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.

Neuroanatomical variability associated with early substance use initiation: Results from the ABCD Study.

The extent to which neuroanatomical variability associated with substance involvement reflects pre-existing risk and/or consequences of substance exposure remains poorly understood. In the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study, we identify associations between global and regional differences in brain structure and early substance use initiation (i.e., occurring <15 years of age; nsanalytic=6,556-9,804), with evidence that associations precede initiation. Neurodevelopmental variability in brain structure may confer risk for substance involvement.

Associations Between Polygenic Scores for Cognitive and Non-cognitive Factors of Educational Attainment and Measures of Behavior, Psychopathology, and Neuroimaging in the Adolescent Brain Cognitive Development Study.

Background: Both cognitive and non-cognitive (e.g., traits like curiosity) factors are critical for social and emotional functioning and independently predict educational attainment. These factors are heritable and genetically correlated with a range of health-relevant traits and behaviors in adulthood (e.g., risk-taking, psychopathology). However, whether these associations are present during adolescence, and to what extent these relationships diverge, could have implications for adolescent health and well-being. Methods: Using data from 5,517 youth of European ancestry from the ongoing Adolescent Brain Cognitive DevelopmentSM Study, we examined associations between polygenic scores (PGS) for cognitive and non-cognitive factors and outcomes related to cognition, socioeconomic status, risk tolerance and decision-making, substance initiation, psychopathology, and brain structure. Results: Cognitive and non-cognitive PGSs were both positively associated with cognitive performance and family income, and negatively associated with ADHD and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk-taking, delayed discounting, and anorexia, as well as lower likelihood of nicotine initiation. The cognitive PGS was further associated with cognition scores and anorexia in within-sibling analyses, suggesting these results do not solely reflect the effects of assortative mating or passive gene-environment correlations. The cognitive PGS showed significantly stronger associations with cortical volumes than the non-cognitive PGS and was associated with right hemisphere caudal anterior cingulate and pars-orbitalis in within-sibling analyses, while the non-cognitive PGS showed stronger associations with white matter fractional anisotropy and a significant within-sibling association for right superior corticostriate-frontal cortex. Conclusions: Our findings suggest that PGSs for cognitive and non-cognitive factors show similar associations with cognition and socioeconomic status as well as other psychosocial outcomes, but distinct associations with regional neural phenotypes in this adolescent sample.

Identification of a convergent spinal neuron population that encodes itch.

Itch is a protective sensation that drives scratching. Although specific cell types have been proposed to underlie itch, the neural circuit basis for itch remains unclear. Here, we used two-photon Ca2+ imaging of the dorsal horn to visualize the neuronal populations that are activated by itch-inducing agents. We identify a convergent population of spinal neurons that is defined by the expression of GRPR. Moreover, we discover that itch is conveyed to the brain via GRPR-expressing spinal output neurons that target the lateral parabrachial nucleus. Further, we show that nalfurafine, a clinically effective kappa opioid receptor agonist, relieves itch by inhibiting GRPR spinoparabrachial neurons. Finally, we demonstrate that a subset of GRPR spinal neurons show persistent, cell-intrinsic Ca2+ oscillations. These experiments provide the first population-level view of the spinal neurons that respond to pruritic stimuli, pinpoint the output neurons that convey itch to the brain, and identify the cellular target of kappa opioid receptor agonists for the inhibition of itch.

Alcohol use and grey matter structure: Disentangling predispositional and causal contributions in human studies.

Alcohol use is a growing global health concern and economic burden. Alcohol involvement (i.e., initiation, use, problematic use, alcohol use disorder) has been reliably associated with broad spectrum grey matter differences in cross-sectional studies. These findings have been largely interpreted as reflecting alcohol-induced atrophy. However, emerging data suggest that brain structure differences also represent pre-existing vulnerability factors for alcohol involvement. Here, we review evidence from human studies with designs (i.e., family-based, genomic, longitudinal) that allow them to assess the plausibility that these correlates reflect predispositional risk factors and/or causal consequences of alcohol involvement. These studies provide convergent evidence that grey matter correlates of alcohol involvement largely reflect predisposing risk factors, with some evidence for potential alcohol-induced atrophy. These conclusions highlight the importance of study designs that can provide causal clues to cross-sectional observations. An integrative model may best account for these data, in which predisposition to alcohol use affects brain development, effects which may then be compounded by the neurotoxic consequences of heavy alcohol use.

Characteristics Associated With Cannabis Use Initiation by Late Childhood and Early Adolescence in the Adolescent Brain Cognitive Development (ABCD) Study.

This cohort study evaluates characteristics associated with early-onset cannabis use.

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders.

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

A Phenome-Wide Association Study (PheWAS) of Late Onset Alzheimer Disease Genetic Risk in Children of European Ancestry at Middle Childhood: Results from the ABCD Study.

Genetic risk for Late Onset Alzheimer Disease (AD) has been associated with lower cognition and smaller hippocampal volume in healthy young adults. However, whether these and other associations are present during childhood remains unclear. Using data from 5556 genomically-confirmed European ancestry youth who completed the baseline session of the ongoing the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®), our phenome-wide association study estimating associations between four indices of genetic risk for late-onset AD (i.e., AD polygenic risk scores (PRS), APOE rs429358 genotype, AD PRS with the APOE region removed (ADPRS-APOE), and an interaction between ADPRS-APOE and APOE genotype) and 1687 psychosocial, behavioral, and neural phenotypes revealed no significant associations after correction for multiple testing (all ps > 0.0002; all pfdr > 0.07). These data suggest that AD genetic risk may not phenotypically manifest during middle-childhood or that effects are smaller than this sample is powered to detect.

Multi-omics cannot replace sample size in genome-wide association studies.

The integration of multi-omics information (e.g., epigenetics and transcriptomics) can be useful for interpreting findings from genome-wide association studies (GWAS). It has been suggested that multi-omics could circumvent or greatly reduce the need to increase GWAS sample sizes for novel variant discovery. We tested whether incorporating multi-omics information in earlier and smaller-sized GWAS boosts true-positive discovery of genes that were later revealed by larger GWAS of the same/similar traits. We applied 10 different analytic approaches to integrating multi-omics data from 12 sources (e.g., Genotype-Tissue Expression project) to test whether earlier and smaller GWAS of 4 brain-related traits (alcohol use disorder/problematic alcohol use, major depression/depression, schizophrenia, and intracranial volume/brain volume) could detect genes that were revealed by a later and larger GWAS. Multi-omics data did not reliably identify novel genes in earlier less-powered GWAS (PPV <0.2; 80% false-positive associations). Machine learning predictions marginally increased the number of identified novel genes, correctly identifying 1-8 additional genes, but only for well-powered early GWAS of highly heritable traits (i.e., intracranial volume and schizophrenia). Although multi-omics, particularly positional mapping (i.e., fastBAT, MAGMA, and H-MAGMA), can help to prioritize genes within genome-wide significant loci (PPVs = 0.5-1.0) and translate them into information about disease biology, it does not reliably increase novel gene discovery in brain-related GWAS. To increase power for discovery of novel genes and loci, increasing sample size is required.

Phenome-wide Investigation of Behavioral, Environmental, and Neural Associations with Cross-Disorder Genetic Liability in Youth of European Ancestry.

Etiologic insights into psychopathology may be gained by using hypothesis-free methods to identify associations between genetic risk for broad psychopathology and phenotypes measured during adolescence, including both markers of child psychopathology and intermediate phenotypes such as neural structure that may link genetic risk with outcomes. We conducted a phenome-wide association study (phenotype n=1,269-1,694) of polygenic risk scores (PRS) for broad spectrum psychopathology (i.e., Compulsive, Psychotic, Neurodevelopmental, and Internalizing) in youth of PCA-selected European ancestry (n=5,556; ages 9-13) who completed the baseline and/or two-year follow-up of the ongoing Adolescent Brain Cognitive Development℠ (ABCD) Study. We found that Neurodevelopmental and Internalizing PRS were significantly associated with a host of proximal as well as distal phenotypes (Neurodevelopmental: 187 and 211; Internalizing: 122 and 173 phenotypes at baseline and two-year follow-up, respectively), whereas Compulsive and Psychotic PRS showed zero and one significant associations, respectively, after Bonferroni correction. Neurodevelopmental PRS were further associated with brain structure metrics (e.g., total volume, mean right hemisphere cortical thickness), with only cortical volume indirectly linking Neurodevelopmental PRS to grades in school. Genetic variation influencing risk to psychopathology manifests broadly as behaviors, psychopathology symptoms, and related risk factors in middle childhood and early adolescence.

Characterizing Alcohol Expectancies in the ABCD Study: Associations with Sociodemographic Factors, the Immediate Social Environment, and Genetic Propensities.

Alcohol expectancies (AEs) are associated with likelihood of alcohol initiation and subsequent alcohol use disorders. It is unclear whether genetic predisposition to alcohol use and/or related traits contributes to shaping how one expects to feel when drinking alcohol. We used the Adolescent Brain Cognitive Development study to examine associations between genetic propensities (i.e., polygenic risk for problematic alcohol use, depression, risk-taking), sociodemographic factors (i.e., parent income), and the immediate social environment (i.e., peer use and disapproval toward alcohol) and positive and negative AEs in alcohol-naïve children (max analytic N = 5,352). Mixed-effect regression models showed that age, parental education, importance of the child's religious beliefs, adverse childhood experiences, and peer disapproval of alcohol use were associated with positive and/or negative AEs, to varying degrees. Overall, our results suggest several familial and psychosocial predictors of AEs but little evidence of contributions from polygenic liability to problematic alcohol use or related phenotypes.

Moderation effects in personality disorder research.

Tests of statistical interactions (or tests of moderation effects) in personality disorder research are a common way for researchers to examine nuanced hypotheses relevant to personality pathology. However, the nature of statistical interactions makes them difficult to reliably detect in many research scenarios. The present study used a flexible, simulation-based approach to estimate statistical power to detect trait-by-trait interactions common to psychopathy research using the Triarchic model of Psychopathy and the Psychopathic Personality Inventory. Our results show that even above-average sample sizes in these literatures (e.g., N = 428) provide inadequate power to reliably detect trait-by-trait interactions, and the sample sizes needed to detect interaction effect sizes in realistic scenarios are extremely large, ranging from 1,300 to 5,200. The implications for trait-by-trait interactions in psychopathy are discussed, as well as how the present findings might generalize to other areas of personality disorder research. We provide recommendations for how to design research studies that can provide informative tests of interactions in personality disorder research, but also highlight that a more realistic option is to abandon the traditional approach when testing for interaction effects and adopt alternative approaches that may be more productive. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Association of Mental Health Burden With Prenatal Cannabis Exposure From Childhood to Early Adolescence: Longitudinal Findings From the Adolescent Brain Cognitive Development (ABCD) Study.

This study assesses whether associations of prenatal cannabis exposure and psychopathology persist into early adolescence.

Psychotic-like Experiences and Polygenic Liability in the Adolescent Brain Cognitive Development Study.

BACKGROUND: Childhood psychotic-like experiences (PLEs) often precede the development of later severe psychopathology. This study examined whether childhood PLEs are associated with several psychopathology-related polygenic scores (PGSs) and additionally examined possible neural and behavioral mechanisms. METHODS: Adolescent Brain Cognitive Development Study baseline data from children with European ancestry (n = 4650, ages 9-10 years, 46.8% female) were used to estimate associations between PLEs (i.e., both total and presence of significantly distressing) and PGSs for psychopathology (i.e., schizophrenia, psychiatric cross-disorder risk, PLEs) and related phenotypes (i.e., educational attainment [EDU], birth weight, inflammation). We also assessed whether variability in brain structure indices (i.e., volume, cortical thickness, surface area) and behaviors proximal to PGSs (e.g., cognition for EDU) indirectly linked PGSs to PLEs using mediational models. RESULTS: Total and significantly distressing PLEs were associated with EDU and cross-disorder PGSs (all %ΔR2s = 0.202%-0.660%; false discovery rate-corrected ps < .006). Significantly distressing PLEs were also associated with higher schizophrenia and PLE PGSs (both %ΔR2 = 0.120%-0.216%; false discovery rate-corrected ps < .03). There was evidence that global brain volume metrics and cognitive performance indirectly linked EDU PGS to PLEs (estimated proportion mediated = 3.33%-32.22%). CONCLUSIONS: Total and significantly distressing PLEs were associated with genomic risk indices of broad-spectrum psychopathology risk (i.e., EDU and cross-disorder PGSs). Significantly distressing PLEs were also associated with genomic risk for psychosis (i.e., schizophrenia, PLEs). Global brain volume metrics and PGS-proximal behaviors represent promising putative intermediary phenotypes that may indirectly link genomic risk to psychopathology. Broadly, polygenic scores derived from genome-wide association studies of adult samples generalize to indices of psychopathology risk among children.

Aberrant levels of cortical myelin distinguish individuals with depressive disorders from healthy controls.

The association between depressive disorders and measures reflecting myelin content is underexplored, despite growing evidence of associations with white matter tract integrity. We characterized the T1w/T2w ratio using the Glasser atlas in 39 UD and 47 HC participants (ages = 19-44, 75% female). A logistic elastic net regularized regression with nested cross-validation and a subsequent linear discriminant analysis conducted on held-out samples were used to select brain regions and classify patients vs. healthy controls (HC). True-label model performance was compared against permuted-label model performance. The T1w/T2w ratio distinguished patients from HC with 68% accuracy (p < 0.001; sensitivity = 63.8%, specificity = 71.5%). Brain regions contributing to this classification performance were located in the orbitofrontal cortex, anterior cingulate, extended visual, and auditory cortices, and showed statistically significant differences in the T1w/T2w ratio for patients vs. HC. As the T1w/T2w ratio is thought to characterize cortical myelin, patterns of cortical myelin in these regions may be a biomarker distinguishing individuals with depressive disorders from HC.

Polygenic risk scores for alcohol involvement relate to brain structure in substance-naïve children: Results from the ABCD study.

Brain imaging-derived structural correlates of alcohol involvement have largely been speculated to arise as a consequence of alcohol exposure. However, they may also reflect predispositional risk. In substance naïve children of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study (n = 3013), mixed-effects models estimated whether polygenic risk scores (PRS) for problematic alcohol use (PAU-PRS) and drinks per week (DPW-PRS) are associated with magnetic resonance imaging-derived brain structure phenotypes (i.e., total and regional: cortical thickness, surface area and volume; subcortical volume; white matter volume, fractional anisotropy, mean diffusivity). Follow-up analyses evaluated whether any identified regions were also associated with polygenic risk among substance naïve children of African ancestry (n = 898). After adjustment for multiple testing correction, polygenic risk for PAU was associated with lower volume of the left frontal pole and greater cortical thickness of the right supramarginal gyrus (|ßs| > 0.009; ps < 0.001; psfdr < 0.046; r2 s < 0.004). PAU PRS and DPW PRS showed nominally significant associations with a host of other regional brain structure phenotypes (e.g., insula surface area and volume). None of these regions showed any, even nominal association among children of African ancestry. Genomic liability to alcohol involvement may manifest as variability in brain structure during middle childhood prior to alcohol use initiation. Broadly, alcohol-related variability in brain morphometry may partially reflect predisposing genomic influence. Larger discovery genome-wide association studies and target samples of diverse ancestries are needed to determine whether observed associations may generalize across ancestral origins.

The longitudinal stability of fMRI activation during reward processing in adolescents and young adults.

BACKGROUND: The use of functional neuroimaging has been an extremely fruitful avenue for investigating the neural basis of human reward function. This approach has included identification of potential neurobiological mechanisms of psychiatric disease and examination of environmental, experiential, and biological factors that may contribute to disease risk via effects on the reward system. However, a central and largely unexamined assumption of much of this research is that neural reward function is an individual difference characteristic that is relatively stable and trait-like over time. METHODS: In two independent samples of adolescents and young adults studied longitudinally (Ns = 145 & 139, 100% female and 100% male, ages 15-21 and 20-22, 2-4 scans and 2 scans respectively), we tested within-person stability of reward-task BOLD activation, with a median of 1 and 2 years between scans. We examined multiple commonly used contrasts of active states and baseline in both the anticipation and feedback phases of a card-guessing reward task. We examined the effects of cortical parcellation resolution, contrast, network (reward regions and resting-state networks), region-size, and activation strength and variability on the stability of reward-related activation. RESULTS: In both samples, contrasts of an active state relative to a baseline were more stable (ICC: intra-class correlation; e.g., Win>Baseline; mean ICC = 0.13 - 0.33) than contrasts of two active states (e.g., Win>Loss; mean ICC = 0.048 - 0.05). Additionally, activation in reward regions was less stable than in many non-task networks (e.g., dorsal attention), and activation in regions with greater between-subject variability showed higher stability in both samples. CONCLUSIONS: These results show that some contrasts from functional neuroimaging activation during a card guessing reward task have partially trait-like properties in adolescent and young adult samples over 1-2 years. Notably, results suggest that contrasts intended to map cognitive function and show robust group-level effects (i.e. Win > Loss) may be less effective in studies of individual differences and disease risk. The robustness of group-level activation should be weighed against other factors when selecting regions of interest in individual difference fMRI studies.

Neuroticism and reward-related ventral striatum activity: Probing vulnerability to stress-related depression.

Elevated neuroticism may confer vulnerability to the depressogenic effects of stressful life events (SLEs). However, the mechanisms underlying this susceptibility remain poorly understood. Accumulating evidence suggests that stress-related disruptions in neural reward processing might undergird links between stress and depression. Using data from the Saint Louis Personality and Aging Network (SPAN) study and Duke Neurogenetics Study (DNS), we examined whether neuroticism moderates links between stressful life events (SLE) and depression as well as SLEs and ventral striatum (VS) response to reward. In the longitudinal SPAN sample (n = 971 older adults), SLEs prospectively predicted future depressive symptoms, especially among those reporting elevated neuroticism, even after accounting for prior depressive symptoms and previous SLE exposure (NxSLE interaction: p = .016, ΔR² = 0.003). Cross-sectional analyses of the DNS, a young adult college sample with neuroimaging data, replicated this interaction (n = 1,343: NxSLE interaction: p = .019, ΔR² = 0.003) and provided evidence that neuroticism moderates the association between SLEs and reward-related VS response (n = 1,195, NxSLE: p = .017, ΔR² = 0.0048). Blunted left VS response to reward was associated with a lifetime depression diagnosis, r = -0.07, p = .02, but not current depressive symptoms, r = -0.003, p = .93. These data suggest that neuroticism may promote vulnerability to stress-related depression and that sensitivity to stress-related reductions in VS response may be a potential neural mechanism underlying vulnerability to clinically significant depression. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Protocol for a machine learning algorithm predicting depressive disorders using the T1w/T2w ratio.

The T1w/T2w ratio is a novel magnetic resonance imaging (MRI) measure that is thought to be sensitive to cortical myelin. Using this novel measure requires developing novel pipelines for the data quality assurance, data analysis, and validation of the findings in order to apply the T1w/T2w ratio for classification of disorders associated with the changes in the myelin levels. In this article, we provide a detailed description of such a pipeline as well as the reference to the scripts used in our recent report that applied the T1w/T2w ratio and machine learning to classify individuals with depressive disorders from healthy controls.