Infant neurodevelopment during the COVID-19 pandemic: Associations with maternal pandemic-related experiences, parenting stress, and self-efficacy

BACKGROUND

Although pandemic-related experiences have been linked to the psychological well-being of mothers, the effects of the COVID-19 pandemic on infant neurodevelopmental outcomes have not been sufficiently studied.

AIMS

To assess whether maternal COVID-19-related experiences (i.e., COVID-19-related health, risk, resource worries, and feelings of grief), parenting stress, and maternal self-efficacy are associated with infant neurodevelopment as measured by the Ages and Stages Questionnaire, Third Edition (ASQ-3) maternal report when infants were between 8 to 10 months of age. Furthermore, this study examined the moderating effect of maternal self-efficacy between maternal COVID-19-related experiences and infant neurodevelopment.

METHODS

This cross-sectional study included 122 women who were drawn from the Perinatal Experiences and COVID-19 Effects (PEACE) Study, with online surveys administered between November 2020 and August 2022.

RESULTS

After controlling for maternal anxiety and depression symptoms and demographic factors, hierarchical regression analysis indicated that parenting stress showed no effect on ASQ-3 scores. However, more adverse COVID-19-related experiences and higher levels of maternal self-efficacy were associated with better infant neurodevelopment. Moreover, there was a significant interaction effect between maternal self-efficacy and COVID-19-related experiences on infant neurodevelopment. For mothers with moderate to high levels of self-efficacy, more adverse COVID-19-related experiences were associated with better infant neurodevelopment. For mothers with low levels of self-efficacy, more adverse COVID-19-related experiences were associated with poorer developmental outcomes in infants.

CONCLUSIONS

Under adverse conditions, confidence in caregiving may afford more optimal infant neurodevelopment. Interventions aimed at fostering maternal self-efficacy and addressing specific stressors can be valuable in promoting positive developmental trajectories for infants born during the pandemic.

Prenatal mental health and emotional experiences during the pandemic: associations with infant neurodevelopment screening results

BACKGROUND

This study determined whether parental mental health and emotional experiences during the prenatal period were linked to infant developmental outcomes through the Ages and Stages Questionnaire (ASQ-3) at 8-10 months.

METHODS

Participants included 133 individuals who were living in the US and were pregnant or had given birth within 6 months prior to enrollment. Respondents were majority White with high education and income levels. Online surveys were administered from May 2020 to September 2021; follow-up surveys were administered from November 2020 to August 2022.

RESULTS

Parent generalized anxiety symptoms were positively associated with infant communication (β = 0.34, 95% CI [0.15, 1.76], p < 0.05), while parent-fetal bonding was positively associated with infant communication (β = 0.20, 95% CI [0.05, 0.76], p < 0.05) and personal-social performance (β = 0.20, 95% CI [0.04, 0.74], p < 0.05). COVID-19-related worry was negatively associated with infant communication (β = -0.30, 95% CI [-0.75, -0.12], p < 0.05) and fine motor performance (β = -0.25, 95% CI [-0.66, -0.03], p < 0.05).

CONCLUSION

Parent mental health and emotional experiences may contribute to infant developmental outcomes in high risk conditions such as a pandemic.

IMPACT STATEMENT

Maternal SARS-CoV-2 infection has been evaluated in relation to child outcomes, however, parent psychosocial experiences should not be overlooked when considering pandemic risks to child development. Specific prenatal mental health and pandemic-related emotional experiences are associated with infant developmental performance, as assessed by the Ages and Stages. Questionnaire (ASQ-3) at 8 to 10 months old. Findings indicate that parental prenatal anxiety and emotional experiences from the pandemic should be assessed when evaluating child developmental delays.

Validation of an ICD-code-based case definition for psychotic illness across three health systems

Background and Hypothesis

Early detection of psychosis is critical for improving outcomes. Algorithms to predict or detect psychosis using electronic health record (EHR) data depend on the validity of the case definitions used, typically based on diagnostic codes. Data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.

Study Design

Using EHRs at three health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into five higher-order groups. 1,133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings.

Study Results

PPVs across all diagnostic groups and hospital systems exceeded 70%: Massachusetts General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62).

Conclusions

We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the development of risk prediction models designed to predict or detect undiagnosed psychosis.

State-Level Recreational Cannabis Legalization Is Not Differentially Associated with Cannabis Risk Perception Among Children: A Multilevel Regression Analysis

Introduction: As more states pass recreational cannabis laws (RCLs) for adults, there is concern that increasing (and state-sanctioned) cannabis acceptance will result in a reduced perception of risk of harm from cannabis among children. We aimed to discover whether children in states with RCLs had decreased perception of risk from cannabis compared with children in states with illicit cannabis. Methods: We analyzed data from the multisite multistate Adolescent Brain and Cognitive Development Study to determine how the perception of cannabis harm among children (age at baseline: 9-10; N=10,395) changes over time in states with and without RCLs. Using multilevel modeling, we assessed survey responses from children longitudinally across 3 years, adjusting for state-, family-, and participant-level clustering and child-level factors, including demographics (sex, race, and socioeconomic status), religiosity, and trait impulsivity. Results: There was no significant main effect of state RCLs on perceived risk of cannabis use, and no differences in change over time by state RCLs, even after controlling for demographic factors and other risk (e.g., impulsivity) and protective (e.g., religiosity) factors. Conclusions: This analysis indicates that state-level RCLs are not associated with differential perception of cannabis risk among children, even after controlling for demographics, trait impulsivity, and religiosity. Future studies could assess how perception of risk from cannabis changes as children and adolescents continue to mature in states with and without RCLs.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

Youth Team Sports Participation Associates With Reduced Dimensional Psychopathology Through Interaction With Biological Risk Factors

Background

Physical activity is associated with mental health benefits in youth. Here, we used causal inference and triangulation with 2 levels of biology to substantiate relationships between sports participation and dimensional psychopathology in youths.

Methods

Baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, which recruited children from 9 to 10 years of age across the United States, were included in multilevel regression models to assess relationships between lifetime participation in team sports (TS), individual sports, and nonsports activities and Child Behavior Checklist (CBCL) scores. We calculated polygenic risk scores for 8 psychiatric disorders to assess interactions with sports exposure on CBCL scores among European descendants. Following rigorous quality control, FreeSurfer-extracted brain magnetic resonance imaging structural data were examined for mediation of CBCL-activities relationships.

Results

Among those with complete data (N = 10,411), causal estimates using inverse probability weighting associated lifetime TS exposure with a 1.05-point reduction in CBCL total (95% CI, -1.54 to -0.56, p < .0001) a relationship that was specific to TS and strengthened with more years of exposure. Associations of attention-deficit/hyperactivity disorder polygenic loading with CBCL total weakened in European children with TS exposure (n = 4041; beta = -0.93, SE = 0.38, p = .013). Furthermore, TS participation and lower CBCL each associated with increased subcortical volumes (n = 8197). Subcortical volume mediated 5.5% of TS effects on CBCL total.

Conclusions

Our findings support prior associations of TS participation with lower psychopathology in youths through additional studies that demonstrate specificity, dose response, and coherence across 2 levels of biology. Longitudinal studies that further clarify causal relationships may justify interventional studies of TS for high-risk youth.

Genetic patterning for child psychopathology is distinct from that for adults and implicates fetal cerebellar development

Childhood psychiatric symptoms are often diffuse but can coalesce into discrete mental illnesses during late adolescence. We leveraged polygenic scores (PGSs) to parse genomic risk for childhood symptoms and to uncover related neurodevelopmental mechanisms with transcriptomic and neuroimaging data. In independent samples (Adolescent Brain Cognitive Development, Generation R) a narrow cross-disorder neurodevelopmental PGS, reflecting risk for attention deficit hyperactivity disorder, autism, depression and Tourette syndrome, predicted psychiatric symptoms through early adolescence with greater sensitivity than broad cross-disorder PGSs reflecting shared risk across eight psychiatric disorders, the disorder-specific PGS individually or two other narrow cross-disorder (Compulsive, Mood-Psychotic) scores. Neurodevelopmental PGS-associated genes were preferentially expressed in the cerebellum, where their expression peaked prenatally. Further, lower gray matter volumes in cerebellum and functionally coupled cortical regions associated with psychiatric symptoms in mid-childhood. These findings demonstrate that the genetic underpinnings of pediatric psychiatric symptoms differ from those of adult illness, and implicate fetal cerebellar developmental processes that endure through childhood.

Uncovering and mitigating bias in large, automated MRI analyses of brain development

Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1,2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3,4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohen's d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Greater male than female variability in regional brain structure across the lifespan

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Association of Maternal Stress and Social Support During Pregnancy With Growth Marks in Children's Primary Tooth Enamel

IMPORTANCE

Exposure to maternal psychosocial stressors during the prenatal and perinatal periods can have major long-term mental health consequences for children. However, valid and inexpensive biomarkers are currently unavailable to identify children who have been exposed to psychosocial stress and the buffers of stress exposure.

OBJECTIVE

To assess whether a growth mark in tooth enamel, the neonatal line, is associated with exposure to prenatal and perinatal maternal psychosocial factors.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study used exfoliated primary canine teeth and epidemiological survey data from 70 children enrolled in the Avon Longitudinal Study of Parents and Children, a birth cohort based in Bristol, England. Exfoliated teeth were collected from children at 5 to 7 years of age. Data were collected from January 1, 1991, to December 31, 1998, and were analyzed from January 1, 2019, to August 10, 2021.

EXPOSURES

Four types of prenatal and perinatal maternal psychosocial factors were studied: stressful life events, psychopathological history, neighborhood disadvantage, and social support. Data were collected from mailed-in questionnaires completed during and shortly after pregnancy.

MAIN OUTCOMES AND MEASURES

Neonatal line width measured within 3 portions of the tooth crown (the cuspal, middle, and innermost third) in exfoliated primary canines.

RESULTS

A total of 70 children (34 of 70 [48.7%] male; 63 of 67 [94.0%] White) were studied. Most children were born full term (57 [83.8%]) and to mothers of typical child-bearing age (60 [88.2%]). Neonatal lines were wider in the canines of children born to mothers who self-reported severe lifetime depression (β = 3.35; 95% CI, 1.48-5.23; P = .001), any lifetime psychiatric problems (β = 2.66; 95% CI, 0.92-4.41; P = .003), or elevated anxiety or depressive symptoms at 32 weeks' gestation (β = 2.29; 95% CI, 0.38-4.20; P = .02). By contrast, neonatal lines were narrower in children born to mothers who self-reported high social support shortly after birth (β = -2.04; 95% CI, -3.70 to -0.38; P = .02). The magnitude of these associations was large, up to 1.2 SD unit differences, and persisted after adjusting for other risk factors.

CONCLUSIONS AND RELEVANCE

In this cohort study, neonatal line width was associated with exposure to maternal perinatal psychosocial factors. Replication and validation of these findings can further evaluate teeth as possible new biomarkers.

In vivo human brain expression of histone deacetylases in bipolar disorder

The etiology of bipolar disorder (BD) is unknown and the neurobiological underpinnings are not fully understood. Both genetic and environmental factors contribute to the risk of BD, which may be linked through epigenetic mechanisms, including those regulated by histone deacetylase (HDAC) enzymes. This study measures in vivo HDAC expression in individuals with BD for the first time using the HDAC-specific radiotracer [¹¹C]Martinostat. Eleven participants with BD and 11 age- and sex-matched control participants (CON) completed a simultaneous magnetic resonance - positron emission tomography (MR-PET) scan with [¹¹C]Martinostat. Lower [¹¹C]Martinostat uptake was found in the right amygdala of BD compared to CON. We assessed uptake in the dorsolateral prefrontal cortex (DLPFC) to compare previous findings of lower uptake in the DLPFC in schizophrenia and found no group differences in BD. Exploratory whole-brain voxelwise analysis showed lower [¹¹C]Martinostat uptake in the bilateral thalamus, orbitofrontal cortex, right hippocampus, and right amygdala in BD compared to CON. Furthermore, regional [¹¹C]Martinostat uptake was associated with emotion regulation in BD in fronto-limbic areas, which aligns with findings from previous structural, functional, and molecular neuroimaging studies in BD. Regional [¹¹C]Martinostat uptake was associated with attention in BD in fronto-parietal and temporal regions. These findings indicate a potential role of HDACs in BD pathophysiology. In particular, HDAC expression levels may modulate attention and emotion regulation, which represent two core clinical features of BD.

Working memory load-dependent changes in cortical network connectivity estimated by machine learning

Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to characterize the interactions among cortical networks that are sensitive to working memory load since such interactions can also hint at the impaired dynamics in patients with poor working memory performance. Functional connectivity is a powerful tool used to investigate coordinated activity among local and distant brain regions. Here, we identified connectivity footprints that differentiate task states representing distinct working memory load levels. We employed linear support vector machines to decode working memory load from task-based functional connectivity matrices in 177 healthy adults. Using neighborhood component analysis, we also identified the most important connectivity pairs in classifying high and low working memory loads. We found that between-network coupling among frontoparietal, ventral attention and default mode networks, and within-network connectivity in ventral attention network are the most important factors in classifying low vs. high working memory load. Task-based within-network connectivity profiles at high working memory load in ventral attention and default mode networks were the most predictive of load-related increases in response times. Our findings reveal the large-scale impact of working memory load on the cerebral cortex and highlight the complex dynamics of intrinsic brain networks during active task states.

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Risk tolerance measured by probability discounting among individuals with primary mood and psychotic disorders

OBJECTIVE

Change in risk tolerance is a feature of multiple psychiatric disorders and may contribute to adverse outcomes. We used a probability discounting (PD) task to measure risk-taking behavior among individuals with bipolar disorder (BPAD), major depressive disorder (MDD), schizoaffective disorder (SCAD), and schizophrenia (SCZ).

METHOD

A PD task was administered to 117 patients and 88 healthy controls (HCs), along with a cognitive battery using the Cambridge Neuropsychological Test Automated Battery, and relevant symptomatology scales. We examined differences in PD rates between diagnostic groups, and compared with HCs, while controlling for potential confounding factors including measures of cognitive functioning.

RESULTS

Individuals with a diagnosis of BPAD or SCAD/SCZ prefer smaller, more guaranteed rewards rather than larger, less likely rewards as compared with healthy controls (p = .002 and p = .034, respectively). There was no effect of performance on cognitive tasks, antipsychotic treatment, or symptomatology on the rate of probability discounting.

CONCLUSION

This study supports the transdiagnostic measurement of risk-taking behaviors, even when such behaviors are not the primary area of psychopathology. Quantifying risk-taking may enable targeted therapeutic strategies across disorders. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Interrogating the Genetic Determinants of Tourette's Syndrome and Other Tic Disorders Through Genome-Wide Association Studies

OBJECTIVE

Tourette's syndrome is polygenic and highly heritable. Genome-wide association study (GWAS) approaches are useful for interrogating the genetic architecture and determinants of Tourette's syndrome and other tic disorders. The authors conducted a GWAS meta-analysis and probed aggregated Tourette's syndrome polygenic risk to test whether Tourette's and related tic disorders have an underlying shared genetic etiology and whether Tourette's polygenic risk scores correlate with worst-ever tic severity and may represent a potential predictor of disease severity.

METHODS

GWAS meta-analysis, gene-based association, and genetic enrichment analyses were conducted in 4,819 Tourette's syndrome case subjects and 9,488 control subjects. Replication of top loci was conducted in an independent population-based sample (706 case subjects, 6,068 control subjects). Relationships between Tourette's polygenic risk scores (PRSs), other tic disorders, ascertainment, and tic severity were examined.

RESULTS

GWAS and gene-based analyses identified one genome-wide significant locus within FLT3 on chromosome 13, rs2504235, although this association was not replicated in the population-based sample. Genetic variants spanning evolutionarily conserved regions significantly explained 92.4% of Tourette's syndrome heritability. Tourette's-associated genes were significantly preferentially expressed in dorsolateral prefrontal cortex. Tourette's PRS significantly predicted both Tourette's syndrome and tic spectrum disorders status in the population-based sample. Tourette's PRS also significantly correlated with worst-ever tic severity and was higher in case subjects with a family history of tics than in simplex case subjects.

CONCLUSIONS

Modulation of gene expression through noncoding variants, particularly within cortico-striatal circuits, is implicated as a fundamental mechanism in Tourette's syndrome pathogenesis. At a genetic level, tic disorders represent a continuous spectrum of disease, supporting the unification of Tourette's syndrome and other tic disorders in future diagnostic schemata. Tourette's PRSs derived from sufficiently large samples may be useful in the future for predicting conversion of transient tics to chronic tic disorders, as well as tic persistence and lifetime tic severity.

PET neuroimaging reveals histone deacetylase dysregulation in schizophrenia

BACKGROUND

Patients with schizophrenia (SCZ) experience chronic cognitive deficits. Histone deacetylases (HDACs) are enzymes that regulate cognitive circuitry; however, the role of HDACs in cognitive disorders, including SCZ, remains unknown in humans. We previously determined that HDAC2 mRNA levels were lower in dorsolateral prefrontal cortex (DLPFC) tissue from donors with SCZ compared with controls. Here we investigated the relationship between in vivo HDAC expression and cognitive impairment in patients with SCZ and matched healthy controls using [11C]Martinostat positron emission tomography (PET).

METHODS

In a case-control study, relative [11C]Martinostat uptake was compared between 14 patients with SCZ or schizoaffective disorder (SCZ/SAD) and 17 controls using hypothesis-driven region-of-interest analysis and unbiased whole brain voxel-wise approaches. Clinical measures, including the MATRICS consensus cognitive battery, were administered.

RESULTS

Relative HDAC expression was lower in the DLPFC of patients with SCZ/SAD compared with controls, and HDAC expression positively correlated with cognitive performance scores across groups. Patients with SCZ/SAD also showed lower relative HDAC expression in the dorsomedial prefrontal cortex and orbitofrontal gyrus, and higher relative HDAC expression in the cerebral white matter, pons, and cerebellum compared with controls.

CONCLUSIONS

These findings provide in vivo evidence of HDAC dysregulation in patients with SCZ and suggest that altered HDAC expression may impact cognitive function in humans.

FUNDING

National Institute of Mental Health (NIMH), Brain and Behavior Foundation, Massachusetts General Hospital (MGH), Athinoula A. Martinos Center for Biomedical Imaging, National Institute of Biomedical Imaging and Bioengineering (NIBIB), NIH Shared Instrumentation Grant Program.

Association of Prenatal Exposure to Population-Wide Folic Acid Fortification With Altered Cerebral Cortex Maturation in Youths

IMPORTANCE

Presently, 81 countries mandate the fortification of grain products with folic acid to lessen the risk of neural tube defects in the developing fetus. Epidemiologic data on severe mental illness suggest potentially broader effects of prenatal folate exposure on postnatal brain development, but this link remains unsubstantiated by biological evidence.

OBJECTIVE

To evaluate associations among fetal folic acid exposure, cortical maturation, and psychiatric risk in youths.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective, observational clinical cohort study was conducted at Massachusetts General Hospital (MGH) among 292 youths 8 to 18 years of age born between January 1993 and December 2001 (inclusive of folic acid fortification rollout ±3.5 years) with normative results of clinical magnetic resonance imaging, divided into 3 age-matched groups based on birthdate and related level of prenatal folic acid fortification exposure (none, partial, or full). Magnetic resonance imaging was performed between January 2005 and March 2015. Two independent, observational, community-based cohorts (Philadelphia Neurodevelopmental Cohort [PNC] and National Institutes of Health Magnetic Resonance Imaging Study of Normal Brain Development [NIH]) comprising 1078 youths 8 to 18 years of age born throughout (PNC, 1992-2003) or before (NIH, 1983-1995) the rollout of folic acid fortification were studied for replication, clinical extension, and specificity. Statistical analysis was conducted from 2015 to 2018.

EXPOSURES

United States-mandated grain product fortification with folic acid, introduced in late 1996 and fully in effect by mid-1997.

MAIN OUTCOMES AND MEASURES

Differences in cortical thickness among nonexposed, partially exposed, and fully exposed youths (MGH) and underlying associations between age and cortical thickness (all cohorts). Analysis of the PNC cohort also examined the association of age-cortical thickness slopes with the odds of psychotic symptoms.

RESULTS

The MGH cohort (139 girls and 153 boys; mean [SD] age, 13.3 [2.3] years) demonstrated exposure-associated cortical thickness increases in bilateral frontal and temporal regions (9.9% to 11.6%; corrected P < .001 to P = .03) and emergence of quadratic (delayed) age-associated thinning in temporal and parietal regions (β = -11.1 to -13.9; corrected P = .002). The contemporaneous PNC cohort (417 girls and 444 boys; mean [SD] age, 13.5 [2.7] years) also exhibited exposure-associated delays of cortical thinning (β = -1.59 to -1.73; corrected P < .001 to P = .02), located in similar regions and with similar durations of delay as in the MGH cohort. Flatter thinning profiles in frontal, temporal, and parietal regions were associated with lower odds of psychosis spectrum symptoms in the PNC cohort (odds ratio, 0.37-0.59; corrected P < .05). All identified regions displayed earlier thinning in the nonexposed NIH cohort (118 girls and 99 boys; mean [SD] age, 13.3 [2.6] years).

CONCLUSIONS AND RELEVANCE

The results of this study suggest an association between gestational exposure to fortification of grain products with folic acid and altered cortical development and, in turn, with reduction in the risk of psychosis in youths.

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on ∼150,000 individuals give a higher accuracy than LDSC estimates based on ∼400,000 individuals (from combined meta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project

BACKGROUND

Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) Consortium aims to clarify the role of genetic variation in brain abnormalities underlying schizophrenia. This article describes the GENUS Consortium sample collection.

METHODS

We identified existing samples collected for schizophrenia studies consisting of patients, controls, and/or individuals at familial high-risk (FHR) for schizophrenia. Samples had single nucleotide polymorphism (SNP) array data or genomic DNA, clinical and demographic data, and neuropsychological and/or brain magnetic resonance imaging (MRI) data. Data were subjected to quality control procedures at a central site.

RESULTS

Sixteen research groups contributed data from 5199 psychosis patients, 4877 controls, and 725 FHR individuals. All participants have relevant demographic data and all patients have relevant clinical data. The sex ratio is 56.5% male and 43.5% female. Significant differences exist between diagnostic groups for premorbid and current IQ (both p<1×10^-10). Data from a diversity of neuropsychological tests are available for 92% of participants, and 30% have structural MRI scans (half also have diffusion-weighted MRI scans). SNP data are available for 76% of participants. The ancestry composition is 70% European, 20% East Asian, 7% African, and 3% other.

CONCLUSIONS

The Consortium is investigating the genetic contribution to brain phenotypes in a schizophrenia sample collection of >10,000 participants. The breadth of data across clinical, genetic, neuropsychological, and MRI modalities provides an important opportunity for elucidating the genetic basis of neural processes underlying schizophrenia.

The human cortex possesses a reconfigurable dynamic network architecture that is disrupted in psychosis

Higher-order cognition emerges through the flexible interactions of large-scale brain networks, an aspect of temporal coordination that may be impaired in psychosis. Here, we map the dynamic functional architecture of the cerebral cortex in healthy young adults, leveraging this atlas of transient network configurations (states), to identify state- and network-specific disruptions in patients with schizophrenia and psychotic bipolar disorder. We demonstrate that dynamic connectivity profiles are reliable within participants, and can act as a fingerprint, identifying specific individuals within a larger group. Patients with psychotic illness exhibit intermittent disruptions within cortical networks previously associated with the disease, and the individual connectivity profiles within specific brain states predict the presence of active psychotic symptoms. Taken together, these results provide evidence for a reconfigurable dynamic architecture in the general population and suggest that prior reports of network disruptions in psychosis may reflect symptom-relevant transient abnormalities, rather than a time-invariant global deficit.

Temporal changes in brain dynamics are linked with cognitive abilities, but neither their stability nor relationship to psychosis is clear. Here, authors describe the dynamic neural architecture in healthy controls and patients with psychosis and find that they are stable over time and can predict psychotic symptoms.

Functional Connectivity Between Anterior Insula and Key Nodes of Frontoparietal Executive Control and Salience Networks Distinguish Bipolar Depression From Unipolar Depression and Healthy Control Subjects

BACKGROUND

Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment.

METHODS

Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity.

RESULTS

Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula-inferior parietal lobule connectivity significantly discriminated patients with bipolar depression.

CONCLUSIONS

Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar disorder, exhibiting reasonable sensitivity and specificity.

S-Adenosyl Methionine and Transmethylation Pathways in Neuropsychiatric Diseases Throughout Life

S-Adenosyl methionine (SAMe), as a major methyl donor, exerts its influence on central nervous system function through cellular transmethylation pathways, including the methylation of DNA, histones, protein phosphatase 2A, and several catecholamine moieties. Based on available evidence, this review focuses on the lifelong range of severe neuropsychiatric and neurodegenerative diseases and their associated neuropathologies, which have been linked to the deficiency/load of SAMe production or/and the disturbance in transmethylation pathways. Also included in this review are the present-day applications of SAMe in the treatment in these diseases in each age group.

A Cross-Sectional Study of Dietary and Genetic Predictors of Blood Folate Levels in Healthy Young Adults

Since 1998, the U.S. has mandated folic acid (FA) fortification of certain grain products to reduce the risk of neural tube defects. Folate intake and red blood cell (RBC) folate concentrations increased substantially post-intervention, although recent studies raise concerns about the level of ongoing benefit. This study investigated blood folate level determinants in healthy young adults, including intake of naturally occurring food folate, synthetic FA, and the interaction of naturally occurring food folate with a common missense variant in the FOLH1 gene thought to affect absorption. Participants (n = 265) completed the Diet History Questionnaire II, RBC folate testing, and were genotyped for the 484T>C FOLH1 variant. Men reported significantly greater intake of all folate sources except for supplemental FA, but RBC folate levels did not significantly differ by sex. Synthetic FA was a stronger predictor of RBC folate than naturally occurring food folate. In the largest racial group, synthetic FA and the interaction of FOLH1 genotype with naturally occurring food folate significantly predicted RBC folate, with the overall model accounting for 13.8% of the variance in RBC folate levels. Blood folate levels rely on a complex interaction of natural and synthetic folate intake as well as FOLH1 genotype.

Neural determinants of human goal-directed vs. habitual action control and their relation to trait motivation

Instrumental learning is mediated by goal-directed and habit systems in the brain. While rodent studies implicate distinct prefrontal/striatal regions in goal-directed and habit learning, neural systems underpinning these two processes in humans remain poorly understood. Here, using a validated discrimination learning task that distinguishes goal-directed learning from habit learning in 72 subjects in fMRI, we investigated the corticostriatal correlates of goal-directed learning and tested whether brain activation during learning is associated with trait motivation and behavioral performance in the post-learning test phase. Participants showed enhanced activation in medial prefrontal and posterior cingulate cortices during goal-directed action selection in the training phase, whereas habitual action selection activated bilateral insula, bilateral dorsal caudate and left precentral gyrus. In addition, early phase of learning was associated with increased activation in the frontoparietal control network and dorsal striatum, whereas default mode regions depicted increased activation in the late phase. Finally, avoidance motivation scores measured by Behavioral Inhibition/Activation System (BIS/BAS) correlated with accuracy during goal-directed learning and showed a nominally significant correlation with activation in dorsomedial prefrontal cortex during goal-directed acquisition of stimuli. These findings reveal the temporal dynamics of instrumental behavior and suggest that avoidance motivation predicts performance and brain activity during goal-directed learning.

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

Progression from selective to general involvement of hippocampal subfields in schizophrenia

Volume deficits of the hippocampus in schizophrenia have been consistently reported. However, the hippocampus is anatomically heterogeneous; it remains unclear whether certain portions of the hippocampus are affected more than others in schizophrenia. In this study, we aimed to determine whether volume deficits in schizophrenia are confined to specific subfields of the hippocampus and to measure the subfield volume trajectories over the course of the illness. Magnetic resonance imaging scans were obtained from Data set 1: 155 patients with schizophrenia (mean duration of illness of 7 years) and 79 healthy controls, and Data set 2: an independent cohort of 46 schizophrenia patients (mean duration of illness of 18 years) and 46 healthy controls. In addition, follow-up scans were collected for a subset of Data set 1. A novel, automated method based on an atlas constructed from ultra-high resolution, post-mortem hippocampal tissue was used to label seven hippocampal subfields. Significant cross-sectional volume deficits in the CA1, but not of the other subfields, were found in the schizophrenia patients of Data set 1. However, diffuse cross-sectional volume deficits across all subfields were found in the more chronic and ill schizophrenia patients of Data set 2. Consistent with this pattern, the longitudinal analysis of Data set 1 revealed progressive illness-related volume loss (~2-6% per year) that extended beyond CA1 to all of the other subfields. This decline in volume correlated with symptomatic worsening. Overall, these findings provide converging evidence for early atrophy of CA1 in schizophrenia, with extension to other hippocampal subfields and accompanying clinical sequelae over time.

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Dopamine D1 signaling organizes network dynamics underlying working memory

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

Correspondence of DNA Methylation Between Blood and Brain Tissue and Its Application to Schizophrenia Research

Given the difficulty of procuring human brain tissue, a key question in molecular psychiatry concerns the extent to which epigenetic signatures measured in more accessible tissues such as blood can serve as a surrogate marker for the brain. Here, we aimed (1) to investigate the blood-brain correspondence of DNA methylation using a within-subject design and (2) to identify changes in DNA methylation of brain-related biological pathways in schizophrenia.We obtained paired blood and temporal lobe biopsy samples simultaneously from 12 epilepsy patients during neurosurgical treatment. Using the Infinium 450K methylation array we calculated similarity of blood and brain DNA methylation for each individual separately. We applied our findings by performing gene set enrichment analyses (GSEA) of peripheral blood DNA methylation data (Infinium 27K) of 111 schizophrenia patients and 122 healthy controls and included only Cytosine-phosphate-Guanine (CpG) sites that were significantly correlated across tissues.Only 7.9% of CpG sites showed a statistically significant, large correlation between blood and brain tissue, a proportion that although small was significantly greater than predicted by chance. GSEA analysis of schizophrenia data revealed altered methylation profiles in pathways related to precursor metabolites and signaling peptides.Our findings indicate that most DNA methylation markers in peripheral blood do not reliably predict brain DNA methylation status. However, a subset of peripheral data may proxy methylation status of brain tissue. Restricting the analysis to these markers can identify meaningful epigenetic differences in schizophrenia and potentially other brain disorders.

Neural predictors of successful brief psychodynamic psychotherapy for persistent depression

BACKGROUND

Psychodynamic psychotherapy has been used to treat depression for more than a century. However, not all patients respond equally well, and there are few reliable predictors of treatment outcome.

METHODS

We used resting (18)F-fluorodeoxyglucose positron emission tomography ((18)FDG-PET) scans immediately before and after a structured, open trial of brief psychodynamic psychotherapy (n = 16) in conjunction with therapy process ratings and clinical outcome measures to identify neural correlates of treatment response.

RESULTS

Pretreatment glucose metabolism within the right posterior insula correlated with depression severity. Reductions in depression scores correlated with a pre- to posttreatment reduction in right insular metabolism, which in turn correlated with higher objective measures of patient insight obtained from videotaped therapy sessions. Pretreatment metabolism in the right precuneus was significantly higher in patients who completed treatment and correlated with psychological mindedness.

CONCLUSIONS

Resting brain metabolism predicted both clinical course and relevant psychotherapeutic process during short-term psychodynamic psychotherapy for depression.

Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset’s utility.

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Vitamin supplementation in the treatment of schizophrenia

This article reviews the current literature addressing the treatment of schizophrenia with vitamin supplementation. It describes the important roles that vitamins play in normal metabolism, and reviews the evidence pertaining to vitamin deficiency and supplementation in patients with schizophrenia. There is mounting evidence suggesting that vitamin supplementation, in particular with folic acid, vitamin B12 and vitamin D, may be important in treatment within certain subgroups of patients. There is a need for larger randomized controlled trials, and further studies examining the incidence of schizophrenia in countries with poor prenatal care and malnutrition, as well as in countries that have adopted mandatory folic acid fortification of grain products, are recommended.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Dopamine genetic risk score predicts depressive symptoms in healthy adults and adults with depression

BACKGROUND

Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression.

METHODS

Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3).

RESULTS

In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = -0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = -0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = -0.86, p = 0.15).

CONCLUSIONS

Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression.

Randomized multicenter investigation of folate plus vitamin B12 supplementation in schizophrenia

IMPORTANCE

More effective treatments are needed for negative symptoms of schizophrenia, which are typically chronic, disabling, and costly. Negative symptoms have previously been associated with reduced blood folate levels, especially among patients with low-functioning variants in genes that regulate folate metabolism, suggesting the potential utility of folate supplementation.

OBJECTIVES

To determine whether folic acid plus vitamin B12 supplementation reduces negative symptoms of schizophrenia and whether functional variants in folate-related genes influence treatment response.

DESIGN

Parallel-group, randomized, double-blind, placebo-controlled clinical trial of 16 weeks of treatment with 2 mg of folic acid and 400 μg of vitamin B12.

SETTING

Three community mental health centers affiliated with academic medical centers in the United States.

PARTICIPANTS

Outpatients with chronic schizophrenia who were psychiatrically stable but displayed persistent symptoms despite antipsychotic treatment. Eligible patients were 18 to 68 years old, were treated with an antipsychotic agent for 6 months or more at a stable dose for 6 weeks or more, and scored 60 or more on the Positive and Negative Syndrome Scale.

INTERVENTION

One hundred forty subjects were randomized to receive daily oral folic acid plus vitamin B12 or placebo.

MAIN OUTCOME MEASURES

Change in negative symptoms (Scale for the Assessment of Negative Symptoms [SANS]), as well as positive and total symptoms (Positive and Negative Syndrome Scale).

RESULTS

Folate plus vitamin B12 improved negative symptoms significantly compared with placebo (group difference, -0.33 change in SANS score per week; 95% CI, -0.62 to -0.05) when genotype was taken into account but not when genotype was excluded. An interaction of the 484C>T variant of FOLH1 (rs202676) with treatment was observed (P = .02), where only patients homozygous for the 484T allele demonstrated significantly greater benefit with active treatment (-0.59 change in SANS score per week; 95% CI, -0.99 to -0.18). In parallel, we observed an inverse relationship between red blood cell folate concentration at baseline and 484C allele load (P = .03), which persisted until 8 weeks of treatment. Change in positive and total symptoms did not differ between treatment groups.

CONCLUSIONS

Folate plus vitamin B12 supplementation can improve negative symptoms of schizophrenia, but treatment response is influenced by genetic variation in folate absorption. These findings support a personalized medicine approach for the treatment of negative symptoms.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00611806.

Genetic variation throughout the folate metabolic pathway influences negative symptom severity in schizophrenia

Low serum folate levels previously have been associated with negative symptom risk in schizophrenia, as has the hypofunctional 677C>T variant of the MTHFR gene. This study examined whether other missense polymorphisms in folate-regulating enzymes, in concert with MTHFR, influence negative symptoms in schizophrenia, and whether total risk allele load interacts with serum folate status to further stratify negative symptom risk. Medicated outpatients with schizophrenia (n = 219), all of European origin and some included in a previous report, were rated with the Positive and Negative Syndrome Scale. A subset of 82 patients also underwent nonfasting serum folate testing. Patients were genotyped for the MTHFR 677C>T (rs1801133), MTHFR 1298A>C (rs1801131), MTR 2756A>G (rs1805087), MTRR 203A>G (rs1801394), FOLH1 484T>C (rs202676), RFC 80A>G (rs1051266), and COMT 675G>A (rs4680) polymorphisms. All genotypes were entered into a linear regression model to determine significant predictors of negative symptoms, and risk scores were calculated based on total risk allele dose. Four variants, MTHFR 677T, MTR 2756A, FOLH1 484C, and COMT 675A, emerged as significant independent predictors of negative symptom severity, accounting for significantly greater variance in negative symptoms than MTHFR 677C>T alone. Total allele dose across the 4 variants predicted negative symptom severity only among patients with low folate levels. These findings indicate that multiple genetic variants within the folate metabolic pathway contribute to negative symptoms of schizophrenia. A relationship between folate level and negative symptom severity among patients with greater genetic vulnerability is biologically plausible and suggests the utility of folate supplementation in these patients.

Individual differences in amygdala-medial prefrontal anatomy link negative affect, impaired social functioning, and polygenic depression risk

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n = 206) and emotional (n = 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala-mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n = 438) using risk scores derived from a large genome-wide association analysis (n = 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala-mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD.

Smoking, but not malnutrition, influences promoter-specific DNA methylation of the proopiomelanocortin gene in patients with and without anorexia nervosa

OBJECTIVE

Our pilot study evaluates the impact of environmental factors, such as nutrition and smoking status, on epigenetic patterns in a disease-associated gene.

METHOD

We measured the effects of malnutrition and cigarette smoking on proopiomelanocortin (POMC) promoter-specific DNA methylation in female patients with and without anorexia nervosa (AN). POMC and its derived peptides (alpha melanocyte stimulating hormone and adrenocorticotropic hormone) are implicated in stress and feeding response. Promoter-specific DNA methylation of the POMC gene was determined in peripheral blood mononuclear cells of 54 healthy female control subjects, 40 underweight patients with AN, and 21 weight-restored patients with AN using bisulfite sequencing. Malnutrition was characterized by plasma leptin.

RESULTS

POMC promoter-specific DNA methylation was not affected by diagnosis or nutritional status but significantly negatively associated with cigarette smoking.

CONCLUSIONS

Although malnutrition may be expected to reduce DNA methylation through its effects on one-carbon metabolism, our negative results are in line with several in vitro and clinical studies that did not show a direct relation between gene-specific DNA methylation and folate levels. In contrast, smoking has been repeatedly reported to alter DNA methylation of specific genes and should be controlled for in future epigenetic studies.

A hypomethylating variant of MTHFR, 677C>T, blunts the neural response to errors in patients with schizophrenia and healthy individuals

BACKGROUND

Responding to errors is a critical first step in learning from mistakes, a process that is abnormal in schizophrenia. To gain insight into the neural and molecular mechanisms of error processing, we used functional MRI to examine effects of a genetic variant in methylenetetrahydrofolate reductase (MTHFR 677C>T, rs1801133) that increases risk for schizophrenia and that has been specifically associated with increased perseverative errors among patients. MTHFR is a key regulator of the intracellular one-carbon milieu, including DNA methylation, and each copy of the 677T allele reduces MTHFR activity by 35%.

METHODOLOGY/PRINCIPAL FINDINGS

Using an antisaccade paradigm, we found that the 677T allele induces a dose-dependent blunting of dorsal anterior cingulate cortex (dACC) activation in response to errors, a pattern that was identical in healthy individuals and patients with schizophrenia. Further, the normal relationship between dACC activation and error rate was disrupted among carriers of the 677T allele.

CONCLUSIONS/SIGNIFICANCE

These findings implicate an epigenetic mechanism in the neural response to errors, and provide insight into normal cognitive variation through a schizophrenia risk gene.

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.