The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Educational attainment (EduA) is correlated with life outcomes, and EduA itself is influenced by both cognitive and non-cognitive factors. A recent study performed a ‘genome-wide association study (GWAS) by subtraction,’ subtracting genetic effects for cognitive performance from an educational attainment GWAS to create orthogonal ‘cognitive’ and ‘non-cognitive’ factors. These cognitive and non-cognitive factors showed associations with behavioral health outcomes in adults; however, whether these correlations are present during childhood is unclear.

Using data from up to 5517 youth (ages 9–11) 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 cognition, risk tolerance, decision-making & personality, substance initiation, psychopathology, and brain structure (e.g. volume, fractional anisotropy [FA]). Within-sibling analyses estimated whether observed genetic associations may be consistent with direct genetic effects.

Both PGSs were associated with greater cognition and lower impulsivity, drive, and severity of psychotic-like experiences. The cognitive PGS was also associated with greater risk tolerance, increased odds of choosing delayed reward, and decreased likelihood of ADHD and bipolar disorder; the non-cognitive PGS was associated with lack of perseverance and reward responsiveness. Cognitive PGS were more strongly associated with larger regional cortical volumes; non-cognitive PGS were more strongly associated with higher FA. All associations were characterized by small effects.

While the small sizes of these associations suggest that they are not effective for prediction within individuals, cognitive and non-cognitive PGS show unique associations with phenotypes in childhood at the population level.

Bipolar I disorder (BD-I) is a chronic and recurrent mood disorder characterized by alternating episodes of depression and mania; it is also associated with substantial morbidity and mortality and with clinically significant functional impairments. While previous studies have used functional magnetic resonance imaging (fMRI) to examine neural abnormalities associated with BD-I, they have yielded mixed findings, perhaps due to differences in sampling and experimental design, including highly variable mood states at the time of scan.

The purpose of this study is to advance our understanding of the neural basis of BD-I and mania, as measured by fMRI activation studies, and to inform the development of more effective brain-based diagnostic systems and clinical treatments.

We conducted a large-scale meta-analysis of whole-brain fMRI activation studies that compared participants with BD-I, assessed during a manic episode, to age-matched healthy controls. Following PRISMA guidelines, we conducted a comprehensive PubMed literature search using two independent coding teams to evaluate primary studies according to pre-established inclusion criteria. We then used multilevel kernel density analysis (MKDA), a well-established, voxel-wise, whole-brain, meta-analytic approach, to quantitatively synthesize all qualifying primary fMRI activation studies of mania. We used ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias, and 10,000 Monte Carlo simulations to correct for multiple comparisons.

We found that participants with BD-I (N=2,042), during an active episode of mania and relative to age-matched healthy controls (N=1,764), exhibit a pattern of significantly (p<0.05-0.0001; FWE-corrected) different activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.

This study supports the formulation of a robust neural basis for BD-I during manic episodes and advances our understanding of the pattern of abnormal activation in this disorder. These results may inform the development of novel brain-based clinical tools for bipolar disorder such as diagnostic biomarkers, non-invasive brain stimulation, and treatment-matching protocols. Future studies should compare the neural signatures of BD-I to other related disorders to facilitate the development of protocols for differential diagnosis and improve treatment outcomes in patients with BD-I.

None Declared

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent psychiatric condition that frequently originates in early development and is associated with a variety of functional impairments. Despite a large functional neuroimaging literature on ADHD, our understanding of the neural basis of this disorder remains limited, and existing primary studies on the topic include somewhat divergent results.

The present meta-analysis aims to advance our understanding of the neural basis of ADHD by identifying the most statistically robust patterns of abnormal neural activation throughout the whole-brain in individuals diagnosed with ADHD compared to age-matched healthy controls.

We conducted a meta-analysis of task-based functional magnetic resonance imaging (fMRI) activation studies of ADHD. This included, according to PRISMA guidelines, a comprehensive PubMed search and predetermined inclusion criteria as well as two independent coding teams who evaluated studies and included all task-based, whole-brain, fMRI activation studies that compared participants diagnosed with ADHD to age-matched healthy controls. We then performed multilevel kernel density analysis (MKDA) a well-established, whole-brain, voxelwise approach that quantitatively combines existing primary fMRI studies, with ensemble thresholding (p<0.05-0.0001) and multiple comparisons correction.

Participants diagnosed with ADHD (N=1,550), relative to age-matched healthy controls (N=1,340), exhibited statistically significant (p<0.05-0.0001; FWE-corrected) patterns of abnormal activation in multiple brains of the cerebral cortex and basal ganglia across a variety of cognitive control tasks.

This study advances our understanding of the neural basis of ADHD and may aid in the development of new brain-based clinical interventions as well as diagnostic tools and treatment matching protocols for patients with ADHD. Future studies should also investigate the similarities and differences in neural signatures between ADHD and other highly comorbid psychiatric disorders.

None Declared

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.

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.

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).

Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

Attention concerns, particularly difficulties with focusing and regulating attention, are reported in diverse clinical contexts. The Ruff 2&7 Selective Attention Test (Ruff 2&7; Ruff & Allen, 1996) is a measure of sustained and selective attention that assesses automatic detection and effortful processing. The goal of this study was to create an internal consistency metric within this test and to determine cognitive predictors by evaluating associations with executive control of attention and other cognitive skills. It was hypothesized that those who are more consistent across Ruff 2&7 performance would have more robust executive functioning skills, particularly those related to regulating and directing attention and the planning and utilization of cognitive resources.

The current study examined a clinical sample of 98 United States veterans with a history of mild traumatic brain injury. After excluding invalid cases (n=24), the final sample consisted of 74 veterans (Age=38.5 (8.9) years old; 13.9 (2.2) years of education; 78% male; 82% white, 7% Black, 8% Hispanic, 2% Asian). A consistency score was defined as the absolute value of the intertrial change in target hits plus errors across each pair of trials of the same stimulus type (Automatic Detection, AD, and Controlled Search, CS). Hierarchical linear regression modeling was used to evaluate the relative contributions of memory and executive functions (Rey Auditory Verbal Learning Test, Delis-Kaplan Executive Function System Tower Test, phonemic fluency, Trail Making Test B) and subjective symptom report (PTSD Checklist for DSM-5, Barkley Adult ADHD Rating Scale for DSM-IV).

The mean deviation scores for the two trial types were similar (AD mean=13.6, SD=5.9; CS mean=13.6, SD=5.3). In predicting consistency across AD trials, delayed recall contributed 11% unique variance (p=.013), while no other block was statistically significant. For CS trials, self-reported PTSD and inattention symptoms contributed a combined 20% of unique variance to the model (p=.007), while there were no statistically significant cognitive predictors in this model.

Contrary to expectation, executive function measures did not explain statistically significant variance in performance across either trial type. Less consistent performance on AD trials was associated with weaker verbal memory. Less consistent performance on CS trials, which theoretically require greater executive control, was not associated with any cognitive scores, but was associated with more severe self-reported psychological and inattention symptoms. These findings buttress the conceptual distinction between AD and CS trial types, and they point to both cognitive and non-cognitive underpinnings of performance consistency.

As neuropsychologists aim to collect valid data, maximize the utility of assessments, make effective use of time, and best serve patient populations, measurement of performance validity is considered a critical issue for the field. As effort may vary across an evaluation, including performance validity tests (PVTs) throughout the assessment is important. Incorporating embedded PVTs in addition to free standing PVTs can be particularly useful in this regard. COWAT and animal naming are commonly administered verbal fluency measures. While there have been past investigations into their potential for detecting invalid performance, they are limited, and more research is needed. Perhaps most promising, Sugarman and Axelrod (2015) described a logistic regression derived formula utilizing the combined raw scores of COWAT and animal naming. The current study aimed to investigate the use of embedded PVTs within COWAT and animal naming to provide further support for the use of embedded PVTs in these measures.

All subjects were from a mixed clinical sample comprising military veterans from two VA Medical Centers in the northeast U.S., who were referred for neuropsychological evaluation. Subjects deemed credible had zero PVT failures. Subjects were considered non-credible performers if they failed at least two out of a possible eight PVTs administered. Subjects who failed one PVT were excluded from the study (n = 53). The final sample consisted of 116 individuals with credible performance (Mean Age = 35.5, SD = 8.8; Mean Edu = 13.6, SD = 2; Mean Est. IQ = 106, SD = 7.9) and 94 individuals with psychometrically determined non-credible performance (Mean Age = 38.5, SD = 9.4; Mean Edu = 113, SD = 2.1; Mean Est. IQ = 101, SD = 8.7). Performance of COWAT and animals in detecting non-credible performances was evaluated through calculation of classification accuracy statistics and use of the logistic regression formulas reported in Sugarman and Axelrod (2015).

For COWAT, the optimal cutoff was a raw score of <27 (specificity = 89%; sensitivity = 31%), and a T-score of <35 (specificity = 92%; sensitivity = 31%). For animal naming, optimal cutoffs were <16 for raw score (specificity = 92%, sensitivity = 38%) and <37 for T-score (specificity = 91%; sensitivity = 33%). The logistic regression formula based on raw scores for both COWAT and animal naming was inadequately sensitive at the recommended cutoff in this sample, but a coefficient of > .28 was revealed to be optimal (91% specificity; 42% sensitivity). When the formula for T-scores was used, a coefficient of > .38 was optimal (91% specificity; 28% sensitivity).

Results of the current research suggest that PVTs embedded within the commonly administered COWAT and animal naming verbal fluency tests can effectively detect low effort, in concordance with generally accepted standards. A logistic regression formula using raw scores in particular appears to be most effective, consistent with findings reported by Sugarman and Axelrod (2015).

While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis.

We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case–control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.

We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case–control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case–control status.

Controls (86.1%) and FEPp (75.63%) were most likely to report ‘because of friends’ as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: ‘to feel better’ as their RFUC (χ2 = 50.97; p < 0.001). RFUC ‘to feel better’ was associated with being a FEPp (OR 1.74; 95% CI 1.03–2.95) while RFUC ‘with friends’ was associated with being a control (OR 0.56; 95% CI 0.37–0.83). The path model indicated an association between RFUC ‘to feel better’ with heavy cannabis use and with FEPp-control status.

Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use ‘to feel better’. People who reported their reason for first using cannabis to ‘feel better’ were more likely to progress to heavy use and develop a psychotic disorder than those reporting ‘because of friends’.