Search

Background: Social withdrawal is a core neuropsychiatric phenomenon in developmental psychopathology. Its presence predicts psychopathology across many domains, including depression, psychosis, autism, anxiety, and suicide. Withdrawn behavior is highly heritable, persistent, and characteristically worsens without intervention. To date, few studies have successfully identified genetic associations with withdrawn behavior, despite the abundance of evidence of its heritability. This may be due to reliance of categorical over dimensional measures of the behaviorally inhibited phenotype. The aim of this study is to identify associations between known psychiatric candidate genes and a dimensionally derived measure of withdrawn behavior. Methods: Genetic information was collected on 20 single-nucleotide polymorphisms (SNPs) from a custom-designed SNP chip and TAQMAN arrays of 4 variable number of tandem repeat (VNTR) genes for 551 individuals from 187 families. Linear mixed modeling was employed to examine the relationship between genotypes of interest and Child Behavior Checklist (CBCL) Withdrawn Behavior Subscale Score (WBS) while controlling for gender and age through multiple linear regressions. Results: Withdrawn behavior was highly associated with polymorphism "rs6314" of the serotonin receptor 2A ("HTR2A") [p = 0.009, estimate = 0.310 (bootstrap 95% CI 0.155-0.448), bootstrap p = 0.001] and "rs1800544" of the alpha 2-adrenergic ("ADRA2A") [ p = 0.001, estimate = -0.310 (bootstrap 95% CI -0.479 to -0.126), bootstrap p = 0.001] genes after correction for gender and age. The association between withdrawn behavior and "ADRA2A" was stronger for younger children. Conclusions: "HTR2A" and "ADRA2A" genes are associated with withdrawn behavior. This reinforces the role of catecholaminergic genes in the heritability of withdrawn behavior.

Objective: Although oppositional defiant disorder (ODD) is usually considered the mildest of the disruptive behavior disorders, it is a key factor in predicting young adult anxiety and depression and is distinguishable from normal childhood behavior. In an effort to understand possible subsets of oppositional defiant behavior (ODB) that may differentially predict outcome, we used latent class analysis of mother report on the Conners' Parent Rating Scales Revised Short Forms (CPRS-R:S). Method: Data were obtained from mother report for Dutch twins (7 years old, n = 7,597; 10 years old, n = 6,548; and 12 years old, n = 5,717) from the Netherlands Twin Registry. Samples partially overlapped at ages 7 and 10 years (19% overlapping) and at ages 10 and 12 years (30% overlapping), but not at ages 7 and 12 years. Oppositional defiant behavior was measured using the six-item Oppositional subscale of the CPRS-R:S. Multilevel LCA with robust standard error estimates was performed using the Latent Gold program to control for twin-twin dependence in the data. Class assignment across ages was determined and an estimate of heritability for each class was calculated. Comparisons with maternal report Child Behavior Checklist (CBCL) scores were examined using linear mixed models at each age, corrected for multiple comparisons. Results: The LCA identified an optimal solution of four classes across age groups. Class 1 was associated with no or low symptom endorsement (69-75% of the children); class 2 was characterized by defiance (11-12%); class 3 was characterized by irritability (9-11%); and class 4 was associated with elevated scores on all symptoms (5-8%). Odds ratios for twins being in the same class at each successive age point were higher within classes across ages than between classes. Heritability within the two "intermediate" classes was nearly as high as for the class with all symptoms, except for boys at age 12. Children in the Irritable class were more likely to have mood symptoms on the CBCL scales than children in the Defiant class but demonstrated similar scores on aggression and externalizing scales. Children in the All Symptoms class were higher in both internalizing and externalizing scales and subscales. Conclusions: The LCA indicates four distinct latent classes of oppositional defiant behavior, in which the distinguishing feature between the two intermediate classes (classes 2 and 3) is the level of irritability and defiance. Implications for the longitudinal course of these symptoms, association with other disorders, and genetics are discussed. (Contains 4 figures and 8 tables.)

Objective: To test the association between the catechol-O-methyltransferase (COMT) Val158Met polymorphism and both aggressive behavior and attention problems in youth. We hypothesized that youth carrying a Met allele would have greater average aggressive behavior scores, and that youth exhibiting Val-homozygosity would have greater average attention problems scores. Method: Complete data on maternally rated Child Behavior Checklist (CBCL) measures of aggressive behavior (AGG) and attention problems (AP), COMT polymorphism data, demographics, and maternal parenting quality were available for 149 youth (6 to 18 years old). Multivariable linear regression models were used to test the degree to which youth COMT Val158Met genotype was associated with AGG and AP while statistically controlling for age, gender, parental socioeconomic status (SES), and maternal parenting quality from the Alabama Parenting Questionnaire. Results: Mothers of Met-carriers rated their children higher on average AGG scores when compared with mothers of Val-homozygotes (p = 0.016). Further analyses revealed that this association was even more robust for maternal ratings of direct aggression (p = 0.007). The hypothesized association between Val-homozygosity and higher average AP scores relative to average AP scores of Met-carriers did not quite reach statistical significance (p = 0.062). Conclusions: After controlling for demographics, SES, and maternal parenting quality as confounders, there remains a strong association between youth carrying a Met allele and higher average AGG scores relative to Val-homozygotes. (Contains 2 tables.)

Objective: To estimate the genetic and environmental contributions to oppositional defiant behavior (ODB) from mother, father, and teacher report using the Conners Revised Short Forms in a large twin sample. Method: ODB data were collected from 1,595 mothers, 1,114 fathers, and 793 teachers of 7-year-old twin pairs from the Netherlands Twin Registry in the 1990-1992 cohort with an 80% response rate. Models were fit for each informant to determine the genetic, environmental, gender, and informant influences on ODB. Results: Genetic analyses of the ODB quantitative scale showed additive genetic (A) by mother (55%), by father (57%), and by teacher (21% girls, 38% boys) unique environmental (E) (mother, 22%; father, 29%; teacher, 48% girls, 39% boys) and shared environmental (C) (mother, 14%; father, 23%; teacher, 31% girls, 23% boys) influences. Conclusions: Additive genetic and unique environmental factors account for the majority of the influences on ODB for boys and girls by all informants.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Copy number variations (CNVs) have been reported to be causal suspects in a variety of psychopathologic traits. We investigate whether de novo and/or inherited CNVs contribute to the risk for Attention Problems (APs) in children. Based on longitudinal phenotyping, 50 concordant and discordant monozygotic (MZ) twin pairs were selected from a sample of ∼3200 MZ pairs. Two types of de novo CNVs were investigated: (1) CNVs shared by both MZ twins, but not inherited (pre-twinning de novo CNVs), which were detected by comparing copy number (CN) calls between parents and twins and (2) CNVs not shared by co-twins (post-twinning de novo CNVs), which were investigated by comparing the CN calls within MZ pairs. The association between the overall CNV burden and AP was also investigated for CNVs genome-wide, CNVs within genes and CNVs outside of genes. Two de novo CNVs were identified and validated using quantitative PCR: a pre-twinning de novo duplication in a concordant-unaffected twin pair and a post-twinning deletion in the higher scoring twin from a concordant-affected pair. For the overall CNV burden analyses, affected individuals had significantly larger CNVs that overlapped with genes than unaffected individuals (P=0.008). This study suggests that the presence of larger CNVs may increase the risk for AP, because they are more likely to affect genes, and confirms that MZ twins are not always genetically identical. [ABSTRACT FROM AUTHOR]

Juvenile bipolar disorder (JBD) has been a subject of significant research and debate. Phenotypic differences between JBD and adult-onset bipolar disorder have led researchers to question whether or not similar neuropathologic mechanisms will be found. While much is known about the genetic and environmental contributions to the adult-onset phenotype, less is known about their contributions to JBD. Here, we review family, twin, adoption, and molecular genetic studies of JBD. Behavioral genetic data suggest both genetic and environmental contributions to JBD, while molecular genetic studies find linkage to age of onset of bipolar disorder to chromosomes 12p, 14q, and 15q. Additionally, changes associated with symptom age of onset have been recently reported in the brain-derived neurotrophic factor (BDNF) and glycogen synthase kinase 3-beta (GSK3-beta) genes. We contend that further progress in discovering the precise genetic and environmental contributions to JBD may depend on advances in phenotypic refinement, an increased appreciation of comorbid conditions, and more investigation of the longitudinal course of the disorder. [ABSTRACT FROM AUTHOR]

The article discusses the significance of behavioral genetics (BG) in child and adolescent psychiatry. It mentions that BG would provide sensible foundation on understanding the causality in child psychiatry. It states that BG would use large samples of twins, siblings and families to do molecular genetic studies.

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved). [ABSTRACT FROM AUTHOR]

Background: The Child Behavior Checklist–juvenile bipolar disorder phenotype (CBCL-JBD) is a quantitative phenotype that is based on parental ratings of the behavior of the child. The phenotype is predictive of DSM-IV characterizations of BD and has been shown to be sensitive and specific. Its genetic architecture differs from that for inattentive, aggressive, or anxious–depressed syndromes. The purpose of this study is to assess the developmental stability of the CBCL-JBD phenotype across ages 7, 10, and 12 years in a large population-based twin sample and to examine its genetic architecture. Methods: Longitudinal data on Dutch mono- and dizygotic twin pairs (N = 8013 pairs) are analyzed to decompose the stability of the CBCL-JBD phenotype into genetic and environmental contributions. Results: Heritability of the CBCL-JBD increases with age (from 63% to 75%), whereas the effects of shared environment decrease (from 20% to 8%). The stability of the CBCL-JBD phenotype is high, with correlations between .66 and .77 across ages 7, 10, and 12 years. Genetic factors account for the majority of the stability of this phenotype. There were no sex differences in genetic architecture. Conclusions: Roughly 80% of the stability in childhood CBCL-JBD is a result of additive genetic effects. [Copyright &y& Elsevier]