Flaviviruses cause systemic or neurotropic-encephalitic pathology in humans. The flavivirus nonstructural protein 1 (NS1) is a secreted glycoprotein involved in viral replication, immune evasion, and vascular leakage during dengue virus infection. However, the contribution of secreted NS1 from related flaviviruses to viral pathogenesis remains unknown. Here, we demonstrate that NS1 from dengue, Zika, West Nile, Japanese encephalitis, and yellow fever viruses selectively binds to and alters permeability of human endothelial cells from lung, dermis, umbilical vein, brain, and liver in vitro and causes tissue-specific vascular leakage in mice, reflecting the pathophysiology of each flavivirus. Mechanistically, each flavivirus NS1 leads to differential disruption of endothelial glycocalyx components, resulting in endothelial hyperpermeability. Our findings reveal the capacity of a secreted viral protein to modulate endothelial barrier function in a tissue-specific manner both in vitro and in vivo, potentially influencing virus dissemination and pathogenesis and providing targets for antiviral therapies and vaccine development.

Background

Preterm birth (PTB) is associated with increased infant mortality, and neurodevelopmental abnormalities among survivors. The aim of this study is to investigate temporal trends, patterns, and predictors of PTB in California from 2007 to 2016, based on the obstetric estimate of gestational age (OA).

Methods

A retrospective cohort study evaluated 435,280 PTBs from the 5,137,376 resident live births (8.5%) documented in the California Birth Statistical Master Files (BSMF) from 2007 to 2016. The outcome variable was PTB; the explanatory variables were birth year, maternal characteristics and health behaviors. Descriptive statistics and logistic regression analysis were used to identify subgroups with significant risk factors associated with PTB. Small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants were identified employing gestational age based on obstetric estimates and further classified by term and preterm births, resulting in six categories of intrauterine growth.

Results

The prevalence of PTB in California decreased from 9.0% in 2007 to 8.2% in 2014, but increased during the last 2 years, 8.4% in 2015 and 8.5% in 2016. Maternal age, education level, race and ethnicity, smoking during pregnancy, and parity were significant risk factors associated with PTB. The adjusted odds ratio (AOR) showed that women in the oldest age group (40-54 years) were almost twice as likely to experience PTB as women in the 20- to 24-year reference age group. The prevalence of PTB was 64% higher in African American women than in Caucasian women. Hispanic women showed less disparity in the prevalence of PTB based on education and socioeconomic level. The analysis of interactions between maternal characteristics and perinatal health behaviors showed that Asian women have the highest prevalence of PTB in the youngest age group (< 20 years; AOR, 1.40; 95% confidence interval (CI), 1.28-1.54). Pacific Islander, American Indian, and African American women ≥40 years of age had a greater than two-fold increase in the prevalence of PTB compared with women in the 20-24 year age group. Compared to women in the Northern and Sierra regions, women in the San Joaquin Valley were 18%, and women in the Inland Empire and San Diego regions 13% more likely to have a PTB. Women who smoked during both the first and second trimesters were 57% more likely to have a PTB than women who did not smoke. Compared to women of normal prepregnancy weight, underweight women and women in obese class III were 23 and 33% more likely to experience PTB respectively.

Conclusions

Implementation of public health initiatives focusing on reducing the prevalence of PTB should focus on women of advanced maternal age and address race, ethnic, and geographic disparities. The significance of modifiable maternal perinatal health behaviors that contribute to PTB, e.g. smoking during pregnancy and prepregnancy obesity, need to be emphasized during prenatal care.

Objective

To identify current maternal and infant predictors of infant mortality, including maternal sociodemographic and economic status, maternal perinatal smoking and obesity, mode of delivery, and infant birthweight and gestational age.

Methods

This retrospective study analyzed data from the linked birth and infant death files (birth cohort) and live births from the Birth Statistical Master files (BSMF) in California compiled by the California Department of Public Health for 2007-2015. The birth cohort study comprised 4,503,197 singleton births including 19,301 infant deaths during the nine-year study period. A subpopulation to study fetal growth consisted of 4,448,300 birth cohort records including 13,891 infant deaths.

Results

The infant mortality rate (IMR) for singleton births decreased linearly (p <0.001) from 4.68 in 2007 to 3.90 (per 1,000 live births) in 2015. However, significant disparities in IMR were uncovered in different population groups depending upon maternal sociodemographic and economic characteristics and maternal characteristics during pregnancy. Children of African American women had almost twice the risk of infant mortality when compared with children of White women (AOR 2.12; 95% CI, 1.98-2.27; p<0.001). Infants of women with Bachelor's degrees or higher were 89% less likely to die (AOR 1.89; 95% CI, 1.76-2.04; p<0.001) when compared to infants of women with education less than high school. Infants of maternal smokers were 75% more likely to die (AOR 1.75; 95% CI, 1.58-1.93; p<0.001) than infants of nonsmokers. Infants of women who were overweight and obese during pregnancy accounted for 55% of IMR over all women in the study. More than half of the infant deaths were to children of women with lower socioeconomic status; infants of WIC participants were 59% more likely to die (AOR 1.59; 95% CI, 1.52-1.67; p<0.001) than infants of non-WIC participants. With respect to infant predictors, infants born with LBW or PTB were more than six times (AOR 6.29; 95% CI, 5.90-6.70; p<0.001) and almost four times (AOR 3.95; 95% CI, 3.73-4.19; p<0.001) more likely to die than infants who had normal births, respectively. SGA and LGA infants were more than two times (AOR 2.03; 95% CI, 1.92-2.15; p<0.001) and 41% (AOR 1.41; 95% CI, 1.32-1.52; p<0.001) more likely to die than AGA infants, respectively.

Conclusions

While the overall IMR in California is declining, wide disparities in death rates persist in different groups, and these disparities are increasing. Our data indicate that maternal sociodemographic and economic factors, as well as maternal prepregnancy obesity and smoking during pregnancy, have a prominent effect on IMR though no causality can be inferred with the current data. These predictors are not typically addressed by direct medical care. Infant factors with a major effect on IMR are birthweight and gestational age-predictors that are addressed by active medical services. The highest value interventions to reduce IMR may be social and public health initiatives that mitigate disparities in sociodemographic, economic and behavioral risks for mothers.

Semantic variant primary progressive aphasia is a clinical syndrome characterized by marked semantic deficits, anterior temporal lobe atrophy and reduced connectivity within a distributed set of regions belonging to the functional network associated with semantic processing. However, to fully depict the clinical signature of semantic variant primary progressive aphasia, it is necessary to also characterize preserved neural networks and linguistic abilities, such as those subserving speech production. In this case-control observational study, we employed whole-brain seed-based connectivity on task-free MRI data of 32 semantic variant primary progressive aphasia patients and 46 healthy controls to investigate the functional connectivity of the speech production network and its relationship with the underlying grey matter. We investigated brain-behaviour correlations with speech fluency measures collected through clinical tests (verbal agility) and connected speech (speech rate and articulation rate). As a control network, we also investigated functional connectivity within the affected semantic network. Patients presented with increased connectivity in the speech production network between left inferior frontal and supramarginal regions, independent of underlying grey matter volume. In semantic variant primary progressive aphasia patients, preserved (verbal agility) and increased (articulation rate) speech fluency measures correlated with increased connectivity between inferior frontal and supramarginal regions. As expected, patients demonstrated decreased functional connectivity in the semantic network (dependent on the underlying grey matter atrophy) associated with average nouns' age of acquisition during connected speech. Collectively, these results provide a compelling model for studying compensation mechanisms in response to disease that might inform the design of future rehabilitation strategies in semantic variant primary progressive aphasia.

The continued emergence of SARS-CoV-2 variants is one of several factors that may cause false-negative viral PCR test results. Such tests are also susceptible to false-positive results due to trace contamination from high viral titer samples. Host immune response markers provide an orthogonal indication of infection that can mitigate these concerns when combined with direct viral detection. Here, we leverage nasopharyngeal swab RNA-seq data from patients with COVID-19, other viral acute respiratory illnesses, and nonviral conditions (n = 318) to develop support vector machine classifiers that rely on a parsimonious 2-gene host signature to diagnose COVID-19. We find that optimal classifiers include an interferon-stimulated gene that is strongly induced in COVID-19 compared with nonviral conditions, such as IFI6, and a second immune-response gene that is more strongly induced in other viral infections, such as GBP5. The IFI6+GBP5 classifier achieves an area under the receiver operating characteristic curve (AUC) greater than 0.9 when evaluated on an independent RNA-seq cohort (n = 553). We further provide proof-of-concept demonstration that the classifier can be implemented in a clinically relevant RT-qPCR assay. Finally, we show that its performance is robust across common SARS-CoV-2 variants and is unaffected by cross-contamination, demonstrating its utility for improved accuracy of COVID-19 diagnostics. IMPORTANCE In this work, we study upper respiratory tract gene expression to develop and validate a 2-gene host-based COVID-19 diagnostic classifier and then demonstrate its implementation in a clinically practical qPCR assay. We find that the host classifier has utility for mitigating false-negative results, for example due to SARS-CoV-2 variants harboring mutations at primer target sites, and for mitigating false-positive viral PCR results due to laboratory cross-contamination. Both types of error carry serious consequences of either unrecognized viral transmission or unnecessary isolation and contact tracing. This work is directly relevant to the ongoing COVID-19 pandemic given the continued emergence of viral variants and the continued challenges of false-positive PCR assays. It also suggests the feasibility of pan-respiratory virus host-based diagnostics that would have value in congregate settings, such as hospitals and nursing homes, where unrecognized respiratory viral transmission is of particular concern.

Objective

To determine recent trends in maternal prepregnancy body mass index (BMI) and to quantify its association with birth and maternal outcomes.

Methods

A population-based retrospective cohort study included resident women with singleton births in the California Birth Statistical Master Files (BSMF) database from 2007 to 2016. There were 4,621,082 women included out of 5,054,968 women registered in the database. 433,886 (8.6%) women were excluded due to invalid or missing information for BMI. Exposures were underweight (BMI < 18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥ 30 kg/m2) at the onset of pregnancy. Obesity was subcategorized into class I (30.0-34.9 kg/m2), class II (35.0-39.9 kg/m2), and class III (≥ 40 kg/m2), while adverse outcomes examined were low birth weight (LBW), very low birth weight (VLBW), macrosomic births, preterm birth (PTB), very preterm birth (VPTB), small-for-gestational-age birth (SGA), large-for-gestational-age birth (LGA), and cesarean delivery (CD). Descriptive analysis, simple linear regression, and multivariate logistic regression were performed, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) for associations were estimated.

Results

Over the ten-year study period, the prevalence of underweight and normal weight women at time of birth declined by 10.6% and 9.7%, respectively, while the prevalence of overweight and obese increased by 4.3% and 22.9%, respectively. VLBW increased significantly with increasing BMI, by 24% in overweight women and by 76% in women with class III obesity from 2007 to 2016. Women with class III obesity also had a significant increase in macrosomic birth (170%) and were more likely to deliver PTB (33%), VPTB (66%), LGA (231%), and CD (208%) than women with a normal BMI. However, obese women were less likely to have SGA infants; underweight women were 51% more likely to have SGA infants than women with a normal BMI.

Conclusions

In California from 2007 to 2016, there was a declining trend in women with prepregnancy normal weight, and a rising trend in overweight and obese women, particularly obesity class III. Both extremes of prepregnancy BMI were associated with an increased incidence of adverse neonatal outcomes; however, the worse outcomes were prominent in those women classified as obese.

Background and objectives

Progressive focal anterior temporal lobe (ATL) neurodegeneration has been historically called semantic dementia. More recently, semantic variant primary progressive aphasia (svPPA) and semantic behavioral variant frontotemporal dementia (sbvFTD) have been linked with predominant left and right ATL neurodegeneration, respectively. Nonetheless, clinical tools for an accurate diagnosis of sbvFTD are still lacking. Expressive prosody refers to the modulation of pitch, loudness, tempo, and quality of voice used to convey emotional and linguistic information and has been linked to bilateral but right-predominant frontotemporal functioning. Changes in expressive prosody can be detected with semiautomated methods and could represent a useful diagnostic marker of socioemotional functioning in sbvFTD.

Methods

Participants underwent a comprehensive neuropsychological and language evaluation and a 3T MRI at the University of California San Francisco. Each participant provided a verbal description of the picnic scene from the Western Aphasia Battery. The fundamental frequency (f0) range, an acoustic measure of pitch variability, was extracted for each participant. We compared the f0 range between groups and investigated associations with an informant-rated measure of empathy, a facial emotion labeling task, and gray matter (GM) volumes using voxel-based morphometry.

Results

Twenty-eight patients with svPPA, 18 with sbvFTD, and 18 healthy controls (HCs) were included. f0 range was significantly different across groups: patients with sbvFTD showed reduced f0 range in comparison with both patients with svPPA (mean difference of -1.4 ± 2.4 semitones; 95% CI -2.4 to -0.4]; p < 0.005) and HCs (mean difference of -1.9 ± 3.0 semitones; 95% CI -3.0 to -0.7]; p < 0.001). A higher f0 range was correlated with a greater informant-rated empathy (r = 0.355; p ≤ 0.05), but not facial emotion labeling. Finally, the lower f0 range was correlated with lower GM volume in the right superior temporal gyrus, encompassing anterior and posterior portions (p < 0.05 FWE cluster corrected).

Discussion

Expressive prosody may be a useful clinical marker of sbvFTD. Reduced empathy is a core symptom in sbvFTD; the present results extend this to prosody, a core component of social interaction, at the intersection of speech and emotion. They also inform the long-standing debate on the lateralization of expressive prosody in the brain, highlighting the critical role of the right superior temporal lobe.

Primary progressive aphasia (PPA) is a clinical syndrome in which patients progressively lose speech and language abilities. Three variants are recognized: logopenic (lvPPA), associated with phonology and/or short-term verbal memory deficits accompanied by left temporo-parietal atrophy; semantic (svPPA), associated with semantic deficits and anterior temporal lobe (ATL) atrophy; non-fluent (nfvPPA) associated with grammar and/or speech-motor deficits and inferior frontal gyrus (IFG) atrophy. Here, we set out to investigate whether the three variants of PPA can be dissociated based on error patterns in a single language task. We recruited 21 lvPPA, 28 svPPA, and 24 nfvPPA patients, together with 31 healthy controls, and analyzed their performance on an auditory noun-to-verb generation task, which requires auditory analysis of the input, access to and selection of relevant lexical and semantic knowledge, as well as preparation and execution of speech. Task accuracy differed across the three variants and controls, with lvPPA and nfvPPA having the lowest and highest accuracy, respectively. Critically, machine learning analysis of the different error types yielded above-chance classification of patients into their corresponding group. An analysis of the error types revealed clear variant-specific effects: lvPPA patients produced the highest percentage of "not-a-verb" responses and the highest number of semantically related nouns (production of baseball instead of throw to noun ball); in contrast, svPPA patients produced the highest percentage of "unrelated verb" responses and the highest number of light verbs (production of take instead of throw to noun ball). Taken together, our findings indicate that error patterns in an auditory verb generation task are associated with the breakdown of different neurocognitive mechanisms across PPA variants. Specifically, they corroborate the link between temporo-parietal regions with lexical processing, as well as ATL with semantic processes. These findings illustrate how the analysis of pattern of responses can help PPA phenotyping and heighten diagnostic sensitivity, while providing insights on the neural correlates of different components of language.

Morphosyntactic assessments are important for characterizing individuals with nonfluent/agrammatic variant primary progressive aphasia (nfvPPA). Yet, standard tests are subject to examiner bias and often fail to differentiate between nfvPPA and logopenic variant PPA (lvPPA). Moreover, relevant neural signatures remain underexplored. Here, we leverage natural language processing tools to automatically capture morphosyntactic disturbances and their neuroanatomical correlates in 35 individuals with nfvPPA relative to 10 healthy controls (HC) and 26 individuals with lvPPA. Participants described a picture, and ensuing transcripts were analyzed via part-of-speech tagging to extract sentence-related features (e.g., subordinating and coordinating conjunctions), verbal-related features (e.g., tense markers), and nominal-related features (e.g., subjective and possessive pronouns). Gradient boosting machines were used to classify between groups using all features. We identified the most discriminant morphosyntactic marker via a feature importance algorithm and examined its neural correlates via voxel-based morphometry. Individuals with nfvPPA produced fewer morphosyntactic elements than the other two groups. Such features robustly discriminated them from both individuals with lvPPA and HCs with an AUC of .95 and .82, respectively. The most discriminatory feature corresponded to subordinating conjunctions was correlated with cortical atrophy within the left posterior inferior frontal gyrus across groups (p_FWE < .05). Automated morphosyntactic analysis can efficiently differentiate nfvPPA from lvPPA. Also, the most sensitive morphosyntactic markers correlate with a core atrophy region of nfvPPA. Our approach, thus, can contribute to a key challenge in PPA diagnosis.

We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.