Rare copy number variation in extremely impulsively violent males

Gut Microbiome in Impulsively Violent Female Convicts

INTRODUCTION

Impulsivity and aggression are often interlinked behavioral traits that have major implications for our society. Therefore, the study of this phenomenon and derivative interventions that could lead to better control of impulsive aggression are of interest.

METHODS

We analyzed the composition and diversity of the gut bacterial microbiome of 33 impulsively violent female convicts with dissocial personality disorder and 20 non-impulsive age-matched women. Further, levels of assorted neurotransmitters and short-chain fatty acids (SCFAs) were analyzed in serum and stool samples. We also assessed all participants using a battery of psychological questionnaires and tested possible correlations between the collected clinical data and the composition and diversity of their microbiomes and metabolites.

RESULTS

We identified four bacterial amplicon sequencing variants that were differentially abundant in non-impulsive versus impulsive women - the genera Bacteroides, Barnesiella, and the order Rhodospirillales were more abundant in impulsive women. In contrast, the genus Catenisphaera was more abundant in non-impulsive women. Fecal tryptophan levels were significantly higher in impulsive women. Association analysis revealed a strong positive intercorrelation between most fecal SCFAs in the entire dataset.

CONCLUSIONS

Our study demonstrated possible associations between gut microbiomes and their metabolites and impulsive behavior in a unique cohort of prisoners convicted of violent assaults and a matched group of non-impulsive women from the same prison. Genus Bacteroides, which was differentially abundant in the two groups, encoded enzymes that affect serotonin pathways and could contribute to this maladaptive behavior. Similarly, increased fecal tryptophan levels in impulsive individuals could affect neuronal circuits in the brain.

Drug target genes and molecular mechanism investigation in isoflurane-induced anesthesia based on WGCNA and machine learning methods

PURPOSE

This study sought to identify drug target genes and their associated molecular mechanisms during isoflurane-induced anesthesia in clinical applications.

METHODS

Microarray data (ID: GSE64617; isoflurane-treated vs. normal samples) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened and hub genes were investigated using weighted correlation network analysis (WGCNA). Protein-protein interactions (PPIs) were constructed among the co-DEGs (common genes between DEGs and hub genes), followed by functional enrichment analyses. Then, three machine learning methods were used to reveal drug targets, followed by validation, nomogram analysis, and gene set enrichment analysis. Finally, an miRNA-target network was constructed.

RESULTS

A total of 686 DEGs were identified between the two groups-of which, 183 DEGs integrated with genes revealed by WCGNA were identified as co-genes. These genes, including contactin-associated protein 1 (CNTNAP1), are mainly involved in functions such as action potentials. PPI network analysis revealed three models, with the machine learning analysis exploring four drug target genes: A2H, FAM155B, SCARF2, and SDR16C5. ROC and nomogram analyses demonstrated the ideal diagnostic value of these target genes. Finally, miRNA-mRNA pairs were constructed based on the four mRNAs and associated 174 miRNAs.

CONCLUSION

FA2H, FAM155B, SCARF2, and SDR16C5 may be novel drug target genes for isoflurane-induced anesthesia. CNTNAP1 may participate in the progression of isoflurane-induced anesthesia via its action potential function.

Increased burden of rare protein-truncating variants in constrained, brain-specific and synaptic genes in extremely impulsively violent males with antisocial personality disorder

The genetic correlates of extreme impulsive violence are poorly understood, and there have been few studies that have characterized a large group of affected individuals both clinically and genetically. We performed whole exome sequencing (WES) in 290 males with the life-course-persistent, extremely impulsively violent form of antisocial personality disorder (APD) and analyzed the spectrum of rare protein-truncating variants (rPTVs). Comparisons were made with 314 male controls and publicly available genotype data. Functional annotation tools were used for biological interpretation. Participants were significantly more likely to harbor rPTVs in genes that are intolerant to loss-of-function variants (odds ratio [OR] 2.06; p < 0.001), specifically expressed in brain (OR 2.80; p = 0.036) and enriched for those involved in neurotransmitter transport and synaptic processes. In 60 individuals (20%), we identified rPTVs that we classified as clinically relevant based on their clinical associations, biological function and gene expression patterns. Of these, 37 individuals harbored rPTVs in 23 genes that are associated with a monogenic neurological disorder, and 23 individuals harbored rPTVs in 20 genes reportedly intolerant to loss-of-function variants. The analysis presents evidence in support of a model where presence of either one or several private, functionally relevant mutations contribute significantly to individual risk of life-course-persistent APD and reveals multiple individuals who could be affected by clinically unrecognized neuropsychiatric Mendelian disease. Thus, Mendelian diseases and increased rPTV burden may represent important factors for the development of extremely impulsive violent life-course-persistent forms of APD irrespective of their clinical presentation.

The effect of microbiome composition on impulsive and violent behavior: A systematic review

The impact of the microbiome on brain function and behavior has recently become an important research topic. We searched for a link between the gut microbiome and impulsive and violent behavior. We focused on critical factors influencing the microbiome establishment that may affect human health later in life, i.e., delivery mode, early-life feeding, and early antibiotic exposure. We searched PubMed, Web of Science, and the Cochrane Library. We included original human studies examining adults and children with impulsive and/or violent behavior that assessed the gut microbiota composition of participants, delivery mode, infant feeding mode, or early antibiotic exposure. Bibliographic searches yielded 429 articles, and 21 met the eligibility criteria. Two studies reported data on patients with schizophrenia with violent behavior, while 19 studies reported data on patients with attention-deficit hyperactivity disorder (ADHD). The results showed several bacterial taxa associated with ADHD symptomatology and with violent behavior in patients with schizophrenia. No association was found between delivery mode and impulsive behavior, nor did any articles relate infant feeding mode to violent human behavior. Those studies investigating early antibiotic exposure yielded ambiguous results. The heterogeneity of the data and the different methodologies of the included studies limited the external validity of the results. We found few studies that addressed the possible microbiome involvement in the pathophysiology of impulsive and violent behavior in humans. Our review revealed a gap in knowledge regarding links between the gut microbiome and these extreme behavioral patterns.

Connecting phenotype to genotype: PheWAS-inspired analysis of autism spectrum disorder

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate.

Contribution of copy number variations to the risk of severe eating disorders

AIM

Eating disorders (EDs) are complex, multifactorial psychiatric conditions. Previous studies identified pathogenic copy number variations associated with NDDs (NDD-CNVs) in ED patients. However, no statistical evidence for an association between NDD-CNVs and EDs has been demonstrated. Therefore, we examined whether NDD-CNVs confer risk for EDs.

METHODS

Using array comparative genomic hybridization (aCGH), we conducted a high-resolution CNV analysis of 71 severe female ED patients and 1045 female controls. According to the American College of Medical Genetics guidelines, we identified NDD-CNVs or pathogenic/likely pathogenic CNVs in NDD-linked loci. Gene set analysis was performed to examine the involvement of synaptic dysfunction in EDs. Clinical data were retrospectively examined for ED patients with NDD-CNVs.

RESULTS

Of the samples analyzed with aCGH, 70 severe ED patients (98.6%) and 1036 controls (99.1%) passed our quality control filtering. We obtained 189 and 2539 rare CNVs from patients and controls, respectively. NDD-CNVs were identified in 10.0% (7/70) of patients and 2.3% (24/1036) of controls. Statistical analysis revealed a significant association between NDD-CNVs and EDs (odds ratio = 4.69, P = 0.0023). NDD-CNVs in ED patients included 45,X and deletions at KATNAL2, DIP2A, PTPRT, RBFOX1, CNTN4, MACROD2, and FAM92B. Four of these genes were related to synaptic function. In gene set analysis, we observed a nominally significant enrichment of rare exonic CNVs in synaptic signaling in ED patients (odds ratio = 2.55, P = 0.0254).

CONCLUSION

Our study provides the first preliminary evidence that NDD-CNVs may confer risk for severe EDs. The pathophysiology may involve synaptic dysfunction.

A PheWAS Model of Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants. There is a need for a better understanding of the connections between genotype information and the phenotypes to sort out the heterogeneity of ASD. In this study, single nucleotide polymorphism (SNP) and phenotype data obtained from a simplex ASD sample are combined using a PheWAS-inspired approach to construct a phenotype-phenotype network. The network is clustered, yielding groups of etiologically related phenotypes. These clusters are analyzed to identify relevant genes associated with each set of phenotypes. The results identified multiple discriminant SNPs associated with varied phenotype clusters such as ASD aberrant behavior (self-injury, compulsiveness and hyperactivity), as well as IQ and language skills. Overall, these SNPs were linked to 22 significant genes. An extensive literature search revealed that eight of these are known to have strong evidence of association with ASD. The others have been linked to related disorders such as mental conditions, cognition, and social functioning.Clinical relevance- This study further informs on connections between certain groups of ASD phenotypes and their unique genetic variants. Such insight regarding the heterogeneity of ASD would support clinicians to advance more tailored interventions and improve outcomes for ASD patients.