Infant hedonic/anhedonic processing index (HAPI-Infant): Assessing infant anhedonia and its prospective association with adolescent depressive symptoms

BACKGROUND

Anhedonia, an impairment in the motivation for or experience of pleasure, is a well-established transdiagnostic harbinger and core symptom of mental illness. Given increasing recognition of early life origins of mental illness, we posit that anhedonia should, and could, be recognized earlier if appropriate tools were available. However, reliable diagnostic instruments prior to childhood do not currently exist.

METHODS

We developed an assessment instrument for anhedonia/reward processing in infancy, the Infant Hedonic/Anhedonic Processing Index (HAPI-Infant). Exploratory factor and psychometric analyses were conducted using data from 6- and 12-month-old infants from two cohorts (N = 188, N = 212). Then, associations were assessed between infant anhedonia and adolescent self-report of depressive symptoms.

RESULTS

The HAPI-Infant (47-items), exhibited excellent psychometric properties. Higher anhedonia scores at 6 (r = 0.23, p < .01) and 12 months (r = 0.19, p < .05) predicted elevated adolescent depressive symptoms, and these associations were stronger than for established infant risk indicators such as negative affectivity. Subsequent analyses supported the validity of short (27-item) and very short (12-item) versions of this measure.

LIMITATIONS

The primary limitations of this study are that the HAPI-Infant awaits additional tests of generalizability and of its ability to predict clinical diagnosis of depression.

CONCLUSIONS

The HAPI-Infant is a novel, psychometrically strong diagnostic tool suitable for recognizing anhedonia during the first year of life with strong predictive value for later depressive symptoms. In view of the emerging recognition of increasing prevalence of affective disorders in children and adolescents, the importance of the HAPI-Infant in diagnosing anhedonia is encouraging. Early recognition of anhedonia could target high-risk individuals for intervention and perhaps prevention of mental health disorders.

Across ages and places: Unpredictability of maternal sensory signals and child internalizing behaviors

BACKGROUND

Patterns of sensory inputs early in life play an integral role in shaping the maturation of neural circuits, including those implicated in emotion and cognition. In both experimental animal models and observational human research, unpredictable sensory signals have been linked to aberrant developmental outcomes, including poor memory and effortful control. These findings suggest that sensitivity to unpredictable sensory signals is conserved across species and sculpts the developing brain. The current study provides a novel investigation of unpredictable maternal sensory signals in early life and child internalizing behaviors. We tested these associations in three independent cohorts to probe the generalizability of associations across continents and cultures.

METHOD

The three prospective longitudinal cohorts were based in Orange, USA (n = 163, 47.2 % female, Mage = 1 year); Turku, Finland (n = 239, 44.8 % female, Mage = 5 years); and Irvine, USA (n = 129, 43.4 % female, Mage = 9.6 years). Unpredictability of maternal sensory signals was quantified during free-play interactions. Child internalizing behaviors were measured via parent report (Orange & Turku) and child self-report (Irvine).

RESULTS

Early life exposure to unpredictable maternal sensory signals was associated with greater child fearfulness/anxiety in all three cohorts, above and beyond maternal sensitivity and sociodemographic factors. The association between unpredictable maternal sensory signals and child sadness/depression was relatively weaker and did not reach traditional thresholds for statistical significance.

LIMITATIONS

The correlational design limits our ability to make causal inferences.

CONCLUSIONS

Findings across the three diverse cohorts suggest that unpredictable maternal signals early in life shape the development of internalizing behaviors, particularly fearfulness and anxiety.

Reliability of ordinal outcomes in forensic black-box studies

Forensic science disciplines such as latent print examination, bullet and cartridge case comparisons, and shoeprint analysis, involve subjective decisions by forensic experts throughout the examination process. Most of the decisions involve ordinal categories. Examples include a three-category outcome for latent print comparisons (exclusion, inconclusive, identification) and a seven-category outcome for footwear comparisons (exclusion, indications of non-association, inconclusive, limited association of class characteristics, association of class characteristics, high degree of association, identification). As the results of the forensic examinations of evidence can heavily influence the outcomes of court proceedings, it is important to assess the reliability and accuracy of the underlying decisions. "Black box" studies are the most common approach for assessing the reliability and accuracy of subjective decisions. In these studies, researchers produce evidence samples consisting of a sample of questioned source and a sample of known source where the ground truth (same source or different source) is known. Examiners provide assessments for selected samples using the same approach they would use in actual casework. These studies often have two phases; the first phase comprises of decisions on samples of varying complexities by different examiners, and the second phase involves repeated decisions by the same examiner on a (usually) small subset of samples that were encountered by examiners in the first phase. We provide a statistical method to analyze ordinal decisions from black-box trials with the objective of obtaining inferences for the reliability of these decisions and quantifying the variation in decisions attributable to the examiners, the samples, and statistical interaction effects between examiners and samples. We present simulation studies to judge the performance of the model on data with known parameter values and apply the model to data from a handwritten signature complexity study, a latent fingerprint examination black-box study, and a handwriting comparisons black-box study.

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome

Background

Adverse early-life experiences (ELA), including poverty, trauma and neglect, affect a majority of the world's children. Whereas the impact of ELA on cognitive and emotional health throughout the lifespan is well-established, it is not clear how distinct types of ELA influence child development, and there are no tools to predict for an individual child their vulnerability or resilience to the consequences of ELAs. Epigenetic markers including DNA-methylation profiles of peripheral cells may encode ELA and provide a predictive outcome marker. However, the rapid dynamic changes in DNA methylation in childhood and the inter-individual variance of the human genome pose barriers to identifying profiles predicting outcomes of ELA exposure. Here, we examined the relation of several dimensions of ELA to changes of DNA methylation, using a longitudinal within-subject design and a high threshold for methylation changes in the hope of mitigating the above challenges.

Methods

We analyzed DNA methylation in buccal swab samples collected twice for each of 110 infants: neonatally and at 12 months. We identified CpGs differentially methylated across time, calculated methylation changes for each child, and determined whether several indicators of ELA associated with changes of DNA methylation for individual infants. We then correlated select dimensions of ELA with methylation changes as well as with measures of executive function at age 5 years. We examined for sex differences, and derived a sex-dependent 'impact score' based on sites that most contributed to the methylation changes.

Findings

Setting a high threshold for methylation changes, we discovered that changes in methylation between two samples of an individual child reflected age-related trends towards augmented methylation, and also correlated with executive function years later. Among the tested factors and ELA dimensions, including income to needs ratios, maternal sensitivity, body mass index and sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, an interaction was observed between a measure of high early-life unpredictability and methylation changes, in presaging executive function.

Interpretation

These findings establish longitudinal, within-subject changes in methylation profiles as a signature of some types of ELA in an individual child. Notably, such changes are detectable beyond the age-associated DNA methylation dynamics. Future studies are required to determine if the methylation profile changes identified here provide a predictive marker of vulnerabilities to poorer cognitive and emotional outcomes.

Experiences of COVID-19-Related Racism and Impact on Depression Trajectories Among Racially/Ethnically Minoritized Adolescents

PURPOSE

In 2020, racially/ethnically minoritized (REMD) youth faced the "dual pandemics" of COVID-19 and racism, both significant stressors with potential for adverse mental health effects. The current study tested whether short- and long-term trajectories of depressive symptoms from before to during the COVID-19 pandemic differed between REMD adolescents who did and did not endorse exposure to COVID-19-era-related racism (i.e., racism stemming from conditions created or exacerbated by the COVID-19 pandemic).

METHODS

A community sample of 100 REMD adolescents enrolled in an ongoing longitudinal study of mental health was assessed before and during the COVID-19 pandemic. Participants were 51% girls, mean age = 16, standard deviation = 2.7, and identified as Latinx/Hispanic (48%), Multiethnic (34%), Asian American (12%), and Black (6%).

RESULTS

REMD adolescents' depressive symptoms were elevated during the COVID-19 pandemic compared to pre-pandemic levels, and increases were more pronounced over time for those who endorsed exposure to COVID-19-era-related racism. In general, Asian American participants endorsed racism experiences at the highest rates compared to others, including being called names (42%), people acting suspicious around them (33%), and being verbally threatened (17%). Additionally, more than half of Black and Asian American participants reported worry about experiencing racism related to the COVID-19 pandemic, even if they had not experienced it to date.

DISCUSSION

REMD adolescents are at increased risk for depressive symptoms related to converging stressors stemming from the COVID-19 pandemic and pandemic-related racism, which has the potential to widen racial/ethnic mental health disparities faced by the REMD youth.

Exposure to unpredictability and mental health: Validation of the brief version of the Questionnaire of Unpredictability in Childhood (QUIC-5) in English and Spanish

Unpredictability is increasingly recognized as a primary dimension of early life adversity affecting lifespan mental health trajectories; screening for these experiences is therefore vital. The Questionnaire of Unpredictability in Childhood (QUIC) is a 38-item tool that measures unpredictability in childhood in social, emotional and physical domains. The available evidence indicates that exposure to unpredictable experiences measured with the QUIC predicts internalizing symptoms including depression and anxiety. The purpose of the present study was to validate English and Spanish brief versions (QUIC-5) suitable for administration in time-limited settings (e.g., clinical care settings, large-scale epidemiological studies). Five representative items were identified from the QUIC and their psychometric properties examined. The predictive validity of the QUIC-5 was then compared to the QUIC by examining mental health in four cohorts: (1) English-speaking adult women assessed at 6-months postpartum (N = 116), (2) English-speaking male veterans (N = 95), (3) English-speaking male and female adolescents (N = 155), and (4) Spanish-speaking male and female adults (N = 285). The QUIC-5 demonstrated substantial variance in distributions in each of the cohorts and is correlated on average 0.84 (r's = 0.81-0.87) with the full 38-item version. Furthermore, the QUIC-5 predicted internalizing symptoms (anxiety and depression) in all cohorts with similar effect sizes (r's = 0.16-0.39; all p's < 0.05) to the full versions (r's = 0.19-0.42; all p's < 0.05). In sum, the QUIC-5 exhibits good psychometric properties and is a valid alternative to the full QUIC. These findings support the future use of the QUIC-5 in clinical and research settings as a concise way to measure unpredictability, identify risk of psychopathology, and intervene accordingly.

Early life exposure to unpredictable parental sensory signals shapes cognitive development across three species

Exposure to early life adversity has long term consequences on cognitive function. Most research has focused on understanding components of early life adversities that contribute to later risk, including poverty, trauma, maltreatment, and neglect. Whereas these factors, in the aggregate, explain a significant proportion of emotional and cognitive problems, there are serious gaps in our ability to identify potential mechanisms by which early life adversities might promote vulnerability or resilience. Here we discuss early life exposure to unpredictable signals from the caretaker as an understudied type of adversity that is amenable to prevention and intervention. We employ a translational approach to discover underlying neurobiological mechanisms by which early life exposure to unpredictable signals sculpts the developing brain. First, we review evidence that exposure to unpredictable signals from the parent during sensitive periods impacts development of neural circuits. Second, we describe a method for characterizing early life patterns of sensory signals across species. Third, we present published and original data illustrating that patterns of maternal care predict memory function in humans, non-human primates, and rodents. Finally, implications are discussed for identifying individuals at risk so that early preventive-intervention can be provided.

A cross-species assay demonstrates that reward responsiveness is enduringly impacted by adverse, unpredictable early-life experiences

Exposure to early-life adversity (ELA) is associated with several neuropsychiatric conditions, including major depressive disorder, yet causality is difficult to establish in humans. Recent work in rodents has implicated impaired reward circuit signaling in anhedonic-like behavior after ELA exposure. Anhedonia, the lack of reactivity to previously rewarding stimuli, is a transdiagnostic construct common to mental illnesses associated with ELA. Here, we employed an assay of reward responsiveness validated across species, the Probabilistic Reward Task (PRT). In the PRT, healthy participants reliably develop a response bias toward the more richly rewarded stimulus, whereas participants with anhedonia exhibit a blunted response bias that correlates with current and future anhedonia. In a well-established model of ELA that generates a stressful, chaotic, and unpredictable early-life environment, ELA led to blunted response biases in the PRT in two separate cohorts, recapitulating findings in humans with anhedonia. The same ELA rats had blunted sucrose preference, further supporting their anhedonic-like phenotypes. Probing the aspects of ELA that might provoke these deficits, we quantified the unpredictability of dam/pup interactions using entropy measures and found that the unpredictability of maternal care was significantly higher in the ELA groups in which PRT and sucrose preference reward deficits were present later in life. Taken together, these data position the PRT, established in clinical patient populations, as a potent instrument to assess the impact of ELA on the reward circuit across species. These findings also implicate the unpredictability of maternal signals during early life as an important driver of reward sensitivity deficits.

Prenatal maternal mood entropy is associated with child neurodevelopment

Emerging evidence indicates that the predictability of signals early in life may influence the developing brain. This study examines links between a novel indicator of maternal mood dysregulation, mood entropy, and child neurodevelopmental outcomes. Associations between prenatal maternal mood entropy and child neurodevelopment were assessed in 2 longitudinal cohorts. Maternal mood was measured several times over pregnancy beginning as early as 15 weeks' gestation. Shannon's mood entropy was applied to distributions of mothers' responses on mood questionnaires. Child cognitive and language development were evaluated at 2 and 6-9 years of age. Higher prenatal maternal mood entropy was associated with lower cognitive development scores at 2 years of age and lower expressive language scores at 6-9 years of age. These associations persisted after adjusting for maternal pre and postnatal mood levels and for other relevant sociodemographic factors. Our findings identify maternal mood entropy as a novel predictor of child neurodevelopment. Characterizing components of maternal mood in addition to level of severity or valence may further our understanding of specific processes by which maternal mood shapes child development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Development and initial validation of self-report measures of general health, preoperative anxiety, and postoperative pain in young children using computer-administered animation

BACKGROUND

For young children, existing measures of children's health-related quality of life must be parent-reported or interviewer-administered for those who cannot read or complete measures independently. Parents' and childrens' reports about the child's health have been shown to disagree.

AIMS

(a) To test the reliability and validity of an animated, computer-administered Child Health Rating Inventories (CHRIS2.0) among children aged 4-12 undergoing surgery; and (b) to develop and test two CHRIS measures of preoperative anxiety and postoperative pain management.

METHODS

We conducted a longitudinal cohort study of a diverse group of 542 children aged 4-12 undergoing surgery. We compared the CHRIS measures to Pediatric Quality of Life Inventory (PedsQL), the Functional Disabilities Inventory (FDI), State-Trait Anxiety Inventory for children (STAI-CH), and the Parent Postoperative Pain Measure (PPPM).

RESULTS

Factor analyses supported the construct validity of the 12-item general physical health and the 8-item mental health CHRIS scales, as well as a composite 20-item scale, and the CHRIS preoperative anxiety and postoperative pain scales. Internal consistency reliability for all CHRIS scales exceeded the standard for group comparisons (Cronbach's α ≥0.70). The CHRIS general health composite was significantly correlated with composite PedsQL and FDI (r = 0.28, P < .001 and r = 0.43, P < .001, respectively). The CHRIS peri-operative anxiety measure was significantly correlated with the STAI-CH (r = 0.44, P < .001), as was the CHRIS postoperative pain scale with the PPPM (r = 0.52, P < .001).

CONCLUSIONS

The CHRIS measures were reliable and valid in this diverse sample of young children (4-12). Because CHRIS measures are self-administered, scored in real time, and run on multiple different platforms, this approach provides a feasible method for the collection of health-related quality of life in young children and those with limited literacy. Our data indicate that this approach is psychometrically sound and has the potential for adding the child's voice to pediatric outcomes.

Why Temporal Persistence of Biometric Features, as Assessed by the Intraclass Correlation Coefficient, Is So Valuable for Classification Performance

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer this question. In a recent report, we introduced the intraclass correlation coefficient (ICC) as an index of temporal persistence for such features. Here, we present a novel approach using synthetic features to study which aspects of a biometric identification study are influenced by the temporal persistence of features. What we show is that using more temporally persistent features produces effects on the similarity score distributions that explain why this quality is so key to biometric performance. The results identified with the synthetic data are largely reinforced by an analysis of two datasets, one based on eye-movements and one based on gait. There was one difference between the synthetic and real data, related to the intercorrelation of features in real data. Removing these intercorrelations for real datasets with a decorrelation step produced results which were very similar to that obtained with synthetic features.

Unpredictable maternal behavior is associated with a blunted infant cortisol response

BACKGROUND

Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is associated with poor physical and mental health. Early-life adversity may dysregulate cortisol response to subsequent stress. This study examines the association between patterns of maternal behavior and infant stress response to a challenge. Specifically, we test whether infant exposure to unpredictable maternal sensory signals is related to the cortisol response to a painful stressor.

METHOD

Participants were 102 mothers and their children enrolled in a longitudinal study. Patterns of maternal sensory signals were evaluated at 6 and 12 months during a 10-min mother-infant play episode. Entropy rate was calculated as a quantitative measure of the degree of unpredictability of maternal sensory signals (visual, auditory, and tactile) exhibited during the play episode. Infant saliva samples were collected for cortisol analysis before and after inoculation at 12 months.

RESULTS

Unpredictable patterns of maternal sensory signals were associated with a blunted infant cortisol response to a painful stressor. This relation persisted after evaluation of covariates including maternal sensitivity and maternal psychological distress.

CONCLUSIONS

This study provides evidence that unpredictable patterns of maternal sensory signals are one process through which caregiving affects the function of infant stress response systems.

Optimally Balanced Gaussian Process Propensity Scores for Estimating Treatment Effects

Propensity scores are commonly employed in observational study settings where the goal is to estimate average treatment effects. This paper introduces a flexible propensity score modeling approach, where the probability of treatment is modeled through a Gaussian process framework. To evaluate the effectiveness of the estimated propensity score, a metric of covariate imbalance is developed that quantifies the discrepancy between the distributions of covariates in the treated and control groups. It is demonstrated that this metric is ultimately a function of the hyperparameters of the covariance matrix of the Gaussian process and therefore it is possible to select the hyperparameters to optimize the metric and minimize overall covariate imbalance. The effectiveness of the GP method is compared in a simulation against other methods of estimating the propensity score and the method is applied to data from Dehejia and Wahba (1999) to demonstrate benchmark performance within a relevant policy application.

Across continents and demographics, unpredictable maternal signals are associated with children's cognitive function

Background

Early life experiences have persisting influence on brain function throughout life. Maternal signals constitute a primary source of early life experiences, and their quantity and quality during sensitive developmental periods exert enduring effects on cognitive function and emotional and social behaviors. Here we examined if, in addition to established qualitative dimensions of maternal behavior during her interactions with her infant and child, patterns of maternal signals may contribute to the maturation of children's executive functions. We focused primarily on effortful control, a potent predictor of mental health outcomes later in life.

Methods

In two independent prospective cohorts in Turku, Finland (N = 135), and Irvine, CA, USA (N = 192) that differed significantly in race/ethnicity and sociodemographic parameters, we assessed whether infant exposure to unpredictable patterns of maternal-derived sensory signals portended poor effortful control.

Outcomes

In both the Irvine and Turku cohorts, unpredictable sequences of maternal behavior during infancy were associated with worse effortful control at one year of age. Longitudinal analyses demonstrated that this association persisted for as long as each cohort was assessed-until two years of age in the Turku cohort and to 9.5 years in the Irvine cohort. The relation of unpredictable maternal signals during infancy and the measures of executive function persisted after adjusting for covariates.

Interpretations

The consistency of our findings across two cohorts from different demographic backgrounds substantiated the finding that patterns, and specifically unpredictable sequences, of maternal behaviors may influence the development of executive functions which may be associated with vulnerability to subsequent psychopathology.

Fund

This research was supported by the National Institutes of Health (NIH) awards P50MH096889, HD051852, NS041298, HD02413, HD050662, HD065823, and by the FinnBrain funders: Academy of Finland (129839, 134950, 253270, 286829, 287908, 308176, 308252), Jane and Aatos Erkko Foundation, Signe and Ane Gyllenberg Foundation, Yrjö Jahnsson Foundation, and State Research Grants (P3498, P3654).

Does Anhedonia Presage Increased Risk of Posttraumatic Stress Disorder? : Adolescent Anhedonia and Posttraumatic Disorders

Anhedonia, the reduced ability to experience pleasure, is a dimensional entity linked to multiple neuropsychiatric disorders, where it is associated with diminished treatment response, reduced global function, and increased suicidality. It has been suggested that anhedonia and the related disruption in reward processing may be critical precursors to development of psychiatric symptoms later in life. Here, we examine cross-species evidence supporting the hypothesis that early life experiences modulate development of reward processing, which if disrupted, result in anhedonia. Importantly, we find that anhedonia may confer risk for later neuropsychiatric disorders, especially posttraumatic stress disorder (PTSD). Whereas childhood trauma has long been associated with increased anhedonia and increased subsequent risk for trauma-related disorders in adulthood, here we focus on an additional novel, emerging direct contributor to anhedonia in rodents and humans: fragmented, chaotic environmental signals ("FRAG") during critical periods of development. In rodents, recent data suggest that adolescent anhedonia may derive from aberrant pleasure/reward circuit maturation. In humans, recent longitudinal studies support that FRAG is associated with increased anhedonia in adolescence. Both human and rodent FRAG exposure also leads to aberrant hippocampal function. Prospective studies are underway to examine if anhedonia is also a marker of PTSD risk. These preliminary cross-species studies provide a critical construct for future examination of the etiology of trauma-related symptoms in adults and for and development of prophylactic and therapeutic interventions. In addition, longitudinal studies of reward circuit development with and without FRAG will be critical to test the mechanistic hypothesis that early life FRAG modifies reward circuitry with subsequent consequences for adolescent-emergent anhedonia and contributes to risk and resilience to trauma and stress in adulthood.

Measuring novel antecedents of mental illness: the Questionnaire of Unpredictability in Childhood

Increasing evidence indicates that, in addition to poverty, maternal depression, and other well-established factors, unpredictability of maternal and environmental signals early in life influences trajectories of brain development, determining risk for subsequent mental illness. However, whereas most risk factors for later vulnerability to mental illness are readily measured using existing, clinically available tools, there are no similar measures for assessing early-life unpredictability. Here we validate the Questionnaire of Unpredictability in Childhood (QUIC) and examine its associations with mental health in the context of other indicators of childhood adversity (e.g., traumatic life events, socioeconomic status, and parenting quality). The QUIC was initially validated through administration to a cohort of adult females (N = 116) and then further refined in two additional independent cohorts (male Veterans, N = 95, and male and female adolescents, N = 175). The QUIC demonstrated excellent internal (α = 0.89) and test-retest reliability (r = 92). Scores on the QUIC were positively correlated with other prospective indicators of exposures to unpredictable maternal inputs in infancy and childhood (unpredictable maternal mood and sensory signals), and accuracy of recall also was confirmed with prospective data. Importantly, the QUIC predicted symptoms of anxiety, depression, and anhedonia in the three study cohorts, and these effects persisted after adjusting for other previously established risk factors. The QUIC, a reliable and valid self-report assessment of exposure to unpredictability in the social, emotional, and physical domains during early life, is a brief, comprehensive, and promising instrument for predicting risk for mental illness.

Intra-individual methylomics detects the impact of early-life adversity

This study shows that methylation profile changes across time in the same individual distinguish a stressful experience from typical infancy, providing a potential predictive marker of vulnerability to disease.

Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an “epigenetic signature” of early-life experiences. Here, we used a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular metabolic enzymes, ion channels, and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate–related transcription factors, indicating their potential up-regulation. Thus, intra-individual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth, and function.

Prenatal maternal mood patterns predict child temperament and adolescent mental health

BACKGROUND

This study quantifies the dynamics of maternal mood focusing on unpredictability, and to assess if greater unpredictability of prenatal maternal mood predicts child temperament and internalizing symptoms through early adolescence.

METHODS

The association between prenatal mood predictability and child internalizing symptoms were assessed in two longitudinal cohorts (N's = 227 and 180). Maternal mood was assessed repeatedly during pregnancy as early as 15 weeks' gestation. Predictability of maternal mood was calculated by applying Shannon's entropy to the distribution of responses on mood questionnaires. Maternal reports of child negative affectivity (a predictor of later internalizing) were collected at 6, 12, 24 months and 7 years of age. Child self-reports of anxiety symptoms were collected at 10 years and reports of depression symptoms at 13 years.

RESULTS

Fetal exposure to more elevated maternal mood entropy predicted higher levels of child negative affectivity at 12 months (r = .36; p < 01), 24 months (r = .31; p < 01) and 7 years (r = .32; p < 01) of age. In addition, children exposed to higher prenatal maternal mood entropy, reported higher levels of anxiety symptoms at 10 years (r = .24; p < 01) and elevated depressive symptoms at 13 years (r = .29; p < .01). These associations persisted after adjusting for maternal pre and postnatal mood valence (e.g. depression levels) and for other relevant demographic characteristics.

CONCLUSIONS

Our findings provide strong support for the notion that patterns of maternal mood influence the developing brain. More specifically, they suggest that prenatal maternal mood predictability may be a critical predictor of developmental mental health trajectories and should be considered when assessing early life influences on lifespan mental health.

LOGISTIC REGRESSION FOR EMPIRICAL STUDIES OF MULTIVARIATE SELECTION

Understanding the mechanics of adaptive evolution requires not only knowing the quantitative genetic bases of the traits of interest but also obtaining accurate measures of the strengths and modes of selection acting on these traits. Most recent empirical studies of multivariate selection have employed multiple linear regression to obtain estimates of the strength of selection. We reconsider the motivation for this approach, paying special attention to the effects of nonnormal traits and fitness measures. We apply an alternative statistical method, logistic regression, to estimate the strength of selection on multiple phenotypic traits. First, we argue that the logistic regression model is more suitable than linear regression for analyzing data from selection studies with dichotomous fitness outcomes. Subsequently, we show that estimates of selection obtained from the logistic regression analyses can be transformed easily to values that directly plug into equations describing adaptive microevolutionary change. Finally, we apply this methodology to two published datasets to demonstrate its utility. Because most statistical packages now provide options to conduct logistic regression analyses, we suggest that this approach should be widely adopted as an analytical tool for empirical studies of multivariate selection.

Using Mixture Models in Temperament Research

Temperamental characteristics can be conceptualised as continuous dimensions or qualitative categories. The continuous versus categorical question concerns the underlying temperamental characteristics and not the measured variables, which can be recorded in either continuous or categorical forms. This paper argues for a categorical conceptualisation of temperamental characteristics and applies a finite mixture model appropriate to this view to two sets of longitudinal observations of infants and young children. This statistical approach provides a good description of the observed predictive relation between behavioural profiles of children at 4 months and the degree of behavioural signs of fear at 14 months. An advantage of the mixture model approach to this data, relative to more standard approaches to developmental data, is that because it takes into account an a-priori theory, it can be used to address improvements and refinements to theories and experimental designs in a straightforward manner.

The Function Biomedical Informatics Research Network Data Repository

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

A Test by Any Other Name: P Values, Bayes Factors, and Statistical Inference

Procedures used for statistical inference are receiving increased scrutiny as the scientific community studies the factors associated with insuring reproducible research. This note addresses recent negative attention directed at p values, the relationship of confidence intervals and tests, and the role of Bayesian inference and Bayes factors, with an eye toward better understanding these different strategies for statistical inference. We argue that researchers and data analysts too often resort to binary decisions (e.g., whether to reject or accept the null hypothesis) in settings where this may not be required.

A hierarchical modeling approach to data analysis and study design in a multi-site experimental fMRI study

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model selection based on the deviance information criterion (DIC), we show that our model provides a good fit to the observed data by sharing information across the sites. We also propose a simple approach for evaluating the efficacy of the multi-site experiment by comparing the results to those that would be expected in hypothetical single-site experiments with the same sample size.

Genetic variations in the dopamine system and facial expression recognition in healthy chinese college students

OBJECTIVE

This study investigated the relation between genetic variations in the dopamine system and facial expression recognition.

METHODS

A sample of Chinese college students (n = 478) was given a facial expression recognition task. Subjects were genotyped for 98 loci [96 single-nucleotide polymorphisms (SNPs) and 2 variable number tandem repeats] in 16 genes involved in the dopamine neurotransmitter system, including its 4 subsystems: synthesis (TH, DDC, and DBH), degradation/transport (COMT,MAOA,MAOB, and SLC6A3), receptors (DRD1,DRD2,DRD3,DRD4, and DRD5), and modulation (NTS,NTSR1,NTSR2, and NLN). To quantify the total contributions of the dopamine system to emotion recognition, we used a series of multiple regression models. Permutation analyses were performed to assess the posterior probabilities of obtaining such results.

RESULTS

Among the 78 loci that were included in the final analyses (after excluding 12 SNPs that were in high linkage disequilibrium and 8 that were not in Hardy-Weinberg equilibrium), 1 (for fear), 3 (for sadness), 5 (for anger), 13 (for surprise), and 15 (for disgust) loci exhibited main effects on the recognition of facial expressions. Genetic variations in the dopamine system accounted for 3% for fear, 6% for sadness, 7% for anger, 10% for surprise, and 18% for disgust, with the latter surviving a stringent permutation test.

CONCLUSIONS

Genetic variations in the dopamine system (especially the dopamine synthesis and modulation subsystems) made significant contributions to individual differences in the recognition of disgust faces.

Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery.

Time trends of methylmercury in walleye in northern Wisconsin: a hierarchical Bayesian analysis

Methylmercury data from walleye fillets collected by multiple agencies from northern Wisconsin lakes from 1982 to 2005 were examined for regional time trends. Hierarchical Bayesian methods were used to model dependencies and provide probability statements for parameters pertaining to individual lakes and the region as a whole. A missing data mechanism allowed the sex of the fish to be included as a predictor since the sexes grow at different rates. A slight regional decrease in methylmercury of 0.60% annually was found, consistent with declining atmospheric mercury deposition. Methylmercury was estimated to have decreased in 77% of the 420 lakes from which walleye were sampled, although uncertainty regarding time trends was greater for most individual lakes than for the region as a whole. Methylmercury in walleye varied widely from lake to lake, but generally accumulated in the fish at similar rates by length after accounting for differences in sex. Slower-growing male walleye had higher methylmercury concentrations than females for a given length, and skin-on fillets were 16% lower in methylmercury than skin-off fillets.

Model inference or model selection: Discussion of Klugkist, Laudy, and Hoijtink (2005)

I. Klugkist, O. Laudy, and H. Hoijtink (2005) presented a Bayesian approach to analysis of variance models with inequality constraints. Constraints may play 2 distinct roles in data analysis. They may represent prior information that allows more precise inferences regarding parameter values, or they may describe a theory to be judged against the data. In the latter case, the authors emphasized the use of Bayes factors and posterior model probabilities to select the best theory. One difficulty is that interpretation of the posterior model probabilities depends on which other theories are included in the comparison. The posterior distribution of the parameters under an unconstrained model allows one to quantify the support provided by the data for inequality constraints without requiring the model selection framework.

Identification of errors and factors associated with errors in data from electronic swine feeders1

Electronic swine feeders are used to automatically measure individual feed intake on group-housed pigs, but the resulting data contain errors caused by feeder malfunctions and animal-feeder interactions. The objectives of this study were to 1) develop criteria to identify errors in data from an electronic feeder that is predominant in the United States; 2) evaluate the frequency of errors in data from three consecutive experiments using the same feeders; and 3) identify factors associated with errors. Across experiments, data included 1,878,321 feed intake records (visits) on 1,721 pigs and 124 pens. Sixteen criteria were developed to detect errors in seven variables related to feed trough weights and times. Logistic regression was used to identify factors associated with the presence or absence of each error type in identified visits (visits where the feeder recognized a transponder) using a model that included the fixed effects of replicate, sex, linear and quadratic effects of day on test, and random effects of feeder within replicate, pig within feeder within replicate, test day within replicate, and week within feeder within replicate. Frequencies of error types in identified visits varied considerably within and between experiments. Errors in feed trough weights were more frequent than errors in time. Percentage of identified visits and of daily feed intake records with at least one error ranged from 4.3 to 18.7% and from 17.2 to 50.0%, respectively, and decreased from the first to the last experiment, reflecting the increasing ability of the managers to operate the feeders. Replicate, sex, test day, feeder within replicate, pig, and day within replicate affected the number of errors that occurred, but their effect varied among error types. Week-to-week variation within a feeder and replicate had the largest effect on number of errors, which was likely associated with feeder management. Results indicate that the frequency of errors in data from electronic swine feeders is substantial, but visits with errors can be identified and their frequency can be decreased by proper feeder management.

Cancer physicians' attitudes toward colorectal cancer follow-up

BACKGROUND

The optimal follow-up strategy for colorectal cancer is unknown.

MATERIALS AND METHODS

We surveyed all Canadian radiation oncologists, medical oncologists and surgeons specializing in colorectal cancer to assess their recommendations for follow-up after potentially curative treatment, the beliefs and attitudes underlying these practices, and the cost implications of different follow-up strategies.

RESULTS

One hundred and sixty practitioners (58%) returned completed surveys. Most recommended clinical assessments every 3-4 months in the first 2 years including carcino-embryonic antigen testing, gradually decreasing in frequency over 5 years. Ninety per cent recommend a surveillance colonoscopy in the first year. The majority felt that specialist involvement in follow-up was important because of the increased opportunities for patients to contribute to research (76%) and teaching (73%). About half felt that specialists were more efficient at providing follow-up than primary care physicians, but these same physicians recommended significantly longer and more expensive follow-up routines on average than others. Primary care physicians were felt to be important allies, especially in managing the psychosocial concerns of patients.

CONCLUSIONS

Surveillance practices are generally in keeping with published recommendations. Most specialists feel that they should remain involved in follow-up, but this may result in increased resource utilization.

The use of multiple imputation for the analysis of missing data

This article provides a comprehensive review of multiple imputation (MI), a technique for analyzing data sets with missing values. Formally, MI is the process of replacing each missing data point with a set of m > 1 plausible values to generate m complete data sets. These complete data sets are then analyzed by standard statistical software, and the results combined, to give parameter estimates and standard errors that take into account the uncertainty due to the missing data values. This article introduces the idea behind MI, discusses the advantages of MI over existing techniques for addressing missing data, describes how to do MI for real problems, reviews the software available to implement MI, and discusses the results of a simulation study aimed at finding out how assumptions regarding the imputation model affect the parameter estimates provided by MI.

Management of persistent or locally recurrent epidermoid cancer of the anal canal with abdominoperineal resection

We retrospectively evaluated the outcome of 22 patients with epidermoid cancer of the anal canal who underwent surgical salvage after failure of primary chemoradiotherapy. Patients who required surgery had significantly more advanced T-stage than those who did not fail chemoradiotherapy. Eighteen patients failed surgical salvage. Invasion through the muscle wall of the bowel was present in 16 of 18 patients compared with two of four patients who have no evidence of disease (follow-up 5-10 years). Failure occurred only in the pelvis in 13 of the patients who died of disease. The mean time to death after surgery was 19 months. We confirm the overall poor results of conventional abdominoperineal resection in those patients who have failed previous therapy. Most failures occur in the pelvis. Transanorectal ultrasound and magnetic resonance imaging (MRI) may allow better selection of patients for exenterative procedures and identify those not amenable to successful salvage.

APC I1307K increases risk of transition from polyp to colorectal carcinoma in Ashkenazi Jews

BACKGROUND & AIMS

The I1307K allele of the APC gene has been shown to confer a modestly elevated risk of colorectal cancer in the Ashkenazi Jewish population (relative risk, 1.5-1.7). However, it is unclear whether the alteration predisposes to adenomas and whether the genetic information can be used in clinical practice. To further address the pathogenic significance of I1307K, we offered both a genetic test and a screening program to individuals considered to be at increased risk for colorectal cancer. We compared the prevalence of polyps and their characteristics between carriers and noncarriers.

METHODS

Invitations to participate in a DNA and colonoscopy screening program were mailed, together with a family questionnaire, to 3540 households forming the Jewish Community in Ottawa. The I1307K variant was analyzed in 242 eligible respondents who were selected because they had a personal or family history of colon cancer. Nearly 80% of these respondents (n = 189; age range, 32-83 years) consented to undergo a single colonoscopic examination.

RESULTS

The overall carrier frequency of I1307K in the study group was 10.3%. A higher proportion of heterozygous gene carriers was found in the subgroup of colon cancer survivors (27%) than among asymptomatic individuals (8%, P < 0.02). A total of 59 polyps were identified in 44 subjects. Histologically confirmed adenomatous polyps were diagnosed in 11.8% of carriers and 12.8% of noncarriers (P > 0.5). No significant differences in polyp size, multiplicity, location, degree of villosity, or age-dependent prevalence were found between the 2 groups of participants.

CONCLUSIONS

The high frequency of I1307K colorectal cancer patients found in the Ashkenazi Jewish community of Ottawa and the equivalent proportion of carriers and noncarriers who developed adenomatous polyps suggest that in this community, I1307K is associated with a significant predisposition to carcinoma but not adenoma.