American Journal of Medical Genetics Part B: Neuropsychiatric Genetics最新文献

Cognitive deficits in people with bipolar disorder (BD) may be the result of the illness or its treatment, but they could also reflect genetic risk factors shared between BD and cognition. We investigated this question using empirical genetic relationships within a sample of patients with BD and their unaffected relatives. Participants with bipolar I, II, or schizoaffective disorder (“narrow” BD, n = 69), related mood disorders (“broad” BD, n = 135), and their clinically unaffected relatives (n = 227) completed five cognitive tests. General cognitive function (g) was quantified via principal components analysis (PCA). Heritability and genetic correlations were estimated with SOLAR-Eclipse. Participants with “narrow” or “broad” diagnoses showed deficits in g, although affect recognition was unimpaired. Cognitive performance was significantly heritable (h² = 0.322 for g, p < 0.005). Coheritability between psychopathology and g was small (0.0184 for narrow and 0.0327 for broad) and healthy relatives of those with BD were cognitively unimpaired. In this family sample, cognitive deficits were present in participants with BD but were not explained by substantial overlaps in genetic determinants of mood and cognition. These findings support the view that cognitive deficits in BD are largely the result of the illness or its treatment.

Depression is a major public health problem with a continued need to uncover its etiology. Current models of depression contend that gene-by-environment (G × E) interactions influence depression risk, and further, that depression is polygenic. Thus, recent models have emphasized two polygenic approaches: a hypothesis-driven multilocus genetic profile score (MGPS; “MGPS × E”) and a polygenic risk score (PRS; “PRS × E”) derived from genome-wide association studies (GWAS). This review for the first time synthesizes current knowledge on polygene by environment “P × E” interaction research predicting primarily depression-related outcomes, and in brief, neurobiological outcomes. The “environment” of focus in this project is stressful life events. It further discusses findings in the context of differential susceptibility and diathesis-stress theories—two major theories guiding G × E work. This synthesis indicates that, within the MGPS literature, polygenic scores based on the serotonin system, the HPA axis, or across multiple systems, interact with environmental stress exposure to predict outcomes at multiple levels of analyses and most consistently align with differential susceptibility theory. Depressive outcomes are the most studied, but neuroendocrine, and neuroimaging findings are observed as well. By contrast, vast methodological differences between GWAS-based PRS studies contribute to mixed findings that yield inconclusive results.

This study investigated the neurodevelopmental impact of pathogenic adenomatous polyposis coli (APC) gene variants in patients with familial adenomatous polyposis (FAP), a cancer predisposition syndrome. We hypothesized that certain pathogenic APC variants result in behavioral–cognitive challenges. We compared 66 FAP patients (cases) and 34 unaffected siblings (controls) to explore associations between APC variants and behavioral and cognitive challenges. Our findings indicate that FAP patients exhibited higher Social Responsiveness Scale (SRS) scores, suggesting a greater prevalence of autistic traits when compared to unaffected siblings (mean 53.8 vs. 47.4, Wilcoxon p = 0.018). The distribution of SRS scores in cases suggested a bimodal pattern, potentially linked to the location of the APC variant, with scores increasing from the 5′ to 3′ end of the gene (Pearson's r = 0.33, p = 0.022). While we observed a trend toward lower educational attainment in cases, this difference was not statistically significant. This study is the first to explore the connection between APC variant location and neurodevelopmental traits in FAP, expanding our understanding of the genotype–phenotype correlation. Our results emphasize the importance of clinical assessment for autistic traits in FAP patients, shedding light on the potential role of APC gene variants in these behavioral and cognitive challenges.

Psychiatric disorders have a complex biological underpinning likely involving an interplay of genetic and environmental risk contributions. Substantial efforts are being made to use artificial intelligence approaches to integrate features within and across data types to increase our etiological understanding and advance personalized psychiatry. Network science offers a conceptual framework for exploring the often complex relationships across different levels of biological organization, from cellular mechanistic to brain-functional and phenotypic networks. Utilizing such network information effectively as part of artificial intelligence approaches is a promising route toward a more in-depth understanding of illness biology, the deciphering of patient heterogeneity, and the identification of signatures that may be sufficiently predictive to be clinically useful. Here, we present examples of how network information has been used as part of artificial intelligence within psychiatry and beyond and outline future perspectives on how personalized psychiatry approaches may profit from a closer integration of psychiatric research, artificial intelligence development, and network science.

To examine whether the level of genetic risk in psychiatric disorders impacts the social functioning of affected individuals, we examine the relationship between genetic risk factors for major depression (MD), anxiety disorders (AD), bipolar disorder (BD), non-affective psychosis (NAP), alcohol use disorder (AUD), and drug use disorder (DUD) in disordered individuals and five adverse social outcomes: unemployment, residence in areas of social deprivation, social welfare, early retirement, and divorce. We examine all cases with registration for these disorders from 1995 to 2015 in individuals born in Sweden. Genetic risk was assessed by the family genetic risk score (FGRS) and statistical estimates by Cox proportional hazard models. High genetic risk was significantly and modestly associated with poorer social outcomes in 23 of 30 analyses. Overall, genetic risk for MD, AD, AUD, and DUD impacted social functioning more strongly in affected individuals than did genetic risk for BD and NAP. Social welfare had the strongest associations with genetic risk, and residence in areas of high deprivation had the weakest. In individuals suffering from psychiatric and substance use disorders, high levels of genetic risk impact not only clinical features but also diverse measures of social functioning.

Autism spectrum disorder (ASD) is complex neurobehavioral condition influenced by several cellular and molecular mechanisms that are often concerned with synaptogenesis and synaptic activity. Based on the excitation/inhibition (E/I) imbalance theory, ASD could be the result of disruption in excitatory and inhibitory synaptic transmission across the brain. The prefrontal cortex (PFC) is the chief regulator of executive function and can be affected by altered neuronal excitation and inhibition in the course of ASD. The molecular mechanisms involved in E/I imbalance are subject to epigenetic regulation. In ASD, altered enrichment and spreading of histone H3 and H4 modifications such as the activation-linked H3K4me2/3, H3K9ac, and H3K27ac, and repression-linked H3K9me2, H3K27me3, and H4K20me2 in the PFC result in dysregulation of molecules mediating synaptic excitation (ARC, EGR1, mGluR2, mGluR3, GluN2A, and GluN2B) and synaptic inhibition (BSN, EphA7, SLC6A1). Histone modifications are a dynamic component of the epigenetic regulatory elements with a pronounced effect on patterns of gene expression with regards to any biological process. The excitation/inhibition imbalance associated with ASD is based on the excitatory and inhibitory synaptic activity in different regions of the brain, including the PFC, the ultimate outcome of which is highly influenced by transcriptional activity of relevant genes.

Individuals with severe and treatment-resistant obsessive-compulsive disorder (trOCD) represent a small but severely disabled group of patients. Since trOCD cases eligible for deep brain stimulation (DBS) probably comprise the most severe end of the OCD spectrum, we hypothesize that they may be more likely to have a strong genetic contribution to their disorder. Therefore, while the worldwide population of DBS-treated cases may be small (~300), screening these individuals with modern genomic methods may accelerate gene discovery in OCD. As such, we have begun to collect DNA from trOCD cases who qualify for DBS, and here we report results from whole exome sequencing and microarray genotyping of our first five cases. All participants had previously received DBS in the bed nucleus of stria terminalis (BNST), with two patients responding to the surgery and one showing a partial response. Our analyses focused on gene-disruptive rare variants (GDRVs; rare, predicted-deleterious single-nucleotide variants or copy number variants overlapping protein-coding genes). Three of the five cases carried a GDRV, including a missense variant in the ion transporter domain of KCNB1, a deletion at 15q11.2, and a duplication at 15q26.1. The KCNB1 variant (hg19 chr20-47991077-C-T, NM_004975.3:c.1020G>A, p.Met340Ile) causes substitution of methionine for isoleucine in the trans-membrane region of neuronal potassium voltage-gated ion channel KV2.1. This KCNB1 substitution (Met340Ile) is located in a highly constrained region of the protein where other rare missense variants have previously been associated with neurodevelopmental disorders. The patient carrying the Met340Ile variant responded to DBS, which suggests that genetic factors could potentially be predictors of treatment response in DBS for OCD. In sum, we have established a protocol for recruiting and genomically characterizing trOCD cases. Preliminary results suggest that this will be an informative strategy for finding risk genes in OCD.

Major depressive disorder (MDD) is a debilitating and prevalent mental disorder with a high disease burden. Despite a wide array of different treatment options, many patients do not respond to initial treatment attempts. Selection of the most appropriate treatment remains a significant clinical challenge in psychiatry, highlighting the need for the development of biomarkers with predictive utility. Recently, the epigenetic modification DNA methylation (DNAm) has emerged to be of great interest as a potential predictor of MDD treatment outcomes. Here, we review efforts to date that seek to identify DNAm signatures associated with treatment response in individuals with MDD. Searches were conducted in the databases PubMed, Scopus, and Web of Science with the concepts and keywords MDD, DNAm, antidepressants, psychotherapy, cognitive behavior therapy, electroconvulsive therapy, transcranial magnetic stimulation, and brain stimulation therapies. We identified 32 studies implicating DNAm patterns associated with MDD treatment outcomes. The majority of studies (N = 25) are focused on selected target genes exploring treatment outcomes in pharmacological treatments (N = 22) with a few studies assessing treatment response to electroconvulsive therapy (N = 3). Additionally, there are few genome-scale efforts (N = 7) to characterize DNAm patterns associated with treatment outcomes. There is a relative dearth of studies investigating DNAm patterns in relation to psychotherapy, electroconvulsive therapy, or transcranial magnetic stimulation; importantly, most existing studies have limited sample sizes. Given the heterogeneity in both methods and results of studies to date, there is a need for additional studies before existing findings can inform clinical decisions.