Estimating the total variance explained by whole-brain imaging for zero-inflated outcomes.

There is a dearth of statistical models that adequately capture the total signal attributed to whole-brain imaging features. The total signal is often widely distributed across the brain, with individual imaging features exhibiting small effect sizes for predicting neurobehavioral phenotypes. The challenge of capturing the total signal is compounded by the distribution of neurobehavioral data, particularly responses to psychological questionnaires, which often feature zero-inflated, highly skewed outcomes. To close this gap, we have developed a novel Variational Bayes algorithm that characterizes the total signal captured by whole-brain imaging features for zero-inflated outcomes. Our zero-inflated variance (ZIV) estimator estimates the fraction of variance explained (FVE) and the proportion of non-null effects (PNN) from large-scale imaging data. In simulations, ZIV demonstrates superior performance over other linear models. When applied to data from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, we found that whole-brain imaging features contribute to a larger FVE for externalizing behaviors compared to internalizing behaviors. Moreover, focusing on features contributing to the PNN, ZIV estimator localized key neurocircuitry associated with neurobehavioral traits. To the best of our knowledge, the ZIV estimator is the first specialized method for analyzing zero-inflated neuroimaging data, enhancing future studies on brain-behavior relationships and improving the understanding of neurobehavioral disorders.

Genetic Correlates of Treatment-Resistant Depression: Insights from Polygenic Scores Across Cognitive, Temperamental, and Sleep Traits in the All of US cohort.

Background: Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable economic and social burdens. The etiological factors contributing to TRD are complex and not fully understood. Objective: To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits, and to explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us Research Program (AoU). Methods: Data from 292,663 participants in the AoU were analyzed using a case-cohort design. Treatment resistant depression (TRD), treatment responsive Major Depressive Disorder (trMDD), and all others who have no formal diagnosis of Major Depressive Disorder (non-MDD) were identified through diagnostic codes and prescription patterns. Polygenic scores (PGS) for 61 unique traits from seven domains were used and logistic regressions were conducted to assess associations between PGS and TRD. Finally, Cox proportional hazard models were used to explore the predictive value of PGS for progression rate from the diagnostic event of Major Depressive Disorder (MDD) to TRD. Results: In the discovery set (104128 non-MDD, 16640 trMDD, and 4177 TRD), 44 of 61 selected PGS were found to be significantly associated with MDD, regardless of treatment responsiveness. Eleven of them were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia and specific neuroticism traits were associated with increased TRD risk (OR range from 1.05 to 1.15), while higher education and intelligence scores were protective (ORs 0.88 and 0.91, respectively). These associations are consistent across two other independent sets within AoU (n = 104,388 and 63,330). Among 28,964 individuals tracked over time, 3,854 developed TRD within an average of 944 days (95% CI: 883 ∼ 992 days) after MDD diagnosis. All eleven previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD. Thus, those having higher education PGS would experiencing slower conversion rates than those who have lower education PGS with hazard ratios in 0.79 (80 th versus 20 th percentile, 95% CI: 0.74 ∼ 0.85). Those who had higher insomnia PGS experience faster conversion rates than those who had lower insomnia PGS, with hazard ratios in 1.21 (80 th versus 20 th percentile, 95% CI: 1.13 ∼ 1.30). Conclusions: Our results indicate that genetic predisposition related to neuroticism, cognitive function, and sleep patterns play a significant role in the development of TRD. These findings underscore the importance of considering genetic and psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance our understanding of pathways leading to treatment resistance. Key Points: Question: What are the predisposing characteristics among individuals who develop treatment-resistant depression (TRD)?Findings: Analysis of data from 292,663 participants in the All of Us Research Program revealed that polygenic scores (PGS) for traits including neuroticism, cognitive function, and sleep patterns were significantly associated with major depressive disorder (MDD) and, particularly, with TRD. Among the 61 traits studied, 11 showed stronger associations with TRD compared to treatment responsive MDD, including traits linked to higher education and intelligence which appeared protective, and neuroticism and insomnia which increased risk.Meaning: The findings underscore the importance of considering predisposing factors when managing and treating TRD. They suggest potential intervening pathways through tailored approach with the identified predisposing characteristics, reducing the risk of progression to treatment resistance in depression. Personalized genetic information that measures the underlying predispositions could eventually enhance therapeutic strategies.

A randomized controlled safety and feasibility trial of floatation-REST in anxious and depressed individuals.

BACKGROUND: Reduced Environmental Stimulation Therapy via floatation (floatation-REST) is a behavioral intervention designed to attenuate exteroceptive sensory input to the nervous system. Prior studies in anxious and depressed individuals demonstrated that single sessions of floatation-REST are safe, well-tolerated, and associated with an acute anxiolytic and antidepressant effect that persists for over 48 hours. However, the feasibility of using floatation-REST as a repeated intervention in anxious and depressed populations has not been well-investigated. METHODS: In this single-blind safety and feasibility trial, 75 individuals with anxiety and depression were randomized to complete six sessions of floatation-REST in different formats: pool-REST (weekly 1-hour float sessions), pool-REST preferred (float sessions with flexibility of duration and frequency), or an active comparator (chair-REST; weekly 1-hour sessions in a Zero Gravity chair). Feasibility (primary outcome) was assessed via an 80% rate of adherence to the assigned intervention; tolerability via study dropout and duration/frequency of REST utilization; and safety via incidence of adverse events and ratings about the effects of REST. RESULTS: Of 1,715 individuals initially screened, 75 participants were ultimately randomized. Six-session adherence was 85% for pool-REST (mean, M = 5.1 sessions; standard deviation, SD = 1.8), 89% for pool-REST preferred (M = 5.3 sessions; SD = 1.6), and 74% for chair-REST (M = 4.4 sessions; SD = 2.5). Dropout rates at the end of the intervention did not differ significantly between the treatment conditions. Mean session durations were 53.0 minutes (SD = 12.3) for pool-REST, 75.4 minutes (SD = 29.4) for pool-REST preferred, and 58.4 minutes (SD = 4.3) for chair-REST. There were no serious adverse events associated with any intervention. Positive experiences were endorsed more commonly than negative ones and were also rated at higher levels of intensity. CONCLUSIONS: Six sessions of floatation-REST appear feasible, well-tolerated, and safe in anxious and depressed individuals. Floatation-REST induces positively-valenced experiences with few negative effects. Larger randomized controlled trials evaluating markers of clinical efficacy are warranted. CLINICAL TRIAL REGISTRATION IDENTIFIER: NCT03899090.

Associations between perinatal risk and physical health in pre-adolescence in the Adolescent Brain Cognitive Development (ABCD) Study®: the unexpected relationship with sleep disruption.

BACKGROUND: To investigate relationships among different physical health problems in a large, sociodemographically diverse sample of 9-to-10-year-old children and determine the extent to which perinatal health factors are associated with childhood physical health problems. METHODS: A cross-sectional study was conducted utilizing the Adolescent Brain Cognitive Development℠ (ABCD) Study (n = 7613, ages 9-to-10-years-old) to determine the associations among multiple physical health factors (e.g., prenatal complications, current physical health problems). Logistic regression models controlling for age, sex, pubertal development, household income, caregiver education, race, and ethnicity evaluated relationships between perinatal factors and childhood physical health problems. RESULTS: There were significant associations between perinatal and current physical health measures. Specifically, those who had experienced perinatal complications were more likely to have medical problems by 9-to-10 years old. Importantly, sleep disturbance co-occurred with several physical health problems across domains and developmental periods. CONCLUSION: Several perinatal health factors were associated with childhood health outcomes, highlighting the importance of understanding and potentially improving physical health in youth. Understanding the clustering of physical health problems in youth is essential to better identify which physical health problems may share underlying mechanisms. IMPACT: Using a multivariable approach, we investigated the associations between various perinatal and current health problems amongst youth. Our study highlights current health problems, such as sleep problems at 9-to-10 years old, that are associated with a cluster of factors occurring across development (e.g., low birth weight, prenatal substance exposure, pregnancy complications, current weight status, lifetime head injury). Perinatal health problems are at large, non-modifiable (in this retrospective context), however, by identifying which are associated with current health problems, we can identify potential targets for intervention and prevention efforts.

Population-Based Risk of Psychiatric Disorders Associated With Recurrent Copy Number Variants.

Importance: Recurrent copy number variants (rCNVs) have been associated with increased risk of psychiatric disorders in case-control studies, but their population-level impact is unknown. Objective: To provide unbiased population-based estimates of prevalence and risk associated with psychiatric disorders for rCNVs and to compare risks across outcomes, rCNV dosage type (deletions or duplications), and locus features. Design, Setting, and Participants: This genetic association study is an analysis of data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort sample of individuals born in Denmark in 1981-2008 and followed up until 2015, including (1) all individuals (n = 92 531) with a hospital discharge diagnosis of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, major depressive disorder (MDD), or schizophrenia spectrum disorder (SSD) and (2) a subcohort (n = 50 625) randomly drawn from the source population. Data were analyzed from January 2021 to August 2023. Exposures: Carrier status of deletions and duplications at 27 autosomal rCNV loci was determined from neonatal blood samples genotyped on single-nucleotide variant microarrays. Main Outcomes and Measures: Population-based rCNV prevalence was estimated with a survey model using finite population correction to account for oversampling of cases. Hazard ratio (HR) estimates and 95% CIs for psychiatric disorders were derived using weighted Cox proportional hazard models. Risks were compared across outcomes, dosage type, and locus features using generalized estimating equation models. Results: A total of 3547 rCNVs were identified in 64 735 individuals assigned male at birth (53.8%) and 55 512 individuals assigned female at birth (46.2%) whose age at the end of follow-up ranged from 7.0 to 34.7 years (mean, 21.8 years). Most observed increases in rCNV-associated risk for ADHD, ASD, or SSD were moderate, and risk estimates were highly correlated across these disorders. Notable exceptions included high ASD-associated risk observed for Prader-Willi/Angelman syndrome duplications (HR, 20.8; 95% CI, 7.9-55). No rCNV was associated with increased MDD risk. Also, rCNV-associated risk was positively correlated with locus size and gene constraint but not with dosage type. Comparison with published case-control and community-based studies revealed a higher prevalence of deletions and lower associated increase in risk for several rCNVs in iPSYCH2015. Conclusions and Relevance: This study found that several rCNVs were more prevalent and conferred less risk of psychiatric disorders than estimated previously. Most case-control studies overestimate rCNV-associated risk of psychiatric disorders, likely because of selection bias. In an era where genetics is increasingly being clinically applied, these results highlight the importance of population-based risk estimates for genetics-based predictions.

Identifying high school risk factors that forecast heavy drinking onset in understudied young adults.

Heavy alcohol drinking is a major, preventable problem that adversely impacts the physical and mental health of US young adults. Studies seeking drinking risk factors typically focus on young adults who enrolled in 4-year residential college programs (4YCP) even though most high school graduates join the workforce, military, or community colleges. We examined 106 of these understudied young adults (USYA) and 453 4YCPs from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) by longitudinally following their drinking patterns for 8 years from adolescence to young adulthood. All participants were no-to-low drinkers during high school. Whereas 4YCP individuals were more likely to initiate heavy drinking during college years, USYA participants did so later. Using mental health metrics recorded during high school, machine learning forecasted individual-level risk for initiating heavy drinking after leaving high school. The risk factors differed between demographically matched USYA and 4YCP individuals and between sexes. Predictors for USYA drinkers were sexual abuse, physical abuse for girls, and extraversion for boys, whereas 4YCP drinkers were predicted by the ability to recognize facial emotion and, for boys, greater openness. Thus, alcohol prevention programs need to give special consideration to those joining the workforce, military, or community colleges, who make up the majority of this age group.

Alcohol milestones and internalizing, externalizing, and executive function: longitudinal and polygenic score associations.

BACKGROUND: Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk. METHODS: Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11-36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones. RESULTS: Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20). CONCLUSIONS: Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

Dietary and Lifestyle Factors of Brain Iron Accumulation and Parkinson's Disease Risk.

Purpose: Iron is an essential nutrient which can only be absorbed through an individual's diet. Excess iron accumulates in organs throughout the body including the brain. Iron dysregulation in the brain is commonly associated with neurodegenerative diseases like Alzheimer's disease and Parkinson's Disease (PD). Our previous research has shown that a pattern of iron accumulation in motor regions of the brain related to a genetic iron-storage disorder called hemochromatosis is associated with an increased risk of PD. To understand how diet and lifestyle factors relate to this brain endophenotype and risk of PD we analyzed the relationship between these measures, estimates of nutrient intake, and diet and lifestyle preference using data from UK Biobank. Methods: Using distinct imaging and non-imaging samples (20,477 to 28,388 and 132,023 to 150,603 participants, respectively), we performed linear and logistic regression analyses using estimated dietary nutrient intake and food preferences to predict a) brain iron accumulation score (derived from T2-Weighted Magnetic Resonance Imaging) and b) PD risk. In addition, we performed a factor analysis of diet and lifestyle preferences to investigate if latent lifestyle factors explained significant associations. Finally, we performed an instrumental variable regression of our results related to iron accumulation and PD risk to identify if there were common dietary and lifestyle factors that were jointly associated with differences in brain iron accumulation and PD risk. Results: We found multiple highly significant associations with measures of brain iron accumulation and preferences for alcohol (factor 7: t=4.02, pFDR=0.0003), exercise (factor 11: t=-4.31, pFDR=0.0001), and high-sugar foods (factor 2: t=-3.73, pFDR=0.0007). Preference for alcohol (factor 7: t=-5.83, pFDR<1×10-8), exercise (factor 11: t=-7.66, pFDR<1×10-13), and high sugar foods (factor 2: t=6.03, pFDR<1×10-8) were also associated with PD risk. Instrumental variable regression of individual preferences revealed a significant relationship in which dietary preferences associated with higher brain iron levels also appeared to be linked to a lower risk for PD (p=0.004). A similar relationship was observed for estimates of nutrient intake (p=0.0006). Voxel-wise analysis of i) high-sugar and ii) alcohol factors confirmed T2-weighted signal differences consistent with iron accumulation patterns in motor regions of the brain including the cerebellum and basal ganglia. Conclusion: Dietary and lifestyle factors and preferences, especially those related to carbohydrates, alcohol, and exercise, are related to detectable differences in brain iron accumulation and alterations in risk of PD, suggesting a potential avenue for lifestyle interventions that could influence risk.

Prospective associations of family conflict with alcohol expectancies in the adolescent brain cognitive development study: effects of race and ethnicity.

Introduction: Alcohol expectancies predict subsequent alcohol use and related problems among adolescents, although predictors of alcohol expectancies remain unclear. This study examined the longitudinal association between family conflict, a sociocultural factor strongly implicated in adolescent alcohol use, and positive and negative alcohol expectancies of adolescents of diverse racial/ethnic backgrounds. Methods: Data were from the Adolescent Brain Cognitive Development Study 4.0 release, a multisite longitudinal study (N = 6,231, baseline age 9-10). Linear mixed-effects regression, with interactions between race/ethnicity and family conflict, tested the association between family conflict and alcohol expectancies, for each racial/ethnicity (e.g., Black vs. non-Black; White vs. non-White). Results: Interactions of family conflict with race/ethnicity in predicting negative and positive alcohol expectancies were statistically significant for models testing Black and White adolescents, but not for Asian, Hispanic, and Other. Family conflict at baseline predicted lower negative alcohol expectancy for Black adolescents (B = -.166, p = 0.033) and positive alcohol expectancy for White adolescents (B = 0.71, p = 0.023) at the year 3 follow-up. All models controlled for sex, age, family socioeconomic status, alcohol expectancies at year 1, and family conflict at year 3. Conclusion: The results indicate that family conflict is a potential risk factor for problematic alcohol expectancies for Black and White adolescents. Although we did not directly compare Black and White adolescents, our findings indicate that family conflict may operate differently for Black and White adolescents. Prevention and intervention efforts targeting family conflict may be relevant for different aspects of alcohol expectancies in Black and White families.

FEMA: Fast and efficient mixed-effects algorithm for large sample whole-brain imaging data.

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

Associations Between Family History of Alcohol and/or Substance Use Problems and Frontal Cortical Development From 9 to 13 Years of Age: A Longitudinal Analysis of the ABCD Study.

Background: Previous investigations that have examined associations between family history (FH) of alcohol/substance use and adolescent brain development have been primarily cross-sectional. Here, leveraging a large population-based sample of youths, we characterized frontal cortical trajectories among 9- to 13-year-olds with (FH+) versus without (FH-) an FH and examined sex as a potential moderator. Methods: We used data from 9710 participants in the Adolescent Brain Cognitive Development (ABCD) Study (release 4.0). FH+ was defined as having ≥1 biological parents and/or ≥2 biological grandparents with a history of alcohol/substance use problems (n = 2433). Our primary outcome was frontal cortical structural measures obtained at baseline (ages 9-11) and year 2 follow-up (ages 11-13). We used linear mixed-effects models to examine the extent to which FH status qualified frontal cortical development over the age span studied. Finally, we ran additional interactions with sex to test whether observed associations between FH and cortical development differed significantly between sexes. Results: For FH+ (vs. FH-) youths, we observed increased cortical thinning from 9 to 13 years across the frontal cortex as a whole. When we probed for sex differences, we observed significant declines in frontal cortical thickness among boys but not girls from ages 9 to 13 years. No associations were observed between FH and frontal cortical surface area or volume. Conclusions: Having a FH+ is associated with more rapid thinning of the frontal cortex across ages 9 to 13, with this effect driven primarily by male participants. Future studies will need to test whether the observed pattern of accelerated thinning predicts future substance use outcomes.

Familial factors rather than paternal age contribute to the aetiology of epilepsy.

BACKGROUND: Whether paternal age associated with offspring's epilepsy risk is a cause of de novo mutation as men age, or just an association due to confounding factors, is still unclear. METHODS: We performed a population-based, multi-generation and sibling comparison study in Taiwan, which included 2 751 232 singletons born in 2001-17 who were followed until 2020. Of these, 819 371/826 087 with information on paternal/maternal grandparents were selected for multi-generation analyses and 1 748 382 with sibling(s) were selected for sibling comparison. Cox proportional hazard regression was used to estimate the hazard ratio (HR) and 95% confidence interval (CI). RESULTS: In the total cohort, there was an increased risk of epilepsy in individuals with advanced paternal age, e.g. the HR for paternal age ≥50 was1.36 (95% CI: 1.15-1.61) compared with paternal age 25-29, and fathers older than mothers, e.g. the HR for parental age difference ≥15 years was 1.29 (95% CI: 1.16-1.43). When accounting for parental age difference, the association between paternal age and epilepsy in offspring was attenuated (HR for paternal age ≥50 was 1.11, 95% CI: 0.93-1.34). Multi-generation analyses did not support the association of advanced grand-paternal age at childbirth of the parent with offspring's risk of epilepsy. Sibling comparison analyses did not support the association of older paternal age with increased risk of epilepsy (HR was 0.96 for per year increase in paternal age, 95% CI: 0.96-0.97). CONCLUSIONS: These results do not support the hypothesis that advanced paternal age is associated with epilepsy in offspring. Instead, familial factors may explain the observed paternal age association with the offspring's risk of epilepsy.

Brain structural covariance network features are robust markers of early heavy alcohol use.

BACKGROUND AND AIMS: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. DESIGN AND SETTING: Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years). CASES: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. MEASUREMENTS: Graph theory metrics of segregation and integration were used to summarize SCN. FINDINGS: Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. CONCLUSION: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

"Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors.

While numerous studies over the last decade have highlighted the important influence of environmental factors on mental health, globally applicable data on physical surroundings are still limited. Access to such data and the possibility to link them to epidemiological studies is critical to unlocking the relationship of environment, brain and behaviour and promoting positive future mental health outcomes. The Adolescent Brain Cognitive Development (ABCD) Study is the largest ongoing longitudinal and observational study exploring brain development and child health among children from 21 sites across the United States. Here we describe the linking of the ABCD study data with satellite-based "Urban-Satellite" (UrbanSat) variables consisting of 11 satellite-data derived environmental indicators associated with each subject's residential address at their baseline visit, including land cover and land use, nighttime lights, and population characteristics. We present these UrbanSat variables and provide a review of the current literature that links environmental indicators with mental health, as well as key aspects that must be considered when using satellite data for mental health research. We also highlight and discuss significant links of the satellite data variables to the default mode network clustering coefficient and cognition. This comprehensive dataset provides the foundation for large-scale environmental epidemiology research.

Effects of parental mental health and family environment on impulsivity in preadolescents: a longitudinal ABCD study®.

Introduction: Impulsivity is a known risk factor for the development of substance use disorders and other psychiatric conditions that is influenced by both genetics and environment. Although research has linked parental mental health to children's impulsivity, potential mediators of this relationship remain understudied. The current investigation leverages the large national Adolescent Brain Cognitive Development (ABCD) Study to assess the mediating role of family conflict - an important social context for youth development - in the relationship between parental mental health and youth impulsivity. Methods: Data were from the first three annual waves of the ABCD study (Baseline N = 11,876 children, Mage = 9.9 years; 48% female; 52% White). Parental mental health conditions were self-reported internalizing, externalizing, and total problems. Youth completed the family conflict scale, and Urgency, Planning (lack of), Perseverance (lack of), Sensation Seeking, and Positive Urgency (UPPS-P) scale to measure impulsivity. To determine if within-family change in conflict from baseline to year 1 explained changes in the strength of relations between baseline parental mental health and year 2 youth impulsivity, longitudinal causal mediation analyses were conducted, controlling for demographic factors (i.e., age, sex, race, household income, parental education, marital status), as well as baseline levels of family conflict and outcomes. Separate mediation models were run for each mental health condition and each UPPS-P subscale. Results: Above and beyond bivariate relations, longitudinal mediation models, which included covariates, showed family conflict significantly (ps < 0.001) mediated relations between all three parental mental health conditions and all but one (i.e., sensation seeking) UPPS-P subscales. The proportion mediated through family conflict for internalizing problems and total problems on facets of impulsivity (except sensation seeking) ranged from 9% (for lack of perseverance) to 17% (for lack of planning). Proportion mediated via family conflict for externalizing problems on youth's impulsivity (except sensation seeking) was slightly higher, ranging between 13% (lack of perseverance) to 21% (lack of planning). Discussion: Family conflict may be an important intergenerational factor linking parental mental health and youth's impulsivity. Addressing parental mental health and family conflict may help curb increased impulsivity in youth, and in turn reduce adolescent substance use disorders.

Population-based Risk of Psychiatric Disorders Associated with Recurrent CNVs.

Recurrent copy number variants (rCNVs) are associated with increased risk of neuropsychiatric disorders but their pathogenic population-level impact is unknown. We provide population-based estimates of rCNV-associated risk of neuropsychiatric disorders for 34 rCNVs in the iPSYCH2015 case-cohort sample (n=120,247). Most observed significant increases in rCNV-associated risk for ADHD, autism or schizophrenia were moderate (HR:1.42-5.00), and risk estimates were highly correlated across these disorders, the most notable exception being high autism-associated risk with Prader-Willi/Angelman Syndrome duplications (HR=20.8). No rCNV was associated with significant increase in depression risk. Also, rCNV-associated risk was positively correlated with locus size and gene constraint. Comparison with published rCNV studies suggests that prevalence of some rCNVs is higher, and risk of psychiatric disorders lower, than previously estimated. In an era where genetics is increasingly being clinically applied, our results highlight the importance of population-based risk estimates for genetics-based predictions.

Associations between alcohol use and sex-specific maturation of subcortical gray matter morphometry from adolescence to adulthood: Replication across two longitudinal samples.

Subcortical brain morphometry matures across adolescence and young adulthood, a time when many youth engage in escalating levels of alcohol use. Initial cross-sectional studies have shown alcohol use is associated with altered subcortical morphometry. However, longitudinal evidence of sex-specific neuromaturation and associations with alcohol use remains limited. This project used generalized additive mixed models to examine sex-specific development of subcortical volumes and associations with recent alcohol use, using 7 longitudinal waves (n = 804, 51% female, ages 12-21 at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). A second, independent, longitudinal dataset, with up to four waves of data (n = 467, 43% female, ages 10-18 at baseline), was used to assess replicability. Significant, replicable non-linear normative volumetric changes with age were evident in the caudate, putamen, thalamus, pallidum, amygdala and hippocampus. Significant, replicable negative associations between subcortical volume and alcohol use were found in the hippocampus in all youth, and the caudate and thalamus in female but not male youth, with significant interactions present in the caudate, thalamus and putamen. Findings suggest a structural vulnerability to alcohol use, or a predisposition to drink alcohol based on brain structure, with female youth potentially showing heightened risk, compared to male youth.

Polygenic risk for neuroticism is associated with less efficient control in more difficult situations.

Neuroticism is a heritable trait and a risk factor for mental health due to its relevance to poor control of negative events. To examine the relationship between genetic propensity for neuroticism and control processing, we used the polygenic risk score (PRS) approach and a stop signal task during fMRI. We hypothesized that genetic propensity for neuroticism may moderate control processing as a function of control difficulty. PRSs for neuroticism were computed from a transdiagnostic group of individuals (n=406) who completed the stop signal task. The level of control difficulty was a function of the stop signal asynchrony: shorter asynchrony allows easier stopping whereas longer asynchrony makes stopping difficult. The relationship between PRS for neuroticism and neural activity for controlling responses was examined by the stop signal asynchrony. Although PRS for neuroticism did not relate to the overall inhibitory control, individuals with high PRS for neuroticism showed greater activity in left dorsal prefrontal cortex, middle temporal gyrus, and dorsal posterior cingulate cortex for difficult control. Thus, the genetic propensity for neuroticism affects neural processing in a difficult control context, which may help to explain why individuals with high levels of neuroticism exert poor control of negative events in difficult situations.

Estimating the Total Variance Explained by Whole-Brain Imaging for Zero-inflated Outcomes.

Zero-inflated outcomes are very common in behavioral data, particularly for responses to psychological questionnaires. Modeling these challenging distributions is further exacerbated by the absence of established statistical models capable of characterizing total signals attributed to whole-brain imaging features, making the accurate assessment of brain-behavior relationships particularly formidable. Given this critical need, we have developed a novel variational Bayes algorithm that characterizes the total signal captured by whole-brain imaging features for zero-inflated outcomes . Our zero-inflated variance (ZIV) estimator robustly estimates the fraction of variance explained (FVE) and the proportion of non-null effects from large-scale imaging data. In simulations, ZIV outperformed other linear prediction algorithms. Applying ZIV to data from one of the largest neuroimaging studies, the Adolescent Brain Cognitive Development SM (ABCD) Study, we found that whole-brain imaging features have a larger FVE for externalizing compared to internalizing behavior. We also demonstrate that the ZIV estimator, especially applied to focal sub-scales, can localize key neurocircuitry associated with human behavior.

Ramipril for the Treatment of COVID-19: RAMIC, a Randomized, Double-Blind, Placebo-Controlled Clinical Trial.

INTRODUCTION: Retrospective studies report that angiotensin-converting enzyme inhibitors (ACEIs) may reduce the severity of COVID-19, but prospective data on de novo treatment with ACEIs are limited. The RAMIC trial was a randomized, multicenter, placebo-controlled, double-blind, allocation-concealed clinical trial to examine the efficacy of de novo ramipril versus placebo for the treatment of COVID-19. METHODS: Eligible participants were aged 18 years and older with a confirmed diagnosis of SARS-CoV-2 infection, recruited from urgent care clinics, emergency departments, and hospital inpatient wards at eight sites in the USA. Participants were randomly assigned to daily ramipril 2.5 mg or placebo orally in a 2:1 ratio, using permuted block randomization. Analyses were conducted on an intention-to-treat basis. The primary outcome was a composite of mortality, intensive care unit (ICU) admission, or invasive mechanical ventilation by day 14. RESULTS: Between 27 May 2020 and 19 April 2021, a total of 114 participants (51% female) were randomized to ramipril (n = 79) or placebo (n = 35). The overall mean (± SD) age and BMI were 45 (± 15) years and 33 (± 8) kg/m2. Two participants in the ramipril group required ICU admission and one died, compared with none in the placebo group. There were no significant differences between ramipril and placebo in the primary endpoint (ICU admission, mechanical ventilation, or death) (3% versus 0%, p = 1.00) or adverse events (27% versus 29%, p = 0.82). The study was terminated early because of a low event rate and subsequent Emergency Use Authorization of therapies for COVID-19. CONCLUSION: De novo ramipril was not different compared with placebo in improving or worsening clinical outcomes from COVID-19 but appeared safe in non-critically ill patients with COVID-19. TRIAL REGISTRATION: Clinicaltrials.gov NCT04366050.