Highlights d PDGFRb cells function as initial sensors of systemic inflammation in the brain d PDGFRb cells relay the infection signal to neurons by secreting chemokine CCL2 d Col1a1 and Rgs5 subgroups of PDGFRb cells are sources of Ccl2 during early infection d PDGFRb-specific Ccl2 knockout blocked LPS-induced increase in synaptic transmission

The 12 most commonly implicated genes in this cohort and the genes with treatment options should be considered as part of the essential panel for early diagnosis of epilepsy onset, if large medical exome analyses or ES are not feasible as first-tier analysis. Genetic results are beginning to improve therapy by antiepileptic medication selections and precision medicine approaches.

Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstract

BackgroundCongenital anomalies are the leading cause of early neonatal death in neonatal intensive care units (NICUs), but the genetic causes are unclear. This study aims to investigate the genetic causes of infant deaths in a NICU in China.MethodsNewborns who died in the hospital or died within 1 week of discharge were enrolled from Children’s Hospital of Fudan University between January 1, 2015 and December 31, 2017. Whole exome sequencing was performed in all patients after death.ResultsThere were 223 deceased newborns with a median age at death of 13 days. In total, 44 (19.7%) infants were identified with a genetic finding, including 40 with single nucleotide variants (SNVs), two with CNVs and two with both SNVs and CNVs. Thirteen (31%, 13/42) patients with SNVs had medically actionable disorders based on genetic diagnosis, which included 10 genes. Multiple congenital malformation was identified as the leading genetic cause of death in NICUs with 13 newborns identified with variants in genes related to multiple congenital malformations. For newborns who died on the first day, the most common genetic cause of death was major heart defects, while metabolic disorders and respiratory failure were more common for newborns who died in the first 2 weeks.ConclusionOur study shows genetic findings among early infant deaths in NICUs and provides critical genetic information for precise genetic counselling for the families. Effective therapies enable the improvement of more than a quarter of newborns with molecular diagnoses if diagnosed in time.

ObjectivesCentral nervous system (CNS) infection has a high incidence and mortality in neonates, but conventional tests are time-consuming and have a low sensitivity. Some rare genetic diseases may have some similar clinical manifestations as CNS infection. Therefore, we aimed to evaluate the performance of metagenomic next-generation sequencing (mNGS) in diagnosing neonatal CNS infection and to explore the etiology of neonatal suspected CNS infection by combining mNGS with whole exome sequencing (WES).MethodsWe prospectively enrolled neonates with a suspected CNS infection who were admitted to the neonatal intensive care unit(NICU) from September 1, 2019, to May 31, 2020. Cerebrospinal fluid (CSF) samples collected from all patients were tested by using conventional methods and mNGS. For patients with a confirmed CNS infection and patients with an unclear clinical diagnosis, WES was performed on blood samples.ResultsEighty-eight neonatal patients were enrolled, and 101 CSF samples were collected. Fourty-three blood samples were collected for WES. mNGS showed a sample diagnostic yield of 19.8% (20/101) compared to 4.95% (5/101) for the conventional methods. In the empirical treatment group, the detection rate of mNGS was significantly higher than that of conventional methods [27% vs. 6.3%, p=0.002]. Among the 88 patients, 15 patients were etiologically diagnosed by mNGS alone, five patients were etiologically identified by WES alone, and one patient was diagnosed by both mNGS and WES. Twelve of 13 diagnoses based solely on mNGS had a likely clinical effect. Six patients diagnosed by WES also experienced clinical effect.ConclusionsFor patients with a suspected CNS infections, mNGS combined with WES might significantly improve the diagnostic rate of the etiology and effectively guide clinical strategies.