Faculty Bibliography

Tobacco smoking is highly prevalent among patients with serious mental illness (SMI), with known deleterious consequences. Smoking cessation is therefore a prioritary public health challenge in SMI. In recent years, several smoking cessation digital interventions have been developed for non-clinical populations. However, their impact in patients with SMI remains uncertain. We conducted a systematic review to describe and evaluate effectiveness, acceptability, adherence, usability and safety of digital interventions for smoking cessation in patients with SMI. PubMed/MEDLINE, EMBASE, CINAHL, Web of Science, PsychINFO and the Cochrane Tobacco Addiction Group Specialized Register were searched. Studies matching inclusion criteria were included and their information systematically extracted by independent investigators. Thirteen articles were included, which reported data on nine different digital interventions. Intervention theoretical approaches ranged from mobile contingency management to mindfulness. Outcome measures varied widely between studies. The highest abstinence rates were found for mSMART MIND (7-day point-prevalent abstinence: 16-40%). Let's Talk About Quitting Smoking reported greater acceptability ratings, although this was not evaluated with standardized measures. Regarding usability, Learn to Quit showed the highest System Usability Scale scores [mean (s.d.) 85.2 (15.5)]. Adverse events were rare and not systematically reported. Overall, the quality of the studies was fair to good. Digitally delivered health interventions for smoking cessation show promise for improving outcomes for patients with SMI, but lack of availability remains a concern. Larger trials with harmonized assessment measures are needed to generate more definitive evidence and specific recommendations.

Knowledge on psychiatric comorbidity in adult ADHD is essential for prevention, detection, and treatment of these conditions. This review (1) focuses on large studies (n> 10,000; surveys, claims data, population registries) to identify (a) overall, (b) sex- and (c) age-specific patterns of comorbidity of anxiety disorders (ADs), major depressive disorder (MDD), bipolar disorder (BD) and substance use disorders (SUDs) in adults with ADHD relative to adults without ADHD; and (2) describes methodological challenges relating to establishing comorbidity in ADHD in adults as well as priorities for future research. Meta-analyses (ADHD: n=550,748; no ADHD n=14,546,814) yielded pooled odds ratios of 5.0(CI:3.29-7.46) for AD, 4.5(CI:2.44-8.34) for MDD, 8.7(CI:5.47-13.89) for BD and 4.6(CI:2.72-7.80) for SUDs, indicating strong differences in adults with compared to adults without ADHD. Moderation by sex was not found: high comorbidity held for both men and women with sex-specific patterns as in the general population: higher prevalences of ADs, MDD and BD in women and a higher prevalence of SUDs in men. Insufficient data on different phases of the adult lifespan prevented conclusions on developmental changes in comorbidity. We discuss methodological challenges, knowledge gaps, and future research priorities.

IMPORTANCE:Gender-diverse youths have higher rates of mental health problems compared with the general population, as shown in both clinical and nonclinical populations. Brain correlates of gender diversity, however, have been reported only among youths with gender dysphoria or in transgender individuals. OBJECTIVE:To examine brain morphologic correlates of gender diversity among adolescents from a general pediatric population who were assigned male or female at birth, separately. DESIGN, SETTING, AND PARTICIPANTS:This cross-sectional study was embedded in Generation R, a multiethnic population-based study conducted in Rotterdam, the Netherlands. Adolescents who were born between April 1, 2002, and January 31, 2006, and had information on self-reported or parent-reported gender diversity and structural neuroimaging at ages 13 to 15 years were included. Data analysis was performed from April 1 to July 31, 2022. EXPOSURES:Gender-diverse experiences among adolescents were measured with selected items from the Achenbach System of Empirically Based Assessment forms and the Gender Identity/Gender Dysphoria Questionnaire for Adolescents and Adults, as reported by adolescents and/or their parents. MAIN OUTCOMES AND MEASURES:High-resolution structural neuroimaging data were collected using a 3-T magnetic resonance imaging scanner (at a single site). We used linear regression models to examine differences in global brain volumetric measures between adolescents who reported gender diversity and those who did not. RESULTS:This study included 2165 participants, with a mean (SD) age of 13.8 (0.6) years at scanning. A total of 1159 participants (53.5%) were assigned female at birth and 1006 (46.5%) were assigned male at birth. With regard to maternal country of origin, 1217 mothers (57.6%) were from the Netherlands and 896 (42.4%) were from outside the Netherlands. Adolescents who reported gender diversity did not differ in global brain volumetric measures from adolescents who did not report gender diversity. In whole-brain, vertexwise analyses among adolescents assigned male at birth, thicker cortices in the left inferior temporal gyrus were observed among youths who reported gender diversity compared with those who did not. No associations were observed between gender diversity and surface area in vertexwise analyses. CONCLUSIONS AND RELEVANCE:The findings of this cross-sectional study suggest that global brain volumetric measures did not differ between adolescents who reported gender diversity and those who did not. However, these findings further suggest that gender diversity in the general population correlates with specific brain morphologic features in the inferior temporal gyrus among youths who are assigned male at birth. Replication of these findings is necessary to elucidate the potential neurobiological basis of gender diversity in the general population. Future longitudinal studies should also investigate the directionality of these associations.

IMPORTANCE:Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. OBJECTIVE:To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations. DESIGN, SETTING, AND PARTICIPANTS:This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022. MAIN OUTCOMES AND MEASURES:The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations. RESULTS:Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6). CONCLUSIONS AND RELEVANCE:This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

BACKGROUND:Although the ICD and DSM differentiate between different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case-control, sibling study examining familial clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014. METHODS:= 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk (RRR) of the sibling of a case having the same (within-disorder RRR) or a different (across-disorder RRR) disorder. RESULTS:Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53 [95% confidence interval (CI): 9.23-14.40] for ASD to 2.93 (95% CI: 2.80-3.07) for personality disorders. The median across-disorder RRR between any pair of psychiatric disorders was 2.16 (95% CI: 1.45-2.43); the median RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93-1.98). There was no consistent increase in across-disorder RRRs between the non-CNS disorders and psychiatric disorders and/or low IQ. CONCLUSION/CONCLUSIONS:These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.

Autism spectrum disorder (ASD), a heritable neurodevelopmental disorder, confers genetic liability that is often expressed among relatives through subclinical, genetically-meaningful traits, or endophenotypes. For instance, relative to controls, parents of individuals with ASD differ in language-related skills, with differences emerging in childhood. To examine ASD-related endophenotypes, this study investigated developmental academic profiles among clinically unaffected siblings of individuals with ASD (n = 29). Lower performance in language-related skills among siblings mirrored previously-reported patterns among parents, which were also associated with greater subclinical ASD-related traits in themselves and their parents, and with greater symptom severity in their sibling with ASD. Findings demonstrated specific phenotypes, derived from standardized academic testing, that may represent childhood indicators of genetic liability to ASD in first-degree relatives.

Suicidal thoughts and behaviors (STB) and emergency department (ED) utilization are prevalent in autistic youth. The current study surveyed clinicians in a pediatric psychiatric ED to examine differences in attitudes on suicide-related care for autistic and non-autistic patient populations. While clinicians rated addressing STB in ASD as important and adaptations to care as necessary, less than half identified ASD as a suicide risk factor and confidence ratings were significantly lower for autistic patients. Previous ASD training predicted confidence and accounted for approximately 25% of the variance in confidence scores. Findings highlight the urgency to develop and disseminate ED clinician training, and address the lack of validated assessment tools, adapted suicide prevention practices, and evidence-based treatments for STB in autistic youth.

BACKGROUND:Understanding the developmental trajectories of children with autism spectrum disorder (ASD) with and without comorbid ADHD is relevant to tailor care plans. This prospective study assessed, for the first time, cognitive, emotional, behavioral, and learning outcomes in adolescence of children with ASD-ADHD and in those with ASD+ADHD in childhood. Possible predictors of severity of ASD core symptoms in adolescence were also evaluated. METHODS:Forty-five adolescents without intellectual disability, 26 diagnosed in childhood with ASD-ADHD and 19 with ASD+ADHD, were evaluated at baseline (mean age: 8.6 ± 1.3) and at 5-year follow-up (mean age: 12.9 ± 0.9). Parents and teachers completed questionnaires on executive functions, theory of mind (ToM), emotional/behavioral difficulties (EBD), and learning style at both time points.. RESULTS:Overall different developmental trajectories for the two groups were found. In general, deficits in metacognition processes, ToM skills, EBD, and learning abilities were more pronounced in the ASD+ group. Over time, the ASD+ADHD group, but not the ASD-ADHD, tended to improve in EBD and metacognition but their level of development continued to be lower compared with ASD+ADHD. EBD in childhood were significant predictors of autism core symptoms of adolescents. CONCLUSIONS:Our findings highlight the importance of an early identification of comorbid ADHD symptoms in ASD to offer treatment strategies based on specific developmental trajectories.

We conducted an observational study of a collection of interactive processes known as "demand-withdraw" in relation to adolescent dating aggression. Couples (N = 209) aged 14-18 years participated in a challenging observational laboratory assessment to measure demands (i.e., pressures for a change), as well as demand → partner withdraw and demand → partner avoid sequences. Actor and partner effects were disentangled via dyadic data analyses. The results indicated a fairly consistent pattern in which demand → withdraw and demand → avoid sequences led by either partner were positively associated with both partners' physical and psychological aggression (measured via a dual informant questionnaire method). Further, higher quality demands (i.e., pressures for change that were specific and encouraged both members of the dyad to increase a given behavior) were inversely associated with aggression. Yet, all of the above associations were attenuated to the point of statistical nonsignificance after controlling for hostility. These results suggest two primary possibilities. The associations of demand → withdraw and demand → avoid sequences with dating aggression may be spurious, with the sequences merely markers for hostility, a known correlate of dating aggression. Alternatively, hostility may mediate the relations of demand → withdraw and demand → avoid sequences with dating aggression. Further research is required to test these competing explanations. Implications for preventive intervention are discussed.