to examine whether one or more of the seven mitochondrial pathways from MitoCarta3[\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e] were enriched in variants associated with OCD risk. Finally, to examine if the genes identified are expressed in the brain, genes with q-value (FDR)\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.1 (i.e., top hits) were entered into the Genotype-Tissue Expression Project (GTEx) Portal (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\\\www.gtexportal.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003cspan address=\\\"http://www.gtexportal.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e; GTEx v7)[\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e], accessed on January 17, 2025.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Statistical Analyses\\u003c/h2\\u003e \\u003cp\\u003eLinear regression was used to test for association between Y-BOCS total score as the dependent variable, and genotypes as predictor variables. For this analysis, correction for multiple testing was performed using Single-Nucleotide Polymorphism Spectral Decomposition (SNPSpD) [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. A power calculation was derived using Quanto 1.2.4 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://hydra.usc.edu/gxe\\u003c/span\\u003e\\u003cspan address=\\\"http://hydra.usc.edu/gxe\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). The p-value for significance was set to 0.001 for the nuclear-encoded mitochondrial DNA analysis using Nyholt/Bonferroni correction approach when considering a type 1 error rate at 5%.\\u003c/p\\u003e \\u003cp\\u003eLogistic regression was used to test the association of mtDNA variants with OCD risk for the each of the TO-PGC discovery sample and the remaining-PGC replication sample. We then used METAL[\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e] to perform a meta-analysis based on the effect sizes and standard errors of the logistic regressions performed for the discovery and replication samples. Nyholt corrected p-value threshold for the logistic regressions and meta-analysis was set to p\\u0026thinsp;=\\u0026thinsp;0.00142, when considering a type 1 error rate at 5% (VeffLi\\u0026thinsp;=\\u0026thinsp;36.101).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. RESULTS\",\"content\":\"\\u003cp\\u003eHere we tested the hypothesis that genetic variants in the mitochondrial system (both autosomal and mtDNA) are associated with OCD risk and clinical severity using our in-house OCD sample (TO-OCD) and OCD sample available in the global PGC consortium (PGC-OCD). See Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e for study design.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Nuclear-Encoded Mitochondrial SNP-based Analysis with OCD Clinical Severity\\u003c/h2\\u003e \\u003cp\\u003eWe investigated the role of nuclear-encoded mitochondrial SNPs in the severity of OCD symptoms based on YBOCS lifetime total score (See table 1 for top hits). The most significant finding was for the SNP rs3820189 in the 5\\u0026rsquo;of the \\u003cem\\u003eMFN2\\u003c/em\\u003e gene with YBOCS total score (N\\u0026thinsp;=\\u0026thinsp;346; P\\u003csub\\u003euncor\\u003c/sub\\u003e= 0.002). This gene is ubiquitously expressed across all tissues in the body, including the brain[\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e] (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ea). While it is highly expressed throughout all developmental stages, its expression peaks during late infancy and young adulthood (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eb). Notably, \\u003cem\\u003eMFN2\\u003c/em\\u003e exhibits its highest expression levels in the frontal cortex (median TPM\\u0026thinsp;=\\u0026thinsp;53.61) and basal ganglia tissues, particularly the nucleus accumbens (median TPM\\u0026thinsp;=\\u0026thinsp;40.6). However, the findings from this analysis did not survive correction for multiple hypothesis testing.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Nuclear-Encoded Mitochondrial Gene-based Analysis with OCD risk\\u003c/h2\\u003e \\u003cp\\u003eWe also investigated the hypothesis that variants in the nuclear-encoded mitochondrial genes are associated with risk for OCD. To test this hypothesis, we used publicly available PGC-OCD genome-wide association summary stats data to perform gene-based (individual mitochondrial gene p-values) and gene-set (pre-defined mitochondrial pathways) analyses in MAGMA. For gene-based analysis, we found the gene \\u003cem\\u003eADCK1\\u003c/em\\u003e (aarF domain containing kinase 1; q-value\\u0026thinsp;=\\u0026thinsp;0.05) showed the strongest association with OCD risk (see table 2 for top hits). \\u003cem\\u003eADCK1\\u003c/em\\u003e is mildly expressed throughout all tissues in the body, including brain regions previously associated with OCD, such as the frontal cortex (median TPM\\u0026thinsp;=\\u0026thinsp;6.45) and the nucleus accumbens (median TPM\\u0026thinsp;=\\u0026thinsp;5.38) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea and c). According to GTEx analysis, when examining expression across the brain, two of our other top hits of \\u003cem\\u003eMTX2\\u003c/em\\u003e and \\u003cem\\u003eALDH6A1\\u003c/em\\u003e genes show the most significant expression levels in brain tissues, more specifically, \\u003cem\\u003eMTX2\\u003c/em\\u003e is highly expressed in the frontal cortex region (median TPM\\u0026thinsp;=\\u0026thinsp;54.74) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea) and \\u003cem\\u003eALDH6A1\\u003c/em\\u003e is highly expressed in the anterior cingulate cortex (median TPM\\u0026thinsp;=\\u0026thinsp;62.12), nucleus accumbens (median TPM\\u0026thinsp;=\\u0026thinsp;59.04), frontal cortex (median TPM\\u0026thinsp;=\\u0026thinsp;56.47), and caudate (median TPM\\u0026thinsp;=\\u0026thinsp;56.48) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea). Moreover, both \\u003cem\\u003eMTX2\\u003c/em\\u003e and \\u003cem\\u003eALDH6A1\\u003c/em\\u003e seem to be important during different developmental stages, being \\u003cem\\u003eMTX2\\u003c/em\\u003e highly expressed across all stages, while ALDH6A1 seems to present a shift from low to high expression during late pre-natal stage. For the gene-set analysis, we included 7 mitochondrial pathways defined by MitoCarta3 database, but none of them were associated with OCD risk (Table\\u0026nbsp;3).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Mitochondrial-DNA SNP-based Analysis with OCD risk\\u003c/h2\\u003e \\u003cp\\u003eWe examined the hypothesis that variants in mtDNA were associated with OCD risk. We identified five SNPs significantly associated with OCD risk: m.1719G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (p\\u0026thinsp;=\\u0026thinsp;1.489E-05) and m.3010G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (p\\u0026thinsp;=\\u0026thinsp;2.423E-04) in the gene 16S ribosomal RNA (\\u003cem\\u003eMT-RNR2\\u003c/em\\u003e), m.10398A\\u0026thinsp;\\u0026gt;\\u0026thinsp;G (p\\u0026thinsp;=\\u0026thinsp;3.172E-04) in the NADH dehydrogenase subunit 3 gene (\\u003cem\\u003eMT-ND3\\u003c/em\\u003e), m.11914G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (p\\u0026thinsp;=\\u0026thinsp;6.085E-04) in the NADH dehydrogenase subunit 4 gene (\\u003cem\\u003eMT-ND4\\u003c/em\\u003e), and m.6260G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (p\\u0026thinsp;=\\u0026thinsp;7.792E-04) in the gene Cytochrome c oxidase subunit I (\\u003cem\\u003eMT-CO1\\u003c/em\\u003e) (Table\\u0026nbsp;4 and Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Three of them were presented in both datasets: m.1719G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A, m.3010G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A, and m.11914G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. DISCUSSION\",\"content\":\"\\u003cp\\u003eTo the best of our knowledge, this is the first study to identify mitochondrial genetic variants associated with OCD risk. We first used a hypothesis-driven approach and we genotyped SNPs from a selected set of nuclear-encoded mitochondrial genes directly involved in or related to OXPHOS, and tested for association with OCD clinical severity as estimated by lifetime YBOCS total score. Thus, we tested our set of nuclear-encoded mitochondrial genes in the severity of clinical OCD symptoms (lifetime YBOCS total score). We found significant results for rs3820189 (P\\u003csub\\u003euncorrected\\u003c/sub\\u003e= 0.002) located in the 5\\u0026rsquo; region of the mitofusin 2 (\\u003cem\\u003eMFN2\\u003c/em\\u003e) gene. This gene is located in the outer membrane of mitochondria and is involved in the mitochondrial dynamic process of fusion and fission, as well as contact with other organelles, particularly the endoplasmic reticulum[\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Mitochondrial dynamic has been shown to play a role in the pathophysiology of several psychiatric disorders (for a review, see[\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]). However, it is important to note that these individual-SNP findings were nominal and did not survive correction for multiple testing. As described above, \\u003cem\\u003eMFN2\\u003c/em\\u003e exhibits its highest expression levels in the frontal cortex and nucleus accumbens. These regions have been consistently associated with OCD in brain imaging studies[\\u003cspan additionalcitationids=\\\"CR47\\\" citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. The nucleus accumbens is one of the regions targeted by the deep brain stimulation (DBS)[\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e], an intervention that has been proven effective in treating OCD symptoms [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. Mitochondrial dysfunction in the nucleus accumbens has been associated with anxiety in rats[\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e], and it may be one of the impaired neurobiological mechanisms targeted by the DBS treatment. DBS intervention, particularly in Parkinson\\u0026rsquo;s disease, has been shown to promote mitochondrial recovery. This process is mediated by mitophagy, a crucial component of the mitochondrial quality control system, which involves proteins such as MFN2. Therefore, although our findings from this primary analysis did not withstand correction for multiple testing, the aforementioned biological evidence, together with our analysis, suggest that genetic variants in the MFN2 gene might play a role in OCD symptom severity and should be further investigated in independent samples.\\u003c/p\\u003e \\u003cp\\u003eOur gene-based analysis revealed the aarF domain-containing kinase 1 (\\u003cem\\u003eADCK1\\u003c/em\\u003e) gene to be significantly associated with OCD risk (table 3). This gene was previously associated with OCD in a large meta-analysis[\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. A study with drosophila reported that ADCK1 acts along YME1-like 1 ATPase (YME1L1) to control optic atrophy 1 (OPA1) and inner membrane mitochondrial protein (IMMT)[\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e]. YME1L1 pathway is known to play a critical role in the regulation of mitochondrial dynamics[\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e] and is also involved in the proteolytic regulation of respiratory chain biogenesis[\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]. This finding along with MFN2 from above suggests the presence of variants in specific mitochondrial dynamic genes playing a role in OCD risk and severity of symptoms. In support to our findings, the mitochondrial dynamic pathway was not significantly associated with OCD risk (Table\\u0026nbsp;3, p\\u0026thinsp;=\\u0026thinsp;0.64).\\u003c/p\\u003e \\u003cp\\u003eAnalysis of mitochondrial pre-established MitoCarta gene-sets (pathways) did not show positive associations with OCD risk likely due to the high degree of genetic heterogeneity seen in psychiatric disorders. We suggest that more hypothesis-driven mitochondrial-related pathways or inclusion of only core subsets of genes may be targeted in future gene-set based studies for more informative findings.\\u003c/p\\u003e \\u003cp\\u003eWe then examined mtDNA common variants in the subgroup of the TO-OCD discovery sample obtained through the PGC, and in the PGC-OCD replication sample. The meta-analysis revealed five SNPs to be significantly associated with OCD risk after multiple testing correction (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.00142) (Table\\u0026nbsp;2). The SNP m.10398A\\u0026thinsp;\\u0026gt;\\u0026thinsp;G is mapped to the \\u003cem\\u003eMT-ND3\\u003c/em\\u003e gene, and it is classified as non-synonymous, i.e. predicted to cause an amino acid substitution at position 114 of the ND3 protein (T114A). This allele substitution has a MutPred score of 0.17 (low risk). The gene \\u003cem\\u003eMT-ND3\\u003c/em\\u003e is responsible for coding a subunit of NADH dehydrogenase, a component of the respiratory chain Complex I. Complex I is essential for normal functioning of OXPHOS, and disturbances in it can severely impact energy metabolism and mitochondrial function. Moreover, MT-ND3 is ubiquitously expressed in the brain[\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e] (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.proteinatlas.org\\u003c/span\\u003e\\u003cspan address=\\\"https://www.proteinatlas.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e; accessed 10/17/2024) and variants within \\u003cem\\u003eMT-ND3\\u003c/em\\u003e have been previously associated with several phenotypes, such as schizophrenia[\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e], risk for neurodegenerative disorders including Parkinson\\u0026rsquo;s disease [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e] and Alzheimer\\u0026rsquo;s disease[\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e], and many others disorders, such as breast cancer[\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e] and type 2 diabetes[\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. Moreover, Smullen et al[\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e] recently described the association of the locus m.10398A\\u0026thinsp;\\u0026gt;\\u0026thinsp;G with increased heteroplasmy in a specific region of the mtDNA, the control region (CR) in dorsolateral prefrontal cortex (DLPFC) post-mortem brain of individuals with Alzheimer\\u0026rsquo;s Disease. This increase in heteroplasmy in the CR was also correlated with reduced expression of the mitochondrial genes \\u003cem\\u003eMT-ND3\\u003c/em\\u003e and \\u003cem\\u003eMT-ND4\\u003c/em\\u003e[\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e]. These findings highlight the critical role of this locus in maintaining mtDNA integrity and regular mitochondrial function, and its potential contribution to brain diseases.\\u003c/p\\u003e \\u003cp\\u003eThe SNPs m.1719G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A and m.3010G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A, m.11914G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A and m.6260G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A, mapped within the genes \\u003cem\\u003eMT-RNR2\\u003c/em\\u003e, \\u003cem\\u003eMT-ND4\\u003c/em\\u003e, and \\u003cem\\u003eMT-CO1\\u003c/em\\u003e, respectively, were found to be associated with OCD risk (Table\\u0026nbsp;4). Although these SNPs are synonymous with minimal functional impact expected[\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e], recent studies have been suggesting a more prominent role for this type of variants in diseases, such as in cancer by, for example, disrupting pre-mRNA splicing (for a review see [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e]). For mtDNA, in particular, synonymous variants may impact codon-anticodon affinity and play a role in modulating traits, disease phenotypes and mitochondrial evolution[\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e]. Two of these SNPs (m.1719G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A and m.3010G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A) are located inside the gene \\u003cem\\u003eMT-RNR2\\u003c/em\\u003e, which primarily encodes the mitochondrial 16S ribosomal RNA (rRNA), but it also encodes humanin, a peptide with cytoprotective properties, playing a role in inflammation, neuroprotection and oxidative stress[\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e]. Humanin has been previously reported as a protective factor in Alzheimer\\u0026rsquo;s disease, based on its role in supressing apoptosis in Aβ-induced neuron death in vitro[\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. \\u003cem\\u003eMT-ND4\\u003c/em\\u003e encodes for the NADH-ubiquinone oxidoreductase chain 4 protein, another core component of the mitochondrial OXPHOS complex I. Dysfunctions in this protein are known for severely impairing the energy supply to neurons, which is believed to contribute to an increasing list of neurodevelopmental and psychiatric disorders, such as schizophrenia[\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e], bipolar disorder[\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e], major depressive disorder[\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e], autism spectrum disorder[\\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e], and Parkinson\\u0026rsquo;s disease[\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e]. Finally, \\u003cem\\u003eMT-CO1\\u003c/em\\u003e encodes for the Cytochrome c oxidase subunit I, which plays a critical role in the OXPHOS complex IV pathway. Dysfunctions in this subunit have also been linked to psychiatric disorders, including schizophrenia[\\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e] and autism spectrum disorder [\\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e]. To the best of our knowledge, this is the first report of mtDNA variants associated with OCD risk. Taken together, the mtDNA variation in the genes reported here may contribute to OCD risk and highlight complex I as a site of variants in OCD. Complex I is a site for leaking electrons and variants in it may contribute to increased OS, an emerging hypothesis for OCD pathophysiology[\\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eLimitations of this study include small sample size and lack of data for inclusion of other ancestry beyond Europeans. Another limitation particularly applicable for the OCD clinical severity analysis is the absence of genetic control for population stratification (participants are self-declared Europeans). Furthermore, healthy controls samples (1000G and NBS) were not screened for OCD or other psychiatric disorders. Our findings were also limited due to low coverage of SNPs available for analysis, and future studies should, use genotyping arrays with better coverage of mtDNA SNPs or use next-generation sequencing data. Another future direction would consider the examining of mtDNA variants influencing the nuclear epigenetics in OCD individuals. Presence of variants on mtDNA compromising its integrity may alter nuclear epigenetic patterns (such as methylation loci) compromising metabolism and contributing to development of complex diseases[\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e]. Our group has reported evidence for genetic and epigenetic factors influencing OCD risk and severity of symptoms[\\u003cspan citationid=\\\"CR81\\\" class=\\\"CitationRef\\\"\\u003e81\\u003c/span\\u003e] and this new perspective may help to clarify pieces of the illness pathophysiology. In the same direction, the interaction between nuclear SNPs and mitochondrial DNA variants is worth exploring in future studies. Finally, the use of more comprehensive clinical and demographic data will allow a better exploration of whether environmental factors would affect these findings. In conclusion, we have identified evidence that mitochondrial variants in both nuclear and mtDNA genes influence OCD risk. Validation of the findings in larger and independent samples is still warranted.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113, 085475 and 090355. This work was supported by research grants from the Ontario Mental Health Foundation and Canadian Institutes for Health Research (Drs. Richter and Kennedy) and private donations to the Frederick W. Thompson Anxiety Disorders Centre at Sunnybrook Health Sciences Centre (Dr. Richter).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVFG, JLK and CCZ are currently supported by the CAMH Foundation and Larry and Judy Tanenbaum Foundation. GZ was supported by the Academic Scholars Award from the Department of Psychiatry at the University of Toronto and is current supported by research funding from the Centre for Addiction and Mental Health, Physicians Services\\u0026rsquo; Incorporated Foundation, BBRF (NARSAD) Young Investigator Grant, and International OCD Foundation Young Investigator Grant.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eJLK is a member of the Scientific Advisory Board of Myriad Neuroscience (paid). JLK, VFG and CCZ are authors on several patents relating to pharmacogenetic tests for psychiatric medications. Dr. Richter has received research support through a grant from Eli Lilly, an honorarium and expenses from Brainsway for participation in a positional board meeting, and speaker honoraria from Lundbeck. JLK and CCZ are authors on a patent on genetic biomarkers of suicide risk. The remaining authors have no conflicts of interest to declare.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eRuscio AM, Stein DJ, Chiu WT, Kessler RC. The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Mol Psychiatry. 2010;15:53\\u0026ndash;63.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBlanco-Vieira T, Radua J, Marcelino L, Bloch M, Mataix-Cols D, do Ros\\u0026aacute;rio MC. The genetic epidemiology of obsessive-compulsive disorder: a systematic review and meta-analysis. 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JAMA Psychiatry. 2021;78:911\\u0026ndash;921.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAvdjieva-Tzavella D, Mihailova S, Lukanov C, Naumova E, Simeonov E, Tincheva R, et al. Mitochondrial DNA mutations in two bulgarian children with autistic spectrum disorders. Balkan J Med Genet. 2012;15:47\\u0026ndash;54.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShrivastava A, Kar SK, Sharma E, Mahdi AA, Dalal PK. A study of oxidative stress biomarkers in obsessive compulsive disorder. J Obsessive Compuls Relat Disord. 2017;15:52\\u0026ndash;56.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBehl A, Swami G, Sircar SS, Bhatia MS, Banerjee BD. Relationship of possible stress-related biochemical markers to oxidative/antioxidative status in obsessive-compulsive disorder. 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Int J Neuropsychopharmacol. 2016;19:25.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003eTable 1 to 4 are available in the Supplementary Files section.\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6149169/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6149169/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eObsessive-compulsive disorder (OCD) is a severe neuropsychiatric disorder with clear evidence of genetic vulnerability, although specific risk factors are not fully understood. Mitochondrial dysfunction has been implicated in other severe neuropsychiatric disorders, particularly through its role in oxidative stress, and thus merits exploration in OCD. Here we first examined the association of a set of 59 mitochondrial single nucleotide polymorphisms (SNPs) with OCD symptom severity. These SNPs are located inside 28 nuclear-encoded mitochondrial genes involved in oxidative phosphorylation, oxidative stress, mitochondrial biogenesis, inflammation, and apoptosis. We used linear regression to test for the association of this SNP set with symptom severity using the Yale-Brown Obsessive Compulsive Scale (YBOCS). We found a nominally significant association for rs3820189 in the 5\\u0026rsquo; of the \\u003cem\\u003eMFN2\\u003c/em\\u003e gene with YBOCS total score (N\\u0026thinsp;=\\u0026thinsp;346; P\\u003csub\\u003euncorrected\\u003c/sub\\u003e= 0.002). We also conducted gene-based and gene-set (pathway) analyses on nuclear-encoded mitochondrial genes and pathways with OCD risk using MAGMA. We found the gene \\u003cem\\u003eADCK1\\u003c/em\\u003e to be associated with OCD (p\\u0026thinsp;=\\u0026thinsp;0.00005, q\\u0026thinsp;=\\u0026thinsp;0.05). No mitochondrial pathways were associated with OCD risk. To further examine mitochondrial genetic variation in OCD risk, we then examined mitochondrial (mt) DNA (mtDNA), the circular genome located inside each mitochondrion. We utilized the Toronto OCD sample (N\\u0026thinsp;=\\u0026thinsp;215) and the 1000 Genome Project (N\\u0026thinsp;=\\u0026thinsp;485) as healthy controls for discovery. For replication, we compared individual-level data from the Psychiatric Genomics Consortium (PGC) OCD Working Group release 2017 (N\\u0026thinsp;=\\u0026thinsp;1691) with the Wellcome Trust sample (N\\u0026thinsp;=\\u0026thinsp;2616) as controls. After data cleaning, 58 common mtDNA SNPs (minor allele frequency greater than 1%) were available for analysis. Meta-analysis across the significant mtDNA variants shared between both samples revealed five SNPs significantly associated with OCD risk which survived Nyholt correction: NC_012920.1:m.1719G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (P\\u0026thinsp;=\\u0026thinsp;1.489E-05), NC_012920.1:m.3010G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (P\\u0026thinsp;=\\u0026thinsp;2.423E-05), NC_012920.1:m.10398A\\u0026thinsp;\\u0026gt;\\u0026thinsp;G (P\\u0026thinsp;=\\u0026thinsp;3.172E-04), NC_012920.1:m.11914G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (P\\u0026thinsp;=\\u0026thinsp;6.085E-04) and NC_012920.1:m.6260G\\u0026thinsp;\\u0026gt;\\u0026thinsp;A (P\\u0026thinsp;=\\u0026thinsp;7.792E-04). To the best of our knowledge, this is the largest study to report the involvement of mitochondrial variants in OCD risk. Further investigations and validation of our findings are warranted.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Examining mitochondrial genetic variation in obsessive-compulsive disorder\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-03-27 18:57:11\",\"doi\":\"10.21203/rs.3.rs-6149169/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"84a6affe-2991-4cfb-b029-6dd4aa6677fc\",\"owner\":[],\"postedDate\":\"March 27th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":45866788,\"name\":\"Biological sciences/Genetics\"},{\"id\":45866789,\"name\":\"Biological sciences/Molecular biology\"}],\"tags\":[],\"updatedAt\":\"2025-06-16T09:01:51+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-03-27 18:57:11\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6149169\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6149169\",\"identity\":\"rs-6149169\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}