Faculty Bibliography

BACKGROUND/UNASSIGNED:Autism spectrum disorder (ASD) shows significant clinical variability, likely due to a combination of genetic and environmental factors. Preterm birth is a known risk factor for ASD, occurring in approximately 13% of diagnosed individuals. While genetic factors contribute to preterm birth in the general population, the relationship between genetic variation, preterm birth, and ASD heterogeneity remains unclear. METHODS/UNASSIGNED:We investigated the genetic factors associated with preterm birth in 31,947 autistic individuals using data from the SPARK (Simons Foundation Powering Autism Research for Knowledge) sample. We conducted 3 ancestry-specific genome-wide association studies for African/African American, admixed American, and non-Finnish European ancestries, followed by a meta-analysis of 3308 preterm cases and 28,639 controls using METAL. Functional mapping and gene-based analyses were performed using FUMA, and genetic correlations were estimated using LDSC and Popcorn. Polygenic risk scores (PRSs) were computed with BridgePRS, using PRS of preterm birth in the general population. RESULTS/UNASSIGNED:Our study identified ancestry-specific genetic loci associated with preterm birth in ASD cases. Although the meta-analysis results were not statistically significant, the estimated single nucleotide polymorphism heritability was 14%, indicating a meaningful contribution of common genetic variants. Across ancestry groups, preterm birth status was not significantly associated with PRSs for any psychiatric or medical conditions analyzed. However, polygenic liability to preterm birth in the general population was linked to several congenital anomalies after multiple testing adjustments. CONCLUSIONS/UNASSIGNED:These findings highlight the importance of diverse ancestries and early-life exposures in understanding ASD heterogeneity. Future research should replicate these findings in larger samples and explore rare variants associated with preterm birth to better understand the relationship between gestational duration and clinical and genetic differences in ASD.

OBJECTIVE:Autism spectrum disorder (ASD) is a neurodevelopmental condition with early-life origins. Maternal health conditions during pregnancy have been linked to autism risk, but most studies focus on single populations, limiting generalizability. We examined whether associations previously reported in a Danish registry-based study hold in a U.S. METHOD/METHODS:We analyzed electronic health records of children born between 2010 and 2017 at Kaiser Permanente Northern California (KPNC) and their mothers. Maternal diagnoses were classified as chronic or non-chronic, and associations with ASD in the child were assessed using Cox models, adjusting for sociodemographic factors, healthcare utilization, and comorbid maternal diagnoses. Methods were aligned with the Danish study for comparability. RESULTS:Among 224,353 children in the KPNC cohort, 5,448 (2.4%) were diagnosed with autism. Of the 42 maternal diagnoses significantly associated with autism in Denmark, 38 were evaluable in KPNC, and 18 remained statistically significant after adjustment. Most associations had point estimates consistent with the Danish study, particularly psychiatric and cardiometabolic conditions. CONCLUSION/CONCLUSIONS:Despite demographic and healthcare differences, 35 of the 38 associations found in the Danish study replicated qualitatively (direction of effect) in the U.S. cohort, suggesting robust cross-setting relevance. Further research is needed to explore underlying mechanisms and effect modifiers.

Evidence suggests that maternal health in pregnancy is associated with autism in the offspring. However, most diagnoses in pregnant women have not been examined, and the role of familial confounding remains unknown. Our cohort included all children born in Denmark between 1998 and 2015 (n = 1,131,899) and their parents. We fitted Cox proportional hazard regression models to estimate the likelihood of autism associated with each maternal prenatal ICD-10 diagnosis, accounting for disease chronicity and comorbidity, familial correlations and sociodemographic factors. We examined the evidence for familial confounding using discordant sibling and paternal negative control designs. Among the 1,131,899 individuals in our sample, 18,374 (1.6%) were diagnosed with autism by the end of follow-up. Across 236 maternal diagnoses we tested (prevalence ≥0.1%), 30 were significantly associated with autism after accounting for sociodemographic factors, disorder chronicity and comorbidity, and correction for multiple testing. This included obstetric, cardiometabolic and psychiatric disorders (for example, diabetes in pregnancy (hazard ratio (HR) 1.19, 95% confidence interval (CI) 1.08-1.31) and depression (HR 1.49, 95% CI 1.27-1.75)), previously shown to be associated with autism. Family-based analyses provided strong evidence for familial confounding in most of the observed associations. Our findings indicate pervasive associations between maternal health in pregnancy and offspring autism and underscore that these associations are largely attributable to familial confounding.

INTRODUCTION/UNASSIGNED:Comorbidity between disorders is pervasive, and its relationship to the main conditions under investigation needs to be addressed for robust causal inference. However, many clinical etiologic studies still fail to capitalize on the theoretical advancements and improved recommendations regarding covariate adjustment in this context. Specifically, studies often lack explicit causal assumptions about the role of comorbidity in exposure-outcome relationships, potentially leading to inappropriate accounting for comorbid conditions and resulting in biased effect estimates. This study aims to explore common causal structures involving comorbidity and provide guidance for handling it in etiologic research. METHODS/UNASSIGNED:We use Directed Acyclic Graphs (DAGs) to depict six causal scenarios involving comorbidity as a confounder, mediator, collider, or consequence of the exposure or outcome, illustrated with real-world clinical examples. Simulations were conducted across 5,000 iterations for each scenario, assessing the impact of conditioning on comorbidity under four effect measures (risk difference, odds ratio, risk ratio, and mean difference). Bias was evaluated by comparing adjusted and unadjusted effect estimates to the true values. RESULTS/UNASSIGNED:The impact of conditioning on comorbidity varied by its causal role. Adjusting for comorbidity mitigated bias when it acted as a confounder but introduced bias when it was a mediator or collider. In instances where comorbidity was a consequence of either the exposure or outcome, the decision to adjust depended on the research objectives and could vary across effect measures. DISCUSSION/UNASSIGNED:Explicit causal assumptions are essential for selecting appropriate analytical strategies in etiologic research. This study provides practical guidance on analytical handling of the measures of comorbidity, highlighting the need for study design and analysis to align with research objectives. Future work should address more complex causal structures and other methodological challenges.

IMPORTANCE/OBJECTIVE:Existing research suggests the impact of infertility on the risk of neurodevelopmental disorders in children, however, studies to date have failed to separate the impact of male and female infertility, often blurring the lines with proxies that encompass all forms of infertility. Moreover, while both health conditions co-occurring with infertility and genetic factors operating upstream have been suggested to influence the association between infertility and child outcomes, their roles and potential impact on observed associations remain unclear. OBJECTIVE:The objectives of this study are to investigate the relationship between female infertility and autism in the child, differentiating it from the effects of male and the couple infertility; consider the role of various maternal and birth factors in the association; and examine the effects of shared familial confounders on the association. DESIGN SETTING AND PARTICIPANTS/METHODS:Danish population-based cohort study, including all singleton live births in Denmark 1998-2015, their parents and parents' siblings. The cohort was followed up until December 31, 2016. EXPOSURES/METHODS:The exposure was a history of female infertility in the mother and the mother's sister. We examined four definitions of female infertility based on the ICD-10 codes derived from the Danish National Patient Register - any female infertility; specified female infertility; female exclusive infertility; and female or male infertility. MAIN OUTCOME AND MEASURES/METHODS:The outcome was diagnosis of autism spectrum disorder (ASD) in the Danish Psychiatric Central Research Register or the national patient register. A multivariable Cox regression model was used to estimate the associations between female infertility and autism, accounting for child's sex, year of birth, maternal age, education level, chronic comorbidities, and pregnancy and birth complications. The effects of shared familial factors on the association were analyzed using exposure information from the child's maternal aunt. RESULTS:=1.10 (95% CI, 1.00-1.20). CONCLUSIONS AND RELEVANCE/CONCLUSIONS:in This population-based birth cohort study, we found a slightly higher risk of autism in children born to mothers with a history of infertility, with the association remaining consistent across various definitions of female infertility and robust to adjustments for demographic, child, and maternal factors. The study suggests for the first time that shared familial factors, possibly both genetic and non-genetic, could be influencing both female infertility and the risk of autism in children, indicating a need for further investigation into these familial effects.

Racial disparities in prescriptions of anti-psychotics have been highlighted before. However, (i) the evidence on other medications, including anti-depressant or mood stabilizing medications is lacking, and (ii) the role of potentially confounding factors and (iii) specificity of such disparities to schizophrenia (SCZ), are still unknown. We used electronic health records (EHRs) from 224,212 adults to estimate the odds ratios of receiving a prescription for different nervous system medications among patients with SCZ of different race/ethnicity, and analogous linear models to investigate differences in prescribed medication doses. To verify specificity of the observed patterns to SCZ, we conducted analogous analyses in depression and bipolar disorder (BD) patients. We found that Black/African American (AA) and Hispanic patients with SCZ were more likely to be prescribed haloperidol (Black/AA: OR = 1.52 (1.33-1.74); Hispanic: OR = 1.32 (1.12-1.55)) or risperidone (Black/AA: OR = 1.27 (1.11-1.45); Hispanic: OR = 1.40 (1.19-1.64)), but less likely to be prescribed clozapine (Black/AA: OR = 0.40 (0.33-0.49); Hispanic: OR = 0.45 (0.35-0.58)), compared to white patients. There were no race/ethnicity-related differences in the prescribed medication doses. These patterns were not specific to SCZ: Asian, Hispanic and Black/AA patients with BD or depression were more likely to be prescribed anti-psychotics, but less likely to be prescribed antidepressants or mood-stabilizers. In conclusion, we found racial/ethnic disparities in the medications prescribed to patients with SCZ and other psychiatric conditions. We discuss the potential implications for the quality of care for patients of diverse races/ethnicities.

BACKGROUND:Mental and physical health conditions are frequently comorbid. Despite the widespread physiological and behavioral changes during pregnancy, the pattern of comorbidities among women in pregnancy is not well studied. This study aimed to systematically examine the associations between mental and somatic disorders before and during pregnancy. METHOD:The study used data from mothers of a nationally representative birth cohort of children born in Israel (1997-2008). We compared the risk of all major somatic disorders (International Classification of Diseases, Ninth Revision) in pregnant women with and without a mental disorder. All analyses were adjusted for maternal age, child's birth year, family socioeconomic status, and the total number of maternal encounters with health services around pregnancy period. RESULTS:The analytical sample included 77,030 mother-child dyads, with 30,083 unique mothers. The mean age at child's birth was 29.8 years. Prevalence of diagnosis of mental disorder around pregnancy in our sample was 4.4%. Comorbidity between mental and somatic disorders was two times higher than the comorbidity between pairs of different somatic disorders. Of the 17 somatic disorder categories, seven were positively associated with mental health disorders. The highly prevalent comorbidities associated with mental disorders in pregnancy included e.g. musculoskeletal (OR = 1.30; 95% CI = 1.20-1.42) and digestive system diseases (OR = 1.23; 95% CI = 1.13-1.34). CONCLUSIONS:We observed that associations between maternal diagnoses and mental health stand out from the general pattern of comorbidity between nonmental health diseases. The study results confirm the need for screening for mental disorders during pregnancy and for potential comorbid conditions associated with mental disorders.

A large number of studies have examined the association between advanced paternal age (APA) and risk of schizophrenia in offspring. Here we present an overview of epidemiological studies on this subject published since 2000, and systematically summarize their methodologies and results. Next, we discuss evidence to elucidate the potential mechanisms contributing to the association between APA and offspring schizophrenia, considering paternal psychiatric morbidity and genetic liability, maternal factors, and findings from family design studies. We propose that multiple mechanisms, including causal and non-causal pathways, contribute to the observed relationship between APA and schizophrenia in offspring, and conclude by highlighting the need for multi-disciplinary studies in disentangling these complex, non-mutually exclusive mechanisms.