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1.
Transl Psychiatry ; 9(1): 283, 2019 Nov 11.
Artigo em Inglês | MEDLINE | ID: mdl-31712607

RESUMO

Infections and mental disorders are two of the major global disease burdens. While correlations between mental disorders and infections have been reported, the possible genetic links between them have not been assessed in large-scale studies. Moreover, the genetic basis of susceptibility to infection is largely unknown, as large-scale genome-wide association studies of susceptibility to infection have been lacking. We utilized a large Danish population-based sample (N = 65,534) linked to nationwide population-based registers to investigate the genetic architecture of susceptibility to infection (heritability estimation, polygenic risk analysis, and a genome-wide association study (GWAS)) and examined its association with mental disorders (comorbidity analysis and genetic correlation). We found strong links between having at least one psychiatric diagnosis and the occurrence of infection (P = 2.16 × 10-208, OR = 1.72). The SNP heritability of susceptibility to infection ranged from ~2 to ~7% in samples of differing psychiatric diagnosis statuses (suggesting the environment as a major contributor to susceptibility), and polygenic risk scores moderately but significantly explained infection status in an independent sample. We observed a genetic correlation of 0.496 (P = 2.17 × 10-17) between a diagnosis of infection and a psychiatric diagnosis. While our GWAS did not identify genome-wide significant associations, we found 90 suggestive (P ≤ 10-5) associations for susceptibility to infection. Our findings suggest a genetic component in susceptibility to infection and indicate that the occurrence of infections in individuals with mental illness may be in part genetically driven.

2.
Nat Hum Behav ; 3(10): 1124, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31554938

RESUMO

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

3.
Hum Genet ; 2019 Sep 13.
Artigo em Inglês | MEDLINE | ID: mdl-31520123

RESUMO

In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.

4.
Nat Commun ; 10(1): 3927, 2019 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-31477735

RESUMO

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10-14). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.

5.
Mol Psychiatry ; 2019 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-31427753

RESUMO

Difficulties with higher-order cognitive functions in youth are a potentially important vulnerability factor for the emergence of problematic behaviors and a range of psychopathologies. This study examined 2013 9-10 year olds in the first data release from the Adolescent Brain Cognitive Development 21-site consortium study in order to identify resting state functional connectivity patterns that predict individual-differences in three domains of higher-order cognitive functions: General Ability, Speed/Flexibility, and Learning/Memory. For General Ability scores in particular, we observed consistent cross-site generalizability, with statistically significant predictions in 14 out of 15 held-out sites. These results survived several tests for robustness including replication in split-half analysis and in a low head motion subsample. We additionally found that connectivity patterns involving task control networks and default mode network were prominently implicated in predicting differences in General Ability across participants. These findings demonstrate that resting state connectivity can be leveraged to produce generalizable markers of neurocognitive functioning. Additionally, they highlight the importance of task control-default mode network interconnections as a major locus of individual differences in cognitive functioning in early adolescence.

6.
Nat Hum Behav ; 3(9): 999, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31384026

RESUMO

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

7.
Neuroimage ; 202: 116091, 2019 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-31415884

RESUMO

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

8.
Nat Commun ; 10(1): 2417, 2019 06 03.
Artigo em Inglês | MEDLINE | ID: mdl-31160569

RESUMO

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures.


Assuntos
Transtorno Bipolar/genética , Modelos Genéticos , Modelos Estatísticos , Herança Multifatorial , Esquizofrenia/genética , Frequência do Gene , Estudo de Associação Genômica Ampla , Humanos , Desequilíbrio de Ligação
9.
Nat Hum Behav ; 3(7): 692-701, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31110341

RESUMO

Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial1 findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-2-4 and large-sample5,6 studies have reported a bilingual executive function advantage (see refs. 7-9 for a review), there have been several failures to replicate these findings10-15, and recent meta-analyses have called into question the reliability of the original empirical claims8,9. Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals7,16,17. However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood18, we found little evidence that it engenders additional benefits to executive function development.

10.
Artigo em Inglês | MEDLINE | ID: mdl-31134293

RESUMO

RATIONALE: The impact of neuroscience-based approaches for psychiatry on pragmatic clinical decision-making has been limited. Although neuroscience has provided insights into basic mechanisms of neural function, these insights have not improved the ability to generate better assessments, prognoses, diagnoses, or treatment of psychiatric conditions. OBJECTIVES: To integrate the emerging findings in machine learning and computational psychiatry to address the question: what measures that are not derived from the patient's self-assessment or the assessment by a trained professional can be used to make more precise predictions about the individual's current state, the individual's future disease trajectory, or the probability to respond to a particular intervention? RESULTS: Currently, the ability to use individual differences to predict differential outcomes is very modest possibly related to the fact that the effect sizes of interventions are small. There is emerging evidence of genetic and neuroimaging-based heterogeneity of psychiatric disorders, which contributes to imprecise predictions. Although the use of machine learning tools to generate clinically actionable predictions is still in its infancy, these approaches may identify subgroups enabling more precise predictions. In addition, computational psychiatry might provide explanatory disease models based on faulty updating of internal values or beliefs. CONCLUSIONS: There is a need for larger studies, clinical trials using machine learning, or computational psychiatry model parameters predictions as actionable outcomes, comparing alternative explanatory computational models, and using translational approaches that apply similar paradigms and models in humans and animals.

11.
Eur J Hum Genet ; 27(9): 1445-1455, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30976114

RESUMO

Human leukocyte antigen (HLA) genes encode proteins with important roles in the regulation of the immune system. Many studies have also implicated HLA genes in psychiatric and neurodevelopmental disorders. However, these studies usually focus on one disorder and/or on one HLA candidate gene, often with small samples. Here, we access a large dataset of 65,534 genotyped individuals consisting of controls (N = 19,645) and cases having one or more of autism spectrum disorder (N = 12,331), attention deficit hyperactivity disorder (N = 14,397), schizophrenia (N = 2401), bipolar disorder (N = 1391), depression (N = 18,511), anorexia (N = 2551) or intellectual disability (N = 3175). We imputed participants' HLA alleles to investigate the involvement of HLA genes in these disorders using regression models. We found a pronounced protective effect of DPB1*1501 on susceptibility to autism (p = 0.0094, OR = 0.72) and intellectual disability (p = 0.00099, OR = 0.41), with an increased protective effect on a comorbid diagnosis of both disorders (p = 0.003, OR = 0.29). We also identified a risk allele for intellectual disability, B*5701 (p = 0.00016, OR = 1.33). Associations with both alleles survived FDR correction and a permutation procedure. We did not find significant evidence for replication of previously-reported associations for autism or schizophrenia. Our results support an implication of HLA genes in autism and intellectual disability, which requires replication by other studies. Our study also highlights the importance of large sample sizes in HLA association studies.

12.
J Affect Disord ; 252: 350-357, 2019 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-30999091

RESUMO

BACKGROUND: Post-traumatic stress disorder (PTSD) is a complex psychiatric disorder that occurs with relatively high frequency after deployment to warzones (∼10%). While twin studies have estimated the heritability to be up to 40%, thus indicating a considerable genetic component in the etiology, the biological mechanisms underlying risk and development of PTSD remain unknown. METHODS: Here, we conduct a genome-wide association study (GWAS; N = 2,481) to identify genome regions that associate with PTSD in a highly homogenous, trauma-exposed sample of Danish soldiers deployed to war and conflict zones. We perform integrated analyses of our results with gene-expression and chromatin-contact datasets to prioritized genes. We also leverage on other large GWAS (N>300,000) to investigate genetic correlations between PTSD and other psychiatric disorders and traits. RESULTS: We discover, but do not replicate, one region, 4q31, close to the IL15 gene, which is genome-wide significantly associated with PTSD. We demonstrate that gene-set enrichment, polygenic risk score and genetic correlation analyses show consistent and significant genetic correlations between PTSD and depression, insomnia and schizophrenia. LIMITATIONS: The limited sample size, the lack of replication, and the PTSD case definition by questionnaire are limitations to the study. CONCLUSIONS: Our results suggest that genetic perturbations of inflammatory response may contribute to the risk of PTSD. In addition, shared genetic components contribute to observed correlations between PTSD and depression, insomnia and schizophrenia.

13.
Psychol Med ; : 1-9, 2019 Mar 08.
Artigo em Inglês | MEDLINE | ID: mdl-30846008

RESUMO

BACKGROUND: Callous-unemotional (CU) traits are critical to developmental, diagnostic, and clinical models of antisocial behaviors (AB). However, assessments of CU traits within large-scale longitudinal and neurobiologically focused investigations remain remarkably sparse. We sought to develop a brief measure of CU traits using items from widely administered instruments that could be linked to neuroimaging, genetic, and environmental data within already existing datasets and future studies. METHODS: Data came from a large and diverse sample (n = 4525) of youth (ages~9-11) taking part in the Adolescent Brain and Cognitive Development (ABCD) Study. Moderated nonlinear factor analysis was used to assess measurement invariance across sex, race, and age. We explored whether CU traits were distinct from other indicators of AB, investigated unique links with theoretically-relevant outcomes, and replicated findings in an independent sample. RESULTS: The brief CU traits measure demonstrated strong psychometric properties and evidence of measurement invariance across sex, race, and age. On average, boys endorsed higher levels of CU traits than girls and CU traits were related to, yet distinguishable from other indicators of AB. The CU traits construct also exhibited expected associations with theoretically important outcomes. Study findings were also replicated across an independent sample of youth. CONCLUSIONS: In a large, multi-site study, a brief measure of CU traits can be measured distinctly from other dimensions of AB. This measure provides the scientific community with a method to assess CU traits in the ABCD sample, as well as in other studies that may benefit from a brief assessment of CU.

15.
Nat Neurosci ; 22(3): 353-361, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30692689

RESUMO

There is mounting evidence that seemingly diverse psychiatric disorders share genetic etiology, but the biological substrates mediating this overlap are not well characterized. Here we leverage the unique Integrative Psychiatric Research Consortium (iPSYCH) study, a nationally representative cohort ascertained through clinical psychiatric diagnoses indicated in Danish national health registers. We confirm previous reports of individual and cross-disorder single-nucleotide polymorphism heritability for major psychiatric disorders and perform a cross-disorder genome-wide association study. We identify four novel genome-wide significant loci encompassing variants predicted to regulate genes expressed in radial glia and interneurons in the developing neocortex during mid-gestation. This epoch is supported by partitioning cross-disorder single-nucleotide polymorphism heritability, which is enriched at regulatory chromatin active during fetal neurodevelopment. These findings suggest that dysregulation of genes that direct neurodevelopment by common genetic variants may result in general liability for many later psychiatric outcomes.


Assuntos
Encéfalo/embriologia , Regulação da Expressão Gênica , Predisposição Genética para Doença , Transtornos Mentais/genética , Encéfalo/metabolismo , Estudos de Coortes , Feminino , Loci Gênicos , Estudo de Associação Genômica Ampla , Humanos , Masculino , Polimorfismo de Nucleotídeo Único , Fatores de Risco
16.
Dev Cogn Neurosci ; 36: 100606, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30595399

RESUMO

The Adolescent Brain Cognitive Development (ABCD) study is poised to be the largest single-cohort long-term longitudinal study of neurodevelopment and child health in the United States. Baseline data on N= 4521 children aged 9-10 were released for public access on November 2, 2018. In this paper we performed principal component analyses of the neurocognitive assessments administered to the baseline sample. The neurocognitive battery included seven measures from the NIH Toolbox as well as five other tasks. We implemented a Bayesian Probabilistic Principal Components Analysis (BPPCA) model that incorporated nesting of subjects within families and within data collection sites. We extracted varimax-rotated component scores from a three-component model and associated these scores with parent-rated Child Behavior Checklist (CBCL) internalizing, externalizing, and stress reactivity. We found evidence for three broad components that encompass general cognitive ability, executive function, and learning/memory. These were significantly associated with CBCL scores in a differential manner but with small effect sizes. These findings set the stage for longitudinal analysis of neurocognitive and psychopathological data from the ABCD cohort as they age into the period of maximal adolescent risk-taking.


Assuntos
Desenvolvimento do Adolescente/fisiologia , Encéfalo/fisiopatologia , Cognição/fisiologia , Transtornos Neurocognitivos/diagnóstico , Comportamento Problema/psicologia , Adolescente , Criança , Feminino , Humanos , Estudos Longitudinais , Masculino , Transtornos Neurocognitivos/patologia
17.
Neuroimage ; 185: 140-153, 2019 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-30339913

RESUMO

The adolescent brain undergoes profound structural changes which is influenced by many factors. Screen media activity (SMA; e.g., watching television or videos, playing video games, or using social media) is a common recreational activity in children and adolescents; however, its effect on brain structure is not well understood. A multivariate approach with the first cross-sectional data release from the Adolescent Brain Cognitive Development (ABCD) study was used to test the maturational coupling hypothesis, i.e. the notion that coordinated patterns of structural change related to specific behaviors. Moreover, the utility of this approach was tested by determining the association between these structural correlation networks and psychopathology or cognition. ABCD participants with usable structural imaging and SMA data (N = 4277 of 4524) were subjected to a Group Factor Analysis (GFA) to identify latent variables that relate SMA to cortical thickness, sulcal depth, and gray matter volume. Subject scores from these latent variables were used in generalized linear mixed-effect models to investigate associations between SMA and internalizing and externalizing psychopathology, as well as fluid and crystalized intelligence. Four SMA-related GFAs explained 37% of the variance between SMA and structural brain indices. SMA-related GFAs correlated with brain areas that support homologous functions. Some but not all SMA-related factors corresponded with higher externalizing (Cohen's d effect size (ES) 0.06-0.1) but not internalizing psychopathology and lower crystalized (ES: 0.08-0.1) and fluid intelligence (ES: 0.04-0.09). Taken together, these findings support the notion of SMA related maturational coupling or structural correlation networks in the brain and provides evidence that individual differences of these networks have mixed consequences for psychopathology and cognitive performance.


Assuntos
Desenvolvimento do Adolescente , Encéfalo/patologia , Rede Nervosa/patologia , Tempo de Tela , Adolescente , Desenvolvimento do Adolescente/fisiologia , Criança , Cognição/fisiologia , Estudos Transversais , Feminino , Humanos , Interpretação de Imagem Assistida por Computador , Individualidade , Estudos Longitudinais , Masculino , Transtornos Mentais/etiologia
18.
Nat Commun ; 9(1): 5296, 2018 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-30546018

RESUMO

Spatial mapping is a promising strategy to investigate the mechanisms underlying the incidence of psychosis. We analyzed a case-cohort study (n = 24,028), drawn from the 1.47 million Danish persons born between 1981 and 2005, using a novel framework for decomposing the geospatial risk for schizophrenia based on locale of upbringing and polygenic scores. Upbringing in a high environmental risk locale increases the risk for schizophrenia by 122%. Individuals living in a high gene-by-environmental risk locale have a 78% increased risk compared to those who have the same genetic liability but live in a low-risk locale. Effects of specific locales vary substantially within the most densely populated city of Denmark, with hazard ratios ranging from 0.26 to 9.26 for environment and from 0.20 to 5.95 for gene-by-environment. These findings indicate the critical synergism of gene and environment on the etiology of schizophrenia and demonstrate the potential of incorporating geolocation in genetic studies.


Assuntos
Meio Ambiente , Predisposição Genética para Doença/genética , Geografia , Esquizofrenia/epidemiologia , Esquizofrenia/genética , Mapeamento Cromossômico/métodos , Dinamarca/epidemiologia , Humanos , Estudo de Prova de Conceito , Fatores de Risco
19.
Front Aging Neurosci ; 10: 317, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30405393

RESUMO

Several imaging modalities, including T1-weighted structural imaging, diffusion tensor imaging, and functional MRI can show chronological age related changes. Employing machine learning algorithms, an individual's imaging data can predict their age with reasonable accuracy. While details vary according to modality, the general strategy is to: (1) extract image-related features, (2) build a model on a training set that uses those features to predict an individual's age, (3) validate the model on a test dataset, producing a predicted age for each individual, (4) define the "Brain Age Gap Estimate" (BrainAGE) as the difference between an individual's predicted age and his/her chronological age, (5) estimate the relationship between BrainAGE and other variables of interest, and (6) make inferences about those variables and accelerated or delayed brain aging. For example, a group of individuals with overall positive BrainAGE may show signs of accelerated aging in other variables as well. There is inevitably an overestimation of the age of younger individuals and an underestimation of the age of older individuals due to "regression to the mean." The correlation between chronological age and BrainAGE may significantly impact the relationship between BrainAGE and other variables of interest when they are also related to age. In this study, we examine the detectability of variable effects under different assumptions. We use empirical results from two separate datasets [training = 475 healthy volunteers, aged 18-60 years (259 female); testing = 489 participants including people with mood/anxiety, substance use, eating disorders and healthy controls, aged 18-56 years (312 female)] to inform simulation parameter selection. Outcomes in simulated and empirical data strongly support the proposal that models incorporating BrainAGE should include chronological age as a covariate. We propose either including age as a covariate in step 5 of the above framework, or employing a multistep procedure where age is regressed on BrainAGE prior to step 5, producing BrainAGE Residualized (BrainAGER) scores.

20.
Alzheimers Dement (Amst) ; 10: 657-668, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30456292

RESUMO

Introduction: We characterize long-term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative. Methods: We apply a latent time joint mixed-effects model to 16 cognitive, functional, biomarker, and imaging outcomes in Alzheimer's Disease Neuroimaging Initiative. Markov chain Monte Carlo methods are used for estimation and inference. Results: We find good concordance between latent time and diagnosis. Change in amyloid positron emission tomography shows a moderate correlation with change in cerebrospinal fluid tau (ρ = 0.310) and phosphorylated tau (ρ = 0.294) and weaker correlation with amyloid-ß 42 (ρ = 0.176). In comparison to amyloid positron emission tomography, change in volumetric magnetic resonance imaging summaries is more strongly correlated with cognitive measures (e.g., ρ = 0.731 for ventricles and Alzheimer's Disease Assessment Scale). The average disease trends are consistent with the amyloid cascade hypothesis. Discussion: The latent time joint mixed-effects model can (1) uncover long-term disease trends; (2) estimate the sequence of pathological abnormalities; and (3) provide subject-specific prognostic estimates of the time until onset of symptoms.

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