Faculty Bibliography

INTRODUCTION/UNASSIGNED:Autism spectrum disorder (ASD) is characterized in part by differences in pragmatic (i.e., social) language use. However, few studies on pragmatic language have included a meaningful number of autistic females, and even fewer have evaluated pragmatic language profiles for sex-specific differences. The existing literature on pragmatic language in autistic individuals without intellectual disability suggests that females may have stronger social communication skills compared to males, but findings are mixed, and there is not a clear profile of specific pragmatic skills that are liable to sex differences. It is also important to develop novel methodologies, such as computational methods, to characterize pragmatic language in ways less labor-intensive than gold-standard hand-coding methods, which are extremely time consuming and typically not feasible in clinical settings. METHODS/UNASSIGNED:The present study examined hand coding of pragmatic language data samples alongside multiple computational linguistic methodological approaches to characterize sex differences in pragmatic language in autistic males and females across narrative and semi-structured conversational tasks that might reveal context-specific patterns across sex and diagnostic groups. RESULTS/UNASSIGNED:Results indicated that most pragmatic domains differed between autistic and non-autistic groups, with autistic males showing the most obvious pragmatic differences, and that differences between diagnostic groups were more pronounced in the semi-structured conversational context. The alignment between computational and hand-coded findings was strongest in domains with clear theoretical overlap (e.g., frequency of emotional words) but was less consistent in areas that were less theoretically aligned (e.g., conversational dynamics and single word function). DISCUSSION/UNASSIGNED:These findings support the promise of computational methods for characterizing narrative abilities, though further study including validation against hand-coded approaches is warranted.

BACKGROUND:Autism spectrum disorder (ASD) has a complex inheritance pattern and is more common in males. Etiological models suggest that majority of ASD risk is transmitted through common and rare de-novo genetic variation. It has been hypothesized that rare variation could be inherited and therefore contribute to the overall risk-burden in subsequent generations, especially through female lineage in disorders with male-skewed sex-ratios. Here we test this hypothesis using multigeneration information on paternal age, because burden of de-novo mutations has been linked to paternal age, and there is a well-established association between older age of fathers and ASD. METHODS:We analyzed combined data from Sweden's, Denmark's and Finland's national registers totaling 12.6 million family-members, including information about parental ages at the time of birth of offspring in two generations, and ASD diagnosis in the third generation. RESULTS:Among the 1,808,892 children in the third generation, 23,397 (1.29%) were diagnosed with ASD. Increased paternal age at the time of birth of a daughter was associated with increased risk of ASD in the daughter's own offspring. Increased paternal age at the time of birth of a son was not associated with increased ASD risk in the son's offspring, nor was older maternal age in the first or second generations. We observed that young maternal age at birth of a son or a daughter was associated with ASD risk in their offspring. CONCLUSIONS:Collectively, our results suggest that etiologic risk-factors for ASD could extend over multiple generations through different underlying mechanisms, suggesting new directions for research on genetic and non-genetic risk-factors.

INTRODUCTION/UNASSIGNED:This article features the application of Causal Data Science (CDS) methods to determine the mechanism for Posttraumatic Stress (PTS) in young, maltreated children, in order to advance knowledge for prevention. Advances in prevention require research that identifies causal factors, but the scientific literature that would inform the identification of causes are almost exclusively based on the application of correlational methods to observational data. Causal inferences from such research will frequently be in error. We conducted the present study to explore the application of CDS methods as an alternative-or a supplement-to experimental methods, which can rarely be applied in human research on causal factors for PTS. METHODS/UNASSIGNED:A data processing pipeline that integrates state-of-the-art CDS algorithms was applied to an existing observational, longitudinal data set collected by the Consortium for Longitudinal Studies in Child Abuse and Neglect (LONGSCAN). This data set contains a sample of 1,354 children who were identified in infancy to early childhood as being maltreated or at risk. RESULTS/UNASSIGNED:A causal network model of 251 variables (nodes) and 818 bivariate relations (edges) was discovered, revealing four direct causes (Emotional Maltreatment at age 0-4, Physical Assault at age 8, Feeling of Safety at age 8, and Witnessing Violence at age 8) and two direct effects (Negative Self-Image and Severe Assault from a Non-Caregiver at age 8) of PTS at age 8, within a network containing a broad diversity of causal pathways. DISCUSSION/UNASSIGNED:These results indicate that CDS methods show promise for research on the complex etiology of PTS in young, maltreated children.

The collection of electroencephalography (EEG) data in neonates typically occurs during sleep. EEG activity is highly sleep-state dependent, therefore differentiating between states during data processing can provide important insights into neurodevelopment. Despite this, there have been a paucity of studies directly comparing how infant EEG data, especially event-related potentials, differ between these sleep states. Here, we adapted the Maryland Analysis of Developmental EEG pipeline (MADE) to integrate sleep-state coding into its automated preprocessing pipeline. We recorded EEG in 102 sleeping one month old infants and evaluated their responses during a resting state and during a three-stimuli auditory oddball paradigm. Examination of resting-state power revealed significant differences between two sleep states, namely active (AS) and quiet (QS) sleep across all frequency bands in both absolute and relative power. For the auditory oddball paradigm, we computed responses to both standard and deviant tones and then created a difference score reflecting the Mismatch Response (MMR). For the novel tones we examined the evoked response (P300). Results revealed for the MMR, a significant electrode cluster by sleep-state interaction (F = 5.36, p = .01), indicating that the MMR was present at all three electrode clusters during AS (p-values <.05), but only at the frontal cluster during QS (t = 2.05, p = .04). There were no differences in the amplitude of the P300 to the novel sound as a function of sleep state.

INTRODUCTION/UNASSIGNED:Poor dental health is linked to poor physical and mental health. This study was aimed to examine the characteristics of U.S. adults that are associated with having seen a dentist in the past year. METHODS/UNASSIGNED:A cross-section of adults aged 18-64 years (N=19,975) from the 2023 National Health Interview Survey was examined. Bivariate analyses examined the associations of sociodemographic and financial variables with recent dental visits in the last 12 months. Multinomial modeling was used to assess these variables to predict 3 outcomes of time since the last dental visit: in the last 12 months; over a year but <10 years; and over 10 years or never, which was the reference category. RESULTS/UNASSIGNED:In young and middle-aged adults, 4.8% of Americans, representing over 9 million people, had either never seen a dentist or not seen a dentist in 10 years or more. The likelihood of a dental visit in the last 12 months increased with education level (no high-school degree versus a graduate or professional degree [AOR=0.21, 95% CI=0.09, 0.50]) and income (income below the federal poverty line versus income in the highest quartile [AOR=0.20, 95% CI=0.11, 0.35]). Having dental coverage in a private plan or Medicaid, compared with having no coverage, predicted having a dental visit within the last 12 months in both multinomial and bivariate analyses. CONCLUSIONS/UNASSIGNED:Access to dental care in young and middle-aged adults is determined by financial ability. Increasing access to dental care could happen once the financial barriers to dental care are reduced, including increasing the age at which a young adult can be covered by a parent's plan and making dental coverage comparable with physical health coverage. Given the current data about the links between dental, mental, and physical health, parity for all care is warranted.

Youth are presenting to Emergency Departments (EDs) following a suicide-related crisis at higher rates and younger ages. Clinicians lack tools to effectively discern suicide risk in younger patients. The present investigation examines how ED-based, suicidal pre-adolescents and adolescents conceptualize death. One hundred and sixty-seven suicidal pre-adolescents and adolescents (10-17 years; M = 12, SD = 1.4) presenting to a psychiatric ED with a suicide-related chief complaint completed assessments of suicidal ideation (SI; passive and active thoughts), suicide attempt (SA), depressive symptoms, and death conceptualizations (Death Avoidance, Escape Acceptance, Neutral Acceptance). Post-discharge SI and SA were assessed via survey emailed to participants 6 months later and via electronic medical record. At baseline, lower levels of Death Avoidance and higher levels of Escape Acceptance were most robustly associated with active SI. Pre-adolescents reported higher levels of Death Avoidance and lower levels of Escape Acceptance than adolescents at baseline. Death conceptualizations did not predict follow-up SI and SA. Youth who have recently experienced a suicide-related crisis are more likely to accept death as an escape from painand spend less time avoiding thoughts about death. This profile appears to be more representative of adolescents, relativeto pre-adolescents who display the opposite pattern.

BACKGROUND/UNASSIGNED:Pregnancy requires finely tuned immune changes that support implantation, placental development, maternal-fetal tolerance, and preparation for labor, yet the normative trajectories of circulating inflammatory proteins across gestation remain poorly defined. This cross-sectional study investigates how circulating inflammatory proteins vary with gestational age in pregnancy and examines the impacts of fundamental biological characteristics, such as gravidity and fetal sex. METHODS/UNASSIGNED:Data were drawn from 1154 pregnant individuals from six study sites of the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) Cohort. We used Olink high-throughput proteomic profiling to map cross-sectional associations between protein expression levels and gestational age at blood draw using linear, spline-based, and generalized additive modeling approaches. RESULTS/UNASSIGNED:Generalized additive models provided the best fit, revealing that immune changes across pregnancy were predominantly nonlinear. Sixty-one proteins showed significant associations with gestational age, with many exhibiting shared inflection points that aligned with major physiological transitions. A small subset of proteins also showed evidence of modification by fetal and maternal characteristics. CD244 displayed different gestational patterns by fetal sex, while CST5 and SIRT2 showed varied gestational associations by maternal gravidity. CONCLUSION/UNASSIGNED:The findings highlight pregnancy as a sequence of coordinated immune transitions rather than a simple linear shift and provide one of the most detailed characterizations to date of circulating inflammatory protein dynamics across human gestation. Establishing these normative trajectories offers a crucial reference for detecting early deviations that may signal risk for pregnancy complications and for identifying biomarkers in maternal and fetal health research.

A large body of evidence supports the role of the prenatal environment in shaping childhood development. The relative contributions of prenatal alcohol use (PAE), maternal socioeconomic, and nutritional status on child development vary in high- versus low-income settings. We analyzed data from a prospective cohort study among mother-infant dyads from Cape Town (CT), South Africa and the Northern Plains (NP), USA. The Mullen Scales of Early Learning were administered by trained assessors to evaluate cognitive, motor, and language development of 1-year old children. We used multiple linear regression models to assess standardized mean differences in development scores by (1) maternal prenatal factors, (2) delivery factors and (3) child factors within each study site. 1,728 infants from CT and 1,140 infants from the NP were included in the analyses. In CT, infants with moderate-to-high PAE had 0.17 SD (95% CI -0.30, -0.04) lower cognitive and 0.15 SD (-0.29, -0.2) lower expressive language scores compared to infants without PAE. In the NP, maternal obesity (BMI > 30 kg/m2) was significantly associated with -0.21 SD (-0.36, -0.06), and -0.13 SD (-0.27, -0.02) reductions in cognitive, and expressive language scores, respectively. Household crowding, lower levels of maternal educational attainment, prenatal maternal depression, low birthweight, admission to neonatal intensive care unit, and male sex had significant negative associations with cognitive and language development in both sites with effects ranging from -0.32 to -0.11 SDs. These results highlight the importance of assessing risk factors by populations across diverse social and cultural environments and emphasize the imperative to formulate intervention packages tailored to the local context.