scholarly journals Transcriptomic networks implicate neuronal energetic abnormalities in three mouse models harboring autism and schizophrenia-associated mutations

2019 ◽  
Author(s):  
Aaron Gordon ◽  
Annika Grønborg-Forsingdal ◽  
Ib Vestergaard Klewe ◽  
Jacob Nielsen ◽  
Michael Didriksen ◽  
...  
Keyword(s):  
Mouse Models ◽  
Genetic Risk ◽  
Copy Number Variants ◽  
Autism Spectrum ◽  
Molecular Pathways ◽  
Post Mortem ◽  
Risk Alleles ◽  
Gene Network Analysis ◽  
Genomic Studies ◽  
Deletion 22Q11.2

AbstractGenetic risk for psychiatric illness is complex, so identification of shared molecular pathways where distinct forms of genetic risk might coincide is of substantial interest. A growing body of genetic and genomic studies suggest that such shared molecular pathways exist across disorders with different clinical presentations, such as schizophrenia and autism spectrum disorder (ASD). But how this relates to specific genetic risk factors is unknown. Further, whether some of the molecular changes identified in brain relate to potentially confounding antemortem or post-mortem factors is difficult to prove. We analyzed the transcriptome from the cortex and hippocampus of three mouse lines modeling human copy number variants (CNVs) associated with schizophrenia and ASD: Df(h15q13)/+, Df(h22q11)/+, and Df(h1q21)/+ which carry the 15q13.3 deletion, 22q11.2 deletion, and 1q21.1 deletion, respectively. Although we found very little overlap of differential expression at the level of individual genes, gene network analysis identified two modules of co-expressed genes that were dysregulated across all three mouse models. One module observed in both cortex and hippocampus was associated with neuronal energetics and firing rate, and overlapped with changes identified in post mortem human brain from SCZ and ASD patients. These data highlight aspects of convergent gene expression in mouse models harboring major risk alleles, and strengthen the connection between neuronal energetic dysfunction and neuropsychiatric disorders in humans.

scholarly journals Targeting the RHOA pathway improves learning and memory in Kctd13 and 16p11.2 deletion mouse models

2020 ◽  
Author(s):  
Sandra Martin Lorenzo ◽  
Valérie Nalesso ◽  
Claire Chevalier ◽  
Marie-Christine Birling ◽  
Yann Herault
Keyword(s):  
Object Recognition ◽  
Recognition Memory ◽  
Mouse Models ◽  
Copy Number Variants ◽  
Gene Copy Number ◽  
Chronic Administration ◽  
Autism Spectrum ◽  
Gene Copy ◽  
List Type ◽  
Object Recognition Memory

ABSTRACTGene copy number variants (CNV) have an important role in the appearance of neurodevelopmental disorders. Particularly, the deletion of the 16p11.2 locus is associated with autism spectrum disorder, intellectual disability, and several other features. Earlier studies highlighted the implication of Kctd13 genetic imbalance in the 16p11.2 deletion through the regulation of the RHOA pathway. Here, we target the pathway and rescue the cognitive phenotypes of the 16p11.2 deletion mouse models. We used a chronic administration of fasudil (HA1077), an inhibitor of the Rho-associated protein kinase (ROCK), in mouse models carrying a heterozygous inactivation of Kctd13, or the deletion of the entire 16p11.2 BP4-BP5 region. We focused our attention on the most robust cognitive phenotypes seen in the 16p11.2 models and we showed that a chronic fasudil treatment can restore object recognition memory in both mouse models but does not change other behavioural traits. These findings confirm KCTD13 as one target gene causing cognitive deficits in 16p11.2 deletion patients, and the pertinence of the RHOA pathway as a therapeutic path and reinforce the contribution of other gene(s) involved in cognitive defects found in the 16p11.2 CNV models.HIGHLIGHTS- Kctd13 haploinsufficiency recapitulates most of the behaviour phenotypes found in the 16p11.2 Del/+ models- Fasudil treatment restores Kctd13 and 16p11.2 Del/+ mutant phenotypes in novel location and novel object recognition memory tests- Fasudil treatment restores the RhoA pathway in Kctd13+/- and 16p11.2 Del/+ models

scholarly journals Gene network analysis reveals a role for striatal glutamatergic receptors in dysregulated risk-assessment behavior of autism mouse models

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Oded Oron ◽  
Dmitriy Getselter ◽  
Shahar Shohat ◽  
Eli Reuveni ◽  
Iva Lukic ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Mouse Models ◽  
Gene Network ◽  
Autism Spectrum ◽  
Transcriptome Data ◽  
Self Injury ◽  
Assessment Activity ◽  
Gene Network Analysis ◽  
Whole Transcriptome ◽  
Multiple Male

Abstract Autism spectrum disorder (ASD) presents a wide, and often varied, behavioral phenotype. Improper assessment of risks has been reported among individuals diagnosed with ASD. Improper assessment of risks may lead to increased accidents and self-injury, also reported among individuals diagnosed with ASD. However, there is little knowledge of the molecular underpinnings of the impaired risk-assessment phenotype. In this study, we have identified impaired risk-assessment activity in multiple male ASD mouse models. By performing network-based analysis of striatal whole transcriptome data from each of these ASD models, we have identified a cluster of glutamate receptor-associated genes that correlate with the risk-assessment phenotype. Furthermore, pharmacological inhibition of striatal glutamatergic receptors was able to mimic the dysregulation in risk-assessment. Therefore, this study has identified a molecular mechanism that may underlie risk-assessment dysregulation in ASD.

scholarly journals Computational identification of variables in neonatal vocalizations predictive for postpubertal social behaviors in a mouse model of 16p11.2 deletion

2021 ◽  
Author(s):  
Mitsuteru Nakamura ◽  
Kenny Ye ◽  
Mariel Barbachan e Silva ◽  
Takahira Yamauchi ◽  
Daniel J. Hoeppner ◽  
...  
Keyword(s):  
Mouse Model ◽  
Mouse Models ◽  
Hidden Variables ◽  
Copy Number Variants ◽  
Autism Spectrum ◽  
Individual Variability ◽  
Phenotypic Characterization ◽  
Olfactory Responses ◽  
Hemizygous Deletion ◽  
The Impact

AbstractAutism spectrum disorder (ASD) is often signaled by atypical cries during infancy. Copy number variants (CNVs) provide genetically identifiable cases of ASD, but how early atypical cries predict a later onset of ASD among CNV carriers is not understood in humans. Genetic mouse models of CNVs have provided a reliable tool to experimentally isolate the impact of CNVs and identify early predictors for later abnormalities in behaviors relevant to ASD. However, many technical issues have confounded the phenotypic characterization of such mouse models, including systematically biased genetic backgrounds and weak or absent behavioral phenotypes. To address these issues, we developed a coisogenic mouse model of human proximal 16p11.2 hemizygous deletion and applied computational approaches to identify hidden variables within neonatal vocalizations that have predictive power for postpubertal dimensions relevant to ASD. After variables of neonatal vocalizations were selected by least absolute shrinkage and selection operator (Lasso), random forest, and Markov model, regression models were constructed to predict postpubertal dimensions relevant to ASD. While the average scores of many standard behavioral assays designed to model dimensions did not differentiate a model of 16p11.2 hemizygous deletion and wild-type littermates, specific call types and call sequences of neonatal vocalizations predicted individual variability of postpubertal reciprocal social interaction and olfactory responses to a social cue in a genotype-specific manner. Deep-phenotyping and computational analyses identified hidden variables within neonatal social communication that are predictive of postpubertal behaviors.

scholarly journals Targeting the RHOA pathway improves learning and memory in adult Kctd13 and 16p11.2 deletion mouse models

2020 ◽  
Author(s):  
Sandra Martin Lorenzo ◽  
Valérie Nalesso ◽  
Claire Chevalier ◽  
Marie-Christine Birling ◽  
Yann HERAULT
Keyword(s):  
Locomotor Activity ◽  
Learning And Memory ◽  
Mouse Models ◽  
Genetic Background ◽  
Copy Number Variants ◽  
Gene Copy Number ◽  
Chronic Administration ◽  
Autism Spectrum ◽  
Gene Copy ◽  
Homologous Region

Abstract Background Gene copy number variants have an important role in the appearance of neurodevelopmental disorders. Particularly, the deletion of the 16p11.2 locus is associated with autism spectrum disorder, intellectual disability, and several other features. Earlier studies highlighted the implication of Kctd13 genetic imbalance in the 16p11.2 deletion through the regulation of the RHOA pathway. Methods Here, we generated a new mouse models with a small deletion of two key exons in Kctd13. Then we targeted the RHOA pathway to rescue the cognitive phenotypes of the Kctd13 and 16p11.2 deletion mouse models in a pure genetic background. We used a chronic administration of fasudil (HA1077), an inhibitor of the Rho-associated protein kinase (ROCK), for several days, in mouse models carrying a heterozygous inactivation of Kctd13, or the deletion of the entire 16p11.2 BP4-BP5 homologous region. Results We found that the small Kctd13 heterozygous deletion induced similar cognitive phenotype to the whole deletion of the 16p11.2 homologous region, in the Del/+ mice. Then we showed the chronic fasudil treatment can restore object recognition memory in adult heterozygous mutant mice for Kctd13 and for 16p11.2 deletion. In addition, the learning and memory improvement was parallel to change in the RHOA pathway. Limitations: The Kcdt13 mutant line does not recapitulate all the phenotypes found in the 16p11.2 Del/+ model. In particular the locomotor activity was not altered at 12 and 18 weeks of age and the object location memory was not defective in 18 weeks old mutants. Similarly, the increased in locomotor activity was not modified by the treatment in the 16p11.2 Del/+ mouse model suggesting other loci involved in such defects. Then, the rescue was only observed after four weeks of treatment but no long term experiment has been done so far. Finally we did not check the social behaviour that require to work in another hybrid genetic background. Conclusion These findings confirm KCTD13 as one target gene causing cognitive deficits in 16p11.2 deletion patients, and the relevance of the RHOA pathway as a therapeutic path for the 16p11.2 deletion. Nevertheless, they reinforce the contribution of other gene(s) involved in cognitive defects found in the 16p11.2 models in older mice.

scholarly journals Intranasal oxytocin administration ameliorates social behavioral deficits in a POGZWT/Q1038R mouse model of autism spectrum disorder

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kohei Kitagawa ◽  
Kensuke Matsumura ◽  
Masayuki Baba ◽  
Momoka Kondo ◽  
Tomoya Takemoto ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Social Behavior ◽  
Mouse Model ◽  
Mouse Models ◽  
De Novo ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
De Novo Mutation ◽  
Behavioral Deficits

AbstractAutism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by core symptoms of impaired social behavior and communication. Recent studies have suggested that the oxytocin system, which regulates social behavior in mammals, is potentially involved in ASD. Mouse models of ASD provide a useful system for understanding the associations between an impaired oxytocin system and social behavior deficits. However, limited studies have shown the involvement of the oxytocin system in the behavioral phenotypes in mouse models of ASD. We have previously demonstrated that a mouse model that carries the ASD patient-derived de novo mutation in the pogo transposable element derived with zinc finger domain (POGZWT/Q1038R mice), showed ASD-like social behavioral deficits. Here, we have explored whether oxytocin (OXT) administration improves impaired social behavior in POGZWT/Q1038R mice and found that intranasal oxytocin administration effectively restored the impaired social behavior in POGZWT/Q1038R mice. We also found that the expression level of the oxytocin receptor gene (OXTR) was low in POGZWT/Q1038R mice. However, we did not detect significant changes in the number of OXT-expressing neurons between the paraventricular nucleus of POGZWT/Q1038R mice and that of WT mice. A chromatin immunoprecipitation assay revealed that POGZ binds to the promoter region of OXTR and is involved in the transcriptional regulation of OXTR. In summary, our study demonstrate that the pathogenic mutation in the POGZ, a high-confidence ASD gene, impairs the oxytocin system and social behavior in mice, providing insights into the development of oxytocin-based therapeutics for ASD.

Has the time come to integrate genetic risk scores into clinical practice?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F.V Moniz Mendonca ◽  
M.I Mendonca ◽  
A Pereira ◽  
J Monteiro ◽  
J Sousa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Practice ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Risk Scores ◽  
Cumulative Number ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Cad Risk

Abstract Background The risk for Coronary Artery Disease (CAD) is determined by both genetic and environmental factors, as well as by the interaction between them. It is estimated that genetic factors could account for 40% to 55% of the existing variability among the population (inheritability). Therefore, some authors have advised that it is time we integrated genetic risk scores into clinical practice. Aim The aim of this study was to evaluate the magnitude of the association between an additive genetic risk score (aGRS) and CAD based on the cumulative number of risk alleles in these variants, and to estimate whether their use is valuable in clinical practice. Methods A case-control study was performed in a Portuguese population. We enrolled 3120 participants, of whom 1687 were CAD patients and 1433 were normal controls. Controls were paired to cases with respect to gender and age. 33 genetic variants known to be associated with CAD were selected, and an aGRS was calculated for each individual. The aGRS was further subdivided into deciles groups, in order to estimate the CAD risk in each decile, defined by the number of risk alleles. The magnitude of the risk (odds ratio) was calculated for each group by multiple logistic regression using the 5th decile as the reference group (median). In order to evaluate the ability of the aGRS to discriminate susceptibility to CAD, two genetic models were performed, the first with traditional risk factors (TRF) and second with TRF plus aGRS. The AUC of the two ROC curves was calculated. Results A higher prevalence of cases over controls became apparent from the 6th decile of the aGRS, reflecting the higher number of risk alleles present (see figure). The difference in CAD risk was only significant from the 6th decile, increasing gradually until the 10th decile. The odds ratio (OR) for the last decile related to 5th decile (median) was 1.87 (95% CI:1.36–2.56; p<0.0001). The first model yielded an AUC=0.738 (95% CI:0.720–0.755) and the second model was slightly more discriminative for CAD risk (AUC=0.748; 95% CI:0.730–0.765). The DeLong test was significant (p=0.0002). Conclusion Adding an aGRS to the non-genetic risk factors resulted in a modest improvement in the ability to discriminate the risk of CAD. Such improvement, even if statistically significant, does not appear to be of real value in clinical practice yet. We anticipate that with the development of further knowledge about different SNPs and their complex interactions, and with the inclusion of rare genetic variants, genetic risk scores will be better suited for use in a clinical setting. Funding Acknowledgement Type of funding source: None

scholarly journals The patterns of family genetic risk scores for eleven major psychiatric and substance use disorders in a Swedish national sample

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kenneth S. Kendler ◽  
Henrik Ohlsson ◽  
Jan Sundquist ◽  
Kristina Sundquist
Keyword(s):  
Genetic Risk ◽  
Molecular Genetic ◽  
National Sample ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Pedigree Data ◽  
Obsessive Compulsive ◽  
Swedish Population ◽  
Compulsive Disorder ◽  
Genetic Risk Scores

AbstractTo clarify the structure of genetic risks for 11 major psychiatric disorders, we calculated, from morbidity risks for disorders in 1st–5th degree relatives controlling for cohabitation effects, in the Swedish population born between 1932 and 1995 (n = 5,830,014), the family genetic risk scores (FGRS) for major depression (MD), anxiety disorders (AD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), bulimia (BUL), anorexia nervosa (AN), alcohol use disorder (AUD), drug use disorder (DUD), ADHD, and autism-spectrum disorder (ASD). For all affected individuals, we calculated their mean standardized FGRS for each disorder. The patterns of FGRS were quite similar for MD and AD, and for AUD and DUD, but substantially less similar for BUL and AN, BD and SZ, and ADHD and ASD. While OCD had high levels of FGRS for MD and AD, the overall FGRS profile differed considerably from MD and AD. ADHD FGRS scores were substantially elevated in AUD and DUD. FGRS scores for BD, OCD, AN, ASD, ADHD, and especially SZ were relatively disorder-specific while genetic risk for MD and AD had more generalized effects. The levels of FGRS for BMI, coronary artery disease, and educational attainment across our disorders replicated prior associations found using molecular genetic methods. All diagnostic categories examined had elevated FGRS for many disorders producing, for each condition, an informative FGRS profile. Using a novel method which approximates, from pedigree data, aggregate genetic risk, we have replicated and extended prior insights into the structure of genetic risk factors for key psychiatric illnesses.

scholarly journals AB0006 GENETIC RISK PROFILE FOR PSORIATIC ARTHRITIS PREDISPOSITION IN ITALIAN PATIENTS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1038.1-1038
Author(s):  
M. S. Chimenti ◽  
C. Ciccacci ◽  
G. De Benedittis ◽  
A. Latini ◽  
P. Conigliaro ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Psoriatic Arthritis ◽  
Candidate Genes ◽  
Genetic Risk ◽  
Protective Role ◽  
Risk Profile ◽  
Joint Disease ◽  
Taqman Assay ◽  
Allelic Discrimination ◽  
Risk Alleles

Background:Psoriatic arthritis (PsA) is a chronic inflammatory joint disease typically associated with psoriasis and classified in the group of spondyloarthritis (1). The pathogenesis is based on an interplay of different genes interacting with several environmental factors including stress, trauma, infections, triggering an inflammatory response related to the activation of innate and acquired immunity in different tissues and organs (2). However, the risk for the development of PsA is not clearly understood.Objectives:The aim of this study was to evaluate, in a cohort of Italian PsA out-patients of the Rheumatology Unit of the University of Rome Tor Vergata, the association of genetic variants in candidate genes for PSA susceptibility and their possible contribute in the modulation of clinical and laboratory features.Methods:The genes were selected according to previous studies describing these genes as involved in susceptibility to rheumatoid arthritis (RA) (3), since a common genetic background can be shared between these diseases. Nine SNPs (single nucleotide polymorphism) in eight candidate genes were analysed: STAT4 (rs7574865), TRAF3IP2 (rs33980500), TNFAIP3 (rs6920220 and rs2230926), MIR146A (rs2910164), PSORS1C1 (rs2233945), IL-10 (rs1800872), HCP5 (rs3099844) and ERAP1 (rs27524). Polymorphisms were analysed in 163 consecutive PsA out-patients and 198 healthy controls (HC). Genotyping was performed by allelic discrimination by TaqMan assay. Alleles frequencies differences between cases and controls or between phenotypic groups were compared using Pearson’s χ 2 test.Results:We have observed an association between PSA susceptibility and the variant alleles of STAT4 [OR= 1.60 (1.15-2.21), P= 0.005], TRAF3IP2 [OR= 1.65 (1.01-2.65), P= 0.04], ERAP1 [OR= 1.40 (1.05-1.85), P= 0.02] and TNFAIP3 (rs6920220) [OR= 1.75 (1.19-2.57), P= 0.004]. On the contrary, the variant allele of IL-10 polymorphism seems to play a protective role [OR= 0.74 (1.05-1.85), P= 0.05]. Moreover, in order to define a genetic risk profile, we have counted the total number of risk alleles in each subject, considering as risk alleles the allelic variant of rs7574865 (STAT4), rs33980500 (TRAF3IP2), rs6920220 (TNFAIP3) and rs27524 (ERAP1) SNPs. Then, we have compared the risk allele number distribution between patients and HC (Fig.1). Classes with 3 or more risk alleles are significantly more represented in patients than in HC (OR= 2.03, P=0.004). The risk to develop the disease increases significantly in subjects with at least four risk alleles (OR= 2.96, P=0.002).Figure 1.Number of risk alleles in patients and controls: rs7574865 (STAT4), rs33980500 (TRAF3IP2), rs6920220 (TNFAIP3) and rs27524 (ERAP1) SNPs.Conclusion:We confirm the associations between five SNPs, already studied in RA, and PSA susceptibility, suggesting a common inflammatory pathway in chronic inflammatory rheumatological diseases. Moreover, we show how the genotyping of only few associated SNPs could help to define a genetic risk profile for PSA development.References:[1]Calabresi E, et al. One year in review 2019: psoriatic arthritis. Clin Exp Rheumatol. 2020;38:1046-55.[2]Chimenti MS, Triggianese P, De Martino E, Conigliaro P, Fonti GL, Sunzini F, Caso F, Perricone C, Costa L, Perricone R. An update on pathogenesis of psoriatic arthritis and potential therapeutic targets. Expert Rev Clin Immunol. 2019 Aug;15(8):823-836.[3]Ciccacci C, et al. Polymorphisms in STAT-4, IL-10, PSORS1C1, PTPN2 and MIR146A genes are associated differently with prognostic factors in Italian patients affected by rheumatoid arthritis. Clin Exp Immunol. 2016;186:157-63.Disclosure of Interests:None declared

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

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