Behavior Genetics

Studies of resemblance for disorders and other traits measured at the binary (yes/no) level between relatives frequently contain individuals who are currently in the negative category but who will become positive in future. For example, a 10-year-old may develop depression in the future, but is as yet unaffected. Such censoring can substantially bias estimates of correlation between relatives. To overcome this problem we develop a model for the association between liability to a disorder, and its age at onset. The model is designed for data from pairs of relatives to enable estimation of the correlation between an individuals' liability to disorder and their age at onset. Usually, such information is not available at the individual level, because age at onset is uniquely available when onset has occurred. Lacking variation in disorder status, data from non-related persons cannot estimate the covariance between liability and age at onset. Data from relatives can resolve this issue when there is a correlation in liability between the relatives, because different age at onset distributions would be expected in concordant vs. discordant pairs of relatives. Greater severity and worse outcomes are often observed among those with earlier onset, so a correlation between disorder liability and age at onset seems likely in many cases. In this article we present the basic theory of the model, implemented as a mixture distribution, and an application to cannabis use in a Virginia Twin Study of Adolescent Behavioral Development. A negative association of (-.212) between age at onset an liability was found, with confidence intervals of -.263 to -.152, which do not cross zero. The method contrasts with Cox Proportional Hazards, in which disorder liability and onset timing are treated as a single dimension.

Studying the genomic control of dyadic social interactions is gaining traction in animal genetics. However, genetic modeling of social interactions poses several challenges, one of which is whether social interactions should be treated as dyadic traits or as aggregated traits at the individual level. In this study, we systematically compared two approaches: dyadic models using dyadic traits and marginal models using marginally aggregated traits and we derived the algebraic relationships between their variance components. In the application, we used a published dataset on post-mixing aggression in pigs, including both directed and undirected aggression records collected during the 9-hour period after mixing among 797 finishing pigs in 59 social groups, as an example to show how model choice can affect variance estimation. Results showed that dyadic models can estimate genetic effects and permanent environmental effects by exploiting repeated dyadic interaction records, thereby enabling a more complete understanding of the sources of variation underlying social interactions. In contrast, marginal models can bias the estimation and interpretation of genetic components, as the aggregated genetic variance may be confounded with other variance components due to the aggregation of dyadic traits. Marginal models may also lead to overestimation of social group and residual variance. These results can provide useful guidance for choosing appropriate modeling strategies for social interaction traits.

Cocaine Use Disorder (CUD) poses a significant public health and socioeconomic challenge. Determining the genetic basis of predisposition for development of CUD is challenging in human populations but can be studied in Drosophila. We assessed cocaine consumption and cocaine preference of 74,875 flies from 598 sequenced, wild-derived, inbred lines from the expanded Drosophila melanogaster Genetic Reference Panel (DGRP3). We found significant genetic variation, sexual dimorphism, and genetic variation in sexual dimorphism for these traits. Whereas most lines showed cocaine avoidance, ~10% of the lines showed innate cocaine preference in at least one sex. Genome-wide association analyses for cocaine consumption, preference, and micro-environmental variance of these traits identified 2,155 polymorphisms in/near 866 genes that were enriched for Gene Ontology terms associated with neurogenesis, development, and behavior. Many of the associated genes had human orthologs with known associations with CUD and other substance use disorders as well as psychiatric and behavioral traits. We confirmed causal associations with cocaine preference for three polymorphisms with large effect sizes by assessing their effects in DGRP3 lines not included in the initial association analyses. Pairwise associations between these polymorphisms exhibited suppressing epistasis. These polymorphisms are in genes with human orthologs that fulfill essential functions in the nervous system, including the glucose transporter SLC2A8; KCNC2, a subunit of the voltage gated potassium channel; and CHRNA7, a nicotinic cholinergic receptor subunit. Thus, studies on Drosophila can provide insights into the genetic and neural mechanisms of CUD.

Background: Attention-deficit/hyperactivity disorder (ADHD) is associated with perinatal and genetic risk factors, including prenatal maternal smoking, pre-pregnancy BMI, gestational age, birth weight, and common genetic variants. These risk factors, as well as ADHD symptoms themselves, have previously been linked to cord blood DNA methylation (DNAm). We tested the hypothesis that cord blood DNAm mediates the effects of these risk factors on ADHD symptoms. Methods: Participants were drawn from two large European population-based cohorts: the Generation R Study and Avon Longitudinal Study of Parents and Children (n=3087). Cord blood DNAm was assessed using Illumina 450k and EPIC v1 arrays. ADHD symptoms were repeatedly measured with parent-based questionnaires between the ages 6 and 10 years. A high-dimensional mediational model based on DNAm principal components mediation analysis (PCMA) estimated the global mediation effect of all tested DNAm sites. Mediation via single principal components and individual DNAm sites was also evaluated using structural equation modeling and Divide-Aggregate Composite-null Test (DACT). Results: DNAm globally mediated the relationships of maternal smoking, low birth weight, and an ADHD polygenic score (PGS) with ADHD symptoms. Specifically, DNAm explained 62% of the total effect for maternal smoking, 56% for birth weight, and 35% for the ADHD-PGS. No association with individual principal components or single DNAm sites survived multiple testing correction. Evidence for mediation was absent for pre-pregnancy BMI and inconsistent for gestational age. Conclusions: In this first epigenome-wide mediation study of ADHD, we demonstrate a role of DNAm at birth in mediating the association of maternal smoking, birth weight and ADHD-related genetic variants with ADHD symptoms. However, lack of individual site-specific findings and the observational design limit causal biological interpretations. We therefore encourage further research of epigenetic pathways for these three risk factors.

Family environments may contribute to childrens long-term health through biological processes, including epigenetic regulation such as DNA methylation (DNAm). However, most studies in this area focus on Euro-American populations while also rarely including fathering data. The current study investigated childrens blood DNAm associations with positive (father caregiving) and negative (parental conflict) family dynamics in a smaller-scale subsistence society living in the Congo Basin rainforest. We measured DNAm from dried blood spots of 54 children (mean age=8.48 years) and conducted three epigenome-wide association studies aimed at discovering differential co-methylated regions (CMRs) associated with family dynamics. Via path models, we investigated the health implications and shared contribution of family factors of the identified CMRs. Differential DNAm associated with family dynamics was localized to genes related to stress, immunology, development, and aging, thus possibly linking to childrens physical health and were simultaneously connected to other family factors such as number of siblings. Our findings suggested similarities in biological embedding of family factors across socio-ecologically diverse contexts.

Early life adversity (ELA) causes lasting psychological and behavioral consequences in humans, with parallel stress and fear responses observed in captive animals. How naturally occurring ELA shapes behavior in non-captive animals remains poorly understood. Investigating these effects across socioecological environments is important for identifying the evolutionary pressures shaping early life sensitivities, and determining whether these behavioral syndromes have deep evolutionary roots. Here, we tested the effects of eight forms of ELA on adult behavior using a large dataset (N=313 males, 346 females) from a free-ranging population of rhesus macaques (Macaca mulatta). We measured adult behaviors indicative of stress and the tenor of social interactions, including agonism, vigilance, self-directed behaviors, and affiliation. Individuals exposed to more ELA received more aggression and less grooming, were more submissive, and were less vigilant. While high status buffered the effects of ELA on grooming, it amplified effects on aggression. Our findings demonstrate that in a large sample of a free-ranging primate, early life environments impact behavior into adulthood. While some behaviors are consistent with patterns in humans and captive animals, suggesting an evolutionarily conserved ELA syndrome, other findings add new insights into the various ways individuals interact with their environment as a function of ELA.

Addiction is a complex and heritable trait which progresses through several developmental stages, each of which is presumably influenced by multiple partially overlapping genetic factors. Cocaine initially produces rewarding effects, followed by aversive effects including anxiety, craving, anhedonia, and withdrawal. These aversive effects have been suggested to contribute to the etiology of cocaine use disorders (CUD), as repeated exposure is thought to desensitize the rewarding effects and sensitize the aversive effects through a process involving both aberrant reward-based learning and aberrant avoidance-based learning. We examined the genetic basis of aversion learning using both food-based and cocaine-based behavioral assays in outbred Heterogenous Stock (HS) rats. A total of 1,074 HS rats (35.3% male) underwent runway operant cocaine-seeking, food-based progressive ratio and punishment testing, and locomotion testing. These phenotypes were significantly heritable (with h2 estimates as high as 0.307) and identified significant (p < 0.05) genetic loci related to avoidance-based learning including from the punishment task on Chromosomes 2, 3, 5, and 6, and the cocaine-operant runway latency task on Chromosome X. 172 positional candidate genes were identified from significant and suggestive loci, including Cdh10, Cdh12, Cdh18 which have previously been associated with smoking initiation from human GWAS, Adcy3, Cfap206, and Drc1 which are associated with primary neuronal cilia, as well as SNPs associated with novelty-related and social interaction phenotypes in independent samples of HS rats. Our results suggest that these aversion learning phenotypes are themselves complex heritable traits influenced by multiple genetic loci, which may pleiotropically affect other aspects of addiction biology.

Motivation: Linkage disequilibrium score (LDSC) regression is a popular method to estimate heritability for complex traits using summary statistics and linkage disequilibrium (LD) reference panels, offering a practical alternative to methods requiring individual-level data. Despite its widespread use, LDSC regression can produce biased heritability estimates. The properties of LDSC regression were investigated using summary statistics from several large-scale Alzheimer's disease (AD) studies and a variety of LD reference panels. These heritability estimates were compared with those obtained from individual-level data. Results: When LDSC regression was applied to summary statistics obtained from meta-analysis, it led to an underestimation of heritability. This can occur if meta-analysis is used to combine studies of different ancestries leading to the caveat of the lack of an appropriate LD reference panel. Additionally meta-analyses often include studies with different phenotype definitions, that not only impacts heritability estimates but also makes them uninterpretable. Summary statistics generated from imputed variants, even those with high imputation accuracy, can lead to underestimation of heritability. For example, the heritability estimates for AD were reduced from 0.265 (se 0.148) to 0.160 (se 0.041) when imputed variants (INFO>0.9) were included compared to analyzing only genotype array variants. A decrease in heritability estimates was also observed when individual-level imputed variant data were analyzed using GCTA-GREML. Our findings highlight the caveats of estimating heritability using meta-analysis summary statistics or imputed data instead of genotyped or sequence data.

Population stratification is a major source of inflated false positive rates in genome wide association studies. However, relatively few studies have examined its impact on gene-gene interaction detection, despite the importance of epistasis for understanding the genetic architecture of complex traits. In this study, we identify scenarios under which population stratification can inflate the interaction test statistics. Through analytical derivations and simulation studies, we show that this inflation is not adequately controlled by including principal components as covariates in the regression model. We then propose an alternative approach that effectively controls the inflation of false-positive rates for interaction test statistics due to population stratification by using single nucleotide polymorphism-by-population structure interaction as an additional covariate term in the regression model.

Anthropogenic copper (Cu) contamination from agriculture, mining, and industrial runoff creates environmental gradients affecting physiology and behavior in wild populations. While Cu toxicity in Drosophila melanogaster is well characterized, it remains unclear whether Cu resistance is one integrated trait or several independently evolving components. Using a subset of recombinant inbred lines (RILs) from the Drosophila Synthetic Population Resource (DSPR), we measured three components of Cu response: feeding avoidance, oviposition avoidance, and physiological tolerance (median lethal time, LT50) under sustained Cu exposure. All three traits showed substantial phenotypic variation among RILs. Feeding and oviposition avoidance were both highly heritable (H 2 ~ 0.88), and RIL identity accounted for 49.5% of the variance in LT50. However, the three traits showed no significant correlation across RILs, indicating distinct genetic architecture. We identified a single male specific quantitative trait locus (QTL) on chromosome 2R that explained 17.7% of the variation in feeding preference; the interval included candidate detoxification genes Jheh1, Jheh2, Jheh3 and sano, the latter of which is associated with olfactory behavior. No significant QTL were detected for oviposition preference, suggesting a highly polygenic structure that may difficult to detect with our limited panel size. Together, these results indicate that Cu resistance in D. melanogaster is genetically modular. Behavioral avoidance during feeding, oviposition, and physiological tolerance are heritable but architecturally distinct components, each with potential to respond to selection independently.

The present study examined the relationship between the DSM-5 diagnostic criteria for gambling disorder (GD) and gambling severity via an item response theory (IRT) analysis in two large German population survey data sets (Buth et al. (2022, 2024)). IRT-based person fit analyses may reveal atypical response patterns (e.g. endorsing criteria linked to higher levels of disorder severity, but not criteria linked to lower levels). We examined the link of such atypical response patterns and mental health as measured by the MHI-5, employing a 2-parameter-logistic (2PL) IRT model and a linear mixed model with random intercepts. Results largely replicated previously reported item severity rankings across both samples: GD criteria such as loss chasing and a preoccupation with gambling were generally linked to lower severity levels, whereas criteria such as withdrawal symptoms or job/family problems where generally linked to higher severity levels. Modelling revealed a reduced assessment sensitivity in lower gambling severity ranges. Furthermore, person fit analyses suggest that atypical symptom patterns may be linked to poorer mental health (MHI-5). Implications for the interpretability of total scores of endorsed criteria and the validity of diagnostic practices determining eligibility for treatment and financial compensation are discussed.

In studies of assortative mating, similarity between variables measured in parents is often quantified using correlation. The order of the parents within any given pair can be arbitrary in these applications, but common correlation estimators are not robust to reordering within pairs. These unordered variable pairs are exchangeable, since the joint distributions of both orders are equal, and a given order is biased if the one variable has a lower expectation than the other. In this work, we characterize the effect of order bias on Pearson correlation estimates assuming exchangeable variables, and develop a new unbiased estimator, CorSym, that does not depend on order within each pair. Exchangeable variables have equal marginal distributions for both variables, a property accounted for by CorSym. In contrast, standard correlation estimators assume the two variables have different distributions, so biased orders skew the underlying mean, variance and covariance estimates. We show, through theory and simulations, how order bias often results in upwardly biased Pearson correlation estimates. Simulations confirm CorSym is unbiased, and validate its estimated confidence intervals. Using real admixed trios (parents and a child) from 1000 Genomes, we first demonstrate that the global ancestry of fathers and mothers are consistent with exchangeability, using both Kolmogorov-Smirnov tests and a Binomial test for order bias. However, ANCESTOR, which estimates parental global ancestry from a child's local ancestry, produces significant order biases in its output that result in substantial Pearson biases, which CorSym overcomes. Compared to ancestry proportions calculated directly on the parents, ANCESTOR also overestimates parent ancestry divergence and experiences another estimation artifact. Overall, CorSym solves an important estimation bias likely to be encountered in the study of assortative mating, providing unbiased and deterministic estimates that do not depend on the arbitrary order of the data.

Background/Objectives: Childhood appetitive traits are heritable behavioural phenotypes hypothesized to link genetic susceptibility to obesity risk. Yet their genetic architecture and role in mediating polygenic adiposity risk remain poorly understood. Methods: We conducted the largest survey of childhood eating behaviour to date, allowing us to perform genome-wide association studies of six appetitive domains derived from 18 items of the parent-reported Children's Eating Behaviour Questionnaire in up to 31,018 eight-year-old children from the Norwegian Mother, Father and Child Cohort Study (MoBa). A trio-based design enabled decomposition of direct and indirect genetic effects on appetite and BMI. Results: We identified ten independent genome-wide significant loci for childhood eating behaviour, primarily across Food Responsiveness, Satiety Responsiveness, and Food Fussiness, eight of which lie at established childhood or adult BMI loci. Food Responsiveness and Satiety Responsiveness showed both phenotypic and genetic correlations with BMI trajectories from early childhood through adolescence. Statistical mediation analyses indicated that 22.1% and 10.4% of the aggregated genetic association with BMI at age 8 could be decomposed through these traits, respectively. Locus-specific patterns further suggested mechanistic pathways, with the FTO locus acting predominantly via Food Responsiveness, and the ADCY3 locus via Satiety Responsiveness. Trio analyses demonstrated that both BMI and eating behaviour associations were predominantly explained by children's inherited alleles, with minimal contribution from indirect effect from parental adiposity, although parental genetic liability influenced reporting of Satiety Responsiveness. Conclusions: Childhood appetitive traits capture a substantial proportion of genetic susceptibility to adiposity through distinct eating behaviour pathways (under standard mediation assumptions). These effects are primarily driven by the child's own genotype rather than indirect parental influences, positioning appetite as a plausible, biologically grounded target for early obesity prevention.

Environmental and dietary factors can exert multigenerational effects on health and development. In this study, we investigated whether early-life metabolic challenge affects the germline genome and epigenome across three generations. Using a murine model of early life obesity via litter size reduction (overnutrition group, ON) and a control group (CT), we followed the paternal lineage focusing on germline genomic and methylation changes employing Genotyping-by-Sequencing (GBS) coupled with methyl-immunoprecipitation (GBS-MeDIP). We found that unrelated ON families clustered together based on identified Single-Nucleotide Polymorphism (SNP), suggesting that the treatment may have genomic impact. Copy number variations (CNVs) events were identified in ON individuals, being enriched in Long Interspersed Nuclear Elements (LINEs) and Long Terminal Repeats (LTRs). While Principal Component Analysis (PCA) of the methylome showed no clear treatment effect, pathway enrichment and regional analyses revealed methylation changes associated with transposable elements and developmental genes. Notably, the ON group exhibited a disruption in the methylation of Repetitive Elements (RE), which was significant in the same type of RE that were also enriched in the observed CNVs. The ON also showed reduced emergence of novel SNPs in offspring compared to the CT group. These findings suggest that multigenerational metabolic challenge can constrain genetic variability and induce genome instability, potentially mediated by transposable element activity rather than widespread changes in DNA methylation. This work highlights the importance of studying both genome and epigenome dynamics under realistic, multigenerational exposure scenarios and suggests that early metabolic challenges can have long-lasting impacts on genomic architecture and evolutionary potential.

Transdiagnostic psychiatric research on reward-guided learning has largely focused on simple associative processes, leaving it unclear whether or how higher-level processes are disrupted. Here, we studied how abstraction, the ability to extract relevant features from complex information, and metacognition, the ability to monitor and evaluate one's own mental processes, map onto specific transdiagnostic dimensions. Using an online sample (N = 249), we examined associations between these processes and three cross-culturally robust transdiagnostic dimensions derived from a large existing dataset (N = 19,505): Compulsive hypersensitivity, Social withdrawal, and Addictive behaviours. Computational modelling of an abstract representation learning task with confidence judgments revealed that Compulsive hypersensitivity was negatively associated with both abstraction ability (pboot = 0.003) and metacognitive sensitivity (pboot = 0.005), while Social withdrawal was positively associated with metacognitive sensitivity alone (pboot = 0.002). Moreover, transdiagnostic dimensions revealed more coherent associations with higher-order cognition than symptom-level analyses, highlighting the added value of examining psychopathology at the factor rather than the symptom level. These findings portray a hierarchical view of cognitive dysfunctions in psychopathology and point to representational and metacognitive processes as potential targets for transdiagnostic intervention.

Importance: Avoidant/restrictive food intake disorder (ARFID) is a feeding and eating disorder characterized by extremely restricted dietary variety and/or quantity resulting in significant physical health impairment and psychosocial dysfunction. ARFID frequently co-occurs with neurodevelopmental conditions, yet the extent to which this co-occurrence reflects shared genetic or environmental influences remains largely unknown, as few twin or genetic studies of ARFID have been conducted. Objective: To examine the extent to which genetic and environmental influences contribute to the association between a broad ARFID phenotype and neurodevelopmental traits. Design, Setting, and Participants: Population-based twin study using data from the Child and Adolescent Twin Study in Sweden, including 30,374 twins born 1992-2008. Main Outcomes and Measures: A broad ARFID phenotype was identified using a composite measure derived from parent reports and national health registers between ages 6 and 12 years. Parents completed measures of neurodevelopmental traits at age 9 or 12 years, including autism (subdomains: social communication problems and restricted/repetitive behaviors), attention-deficit/hyperactivity disorder (ADHD, subdomains: inattention and impulsivity/hyperactivity), tic disorders, learning disorders, oppositional defiant disorder, conduct disorder, obsessive-compulsive disorder (OCD), sensory perception problems, and sleep problems. Phenotypic associations were estimated using polyserial correlations. Bivariate twin models decomposed variance and covariance into genetic and environmental components. Results: Phenotypic correlations with the broad ARFID phenotype ranged from 0.18 (95% CI: 0.15-0.21) for OCD to 0.36 (95% CI: 0.33-0.38) for autism. Broad genetic correlations (rH; additive plus dominant genetic influences) ranged from 0.27 (95% CI: 0.21-0.33) for conduct disorder to 0.52 (95% CI: 0.44-0.60) for autism-restricted/repetitive behaviors. Genetic factors explained 77% to 95% of all phenotypic correlations. Non-shared environmental correlations were minimal to small, with the largest observed for autism (0.17; 95% CI: 0.08-0.26). Conclusions and Relevance: The broad ARFID phenotype shares substantial genetic influences with a number of neurodevelopmental traits. These findings suggest that the frequent co-occurrence of ARFID with neurodevelopmental traits largely reflects shared genetic influences rather than overlapping environmental influences, supporting the conceptualization of ARFID within a broader neurodevelopmental framework.

In many insect species, mating is coordinated through multimodal signaling, yet less obvious channels are often overlooked. In the burying beetle Nicrophorus vespilloides, chemical communication is well-documented, but the role of substrate-borne vibrational signals (stridulations) during courtship remains unknown. We investigated whether stridulation is essential for mating success through two sets of experiments. First, we found a positive correlation between the frequency of stridulations and both the number and duration of copulation events. Second, we employed a silencing experiment to test the necessity of these signals by silencing males, females, or both partners. We found no significant differences between silenced and control groups regarding the frequency or duration of physical contact and mounting events, suggesting that stridulation is not required for mate recognition or the initiation of courtship. However, the proportion of successful copulations relative to mounting events was significantly lower when females were silenced. These results suggest that while N. vespilloides relies on a redundant multimodal system that likely utilizes chemical cues to initiate mating, vibrational signals, particularly from the female, may play a critical role in facilitating successful copulation. This study provides the first evidence for the role of stridulation in the mating behavior of N. vespilloides and highlights the potential for female-mediated vibrational signaling in burying beetle courtship.

Adolescent use of alcohol, nicotine, and marijuana remains a major public health concern in the United States. Early identification of youth at elevated risk is critical for prevention before use begins or escalates. We developed and evaluated a longitudinal machine learning framework to predict alcohol, nicotine, and marijuana use at the next observed assessment wave. Data came from the Adolescent Brain Cognitive Development (ABCD) Study Release 6.0. The models incorporated predictors from multiple domains, including demographics, friends, family and community context, mental health, physical health, and prior substance-related behaviors. To reduce information leakage across individuals, we implemented a leakage-aware stacked ensemble. This ensemble combined diverse base learners through out-of-fold predictions and an elastic-net meta-learner. Across all three substances, the lagged stacked ensemble outperformed the cross-sectional stack and all single base learners. Adolescents identified as highest risk showed substantially higher observed rates of substance use than would be expected under random screening. Feature-importance analyses showed that the full longitudinal models were strongly influenced by developmental timing and prior-use history. Analyses restricted to current-wave features revealed distinct substance-specific risk patterns beyond prior-use history and developmental timing. Bootstrap stability analyses identified top-ranked features showing consistent positive predictive relevance across resampled adolescents. These findings suggest that longitudinal, leakage-aware machine learning can generate substance-specific risk estimates to support targeted prevention and screening in adolescent populations.

Animals fight for resources to obtain fitness benefits; most contests are intrasexual, and males tend to fight more than females. Although the genetic basis of male aggression is well studied, we know little about the genetic variation of female aggression. Female aggression varies with reproductive status and is potentially influenced not only by her genotype, but also by the genotype of her mate. Here we measured both male and female aggression in a set of Drosophila melanogaster inbred lines by competing each line against a standard competitor. Aggression varied among lines for both sexes, but male and female aggression were not correlated. Female aggression for many lines increased with mating, as expected, but not all lines changed aggression. However, when females were mated to males of different lines, male genotype did not affect the post-mating change in aggression, suggesting that ejaculate-mediated effects do not vary across these lines. The aggression level of the standard opponent was positively correlated with that of focal individuals indicating that individuals modulate their behavior according to the genotype of their opponent.

The social anxiety disorder (SAD) is one of the most common mental health disorders, often developing in adolescence. It can severely impair educational achievement, career progression, and social functioning. Certain individuals within the Chinese Kunming dog (CKD) population display spontaneous, SAD-like behaviors towards strangers, offering a valuable model for genetic investigation. Using whole-genome sequencing data, we conducted a genome-wide association study on this SAD-like behavior in 100 CKDs, identifying several genes previously linked to human psychiatric disorders. Notably, SLC6A3 reached genome-wide significance, whereas CADPS2 exceeded only the suggestive threshold and is therefore considered a network-supported candidate locus. By integrating weighted gene co-expression network analysis with public RNA-seq data from the VTA of 38 mice (after quality control), we further showed that Slc6a3 and Cadps2 are part of a co-expression network module associated with the dopamine system. These findings suggest that this specific module may play a functional role in the stranger-directed anxiety-related behaviours in CKDs. Furthermore, we identified Nrip3 as a key candidate transcriptional coregulator in this specific module. Subsequent virus-mediated overexpression and behavioural experiments showed that Nrip3 regulates gene expression within this network and induces a spectrum of behavioural alterations in mice, including social avoidance, anhedonia, and increased locomotor activity. Collectively, this study highlights the involvement of dopamine system genes in canine social anxiety and suggests Nrip3 as an upstream regulator of Slc6a3 associated with anxiety. The identification of conserved anxiety-related signatures between humans and dogs further supports the dog as a valuable translational model for psychiatric research.