Zac1 and the Imprinted Gene Network program juvenile NAFLD in response to maternal metabolic syndrome.

BACKGROUND AND AIMS: Within the next decade, NAFLD is predicted to become the most prevalent cause of childhood liver failure in developed countries. Predisposition to juvenile NAFLD can be programmed during early life in response to maternal metabolic syndrome (MetS), but the underlying mechanisms are poorly understood. We hypothesized that imprinted genes, defined by expression from a single parental allele, play a key role in maternal MetS-induced NAFLD, due to their susceptibility to environmental stressors and their functions in liver homeostasis. We aimed to test this hypothesis and determine the critical periods of susceptibility to maternal MetS. APPROACH AND RESULTS: We established a mouse model to compare the effects of MetS during prenatal and postnatal development on NAFLD. Postnatal but not prenatal MetS exposure is associated with histological, biochemical, and molecular signatures of hepatic steatosis and fibrosis in juvenile mice. Using RNA sequencing, we show that the Imprinted Gene Network (IGN), including its regulator Zac1, is up-regulated and overrepresented among differentially expressed genes, consistent with a role in maternal MetS-induced NAFLD. In support of this, activation of the IGN in cultured hepatoma cells by overexpressing Zac1 is sufficient to induce signatures of profibrogenic transformation. Using chromatin immunoprecipitation, we demonstrate that Zac1 binds the TGF-ß1 and COL6A2 promoters, forming a direct pathway between imprinted genes and well-characterized pathophysiological mechanisms of NAFLD. Finally, we show that hepatocyte-specific overexpression of Zac1 is sufficient to drive fibrosis in vivo. CONCLUSIONS: Our findings identify a pathway linking maternal MetS exposure during postnatal development to the programming of juvenile NAFLD, and provide support for the hypothesis that imprinted genes play a central role in metabolic disease programming.

Lyme Disease Under-Ascertainment During the COVID-19 Pandemic in the United States: Retrospective Study.

Background: The COVID-19 pandemic resulted in a massive disruption in access to care and thus passive, hospital- and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace utilization and outdoor activities, putting more people into contact with potential vectors and associated vector-borne diseases. Lyme disease reporting relies on passive surveillance systems, which were likely disrupted by changes in health care-seeking behavior during the pandemic. Objective: This study aimed to quantify the likely under-ascertainment of cases of Lyme disease during the COVID-19 pandemic in the United States and North Carolina. Methods: We fitted publicly available, reported Lyme disease cases for both the United States and North Carolina prior to the year 2020 to predict the number of anticipated Lyme disease cases in the absence of the pandemic using a Bayesian modeling approach. We then compared the ratio of reported cases divided by the predicted cases to quantify the number of likely under-ascertained cases. We then fitted geospatial models to further quantify the spatial distribution of the likely under-ascertained cases and characterize spatial dynamics at local scales. Results: Reported cases of Lyme Disease were lower in 2020 in both the United States and North Carolina than prior years. Our findings suggest that roughly 14,200 cases may have gone undetected given historical trends prior to the pandemic. Furthermore, we estimate that only 40% to 80% of Lyme diseases cases were detected in North Carolina between August 2020 and February 2021, the peak months of the COVID-19 pandemic in both the United States and North Carolina, with prior ascertainment rates returning to normal levels after this period. Our models suggest both strong temporal effects with higher numbers of cases reported in the summer months as well as strong geographic effects. Conclusions: Ascertainment rates of Lyme disease were highly variable during the pandemic period both at national and subnational scales. Our findings suggest that there may have been a substantial number of unreported Lyme disease cases despite an apparent increase in greenspace utilization. The use of counterfactual modeling using spatial and historical trends can provide insight into the likely numbers of missed cases. Variable ascertainment of cases has implications for passive surveillance programs, especially in the trending of disease morbidity and outbreak detection, suggesting that other methods may be appropriate for outbreak detection during disturbances to these passive surveillance systems.

Neurosurgery Influences and X: A Social Media Analysis.

BACKGROUND: There exists a complex and ever-evolving relationship between social media and medicine. This study investigates the usage of X (formerly Twitter) among neurosurgeons and explores how virtual engagement potentially impacts this specialty. METHODS: The researchers examined X posts from the top fifty influential neurosurgeons over 6 months. Demographics and practice information were collected. Posts were categorized into 9 predetermined coding definitions. Descriptive statistics were used to summarize user characteristics. χ2 tests and two-tailed T-tests were employed to examine patterns of posting behavior. RESULTS: Most influencers practiced in an academic setting (89%) and 43% of them were age fifty or older. Only 15% identified as female. Cerebrovascular subspecialists accounted for 39% of the cohort. Reposting was the most popular type of posting, constituting 61% of all posts. The most common postcategory observed was "Professional Events" (31%), while "Patient Education" was the least common (0.8%). Private practice and general neurosurgeons infrequently posted about "Professional Events" (5.1%, P < 0.01 and 3.2%, P < 0.01, respectively). "Personal Thoughts" constituted the second most common category, with a notable increase among users younger than 50 (25%, P < 0.01), individuals who identified as female (62%, P < 0.01), those in private practice (69%, P < 0.01), and general neurosurgeons (86%, P < 0.01). CONCLUSIONS: Neurosurgeons of all ages use X to advance their careers and stay updated. However, the utilization of this influential platform likely varies depending on the current practice setting and individual career goals. Neurosurgeons on X appear to have the greatest influence within an academic context, particularly when promoting professional events.