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.

Characteristics of women concordant and discordant for urine drug screens for cannabis exposure and self-reported cannabis use during pregnancy.

BACKGROUND: Increasing cannabis use among pregnant people and equivocal evidence linking prenatal cannabis exposure to adverse outcomes in offspring highlights the need to understand its potential impact on pregnancy and child outcomes. Assessing cannabis use during pregnancy remains a major challenge with potential influences of stigma on self-report as well as detection limitations of easily collected biological matrices. OBJECTIVE: This descriptive study examined the concordance between self-reported (SR) cannabis use and urine drug screen (UDS) detection of cannabis exposure during the first trimester of pregnancy and characterized concordant and discordant groups for sociodemographic factors, modes of use, secondhand exposure to cannabis and tobacco, and alcohol use and cotinine positivity. STUDY DESIGN: The Cannabis Use During Development and Early Life (CUDDEL) Study is an ongoing longitudinal study that recruits pregnant individuals presenting for obstetric care, who report lifetime cannabis use as well as using (n = 289) or not using cannabis (n = 169) during pregnancy. During the first trimester pregnancy visit, SR of cannabis use and a UDS for cannabis, other illicit drugs and nicotine are acquired from eligible participants, of whom 333 as of 05/01/2023 had both. RESULTS: Using available CUDDEL Study data on both SR and UDS (n = 333; age 26.6 ± 4.7; 88.6% Black; 45.4% below federal poverty threshold; 56.5% with paid employment; 89% with high school education; 22% first pregnancy; 12.3 ± 3.6 weeks gestation), we classified pregnant individuals with SR and UDS data into 4 groups based on concordance (k = 0.49 [95% C.I. 0.40-0.58]) between SR cannabis use and UDS cannabis detection during the first trimester: 1) SR+/UDS+ (n = 107); 2) SR-/UDS- (n = 142); 3) SR+/UDS- (n = 44); 4) SR-/UDS+ (n = 40). Those who were SR+/UDS- reported less frequent cannabis use and fewer hours under the influence of cannabis during their pregnancy. Those who were SR-/UDS+ were more likely to have joined the study at a lower gestational age with 62.5% reporting cannabis use during their pregnancy prior to being aware that they were pregnant. Of the 40 SR-/UDS+ women, 14 (i.e., 35%) reported past month secondhand exposure, or blunt usage. In the subset of individuals with SR and UDS available at trimester 2 (N = 160) and 3 (N = 140), concordant groups were mostly stable and > 50% of those in the discordant groups became concordant by the second trimester. Classifying individuals as exposed or not exposed who were SR+ and/or UDS+ resulted in minor changes in group status based on self-report at screening. CONCLUSION: Overall, there was moderate concordance between SR and UDS for cannabis use/exposure during pregnancy. Instances of SR+/UDS- discordancy may partially be attributable to lower levels of use that are not detected on UDS. SR-/UDS+ discordancy may arise from recent use prior to knowledge of pregnancy, extreme secondhand exposure, deception, and challenges with completing questionnaires. Acquiring both self-report and biological detection of cannabis use/exposure allows for the examination of convergent evidence. Classifying those who are SR+ and/or UDS+ as individuals who used cannabis during their first trimester after being aware of their pregnancy resulted in only a minor change in exposure status; thus, relying on self-report screening, at least in this population and within this sociocultural context likely provides an adequate approximation of cannabis use during pregnancy.

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 COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study.

COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N = 416 including n = 224 COVID-19 cases; Mage = 58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF). We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing. COVID-19 case status was not significantly associated with DBSI-RF (|ß|'s < 0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (ß's > 0.3, all pFDR = 0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology. Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.

Assessment of substance exposures in nail clipping samples: A systematic review.

BACKGROUND: Studies of prenatal substance exposure often rely on self-report, urine drug screens, and/or analyses of blood or meconium biomarkers. Accuracy of these measures is limited when assessing exposure over many weeks or months of gestation. Nails are increasingly being considered as a matrix from which to assess substance exposure. This systematic review synthesizes data on the validity of detecting alcohol, nicotine, cannabis, and opioid from nail clippings, with an emphasis on prenatal exposure assessment. METHODS: The systematic review was conducted using PRISMA 2020 guidelines. Seven databases were searched with keywords relevant to the four substances of interest. Results were summarized grouping manuscripts by the exposure of interest with focus on accuracy and feasibility. RESULTS: Of 2384 papers initially identified, 35 manuscripts were included in our qualitative synthesis. Only a few studies specifically looked at pregnant individuals or mother-child dyads. Across the four substances, many studies demonstrated a dose-response relationship between exposure and concentration of analytes in nails. Nail assays appear to detect lower level of exposure compared to hair; however, sample insufficiency, especially for multi-substance assays, remains a limitation. CONCLUSIONS: Based on the reviewed studies, nail clippings are an acceptable and potentially preferable matrix for the evaluation of these four prenatal substances when sampling frequency and/or study design necessitates assessment of past exposures over an extended period. Nails have the advantage of infrequent sampling and minimal invasiveness to assess a broad exposure period. Future studies should examine validity of analytes in toenail versus fingernail clippings.

Shared and unique heritability of hippocampal subregion volumes in children and adults.

Behavioral genetic analyses have not demonstrated robust, unique, genetic correlates of hippocampal subregion volume. Genetic differentiation of hippocampal longitudinal axis subregion volume has not yet been investigated in population-based samples, although this has been demonstrated in rodent and post-mortem human tissue work. The following study is the first population-based investigation of genetic factors that contribute to gray matter volume along the hippocampal longitudinal axis. Twin-based biometric analyses demonstrated that longitudinal axis subregions are associated with significant, unique, genetic variance, and that longitudinal axis subregions are also associated with significant shared, hippocampus-general, genetic factors. Our study's findings suggest that genetic differences in hippocampal longitudinal axis structure can be detected in individual differences in gray matter volume in population-level research designs.

Investigating the Relationship Between Smoking Behavior and Global Brain Volume.

Background: Previous studies have shown that brain volume is negatively associated with cigarette smoking, but there is an ongoing debate about whether smoking causes lowered brain volume or a lower brain volume is a risk factor for smoking. We address this debate through multiple methods that evaluate directionality: Bradford Hill's criteria, which are commonly used to understand a causal relationship in epidemiological studies, and mediation analysis. Methods: In 32,094 participants of European descent from the UK Biobank dataset, we examined the relationship between a history of daily smoking and brain volumes, as well as an association of genetic risk score to ever smoking with brain volume. Results: A history of daily smoking was strongly associated with decreased brain volume, and a history of heavier smoking was associated with a greater decrease in brain volume. The strongest association was between total gray matter volume and a history of daily smoking (effect size = -2964 mm3, p = 2.04 × 10-16), and there was a dose-response relationship with more pack years smoked associated with a greater decrease in brain volume. A polygenic risk score for smoking initiation was strongly associated with a history of daily smoking (effect size = 0.05, p = 4.20 × 10-84), but only modestly associated with total gray matter volume (effect size = -424 mm3, p = .01). Mediation analysis indicated that a history of daily smoking mediated the relationship between the smoking initiation polygenic risk score and total gray matter volume. Conclusions: A history of daily smoking is strongly associated with a decreased total brain volume.

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.

Prenatal cannabis exposure is associated with localized brain differences that partially mediate associations with increased adolescent psychopathology.

Prenatal cannabis exposure (PCE) is associated with mental health problems, but the neurobiological mechanisms remain unknown. We find that PCE is associated with localized differences across neuroimaging metrics that longitudinally mediate associations with mental health in adolescence (n=9,322-10,186). Differences in brain development may contribute to PCE-related variability in adolescent mental health.

Personality traits moderate associations between word recall and subjective memory.

Cognitive gerontology research requires consideration of performance as well as perceptions of performance. While subjective memory is positively associated with memory performance, these correlations typically are modest in magnitude, leading to the need to consider whether certain people may show weaker or stronger linkages between performance and perceptions. The current study leveraged personality (NEO Big Five), memory performance (i.e., word recall), and perceptions of memory ability (i.e., metamemory in adulthood and memory decline) data from the St. Louis Personality and Aging Network (SPAN) study (n = 774, mean age: 71.52 years). Extraversion and conscientiousness held the most consistent associations with the cognitive variables of interest, as both traits were positively associated with metamemory and word recall, but negatively associated with subjective decline. Moreover, extraversion moderated associations between word recall and both memory capacity and complaints, insofar that objective-subjective associations were weaker for those adults higher in extraversion. These findings highlight the need to understand how personality influences the sources of information employed for subjective cognitive beliefs.

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.

Reliability of diurnal salivary cortisol metrics: A meta-analysis and investigation in two independent samples.

Stress-induced dysregulation of diurnal cortisol is a cornerstone of stress-disease theories; however, observed associations between cortisol, stress, and health have been inconsistent. The reliability of diurnal cortisol features may contribute to these equivocal findings. Our meta-analysis (5 diurnal features from 11 studies; total participant n = 3307) and investigation (15 diurnal cortisol features) in 2 independent studies (St. Louis Personality and Aging Network [SPAN] Study, n = 147, ages 61-73; Minnesota Longitudinal Study of Risk and Adaptation [MLSRA] Study, n = 90, age 37) revealed large variability in the day-to-day test-retest reliability of diurnal features derived from salivary cortisol data (i.e., ICC = 0.00-0.75). Collectively, these data indicate that some commonly used diurnal cortisol features have poor reliability that is insufficient for individual differences research (e.g., cortisol awakening response) while others (e.g., area under the curve with respect to ground) have fair-to-good reliability that could support reliable identification of associations in well-powered studies.

Associations between COVID-19 and putative markers of neuroinflammation: A diffusion basis spectrum imaging study.

COVID-19 remains a significant international public health concern. Yet, the mechanisms through which symptomatology emerges remain poorly understood. While SARS-CoV-2 infection may induce prolonged inflammation within the central nervous system, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal UK Biobank neuroimaging data acquired prior to and following COVID-19 testing (N=416 including n=224 COVID-19 cases; Mage=58.6). Putative neuroinflammation was assessed in gray matter structures and white matter tracts using non-invasive Diffusion Basis Spectrum Imaging (DBSI), which estimates inflammation-related cellularity (DBSI-restricted fraction; DBSI-RF) and vasogenic edema (DBSI-hindered fraction; DBSI-HF).We hypothesized that COVID-19 case status would be associated with increases in DBSI markers after accounting for potential confound (age, sex, race, body mass index, smoking frequency, and data acquisition interval) and multiple testing. COVID-19 case status was not significantly associated with DBSI-RF (|ß|'s<0.28, pFDR >0.05), but with greater DBSI-HF in left pre- and post-central gyri and right middle frontal gyrus (ß's>0.3, all pFDR=0.03). Intriguingly, the brain areas exhibiting increased putative vasogenic edema had previously been linked to COVID-19-related functional and structural alterations, whereas brain regions displaying subtle differences in cellularity between COVID-19 cases and controls included regions within or functionally connected to the olfactory network, which has been implicated in COVID-19 psychopathology. Nevertheless, our study might not have captured acute and transitory neuroinflammatory effects linked to SARS-CoV-2 infection, possibly due to symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with COVID-19.

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.

Neuroinflammation in the Amygdala Is Associated With Recent Depressive Symptoms.

BACKGROUND: Converging evidence suggests that elevated inflammation may contribute to depression. Yet, the link between peripheral inflammation and neuroinflammation in depression is unclear. Here, using data from the UK Biobank, we estimated associations among depression, C-reactive protein (CRP) as a measure of peripheral inflammation, and neuroinflammation as indexed by diffusion basis spectral imaging-based restricted fraction (DBSI-RF). METHODS: DBSI-RF was derived from diffusion-weighted imaging data (N = 11,512) for whole-brain gray matter (global-RF), and regions of interest in the bilateral amygdala (amygdala-RF) and hippocampus (hippocampus-RF), and CRP was estimated from blood (serum) samples. Self-reported recent depression symptoms were measured using a 4-item assessment. Linear regressions were used to estimate associations between CRP and DBSI-RFs with depression while adjusting for the following covariates: age, sex, body mass index, smoking, drinking, and medical conditions. RESULTS: Elevated CRP was associated with higher depression symptoms (ß = 0.04, false discovery rate-corrected p < .005) and reduced global-RF (ß = -0.03, false discovery rate-corrected p < .001). Higher amygdala-RF was associated with elevated depression-an effect resilient to added covariates and CRP (ß = 0.02, false discovery rate-corrected p < .05). Interestingly, this association was stronger in individuals with a lifetime history of depression (ß = 0.07, p < .005) than in those without (ß = 0.03, p < .05). Associations between global-RF or hippocampus-RF with depression were not significant, and no DBSI-RF indices indirectly linked CRP with depression (i.e., mediation effect). CONCLUSIONS: Peripheral inflammation and DBSI-RF neuroinflammation in the amygdala are independently associated with depression, consistent with animal studies suggesting distinct pathways of peripheral inflammation and neuroinflammation in the pathophysiology of depression and with investigations highlighting the role of the amygdala in stress-induced inflammation and depression.

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 systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility.

Brain aging is a complex, multifaceted process that can be challenging to model in ways that are accurate and clinically useful. One of the most common approaches has been to apply machine learning to neuroimaging data with the goal of predicting age in a data-driven manner. Building on initial brain age studies that were derived solely from T1-weighted scans (i.e., unimodal), recent studies have incorporated features across multiple imaging modalities (i.e., "multimodal"). In this systematic review, we show that unimodal and multimodal models have distinct advantages. Multimodal models are the most accurate and sensitive to differences in chronic brain disorders. In contrast, unimodal models from functional magnetic resonance imaging were most sensitive to differences across a broad array of phenotypes. Altogether, multimodal imaging has provided us valuable insight for improving the accuracy of brain age models, but there is still much untapped potential with regard to achieving widespread clinical utility.

Prenatal Selective Serotonin Reuptake Inhibitor Exposure, Depression, and Brain Morphology in Middle Childhood: Results From the ABCD Study.

Background: Prenatal selective serotonin reuptake inhibitor (SSRI) exposure has been inconsistently linked to depression, and little is known about neural correlates. We examined whether prenatal SSRI exposure is associated with depressive symptoms and brain structure during middle childhood. Methods: Prenatal SSRI exposure (retrospective caregiver report), depressive symptoms (caregiver-reported Child Behavior Checklist), and brain structure (magnetic resonance imaging-derived subcortical volume; cortical thickness and surface area) were assessed in children (analytic ns = 5420-7528; 235 with prenatal SSRI exposure; 9-10 years of age) who completed the baseline Adolescent Brain Cognitive Development Study session. Linear mixed-effects models nested data. Covariates included familial, pregnancy, and child variables. Matrix spectral decomposition adjusted for multiple testing. Results: Prenatal SSRI exposure was not independently associated with depression after accounting for recent maternal depressive symptoms. Prenatal SSRI exposure was associated with greater left superior parietal surface area (b = 145.3 mm2, p = .00038) and lateral occipital cortical thickness (b = 0.0272 mm, p = .0000079); neither was associated with child depressive symptoms. Child depression was associated with smaller global brain structure. Conclusions: Our findings, combined with adverse outcomes of exposure to maternal depression and the utility of SSRIs for treating depression, suggest that risk for depression during middle childhood should not discourage SSRI use during pregnancy. Associations between prenatal SSRI exposure and brain structure were small in magnitude and not associated with depression. It will be important for future work to examine associations between prenatal SSRI exposure and depression through young adulthood, when risk for depression increases.

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.