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The current study examined associations between various dimensions of medical fear (e.g., blood, mutilation, sharp objects, injection/blood draws, examinations/symptoms) and perceptions of provider trust, provider empathy, healthcare system mistrust, and attitudes toward medical care-seeking. Additionally, we explored the associations between different dimensions of medical fear and medical care engagement. A convenience sample of 479 young adults (18-26 years) attending a large, urban Mid-Atlantic university completed a cross-sectional online survey during the fall of 2022 assessing medical fears, provider trust, perceptions of provider empathy, medical care-seeking attitudes, and medical mistrust. Participants with medical fears (n = 211) answered an additional open-ended question regarding medical care engagement. Multiple regression models were used to examine associations between medical fear dimensions and outcome measures. A binary logistic regression was performed to examine the likelihood of health care engagement based on different medical fear dimensions. Statistical significance was set at p < .05. Participants identified as 75.8% female (n = 363), 47.0% White (n = 219), and 25.7% (n = 122) reported having a chronic illness. Increasing levels of mutilation fear were significantly associated with lower ratings of provider trust (β = -.286, p < .001) and empathy (β = -.172, p = .010), as well as more medical mistrust (β = .227, p < .001). None of the five medical fear dimensions were significantly associated with medical engagement. Findings highlight the role of mutilation fears in patient-provider relationships and views about the healthcare system in general. While these fears were not associated with medical care avoidance in our study, their association with patient-provider relationships may have implications for adherence to medical recommendations and health outcomes. Patient-centered collaborative care that takes medical fears into consideration may help strengthen patient-provider relationships and mitigate potential negative health outcomes.

The application of next-generation sequencing to study congenital heart disease (CHD) is increasingly providing new insights into the causes and mechanisms of this prevalent birth anomaly. Whole-exome sequencing analysis identifies damaging gene variants altering single or contiguous nucleotides that are assigned pathogenicity based on statistical analyses of families and cohorts with CHD, high expression in the developing heart and depletion of damaging protein-coding variants in the general population. Gene classes fulfilling these criteria are enriched in patients with CHD and extracardiac abnormalities, evidencing shared pathways in organogenesis. Developmental single-cell transcriptomic data demonstrate the expression of CHD-associated genes in particular cell lineages, and emerging insights indicate that genetic variants perturb multicellular interactions that are crucial for cardiogenesis. Whole-genome sequencing analyses extend these observations, identifying non-coding variants that influence the expression of genes associated with CHD and contribute to the estimated ~55% of unexplained cases of CHD. These approaches combined with the assessment of common and mosaic genetic variants have provided a more complete knowledge of the causes and mechanisms of CHD. Such advances provide knowledge to inform the clinical care of patients with CHD or other birth defects and deepen our understanding of the complexity of human development. In this Review, we highlight known and candidate CHD-associated human genes and discuss how the integration of advances in developmental biology research can provide new insights into the genetic contributions to CHD.In this Review, Seidman and colleagues summarize the progress over the past 10 years with regard to genomic discoveries and strategies at the forefront of research on congenital heart disease (CHD), highlighting definitive and candidate genes associated with CHD in humans and the potential of integrating technological advances to gain new insights into the genetic architecture of CHD.

To maintain its development, the growing fetus is directly dependent on the placenta, an organ that acts as both a modulator and mediator. As an essential component of pregnancy that is derived from both maternal and fetal tissues, the placenta facilitates the passage of all oxygen and nutrients from the expecting parent to their fetuses. Further, the placenta conveys multiple impacts of the maternal environment to the growing fetus. The timing of placental development parallels that of the fetal cardiovascular system, and placental anomalies are implicated as a potential cause of congenital heart disease. For example, congenital heart disease is more common in pregnancies complicated by maternal preeclampsia, a condition characterized by placental dysfunction. Given the placenta’s intermediary links to the maternal environment and fetal health outcomes, it is an emerging focus of evolutionary medicine, which seeks to understand how interactions between humans and the environment affect our biology and give rise to disease. The present review provides an overview of the evolutionary and developmental courses of the placenta as well as their implications on infant health.

MicroRNAs (miRNAs) are regulators of myriad cellular events, but evidence for a single miRNA that can efficiently differentiate multipotent stem cells into a specific lineage or regulate direct reprogramming of cells into an alternative cell fate has been elusive. Here we show that miR-145 and miR-143 are co-transcribed in multipotent murine cardiac progenitors before becoming localized to smooth muscle cells, including neural crest stem-cell-derived vascular smooth muscle cells. miR-145 and miR-143 were direct transcriptional targets of serum response factor, myocardin and Nkx2-5 (NK2 transcription factor related, locus 5) and were downregulated in injured or atherosclerotic vessels containing proliferating, less differentiated smooth muscle cells. miR-145 was necessary for myocardin-induced reprogramming of adult fibroblasts into smooth muscle cells and sufficient to induce differentiation of multipotent neural crest stem cells into vascular smooth muscle. Furthermore, miR-145 and miR-143 cooperatively targeted a network of transcription factors, including Klf4 (Kruppel-like factor 4), myocardin and Elk-1 (ELK1, member of ETS oncogene family), to promote differentiation and repress proliferation of smooth muscle cells. These findings demonstrate that miR-145 can direct the smooth muscle fate and that miR-145 and miR-143 function to regulate the quiescent versus proliferative phenotype of smooth muscle cells. Muscle cell fate and plasticity Two microRNAs, miR-145 and miR-143, have been shown to be present in multipotent cardiac progenitor cells in the mouse embryo. miR-145 is necessary for myocardin-induced reprogramming of adult fibroblasts into smooth muscle cells, and sufficient to induce differentiation of neural crest stem cells into vascular smooth muscle cells (VSMCs). Together, miR-145 and miR-143 target a network of transcription factors to promote differentiation and repress proliferation of smooth muscle cells. These findings provide evidence that miRNAs can act as switches to direct cells to a specific differentiated lineage. In addition, the role of miR-145 and miR-143 in regulating the differentiated versus proliferative phenotype of VSMCs may be relevant in many vascular diseases, as VSMC oscillation between these two states contributes to vascular occlusion. Evidence for a single microRNA (miRNA) that can efficiently differentiate multipotent stem cells into a specific lineage or regulate direct reprogramming of cells into an alternative cell fate has been elusive. Two miRNAs, miR-145 and miR-143, are now shown to be co-transcribed in multipotent cardiac progenitors before becoming localized to smooth muscle cells. miR-145 was found to be necessary for myocardin-induced reprogramming of adult fibroblasts and sufficient to induce differentiation of multipotent neural crest stem cells.

Although DNA methylation is the best characterized epigenetic mark, the mechanism by which it is targeted to specific regions in the genome remains unclear. Recent studies have revealed that local DNA methylation profiles might be dictated by cis- regulatory DNA sequences that mainly operate via DNA-binding factors. Consistent with this finding, we have recently shown that disruption of CTCF-binding sites by rare single nucleotide variants (SNVs) can underlie cis -linked DNA methylation changes in patients with congenital anomalies. These data raise the hypothesis that rare genetic variation at transcription factor binding sites (TFBSs) might contribute to local DNA methylation patterning. In this work, by combining blood genome-wide DNA methylation profiles, whole genome sequencing-derived SNVs from 247 unrelated individuals along with 133 predicted TFBS motifs derived from ENCODE ChIP-Seq data, we observed an association between the disruption of binding sites for multiple TFs by rare SNVs and extreme DNA methylation values at both local and, to a lesser extent, distant CpGs. While the majority of these changes affected only single CpGs, 24% were associated with multiple outlier CpGs within ±1kb of the disrupted TFBS. Interestingly, disruption of functionally constrained sites within TF motifs lead to larger DNA methylation changes at nearby CpG sites. Altogether, these findings suggest that rare SNVs at TFBS negatively influence TF-DNA binding, which can lead to an altered local DNA methylation profile. Furthermore, subsequent integration of DNA methylation and RNA-Seq profiles from cardiac tissues enabled us to observe an association between rare SNV-directed DNA methylation and outlier expression of nearby genes. In conclusion, our findings not only provide insights into the effect of rare genetic variation at TFBS on shaping local DNA methylation and its consequences on genome regulation, but also provide a rationale to incorporate DNA methylation data to interpret the functional role of rare variants.

Background The Covid-19 pandemic initiated an enduring shift in working patterns, with many employees now working at home (w@h). This shift has exacerbated existing high levels of occupational sedentary behaviour (SB) in office workers, which is a recognised risk to health and well-being. This study aimed to use the Capability-Opportunity-Motivation-Behaviour (COM-B) model to better understand both employees’ SB, and line managers behaviour to assist employees to reduce SB when w@h, and identify how employees can best be supported to reduce SB. Methods Three online focus groups with employees aged 18–40 working in desk-based roles (e.g. administrative / sales / customer services) ( n  = 21), and three with line managers ( n  = 21) were conducted. The focus groups facilitated discussion regarding participants’ current behaviour, what impacts it, and what could be done to reduce employee SB when w@h. The focus group data were thematically analysed guided by the COM-B framework to understand influences on behaviour, and to identify promising intervention strategies. Results Most participants recognised that w@h had elevated employee occupational SB, and line managers reported the importance of supporting employees to manage their workload, and encouraging and modelling taking breaks. There were multiple influences on both employee and line manager behaviour with capability, opportunity and motivation all perceived as influential, although not equally. For example, a major theme related to the reduced physical opportunities for employees to reduce their SB when w@h, including blurred work-life boundaries. Changes in physical opportunities also made supporting employees challenging for line managers. Additionally, the w@h environment included unique social opportunities that negatively impacted the behaviour of both groups, including an expectation to always be present online, and social norms. A range of strategies for reducing SB when w@h at both individual and organisational level were suggested. Conclusions It was evident that SB when w@h is influenced by a range of factors, and therefore multi-component intervention strategies are likely to be most effective in reducing SB. Future intervention research is a priority to evaluate and refine strategies, and inform w@h guidance to protect both the short-term and long-term health consequences of elevated SB for those who continue to w@h.

There are established associations between advanced paternal age and offspring risk for psychiatric and developmental disorders. These are commonly attributed to genetic mutations, especially de novo single nucleotide variants (dnSNVs), that accumulate with increasing paternal age. However, the actual magnitude of risk from such mutations in the male germline is unknown. Quantifying this risk would clarify the clinical significance of delayed paternity. Using parent-child trio whole-exome-sequencing data, we estimate the relationship between paternal-age-related dnSNVs and risk for five disorders: autism spectrum disorder (ASD), congenital heart disease, neurodevelopmental disorders with epilepsy, intellectual disability and schizophrenia (SCZ). Using Danish registry data, we investigate whether epidemiologic associations between each disorder and older fatherhood are consistent with the estimated role of dnSNVs. We find that paternal-age-related dnSNVs confer a small amount of risk for these disorders. For ASD and SCZ, epidemiologic associations with delayed paternity reflect factors that may not increase with age. Advanced paternal age associates with increased risk for psychiatric and developmental disorders in offspring. Here, Taylor et al. utilize parent-child trio exome sequencing data sets to estimate the contribution of paternal age-related de novo mutations to multiple disorders, including heart disease and schizophrenia.

Although weekend recovery sleep is common, the physiological responses to weekend recovery sleep are not fully elucidated. Identifying molecular biomarkers that represent adequate versus insufficient sleep could help advance our understanding of weekend recovery sleep. Here, we identified potential molecular biomarkers of insufficient sleep and defined the impact of weekend recovery sleep on these biomarkers using metabolomics in a randomized controlled trial. Healthy adults (n = 34) were randomized into three groups: control (CON: 9-h sleep opportunities); sleep restriction (SR: 5-h sleep opportunities); or weekend recovery (WR: simulated workweek of 5-h sleep opportunities followed by ad libitum weekend recovery sleep and then 2 days with 5-h sleep opportunities). Blood for metabolomics was collected on the simulated Monday immediately following the weekend. Nine machine learning models, including a machine learning ensemble, were built to classify samples from SR versus CON. Notably, SR showed decreased glycerophospholipids and sphingolipids versus CON. The machine learning ensemble showed the highest G-mean performance and classified 50% of the WR samples as insufficient sleep. Our findings show insufficient sleep and recovery sleep influence the plasma metabolome and suggest more than one weekend of recovery sleep may be necessary for the identified biomarkers to return to healthy adequate sleep levels.

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD ( n  = 2,238 DNVs) compared to controls ( n  = 4,177; P  = 8.7 × 10 −4 ). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P  = 1 × 10 −5 ). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1–5.0, P  = 5.4 × 10 −3 ). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1–1.2, P  = 8.8 × 10 −5 ). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs. Computational analyses integrating whole-genome sequencing, cardiac epigenomic data and RNA-binding-protein data identify a role for noncoding de novo mutations in congenital heart disease.

Rare coding mutations cause ∼45% of congenital heart disease (CHD). Noncoding mutations that perturb cis -regulatory elements (CREs) likely contribute to the remaining cases, but their identification has been problematic. Using a lentiviral massively parallel reporter assay (lentiMPRA) in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), we functionally evaluated 6,590 noncoding de novo variants (ncDNVs) prioritized from the whole-genome sequencing of 750 CHD trios. A total of 403 ncDNVs substantially affected cardiac CRE activity. A majority increased enhancer activity, often at regions with undetectable reference sequence activity. Of ten DNVs tested by introduction into their native genomic context, four altered the expression of neighboring genes and iPSC-CM transcriptional state. To prioritize future DNVs for functional testing, we used the MPRA data to develop a regression model, EpiCard. Analysis of an independent CHD cohort by EpiCard found enrichment of DNVs. Together, we developed a scalable system to measure the effect of ncDNVs on CRE activity and deployed it to systematically assess the contribution of ncDNVs to CHD. Lentiviral massively parallel reporter assay (lentiMPRA) analysis of cardiac cis -regulatory elements characterizes the effects of noncoding de novo variants identified in congenital heart disease. EpiCard is a model for variant prioritization.