Salivary oxytocin concentrations in children and adolescents with and without OCD

doi:10.21203/rs.3.rs-4654936/v1

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Salivary oxytocin concentrations in children and adolescents with and without OCD

https://doi.org/10.21203/rs.3.rs-4654936/v1

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Introduction:

Oxytocin has been implicated as a biological mechanism within obsessive-compulsive disorder (OCD). Few studies only involving adults have investigated this hypothesis and found inconsistent results. We investigated whether salivary oxytocin concentrations differed between children and adolescents with and without OCD and qualified our comparative analysis by investigating the possible covariates age, pubertal stage, and sex.

Methods

Participants included 113 children and adolescents (8–17 years) with OCD and 88 children and adolescents without any previous or current psychiatric disorder and their parents (254 parents included). Salivary oxytocin concentrations were measured with enzyme-linked immunosorbent assay (ELISA). Statistical analyses were performed using frequentist and Bayesian approaches.

Results

We found no evidence of a difference in mean salivary oxytocin concentrations between children and adolescents with and without OCD. Bayesian analyses indicated anecdotal to moderate support for the null hypothesis. We found an association between oxytocin and age and pubertal stage, which by visual inspection of plots and post-hoc tests indicated a nonlinear relationship. We found no association between oxytocin and sex.

Conclusion

Our findings do not suggest elevated oxytocin concentrations in pediatric OCD. Nonlinear changes in oxytocin across development show the importance of accounting for hormonal and behavioral changes during puberty.

Health sciences/Diseases/Psychiatric disorders/Obsessive compulsive disorder

Biological sciences/Psychology

Oxytocin

Obsessive-Compulsive Disorder

children

adolescents

pubertal stage

age

Pediatric obsessive-compulsive disorder (OCD) is a common and impairing psychiatric disorder marked by excessive worry, cleaning, checking or other unwanted, repetitive thoughts and behaviors¹. The biological mechanisms underlying OCD are not fully understood.

Oxytocin, a neuropeptide synthesized in the hypothalamus, has been proposed to play a key role in OCD². OCD-like behaviors in animals and humans have been observed under conditions of elevated oxytocin. For example, injecting oxytocin in the brains of rats and squirrel monkeys induced licking and grooming behavior – possibly analogous to cleaning compulsions². Pregnant and postpartum women, groups marked by elevated oxytocin concentrations, have reported obsessions about and compulsive checking of their child’s well-being². These observations led to the hypothesis that oxytocin concentrations may be elevated in OCD². This hypothesis has been investigated in three studies so far. The first study of 29 adults with OCD, 23 with Tourette’s syndrome, and 31 controls found no differences in oxytocin concentrations in cerebrospinal fluid (CSF) among the three groups³. Another study of 14 adults with OCD and 26 controls found no significant difference in CSF oxytocin between the two groups⁴. A more recent study – the largest to date (44 adult patients with OCD and 44 controls) – found significantly higher concentrations of plasma oxytocin in patients with OCD⁵. Studies that investigate oxytocin concentrations in children and adolescents with OCD are needed as OCD often onsets in childhood and oxytocin system functioning changes across the lifespan⁶.

Oxytocin concentrations often show high variability, which can complicate the detection of group differences^7,8. Thus, studies that identify the sources of this variation and attempt to account for it before performing group comparisons could contribute with important knowledge. In children and adolescents, age, sex, and pubertal stage may account for variation in oxytocin concentrations as major physiological and behavioral changes occur during this stage in life and sex differences in oxytocin have been observed^6,9,10.

Thus, we investigated whether salivary oxytocin concentrations differed between children and adolescents with OCD and children and adolescents without OCD, while controlling for age, pubertal stage, and sex. We also explored whether and how these variables contributed to variance in salivary oxytocin.

2.1. Study design

This is a sub-study of the TECTO trial (Treatment Effects of Family Based Cognitive Therapy in Children and Adolescents with Obsessive-Compulsive Disorder)¹¹. The TECTO trial is a randomized clinical trial (RCT) comparing family-based cognitive behavioral therapy with family-based psychoeducation and relaxation training in 130 children and adolescents with OCD¹¹ combined with a case-control study including 90 age- and sex-matched controls without current or previous psychiatric diagnoses (described in this paper as “children and adolescents without OCD”). In the present study, we used baseline data only. Data collection started July 2018 and finished September 2022.

The TECTO trial complies to the Helsinki Declaration¹² was approved by the ethics committee (Scientific Ethics Committees for the Capital Region of Denmark) (H-18010607) and the Knowledge Centre on Data Protection Compliance in The Capital Region of Denmark and was registered with clinical trials.gov (NCT03595098).

2.2. Participants and procedures

We included children and adolescents (8–17 years) and their parents as participants. Presence or absence of psychiatric diagnoses were based on the Kiddie-Schedule for Affective Disorders and Schizophrenia – Present and Lifetime Version (K-SADS-PL)¹³ and the criteria for International Classification of Diseases‑10 (ICD-10)¹⁴. Parents or legal guardians provided written informed consent concerning their child’s and their own participation. For detailed information on the eligibility screening, inclusion and exclusion criteria and consent procedure see Appendix A.

Saliva samples for oxytocin were collected with Salivettes (Sarstedt, Rommelsdorf, Germany). Participants were asked to refrain from eating two hours and drinking liquids 30 minutes prior to sampling. A detailed description of the handling of the saliva samples are available in Appendix A. The samples were analyzed with immunoassay using Enzo® (NY, USA) oxytocin kits according to the manufacturer’s instructions, and concentrations were calculated using WorkOut 2.5 (Dazdaq Solutions Ltd, Brighton, UK). The intra-assay coefficient of variation was 13% and the inter-assay coefficient of variation was 20%.

Children and adolescents reported their pubertal status after instruction from a trained investigator using Tanner staging^15,16. The children and adolescents chose the most fitting pubertal stage among pictorial presentations of secondary sex characteristics on a 5 point scale ranging from 1 (pre-pubertal development) to 5 (full adult development)^15,16. We did not use classification of the specific sex characteristics but asked the children and adolescents to report the best fitting total pubertal stage. In one post hoc analysis, we assigned parents “pubertal stage 6” indicating “adults”. However, this is not a part of the original Tanner staging. Throughout the paper, we use the term pubertal stage to describe Tanner stage.

2.3. Statistical analysis

We registered our statistical analysis plan prior to any data analysis (date of registration June 7, 2023, https://osf.io/hmc43). Changes from the pre-registered plan are described in the Appendix B. We used frequentist statistics and supplemented with Bayesian statistics for some analyses, as it can provide information on the degree to which the data favor the alternative hypothesis (H₁) or the null hypothesis (H₀)¹⁷. We used quantification by Bayes factors (BF₁₀) in the analyses of our primary models including OCD status. We interpreted the Bayes Factor using a classification scheme by Lee and Wagenmaker¹⁸ with a BF₁₀ of 1 indicating no difference in the support of the H₁- compared to the H₀. Values above 1 indicate support of the H_1, and values below 1 indicate support of the H₀. The degree of support is divided by cutoffs describing anecdotal, moderate, strong, very strong, or extreme evidence. We used the predictive performance (ELPD-LOO) for all other model comparisons with Bayesian statistics. For a more detailed description of the Bayesian methods and analyses of sensitivity to the prior distributions, see Appendix C. Analyses were performed using R (version 4.2.0 and 4.3.0 for the random forest analyses).

We excluded outliers in oxytocin concentrations (values ± 3 SDs from the mean) and applied a logarithmic transformation. In our pre-registration, assuming n = 220 (children and adolescents with OCD: 130, healthy controls: 90), α = 0.05 (2-sided), and β = 0.80, we noted that we were able to reliably detect a Cohen’s d of at least 0.4 (calculated using r package “pwr” as a Cohens d of 0.39). Our sample size was slightly reduced by missing information and outliers, however, without major change in the effect size we could detect (n = 201 (children and adolescents with OCD: 113, children and adolescents without OCD: 88), α = 0.05 (2-sided), and β = 0.80, Cohens d of 0.40). We did not adjust for multiple comparisons as the study was exploratory, but we reported all comparisons and considered the risk of false discoveries.

The following primary statistical models were run (see also Appendix E):

Model 1: Using a Student’s t-test we investigated the difference in children and adolescents oxytocin concentrations (dependent variable) between children and adolescents with and without OCD (OCD status; independent variable). A Bayes factor was calculated to compare H₁ (an effect of OCD status) to H₀ (no effect of OCD status).

Model 2: A backward stepwise regression explored the variance in children and adolescent’s oxytocin concentrations (dependent variable) explained by OCD status, age, sex, and age-sex interaction (independent variables). The reduced model of the stepwise regression was used to analyze the effect of OCD status on oxytocin concentrations. We used Bayesian analysis to compare H₁ (the reduced model plus an effect of OCD status) to H₀ (the reduced model). Additionally, we used Bayesian analysis to compare the result of the stepwise regression and thereby the significant effects of relevant variables by comparing H₁ (the reduced model) to H₀ (intercept model).

Model 3: We investigated the variance explained by child and adolescent pubertal stage by repeating Model 2 with pubertal stage instead of age.

Model 4: We explored the effect of age and sex by analyzing all participants (children and adolescents, and parents). A backward stepwise regression of a mixed effects model with participant oxytocin concentration (dependent variable), age, sex, and the interaction between age and sex (fixed effects) and a “family-variable” (random effect) was used. The family-variable (a nominal variable denoting family membership) was included because previous research has shown associations between the oxytocin concentrations of parent couples (mothers and fathers)¹⁹ as well as parents and their children²⁰.

To further explore the data, we ran the following post hoc models and tests that were not pre-registered:

Post Hoc Model A: We explored the observed nonlinearity in the child and adolescent data by repeating Model 2 with a quadratic age variable (age²).

Post Hoc test B: To investigate if either age or pubertal stage best accounts for variation in oxytocin levels, we compared Model 3 with OCD and Post Hoc Model A with OCD using Bayesian analysis.

Post Hoc Model C: We repeated Model 4 with pubertal stage instead of age for all participants assigning parents an adult “pubertal stage 6”. Bayesian analyses were used to compare the reduced Post Hoc Model C to the reduced Model 4.

Post Hoc Model D: To further explore the adult data we repeated Model 4 in adults alone.

Post Hoc test with random forest: A random forest approach (described in Appendix D) explored non-linear associations between salivary oxytocin and relevant covariates. We explored sex, age, pubertal stage, and information on menarche status, menopause status and use of hormonal contraception.

Complete case analyses were performed. Sample selection is presented in Fig. 1. Due to missing information on pubertal stage for some children and adolescents we refitted models without child and adolescent pubertal stage to data which excluded children and adolescents with missing pubertal stage when comparing models with pubertal stage to models without pubertal stage. We excluded cases with less than two family members from the models that included the ‘family-variable’. We report supplementary analyses (described in Appendix F) of variables that could cause variation in oxytocin, but this was not a main objective of this study (time of sample, psychosocial functioning, OCD severity score, social responsiveness, menarche, and menstrual cycle phase).

Participant characteristics are presented in Table 1 (children and adolescents) and Table 2 (parents).

Table 1

Descriptive characteristics of the children and adolescents included in Model 1 and Model 2. Children in Model 3 and Model 4 are a subsample of the children.
		Children and adolescents with OCD	Children and adolescents without OCD	Test (p-value)
n		113	88
Age (years)				0.26_A
	Mean (SD)	13.37 (2.83)	12.92 (2.78)
	Median (min, max)	13.81 (8.08, 17.99)	12.37 (8.09,17.83)
	Missing (n)	0	0
Sex (n (%))				0.98_B
	Female	58 (51.3%)	45 (51.1%)
	Male	55 (48.7%)	43 (48.9%)
	Missing	0	0
Pubertal stage (n (%))				0.39_B
	Pubertal stage 1	32 (28.3%)	23 (26.1%)
	Pubertal stage 2	13 (11.5%)	20 (22.7%)
	Pubertal stage 3	20 (17.7%)	14 (15.9%)
	Pubertal stage 4	25 (22.1%)	23 (26.1%)
	Pubertal stage 5	13 (11.5%)	8 (9.1%)
	Missing	10 (8.8%)	0 (0%)
Nationality (n (%))				-
	Danish	95 (84,1%)	63 (71.6%)
	Other	3 (2.7%)	2 (2.3%)
	Missing	15 (13.3%)	23 (26.1%)
Comorbid psychiatric disorders (n (%))			-	-
	Anxiety disorders ICD-10 F40-41, F93	12 (10.6%)	-
	Stress and adjustment ICD-10 F43	12 (10.6%)	-
	Asperger’s Syndrome ICD-10 F84.5	14 (12.4%)	-
	Hyperkinetic disorders ICD-10 F90.0	13 (11.5%)	-
	Tic disorders ICD-10 F95	13 (11.5%)	-
	Other*	20 (17.7%)	-
Medication (n (%))			-	-
	Children receiving medication*	24 (21.2%)	-
Somatic disorders (n (%))			-	-
	Children with a somatic disorder*	32 (28.3%)	-

* Other describes all other diagnoses. For detailed information on patient medication and comorbid and somatic disorders see Appendix 4. _At-test, _BChi-squared test. Note: n, number; SD, standard deviation; OCD, obsessive-compulsive disorder; ICD-10, International Classification of Diseases-10

Table 2

Descriptive characteristics of parents included in Model 4
		Children and adolescents with OCD	Children and adolescents without OCD
n
	Mothers	92	58
	Fathers	72	32
Mother age (years)
	Mean (SD)	45.72 (5.03)	45.97 (5.10)
	Median (min, max)	45.61 (32.76,56.24)	46.45 (34.97,57.19)
	Missing (n)	0	0
Father age (years)
	Mean (SD)	48.17 (5.67)	47.47 (6.78)
	Median (min, max)	48.91 (33.1,73.51)	47.08 (34.45,62.73)
	Missing (n)	0	0
Nationality Mother (n (%))
	Danish	77 (83.7%)	46 (79.3%)
	Other	5 (5.4%)	3 (5.2%)
	Missing	10 (10.9%)	9 (15.5%)
Nationality Father (n (%))
	Danish	57 (79.2%)	24 (75%)
	Other	5 (6.9%)	1 (3.1%)
	Missing (n)	10 (13.9%)	7 (21.9%)
Parental education mothers (n (%))
	Upper secondary education or below	8 (8.70%)	1 (1.7%)
	Short-cycle tertiary education	14 (15.2%)	3 (3.2%)
	Bachelor’s degree or equivalent	38 (41.3%)	22 (37.9%)
	Master’s degree or above	22 (23.9%)	23 (39.7%)
	Missing (n)	10 (10.9%)	9 (15.5%)
Parental education fathers (n (%))
	Upper secondary education or below	12 (16.7%)	3 (9.4%)
	Short-cycle tertiary education	8 (11.1%)	3 (9.4%)
	Bachelor’s degree or equivalent	16 (22.2%)	6 (18.8%)
	Master’s degree or above	25 (34.7%)	13 (40.6%)
	Missing (n)	11 (15.3%)	7 (21.9%)
Note: n, number; SD, standard deviation; OCD, obsessive-compulsive disorder

In Model 1, salivary oxytocin concentrations did not significantly differ between children and adolescents with and without OCD (p = 0.2682, Table 3 and further details in Appendix E), but the Bayes factor showed only anecdotal support for the H₀ hypothesis (BF₁₀ = 0.37, Table 3), a result which was particularly sensitive to the prior distribution (see Appendix C).

Table 3

Result of student’s t-test of salivary oxytocin levels in children and adolescents with and without OCD (OCD-status) and Bayesian statistics (Model 1)
			t-statistics	p-value	Bayesian analysis
Model 1
1. Test	H₁	OCD-status	1.111	0.2682	BF₁₀ = 0.37
1. Test	H₀	Intercept
Note. BF, Bayes factor; H₁, alternative hypothesis; H₀, null hypothesis

In Model 2, the age-sex interaction, sex, and OCD-status did not significantly contribute to variation in child and adolescent oxytocin and were thus removed in the first three steps (see Appendix E). The reduced model showed a significant positive linear relationship [Figure 2 and Fig. 4 (pink line)] between age and child and adolescent oxytocin (p = 0.0031, Table 4, and see Appendix E). The Bayesian analysis showed that the model including child and adolescent age had a better predictive performance but a large standard error (SE) (ELPD-LOO = -3.4, SE = 2.7, Table 4). When we reexamined the relationship between child and adolescent oxytocin and OCD-status while controlling for age, OCD-status did not significantly account for variation in oxytocin (p = 0.3605, Table 4, and see Appendix E). The corresponding Bayes factor showed moderate support for no difference in oxytocin concentrations between children and adolescents with and without OCD controlling for age (BF₁₀ = 0.31, Table 3) but with considerable prior sensitivity (see Appendix C).

Table 4

Results of reduced models, reduced models with OCD, and Bayesian statistics of Model 2 and Model 3
			F-statistics	p-value	Bayesian analysis
Model 2
1. Test	H₁	Reduced model (age)	8.913	0.0031	H₁- H₀ ELPD-LOO (SE) = 3.5(2.7)
1. Test	H₀	Intercept
2. Test	H₁	Reduced model (age) and OCD-status	0.840	0.3605	BF₁₀₌0.31
2. Test	H₀	Reduced model (age)
Model 3
1. Test	H₁	Reduced model (pubertal stage)	5.384	0.0004	H₁- H₀ ELPD-LOO (SE) = 6.6(4.1)
1. Test	H₀	Intercept
2. Test	H₁	Reduced model (pubertal stage) and OCD-status	2.113	0.1477	BF₁₀₌0.52
2. Test	H₀	Reduced model (pubertal stage)
Note: BF, Bayes factor; H₁, alternative hypothesis; H₀, null hypothesis; ELPD-LOO, expected log-pointwise predictive density estimated by leave-one-out cross validation; SE, standard error

In Model 3, the pubertal stage-sex interaction, sex, and OCD-status were removed in the first three steps as they did not significantly contribute to the variation in child and adolescent oxytocin (see Appendix E). The reduced model showed a significant relationship (Fig. 3) between child and adolescent oxytocin and pubertal stage (p = 0.0004, Table 4 and see Appendix E). Bayesian analysis showed a better predictive performance of a model including pubertal stage, but with a large standard error (ELPD-LOO=-6.5, SE 4.1, Table 4). When controlling for pubertal stage, OCD-status did still not significantly account for variation in oxytocin (p = 0.1477, Table 4 and Appendix E). The corresponding Bayes factor showed anecdotal support for no difference in oxytocin concentrations between children and adolescents with and without OCD controlling for pubertal stage (BF₁₀ = 0.52, Table 4) with considerable prior sensitivity (see Appendix C).

In Model 4, including children and adolescents, and parents, the age-sex interaction and sex did not significantly contribute to the variation in oxytocin and were removed from the model in the first two steps (see Appendix E). The reduced model showed a significant positive, linear relationship [Figure 4 (blue line)] between participant age and oxytocin (p < 0.0003, see Appendix E).

The reduced exploratory Post Hoc Model A showed a significant relationship between oxytocin and quadratic age [Figure 2 and Fig. 4 (purple line); p = 0.0496, see Appendix E].

Post Hoc test B showed that the predictive performance of the model including pubertal stage and OCD (reduced Model 3 with OCD) was slightly better than the model with quadratic age and OCD (reduced Post Hoc Model A and OCD) (ELPD-LOO = 2.9, SE 3.0, see Appendix C). However, the standard error of the difference in predictive performance was large.

Visual inspection of Fig. 4, illustrating the reduced Model 2 (child and adolescent age, pink line), the reduced Post Hoc Model A (child and adolescent quadratic age, purple line), and the reduced Model 4 (child, adolescent, and parent age, blue line), indicates that the models in children and adolescents cannot be extrapolated to adults and the model in all participants seemed problematic in estimating in children and adolescents.

In Post Hoc Model C, we used “pubertal stage 6” for the adults and found a significant relationship (Figure E.1 in Appendix E) between salivary oxytocin and the modified pubertal stage in the sample including children, adolescents, and adults (p = 0.005, see Appendix E). The Bayesian analysis showed a better predictive performance of the model with the modified pubertal stage compared to the model with age (ELPD-LOO = 5.9, SE 5.1, see Appendix C).

In Post Hoc Model D, including only adults, the age-sex interaction, sex, and age did not contribute to the variation in oxytocin (p = 0.10, see Appendix E).

Sensitivity analyses of the Bayesian analyses of the models showed a general sensitivity to priors and little difference in predictive performance between the compared models with high standard errors (Appendix C).

The random forest analysis in children and adolescents alone and in children, adolescents, and adults indicated that pubertal stage/modified pubertal stage and age were the most important variables. Furthermore, these findings both in visual presentation of the predictions and the mean squared error (MSE) resembled the findings from the linear models (see Appendix D).

In the additional analyses in our appendix, we found that adult females had significantly higher oxytocin concentrations during menstruation than during ovulation (see Appendix F). The remaining analyses were not statistically significant.

We evaluated the hypothesis that salivary oxytocin is elevated in a young population with OCD. We included a relatively large sample of children with and without OCD while controlling for potential variance in oxytocin concentrations related to age, pubertal stage, and sex. Overall, we found no support for the hypothesis of elevated oxytocin concentrations in OCD. Our results contrast with those of Marazitti et al. who found higher oxytocin concentrations in adults with OCD⁵. The contrasting findings could be explained by the use of different physiological fluids (saliva versus plasma). Our findings are consistent with findings in adults with OCD by Leckman and colleagues³ and Altemus and colleagues⁴. Our complementary Bayesian analyses showed only anecdotal to moderate support for the null hypothesis, even with a larger sample size than the previous studies. Notably, a meta-analysis pooling the two aforementioned studies in adults also found no significant difference²¹. While it may be that oxytocin concentrations do not differ between children and adolescents with and without OCD, the null findings could also be due to sample sizes too small to detect a discrete group difference. Another consideration of the null findings is the heterogeneous nature of OCD with multiple different phenomenological manifestations²² which perhaps makes assuming overall group differences in biological markers too simplistic. A focus on trans-diagnostic mechanisms have been suggested as important in OCD research²² which could also be relevant in the research of oxytocin and OCD. Oxytocin has been implicated in regulation of anxiety and interpersonal behaviors²³. One research group investigated a theory of oxytocin as a biochemical signal of safety with anxiolytic effects and associated with behaviors, such as family accommodation, that are common in both anxiety and OCD²⁴. They investigated 50 children with clinical anxiety and found negative associations between salivary oxytocin, anxiety levels, and subscales of family accommodation²⁴. Family accommodation is frequent in children with OCD²⁵ and associated with a poor treatment outcome²⁶, and a focus on oxytocin’s relation to family behaviors, like family accommodation, or other family factors rather than the overall OCD diagnosis could help understand poor treatment outcomes.

Our findings indicate that oxytocin increases with age from 8 to 17 years. This finding is consistent with findings from a study of children and adolescents (7–16 years) with clinical anxiety²⁴. Another study in children (5–90 months of age) concluded that oxytocin decreases from 5 months to 90 months²⁷. However, the scatter plot visualizing this data suggests an elbow shaped curve may fit this data better than a straight line²⁷. Several of our analyses (scatter plot, quadratic age, and pubertal stage) support a nonlinear relationship with oxytocin concentrations slightly increasing from 8 to 15 years, and from pubertal stage 1 to 4, followed by a slight decrease. The exploration of the relationship between age and oxytocin in our parent sample (age range ≈ 33–73 years) indicates that oxytocin increases sometime after puberty. The importance of pubertal stage could support that hormonal or behavioral changes during puberty cause important variation in oxytocin activity¹⁰. Our exploration with random forest analyses resembled the results from the models using quadratic age and pubertal stage suggesting that these models capture the main signal in this age range.

Our results did not indicate that sex accounts for variation in oxytocin levels in children and adolescents or adults. Previous findings on sex differences in oxytocin in adults are mixed^28–31. The contrasting results could be due to studies investigating different ages and sex differences may only occur in some age ranges.

This study has strengths and limitations, which should be considered when interpreting our results. Our sample is relatively large compared to prior research in the field and used frequentist and Bayesian statistics providing additional information regarding relative evidence for a null hypothesis. Whether salivary and other peripheral measures of oxytocin reflect central oxytocin concentrations under basal conditions is unclear^7,32,33. Thus, inferences about central oxytocin activity based on peripheral measures might not be reliable. However, saliva sampling is a noninvasive and feasible method in youth. We included a clinically representative group of children and adolescents with OCD with multiple comorbidities, however comorbidity can cause variability in oxytocin²¹. We used a cross-sectional design which is a limitation when making inferences about oxytocin changes across development where a longitudinal approach would be more correct. We used no correction for multiple testing, thus statistical significance should be interpreted carefully. With the goal of transparency, we pre-registered our analysis plan. Pubertal stage was assessed without clinical examination, which decreases its accuracy³⁴. Yet, pubertal stage has not been examined in relation to oxytocin.

Salivary oxytocin concentrations appear not to be related to OCD in children and adolescents. Future studies in oxytocin and OCD could focus on more specific components of OCD like family factors or family behaviors. Oxytocin concentration fluctuations across development suggest that hormonal or behavioral changes during puberty may influence oxytocin system activity. Future studies across a wider age range and using nonlinear models may increase the understanding of oxytocin concentrations across the lifespan.

Code availability statement

Analysis scripts from R are available on request to the authors.

Biological material availability

The saliva samples have been dispersed after the final analysis to follow our protocol and the biological material is therefore no longer available.

Conflict of interest

One of the co-authors on this study, Dr. Daniel Quintana, is on the Editorial Board of Communications Psychology. The authors declare no other competing interests.

Competing Interests

One of the co-authors on this study, Dr. Daniel S. Quintana, is on the Editorial Board of Nature Communications Psychology. The authors declare no other competing interests.

Funding

acquisition: ACM, LP, KJP, AKP, NNL

Author Contribution

Conceptualization: ACM, LC, EL, LP, KJP, AKP, NNLMethodology: ACM, LC, MG, EL, DQ, NRJ, CSL, LB, GC, NNLValidation: ELFormal analysis: ACM, MGInvestigation: ACM, CSL, LP, VU, SC, CU, NK, CT, JH, MR, KJP, AKP, NNLResources: LC, NRJ, AKP, NNLWriting - Original Draft: ACM, MGWriting - Review & Editing: LC, MG, EL, DQ, NRJ, CSL, LB, GC, LP, VU, SC, CU, NK, CT, JH, MR, KJP, AKP, NNLVisualization: ACM, MGSupervision: LC, AKP, NNLProject administration: SC, NNLFunding acquisition: ACM, LP, KJP, AKP, NNL

Acknowledgement

We would like to acknowledge the employees in TECTO who helped with data collection for the project: Tin Aaen Gudmandsen, Iben Thiemer Clemmesen, Emilie Damløv Thorsen and Klara Sofie Vangstrup Halberg. We would also like to acknowledge the Department of Clinical Biochemistry, Rigshospitalet, Glostrup, for analyzing the oxytocin samples. We are also grateful to the families who participated in this study.

Data Availability

After publication of all results from the TECTO trial, we plan to make a depersonalized data set publicly available on the EU ZENODO database.

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Competing interest reported. One of the co-authors on this study, Dr. Daniel S. Quintana, is on the Editorial Board of Nature Communications Psychology. The authors declare no other competing interests.

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Salivary oxytocin concentrations in children and adolescents with and without OCD

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