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BACKGROUND: It is well-established that parental obesity is a strong risk factor for offspring obesity. Further, a converging body of evidence now suggests that maternal weight profiles may affect the developing offsprings brain in a manner that confers future obesity risk. Here, we investigated how pre-pregnancy maternal weight status influences the reward-related striatal areas of the offsprings brain during in utero development. METHODS: We used diffusion tensor imaging to quantify the microstructure of the striatal brain regions of interest in neonates (N = 116 [66 males, 50 females], mean gestational weeks at birth [39.88], SD = 1.14; at scan [43.56], SD = 1.05). Linear regression was used to test the associations between maternal pre-pregnancy body mass index (BMI) and infant striatal mean diffusivity. RESULTS: High maternal pre-pregnancy BMI was associated with higher mean MD values in the infants left caudate nucleus. Results remained unchanged after the adjustment for covariates. CONCLUSIONS: In utero exposure to maternal adiposity might have a growth-impairing impact on the mean diffusivity of the infants left caudate nucleus. Considering the involvement of the caudate nucleus in regulating eating behavior and food-related reward processing later in life, this finding calls for further investigations to define the prognostic relevance of early-life caudate nucleus development and weight trajectories of the offspring.

BackgroundAn extensive body of animal literature supports the premise that maternal obesity during pregnancy can alter the development of the fetal hypothalamus (HTH, a critical regulator of energy balance) with implications for offspring obesity risk (i.e., long-term energy imbalance). Yet, the relationship in humans between maternal overweight/obesity during pregnancy and fetal hypothalamic development remains largely unknown. Here, using an international (Finland and California, USA) multi-site diffusion tensor imaging (DTI) dataset, we test the hypothesis that maternal pre-pregnancy BMI is associated with newborn offspring HTH mean diffusivity (HTH MD, a replicable neural correlate of BMI in adults).MethodsHTH MD was independently quantified in two separate BMI-matched cohorts (up to class II obesity; BMIRange = 17-35) using a high-resolution atlas-based definition of HTH. A total of n = 231 mother-child dyads were available for this analysis (nSite,1 = 152, age at MRI = 26.7 ± 8.1 days, gestational age at birth = 39.9 ± 1.2 weeks, nM/F = 82/70, BMI = 24.2 ± 3.8; nSite,2 = 79, age at MRI = 25.6 ± 12.5 days, gestational age at birth = 39.3 ± 1.5 weeks, nM/F = 45/34, BMI = 25.1 ± 4.0). The association between maternal pre-pregnancy BMI and newborn offspring HTH MD was examined separately in each cohort using linear regression adjusting for gestational age at birth, postnatal age at scan, sex, whole white matter mean diffusivity, and DTI quality control criteria. In post hoc analyses, additional potentially confounding factors including socioeconomic status, ethnicity, and obstetric risk were adjusted where appropriate.ResultsThe distribution of maternal pre-pregnancy BMI was comparable across sites but differed by ethnicity and socioeconomic status. A positive linear association between maternal pre-pregnancy BMI and newborn offspring HTH MD was observed at both sites ([Formula: see text]Site,1 = 0.17, pSite,1 = 0.01; [Formula: see text]Site,2 = 0.22, pSite,2 = 0.03) and remained significant after adjusting for cohort-relevant covariates.ConclusionsThese findings translate the preclinically established association between maternal obesity during pregnancy and offspring hypothalamic microstructure to the human context. In addition to further replication/generalization, future efforts to identify biological mediators of the association between maternal obesity and fetal HTH development are warranted to develop targeted strategies for the primary prevention of childhood obesity.

The normative, developmental changes in affect-biased attention during the preschool years are largely unknown. To investigate the attention bias for emotional versus neutral faces, an eye-tracking measurement and free viewing of paired pictures of facial expressions (i.e., happy, fearful, sad, or angry faces) and nonface pictures with neutral faces were conducted with 367 children participating in a Finnish cohort study at the age of 2.5 years and with 477 children at the age of 5 years, 216 of which having follow-up measurements. We found an attention-orienting bias for happy and fearful faces versus neutral faces at both age points. An attention-orienting bias for sad faces emerged between 2.5 and 5 years. In addition, there were significant biases in sustained attention toward happy, fearful, sad, and angry faces versus neutral faces, with a bias in sustained attention for fearful faces being the strongest. All biases in sustained attention increased between 2.5 and 5 years of age. Moderate correlations in saccadic latencies were found between 2.5 and 5 years. In conclusion, attention biases for emotional facial expressions seem to be age-specific and specific for the attentional subcomponent. This implies that future studies on affect-biased attention during the preschool years should use small age ranges and cover multiple subcomponents of attention.

Most infants exhibit an attentional bias for faces and fearful facial expressions. These biases reduce toward the third year of life, but little is known about the development of the biases beyond early childhood. We used the same methodology longitudinally to assess attention disengagement patterns from nonface control pictures and faces (neutral, happy, and fearful expressions) in a large sample of children at 8, 30, and 60 months (N = 389/393/492, respectively; N = 72 for data in all three assessment; girls >45.3% in each assessment). "Face bias" was measured as a difference in disengagement probability (DP) from faces (neutral/happy) versus nonface patterns. "Fear bias" was calculated as a difference in DP for fearful versus happy/neutral faces. At group level, DPs followed a nonlinear longitudinal trajectory in all face conditions, being lowest at 8 months, highest at 30 months, and intermediate at 60 months. Face bias declined between 8 and 30 months, but did not change between 30 and 60 months. Fear bias declined linearly from 8 to 60 months. Individual differences in disengagement were generally not stable across age, but weak correlations were found in face bias between 8- and 60-month, and in DPs between 30- and 60-month (rs = 0.22-0.41). The results suggest that prioritized attention to faces--that is, a hallmark of infant cognition and a key aspect of human social behavior--follows a nonlinear trajectory in early childhood and may have only weak continuity from infancy to mid childhood.

High levels of early emotionality (of either negative or positive valence) are hypothesized to be important precursors to early psychopathology, with attention-deficit/hyperactivity disorder (ADHD) a prime early target. The positive and negative affect domains are prime examples of Research Domain Criteria (RDoC) concepts that may enrich a multilevel mechanistic map of psychopathology risk. Utilizing both variable-centered and person-centered approaches, the current study examined whether levels and trajectories of infant negative and positive emotionality, considered either in isolation or together, predicted children's ADHD symptoms at 4 to 8 years of age. In variable-centered analyses, higher levels of infant negative affect (at as early as 3 months of age) were associated with childhood ADHD symptoms. Findings for positive affect failed to reach statistical threshold. Results from person-centered trajectory analyses suggest that additional information is gained by simultaneously considering the trajectories of positive and negative emotionality. Specifically, only when exhibiting moderate, stable or low levels of positive affect did negative affect and its trajectory relate to child ADHD symptoms. These findings add to a growing literature that suggests that infant negative emotionality is a promising early life marker of future ADHD risk and suggest secondarily that moderation by positive affectivity warrants more consideration.

BackgroundEarly 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.MethodsIn 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.OutcomesIn 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.InterpretationsThe 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).

Parental executive functioning (EF) is considered one key contributing source, via direct and indirect routes, of inter-individual variation in offspring EF. The current study investigated the unexplored associations between maternal EF and infant EF as well as its precursor, sustained attention. Ninety-seven mother-infant-dyads from the FinnBrain Birth Cohort Study participated. Maternal EF was assessed using selected measures from the Cogstate test battery. At 8 months, infants completed Lab-TAB Blocks and modified A-not-B tasks. A modest but robust link between maternal EF and infant attention was revealed in girls. There was no association between mother and infant EF in either sex at 8 months. Notable directions for future research, and potential underlying mechanisms of sex differences are discussed. [ABSTRACT FROM AUTHOR]

Anti‐science attitudes can be resilient to scientific evidence if they are rooted in psychological motives. One such motive is trait reactance, which refers to the need to react with opposition when one's freedom of choice has been threatened. In three studies, we investigated trait reactance as a psychological motivation to reject vaccination. In the longitudinal studies (n = 199; 293), we examined if trait reactance measured before the COVID‐19 pandemic was related to people's willingness to get vaccinated against COVID‐19 up to 2 years later during the pandemic. In the experimental study (n = 398), we tested whether trait reactance makes anti‐vaccination attitudes more resistant to information and whether this resistance can be mitigated by framing the information to minimize the risk of triggering state reactance. The longitudinal studies showed that higher trait reactance before the COVID‐19 pandemic was related to lower willingness to get vaccinated against COVID‐19. Our experimental study indicated that highly reactant individuals' willingness to vaccinate was unaffected by the amount and framing of the information provided. Trait reactance has a strong and durable impact on vaccination willingness. This highlights the importance of considering the role of trait reactance in people's vaccination‐related decision‐making. [ABSTRACT FROM AUTHOR]

Pre-eclampsia (PE) is a hypertensive disorder of pregnancy which is associated with increased risk of neurodevelopmental disorders in exposed offspring. The pathophysiological mechanisms mediating this relationship are currently unknown, and one potential candidate is the anti-angiogenic factor soluble Fms-like tyrosine kinase 1 (sFlt-1), which is highly elevated in PE. While sFlt-1 can impair angiogenesis via inhibition of VEGFA signalling, it is unclear whether it can directly affect neuronal development independently of its effects on the vasculature. To test this hypothesis, the current study differentiated the human neural progenitor cell (NPC) line ReNcell® VM into a mixed culture of mature neurons and glia, and exposed them to sFlt-1 during development. Outcomes measured were neurite growth, cytotoxicity, mRNA expression of nestin, MBP, GFAP, and ßIII-tubulin, and neurosphere differentiation. sFlt-1 induced a significant reduction in neurite growth and this effect was timingand dose-dependent up to 100 ng/ml, with no effect on cytotoxicity. sFlt-1 (100 ng/ml) also reduced ßIII-tubulin mRNA and neuronal differentiation of neurospheres. Undifferentiated NPCs and mature neurons/glia expressed VEGFA and VEGFR-2, required for endogenous autocrine and paracrine VEGFA signalling, while sFlt-1 treatment prevented the neurogenic effects of exogenous VEGFA. Overall, these data provide the first experimental evidence for a direct effect of sFlt-1 on neurite growth and neuronal differentiation in human neurons through inhibition of VEGFA signalling, clarifying our understanding of the potential role of sFlt-1 as a mechanism by which PE can affect neuronal development. [ABSTRACT FROM AUTHOR]

Temperament is important to consider when investigating factors influencing communicative development in infancy. Existing research supporting the assumption that temperament and verbal language development are interrelated covers mainly verbal development in toddlerhood onward, but few studies focus on these relations in infancy. The present study of 91 infants from a general population pregnancy cohort in Finland used parent reports to investigate associations between temperament and the development of preverbal gesturing and receptive vocabulary in infancy. We found that infant temperament explained a substantially larger proportion of the variance in expressive communicative gesturing compared to receptive vocabulary. High Duration of "orienting" and "Soothability," indicators of orienting/regulation capacity, and higher positive emotionality were found to be favourable for the use of communicative gestures. These temperament characteristics might promote interaction and thus advance communicative development. Knowledge on associations between infant temperament and communicative development is important in supporting outcomes in children with temperament characteristics possibly less favourable for communication development.

This study tested whether executive functioning (EF)/learning tasks from the CogState computerized test battery show a unitary latent structure. This information is important for the construction of composite measures on these tasks for applied research purposes. Based on earlier factor analytic research, we identified five CogState tasks that have been labeled as EF/learning tasks and examined their intercorrelations in a new sample of Finnish birth cohort mothers (N = 233). Using confirmatory factor analyses, we compared two single-factor EF/learning models. The first model included the recommended summative scores for each task. The second model exchanged summative scores for first test round results for the three tasks providing these data, as initial task performance is expected to load more heavily on EF. A single-factor solution provided a good fit for the present five EF/learning tasks. The second model, which was hypothesized to tap more onto EF, had slightly better fit indices, X[superscript 2](5) = 1.37, p = 0.93, standardized root mean square residual (SRMR) = 0.02, root mean square error of approximation (RMSEA) = 0.00, 90% CI = [0.00-0.03], comparative fit index (CFI) = 1.00, and more even factor loadings (0.30-0.56) than the first model, X[superscript 2](5) = 4.56, p = 0.47, SRMR = 0.03, RMSEA = 0.00, 90% CI = [0.00-0.09], CFI = 1.00, factor loadings (0.20-0.74), which was hypothesized to tap more onto learning. We conclude that the present CogState sum scores can be used for studying EF/learning in healthy adult samples, but call for further research to validate these sum scores against other EF tests.