Genes Brain and Behavior最新文献

{"title":"Paleogenomic insights into cooperation in the ancient Andes from positive selection on oxytocin pathway genes","authors":"Sophie K. Joseph,&nbsp;Elizabeth Wagman,&nbsp;Nabeel Diab,&nbsp;Nicholas Ryu,&nbsp;Minwoo Lee,&nbsp;Randall Haas,&nbsp;James K. Rilling,&nbsp;Mark S. Aldenderfer,&nbsp;John Lindo","doi":"10.1111/gbb.12877","DOIUrl":"10.1111/gbb.12877","url":null,"abstract":"<p>Human societies are characterized by norms that restrict selfish behavior and promote cooperation. The oxytocin system is an important modulator of social behavior that may be involved in the evolution of cooperation. Oxytocin acts in both the nucleus accumbens and the anterior cingulate cortex to promote social bonding and social cohesion. Expression of the <i>CD38</i> and <i>OXTR</i> genes is known to affect oxytocin secretion and binding, respectively, in these brain areas. The Andean highlands provide an excellent opportunity to evaluate the role of oxytocin in the evolution of cooperation. The rich archeological record spans 13,000 years of population growth and cooperative challenges through periods of highland exploration, hunting economies, agro-pastoralism, and urbanization. Through allele trajectory modeling using both ancient and contemporary whole genomes, we find evidence for strong positive selection on the <i>OXTR</i> and <i>CD38</i> alleles linked with increased oxytocin signaling. These selection events commenced around 2.5 and 1.25 thousand years ago, placing them in the region's Upper Formative and Tiwanaku periods—a time of population growth, urbanization, and relatively low rates of violence. Along with remarkable and enduring cultural developments, increased oxytocin secretion and receptor binding in these brain areas may have facilitated large-scale cooperation that promoted early urbanization in the Titicaca Basin of the Andean highlands.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12877","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139688989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large analysis of genetic manipulations reveals an inverse correlation between initial alcohol resistance and rapid tolerance phenotypes","authors":"Maggie M. Chvilicek,&nbsp;Alexandra Seguin,&nbsp;Daniel R. Lathen,&nbsp;Iris Titos,&nbsp;Pearl N. Cummins-Beebee,&nbsp;Miguel A. Pabon,&nbsp;Maša Miščević,&nbsp;Emily Nickel,&nbsp;Collin B. Merrill,&nbsp;Aylin R. Rodan,&nbsp;Adrian Rothenfluh","doi":"10.1111/gbb.12884","DOIUrl":"https://doi.org/10.1111/gbb.12884","url":null,"abstract":"<p>Tolerance occurs when, following an initial experience with a substance, more of the substance is required subsequently to induce identical behavioral effects. Tolerance is not well-understood, and numerous researchers have turned to model organisms, particularly <i>Drosophila melanogaster</i>, to unravel its mechanisms. Flies have high translational relevance for human alcohol responses, and there is substantial overlap in disease-causing genes between flies and humans, including those associated with Alcohol Use Disorder. Numerous <i>Drosophila</i> tolerance mutants have been described; however, approaches used to identify and characterize these mutants have varied across time and labs and have mostly disregarded any impact of initial resistance/sensitivity to ethanol on subsequent tolerance development. Here, we analyzed our own, as well as data published by other labs to uncover an inverse correlation between initial ethanol resistance and tolerance phenotypes. This inverse correlation suggests that initial resistance phenotypes can explain many ‘perceived’ tolerance phenotypes, thus classifying such mutants as ‘secondary’ tolerance mutants. Additionally, we show that tolerance should be measured as a relative increase in time to sedation between an initial and second exposure rather than an absolute change in time to sedation. Finally, based on our analysis, we provide a method for using a linear regression equation to assess the residuals of potential tolerance mutants. These residuals provide predictive insight into the likelihood of a mutant being a ‘primary’ tolerance mutant, where a tolerance phenotype is not solely a consequence of initial resistance, and we offer a framework for understanding the relationship between initial resistance and tolerance.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12884","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139655215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Principal and independent genomic components of brain structure and function","authors":"Lennart M. Oblong,&nbsp;Sourena Soheili-Nezhad,&nbsp;Nicolò Trevisan,&nbsp;Yingjie Shi,&nbsp;Christian F. Beckmann,&nbsp;Emma Sprooten","doi":"10.1111/gbb.12876","DOIUrl":"10.1111/gbb.12876","url":null,"abstract":"<p>The highly polygenic and pleiotropic nature of behavioural traits, psychiatric disorders and structural and functional brain phenotypes complicate mechanistic interpretation of related genome-wide association study (GWAS) signals, thereby obscuring underlying causal biological processes. We propose genomic principal and independent component analysis (PCA, ICA) to decompose a large set of univariate GWAS statistics of multimodal brain traits into more interpretable latent genomic components. Here we introduce and evaluate this novel methods various analytic parameters and reproducibility across independent samples. Two UK Biobank GWAS summary statistic releases of 2240 imaging-derived phenotypes (IDPs) were retrieved. Genome-wide beta-values and their corresponding standard-error scaled <i>z</i>-values were decomposed using genomic PCA/ICA. We evaluated variance explained at multiple dimensions up to 200. We tested the inter-sample reproducibility of output of dimensions 5, 10, 25 and 50. Reproducibility statistics of the respective univariate GWAS served as benchmarks. Reproducibility of 10-dimensional PCs and ICs showed the best trade-off between model complexity and robustness and variance explained (PCs: |<i>r</i>_<i>z</i> − max| = 0.33, |<i>r</i>_raw − max| = 0.30; ICs: |<i>r</i>_<i>z</i> − max| = 0.23, |<i>r</i>_raw − max| = 0.19). Genomic PC and IC reproducibility improved substantially relative to mean univariate GWAS reproducibility up to dimension 10. Genomic components clustered along neuroimaging modalities. Our results indicate that genomic PCA and ICA decompose genetic effects on IDPs from GWAS statistics with high reproducibility by taking advantage of the inherent pleiotropic patterns. These findings encourage further applications of genomic PCA and ICA as fully data-driven methods to effectively reduce the dimensionality, enhance the signal to noise ratio and improve interpretability of high-dimensional multitrait genome-wide analyses.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12876","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139472969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovery and validation of genes driving drug-intake and related behavioral traits in mice","authors":"Tyler A. Roy,&nbsp;Jason A. Bubier,&nbsp;Price E. Dickson,&nbsp;Troy D. Wilcox,&nbsp;Juliet Ndukum,&nbsp;James W. Clark,&nbsp;Stacey J. Sukoff Rizzo,&nbsp;John C. Crabbe,&nbsp;James M. Denegre,&nbsp;Karen L. Svenson,&nbsp;Robert E. Braun,&nbsp;Vivek Kumar,&nbsp;Stephen A. Murray,&nbsp;Jacqueline K. White,&nbsp;Vivek M. Philip,&nbsp;Elissa J. Chesler","doi":"10.1111/gbb.12875","DOIUrl":"10.1111/gbb.12875","url":null,"abstract":"<p>Substance use disorders are heritable disorders characterized by compulsive drug use, the biological mechanisms for which remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference and sensation seeking, are predictive of drug-use phenotypes, thereby implicating shared genetic mechanisms. High-throughput behavioral screening in knockout (KO) mice allows efficient discovery of the function of genes. We used this strategy in two rounds of candidate prioritization in which we identified 33 drug-use candidate genes based upon predisposing drug-naïve phenotypes and ultimately validated the perturbation of 22 genes as causal drivers of substance intake. We selected 19/221 KO strains (8.5%) that had a difference from control on at least one drug-naïve predictive behavioral phenotype and determined that 15/19 (~80%) affected the consumption or preference for alcohol, methamphetamine or both. No mutant exhibited a difference in nicotine consumption or preference which was possibly confounded with saccharin. In the second round of prioritization, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15/401 KO strains (3.7%, which included one gene from the first cohort) that differed most from controls for the predisposing phenotypes. 8 of 15 gene deletions (53%) affected intake or preference for alcohol, methamphetamine or both. Using multivariate and bioinformatic analyses, we observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"23 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12875","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139075752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Referees","authors":"","doi":"10.1111/gbb.12878","DOIUrl":"10.1111/gbb.12878","url":null,"abstract":"<p>Alexander, Matthew.</p><p>Anokhin, Andrey.</p><p>Atkinson, Nigel.</p><p>Bachtell, Ryan.</p><p>Bajo, Michal.</p><p>Bales, Karen.</p><p>Barrot, Michel.</p><p>Bast, Tobias.</p><p>Beckstead, Michael.</p><p>Belleau, Emily.</p><p>Besheer, Joyce.</p><p>Biernacka, Joanna.</p><p>Blundell, Jacqueline.</p><p>Bordt, Evan.</p><p>Bosch, Oliver.</p><p>Brown, Richard.</p><p>Bryant, Camron.</p><p>Candlish, Michael.</p><p>Cavanaugh, Daniel.</p><p>Cheatwood, Joseph.</p><p>Chester, Julia.</p><p>Chowdhury, Budhaditya.</p><p>Clarke, Gerard.</p><p>Clayton, David.</p><p>Colwell, Christopher.</p><p>Cook, Melloni.</p><p>Couto, Antoine.</p><p>Cushing, Bruce.</p><p>De Fraga,</p><p>Deak, Joseph.</p><p>Diaz, Heijtz,</p><p>Dijkstra, Peter.</p><p>Ehlers, Cindy.</p><p>Fendt, Markus.</p><p>Ferguson, David.</p><p>Fuchsova, Beata.</p><p>Furtjes, Anna.</p><p>Geiger, Madeleine.</p><p>Geleoc, Gwenaelle.</p><p>Gizer, Ian.</p><p>Glover, Elizabeth.</p><p>Greeson, Ben.</p><p>Grinevich, Valery.</p><p>Gu, Bin.</p><p>Hammack, Sayamwong.</p><p>Hatoum, Alexander.</p><p>Hauber, Mark.</p><p>Hendricks, Audrey.</p><p>Hill, Shirley.</p><p>Hopf, Frederic.</p><p>Johnson, Emma.</p><p>Johnson, Michael.</p><p>Jurek, Benjamin.</p><p>Kenkel, William.</p><p>Kiraly, Drew.</p><p>Konopka, Genevieve.</p><p>Kopec, Ashley.</p><p>Kuhn, Donald.</p><p>Kumar, Vivek.</p><p>Larue, Lionel.</p><p>LaSarge, Candi.</p><p>Lipina, Tatiana.</p><p>Logan, Ryan.</p><p>Lopez, Sofia.</p><p>Lord, Kathryn.</p><p>Lucas, Guilherme.</p><p>Luciano, Michelle.</p><p>Lugo, Joaquin.</p><p>Mayfield, Roy.</p><p>McDermott, Brian.</p><p>Mello, Claudio.</p><p>Menon, Rohit.</p><p>Miller, Alex.</p><p>Miranda-Barrientos, Jorge.</p><p>Mosienko, Valentina.</p><p>Moy, Sherly.</p><p>Mulligan, Megan.</p><p>Murlanova, Kateryna.</p><p>Ozburn, Angela.</p><p>Pathak, Gita.</p><p>Patten, Shunmoogum.</p><p>Paul, Sarah.</p><p>Pawluski, Jodi.</p><p>Pignataro, Giuseppe.</p><p>Pletnikov, Mikhail.</p><p>Ploski, Jonathan.</p><p>Ponomarev, Igor.</p><p>Powell, Susan.</p><p>Pryce, Christopher.</p><p>Raber, Jacob.</p><p>Ragozzino, Michael.</p><p>Randall, Patrick.</p><p>Rasband, Matthew.</p><p>Redei, Eva.</p><p>Riley, Brien.</p><p>Roman, Gregg.</p><p>Schmidtner, Anna.</p><p>Schreihofer, Derek.</p><p>Serafini, Gianluca.</p><p>Sherva, Richard.</p><p>Siegel, Jessica.</p><p>Snyder, Brina.</p><p>Sokoloff, Greta.</p><p>Sorenson, Michael.</p><p>Stitzel, Jerry.</p><p>Tabakoff, Boris.</p><p>Terman, Jonathan.</p><p>Thomas, Nathaniel.</p><p>Thorogood, Rose.</p><p>Wall, Tamara.</p><p>Waterland, Robert.</p><p>Wedow, Robbee.</p><p>Willadsen, Maria.</p><p>Williams, Aislinn.</p><p>Wray, Naomi.</p><p>Yan, Hua.</p><p>Yoshino, Yuta.</p><p>Young, Andrew.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138822528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impaired reversal learning in the Dlg2+/− rat model of genetic risk for psychiatric disorder: Important questions regarding the neuro-behavioral mechanisms of reversal learning","authors":"Tobias Bast,&nbsp;Rachel Grasmeder Allen,&nbsp;Silvia Maggi,&nbsp;Jacco Renstrom","doi":"10.1111/gbb.12870","DOIUrl":"10.1111/gbb.12870","url":null,"abstract":"<p>In this issue, Griesius et al report that heterozygous Dlg2+/- rats showed a reversal learning impairment on a specific bowl-digging task, whereas other reversal tasks were unaffected. The study suggests that Dlg2 gene disruption, which has been linked to neuropsychiatric disorders, including schizophrenia, may cause relatively specific impairments in reversal learning, an important aspect of cognitive flexibility. The study draws attention to two important issues regarding the neuro-behavioral mechanisms of reversal learning, namely that hippocampal dysfunction, which is prominent in Dlg2+/- rats, may contribute to reversal learning impairments and that, depending on the task and previous experience, brain and behavioral mechanisms of reversal learning may differ.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12870","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138529427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The polygenic and reactive nature of observed parenting","authors":"Jana Runze,&nbsp;Marian J. Bakermans-Kranenburg,&nbsp;Charlotte A. M. Cecil,&nbsp;Marinus H. van IJzendoorn,&nbsp;Irene Pappa","doi":"10.1111/gbb.12874","DOIUrl":"10.1111/gbb.12874","url":null,"abstract":"<p>In Wertz et al. (2019), parents' polygenic scores of educational attainment (PGS-EA) predicted parental sensitive responses to the child's needs for support, as observed in a dyadic task (i.e., observed sensitivity). We aimed to replicate and expand these findings by combining longitudinal data, child genotype data and several polygenic scores in the Generation R Study. Mother–child dyads participated in two developmental periods, toddlerhood (14 months old; <i>n</i> = 648) and early childhood (3–4 years old, <i>n</i> = 613). Higher maternal PGS-EA scores predicted higher observed sensitivity in toddlerhood (<i>b</i> = 0.12, 95% CI 0.03, 0.20) and early childhood (<i>b</i> = 0.16, 95% CI 0.08, 0.24). Child PGS-EA was significantly associated with maternal sensitivity in early childhood (<i>b</i> = 0.11, 95% CI 0.02, 0.21), and the effect of maternal PGS-EA was no longer significant when correcting for child PGS-EA. A latent factor of PGSs based on educational attainment, intelligence (IQ) and income showed similar results. These polygenic scores might be associated with maternal cognitive and behavioral skills that help shape parenting. Maternal PGSs predicted observed sensitivity over and above the maternal phenotypes, showing an additional role for PGSs in parenting research. In conclusion, we replicated the central finding of Wertz et al. (2019) that parental PGS-EA partially explains parental sensitivity. Our findings may be consistent with evocative gene–environment correlation (rGE), emphasizing the dynamic nature of parenting behavior across time, although further research using family trios is needed to adequately test this hypothesis.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12874","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138452977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PAC1 receptor modulation of freezing and flight behavior in periaqueductal gray","authors":"Ersin Yavas,&nbsp;Irina Zhuravka,&nbsp;Michael S. Fanselow","doi":"10.1111/gbb.12873","DOIUrl":"10.1111/gbb.12873","url":null,"abstract":"<p>The midbrain periaqueductal gray (PAG) region is a critical anatomical regulator of fear-related species-specific defensive reactions (SSDRs). Pituitary adenylate-cyclase-activating polypeptide (PACAP), and its main receptor PAC1, play an important role in fear-related behavior and anxiety disorders. However, the function of the PACAP-PAC1 system within the PAG with regards to SSDRs has received little attention. To address this gap, we used transgenic PAC1^flox/flox mice to examine both conditional and unconditional defensive reactions. We performed conditional PAC1 gene deletion within the ventrolateral(vl)PAG of PAC1^flox/flox mice using an adeno-associated virus (AAV) coding for Cre recombinase. Following viral expression, we used a white noise fear conditioning preparation that produces both an unconditional activity burst to the onset of noise that is followed by conditional freezing. On Day 1, mice received five white noise foot-shock pairings, whereas on Day 2, they were exposed to white noise five times without shock and we scored the activity burst and freezing to the white noise. Following behavioral testing, histology for immunofluorescent analysis was conducted in order to identify PACAP positive cells and stress-induced <i>c-fos</i> activity respectively. We found that PAC1 deletion in vlPAG increased the unconditional activity burst response but disrupted conditional freezing. PAC1 deletion was accompanied by higher <i>c-fos</i> activity following the behavioral experiments. Furthermore, a significant portion of PACAP-EGFP positive cells showed overlapping expression with VGAT, indicating their association with inhibitory neurons. The findings suggested that intact PACAP-PAC1 mechanisms are essential for SSDRs in vlPAG. Therefore, midbrain PACAP contributes to the underlying molecular mechanisms regulating fear responses.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12873","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138177704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of polygenic scores for depression and neuroticism with perceived stress in daily life during a long-lasting stress period","authors":"Hannah L. Peter,&nbsp;Marina Giglberger,&nbsp;Fabian Streit,&nbsp;Josef Frank,&nbsp;Ludwig Kreuzpointner,&nbsp;Marcella Rietschel,&nbsp;Brigitte M. Kudielka,&nbsp;Stefan Wüst","doi":"10.1111/gbb.12872","DOIUrl":"10.1111/gbb.12872","url":null,"abstract":"<p>Genetic factors contribute significantly to interindividual differences in the susceptibility to stress-related disorders. As stress can also be conceptualized as environmental exposure, controlled gene–environment interaction (GxE) studies with an in-depth phenotyping may help to unravel mechanisms underlying the interplay between genetic factors and stress. In a prospective-longitudinal quasi-experimental study, we investigated whether polygenic scores (PGS) for depression (DEP-PGS) and neuroticism (NEU-PGS), respectively, were associated with responses to chronic stress in daily life. We examined law students (<i>n</i> = 432) over 13 months. Participants in the stress group experienced a long-lasting stress phase, namely the preparation for the first state examination for law students. The control group consisted of law students without particular stress exposure. In the present manuscript, we analyzed perceived stress levels assessed at high frequency and in an ecologically valid manner by ambulatory assessments as well as depression symptoms and two parameters of the cortisol awakening response. The latter was only assessed in a subsample (<i>n</i> = 196). No associations between the DEP-PGS and stress-related variables were found. However, for the NEU-PGS we found a significant GxE effect. Only in individuals experiencing academic stress a higher PGS for neuroticism predicted stronger increases of perceived stress levels until the exam. At baseline, a higher NEU-PGS was associated with higher perceived stress levels in both groups. Despite the small sample size, we provide preliminary evidence that the genetic disposition for neuroticism is associated with stress level increases in daily life during a long-lasting stress period.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50159176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nature and nurture: Comparing mouse behavior in classic versus revised anxiety-like and social behavioral assays in genetically or environmentally defined groups","authors":"Janet Ronquillo,&nbsp;Michael T. Nguyen,&nbsp;Linnea Y. Rothi,&nbsp;Trung-Dan Bui-Tu,&nbsp;Jocelyn Yang,&nbsp;Lindsay R. Halladay","doi":"10.1111/gbb.12869","DOIUrl":"10.1111/gbb.12869","url":null,"abstract":"<p>Widely used rodent anxiety assays like the elevated plus maze (EPM) and the open field test (OFT) are conflated with rodents' natural preference for dark over light environments or protected over open spaces. The EPM and OFT have been used for decades but are often criticized by behavioral scientists. Years ago, two revised anxiety assays were designed to improve upon the “classic” tests by excluding the possibility to avoid or escape aversion. The 3-D radial arm maze (3DR) and the 3-D open field test (3Doft) utilize continual motivational conflict to better model anxiety; each consist of an open space connected to ambiguous paths toward uncertain escape. Despite their utility, the revised assays have not caught on. This could be because no study yet has directly compared classic and revised assays in the same animals. To remedy this, we contrasted behavior from a battery of assays (EPM, OFT, 3DR, 3Doft and a sociability test) in mice defined genetically by isogenic strain, or environmentally by postnatal experience. One major motivation for this work is to inform future studies by offering a transparent look at individual outcomes on these assays, as there is no one-size-fits-all test to assess rodent anxiety-like behavior. Findings suggest that classic assays may sufficiently characterize differences across genetically defined groups, but the revised 3DR may be advantageous for investigating more nuanced behavioral differences such as those stemming from environmental factors. Finally, exposure to multiple assays significantly affected sociability, highlighting concerns for designing and interpreting batteries of rodent behavioral tests.</p>","PeriodicalId":50426,"journal":{"name":"Genes Brain and Behavior","volume":"22 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gbb.12869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49693514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}