Recurrent Potent Human Neutralizing Antibodies to Zika Virus in Brazil and Mexico.

Antibodies to Zika virus (ZIKV) can be protective. To examine the antibody response in individuals who develop high titers of anti-ZIKV antibodies, we screened cohorts in Brazil and Mexico for ZIKV envelope domain III (ZEDIII) binding and neutralization. We find that serologic reactivity to dengue 1 virus (DENV1) EDIII before ZIKV exposure is associated with increased ZIKV neutralizing titers after exposure. Antibody cloning shows that donors with high ZIKV neutralizing antibody titers have expanded clones of memory B cells that express the same immunoglobulin VH3-23/VK1-5 genes. These recurring antibodies cross-react with DENV1, but not other flaviviruses, neutralize both DENV1 and ZIKV, and protect mice against ZIKV challenge. Structural analyses reveal the mechanism of recognition of the ZEDIII lateral ridge by VH3-23/VK1-5 antibodies. Serologic testing shows that antibodies to this region correlate with serum neutralizing activity to ZIKV. Thus, high neutralizing responses to ZIKV are associated with pre-existing reactivity to DENV1 in humans.

Molecular landscapes of human hippocampal immature neurons across lifespan.

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity and unique brain functions in rodents1,2 and are dysregulated in multiple human neurological disorders3-5. Little is known about the molecular characteristics of adult human hippocampal imGCs, and even their existence is under debate1,6-8. Here we performed single-nucleus RNA sequencing aided by a validated machine learning-based analytic approach to identify imGCs and quantify their abundance in the human hippocampus at different stages across the lifespan. We identified common molecular hallmarks of human imGCs across the lifespan and observed age-dependent transcriptional dynamics in human imGCs that suggest changes in cellular functionality, niche interactions and disease relevance, that differ from those in mice9. We also found a decreased number of imGCs with altered gene expression in Alzheimer's disease. Finally, we demonstrated the capacity for neurogenesis in the adult human hippocampus with the presence of rare dentate granule cell fate-specific proliferating neural progenitors and with cultured surgical specimens. Together, our findings suggest the presence of a substantial number of imGCs in the adult human hippocampus via low-frequency de novo generation and protracted maturation, and our study reveals their molecular properties across the lifespan and in Alzheimer's disease.

Interplay between DISC1 and GABA signaling regulates neurogenesis in mice and risk for schizophrenia.

How extrinsic stimuli and intrinsic factors interact to regulate continuous neurogenesis in the postnatal mammalian brain is unknown. Here we show that regulation of dendritic development of newborn neurons by Disrupted-in-Schizophrenia 1 (DISC1) during adult hippocampal neurogenesis requires neurotransmitter GABA-induced, NKCC1-dependent depolarization through a convergence onto the AKT-mTOR pathway. In contrast, DISC1 fails to modulate early-postnatal hippocampal neurogenesis when conversion of GABA-induced depolarization to hyperpolarization is accelerated. Extending the period of GABA-induced depolarization or maternal deprivation stress restores DISC1-dependent dendritic regulation through mTOR pathway during early-postnatal hippocampal neurogenesis. Furthermore, DISC1 and NKCC1 interact epistatically to affect risk for schizophrenia in two independent case control studies. Our study uncovers an interplay between intrinsic DISC1 and extrinsic GABA signaling, two schizophrenia susceptibility pathways, in controlling neurogenesis and suggests critical roles of developmental tempo and experience in manifesting the impact of susceptibility genes on neuronal development and risk for mental disorders.

Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia.

The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk-(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia.

Changes in patterns of age-related network connectivity are associated with risk for schizophrenia.

Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in first-degree relatives of SCZ patients mostly including unaffected siblings (SIB) with neurotypical controls (NC) at the same age stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Two of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.05). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlates with genetic risk for SCZ and is detectable with MRI in young participants.

Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance.

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Estimated population-level impact of pneumococcal conjugate vaccines against all-cause pneumonia mortality among unvaccinated age groups in five Latin American countries.

BACKGROUND: Pneumococcal conjugate vaccines (PCVs) provide strong direct protection in children, while limited data are available on their indirect effect on mortality among older age groups. This multi-country study aimed to assess the population-level impact of pediatric PCVs on all-cause pneumonia mortality among ≥5 years of age, and invasive pneumococcal disease (IPD) cases in Chile. METHODS: Demographic and mortality data from Argentina, Brazil, Chile, Colombia, and Mexico were collected considering the ≥ 5-year-old population, from 2000-2019, with 1,795,789 deaths due to all-cause pneumonia. IPD cases in Chile were also evaluated. Time series models were employed to evaluate changes in all-cause pneumonia deaths during the post-vaccination period, with other causes of death used as synthetic controls for unrelated temporal trends. RESULTS: No significant change in death rates due to all-cause pneumonia was detected following PCV introduction among most age groups and countries. The proportion of IPD cases caused by vaccine serotypes decreased from 29% (2012) to 6% (2022) among ≥65 years in Chile. DISCUSSION: While an effect of PCV against pneumonia deaths (a broad clinical definition that may not be specific enough to measure indirect effects) was not detected, evidence of indirect PCV impact was observed among vaccine-type-specific IPD cases.

Orthogonal approaches required to measure proteasome composition and activity in mammalian brain tissue.

Proteasomes are large macromolecular complexes with multiple distinct catalytic activities that are each vital to human brain health and disease. Despite their importance, standardized approaches to investigate proteasomes have not been universally adapted. Here, we describe pitfalls and define straightforward orthogonal biochemical approaches essential to measure and understand changes in proteasome composition and activity in the mammalian central nervous system. Through our experimentation in the mammalian brain, we determined an abundance of catalytically active proteasomes exist with and without a 19S cap(s), the regulatory particle essential for ubiquitin-dependent degradation. Moreover, we learned that in-cell measurements using activity-based probes (ABPs) are more sensitive in determining the available activity of the 20S proteasome without the 19S cap and in measuring individual catalytic subunit activities of each ß subunit within all neuronal proteasomes. Subsequently, applying these tools to human brain samples, we were surprised to find that post-mortem tissue retained little to no 19S-capped proteasome, regardless of age, sex, or disease state. In comparing brain tissues (parahippocampal gyrus) from patients with Alzheimer's disease (AD) and unaffected individuals, the available 20S proteasome activity was significantly elevated in severe cases of AD, an observation not previously noted. Taken together, our study establishes standardized approaches for the comprehensive investigation of proteasomes in mammalian brain tissue, and we reveal new insight into brain proteasome biology.

Incorporating Efficacy Data from Initial Trials Into Subsequent Evaluations: Application to Vaccines Against Respiratory Syncytial Virus.

BACKGROUND: When a randomized controlled trial fails to demonstrate statistically significant efficacy against the primary endpoint, a potentially costly new trial would need to be conducted to receive licensure. Incorporating data from previous trials might allow for more efficient follow-up trials to demonstrate efficacy, speeding the availability of effective vaccines. METHODS: Based on the outcomes from a failed trial of a maternal vaccine against respiratory syncytial virus (RSV), we simulated data for a new Bayesian group-sequential trial. We analyzed the data either ignoring data from the previous trial (i.e., weakly informative prior distributions) or using prior distributions incorporating the historical data into the analysis. We evaluated scenarios where efficacy in the new trial was the same, greater than, or less than that in the original trial. For each scenario, we evaluated the statistical power and type I error rate for estimating the vaccine effect following interim analyses. RESULTS: When we used a stringent threshold to control the type I error rate, analyses incorporating historical data had a small advantage over trials that did not. If control of type I error is less important (e.g., in a postlicensure evaluation), the incorporation of historical data can provide a substantial boost in efficiency. CONCLUSIONS: Due to the need to control the type I error rate in trials used to license a vaccine, incorporating historical data provides little additional benefit in terms of stopping the trial early. However, these statistical approaches could be promising in evaluations that use real-world evidence following licensure.

Hypertension Control During the Coronavirus Disease 2019 Pandemic: A Cohort Study Among US Veterans.

DESIGN: Retrospective cohort study. OBJECTIVE: We sought to examine whether disruptions in follow-up intervals contributed to hypertension control. BACKGROUND: Disruptions in health care were widespread during the coronavirus disease 2019 pandemic. PATIENTS AND METHODS: We identified a cohort of individuals with hypertension in both prepandemic (March 2019-February 2020) and pandemic periods (March 2020-February 2022) in the Veterans Health Administration. First, we calculated follow-up intervals between the last prepandemic and first pandemic blood pressure measurement during a primary care clinic visit, and between measurements in the prepandemic period. Next, we estimated the association between the maintenance of (or achieving) hypertension control and the period using generalized estimating equations. We assessed associations between follow-up interval and control separately for periods. Finally, we evaluated the interaction between period and follow-up length. RESULTS: A total of 1,648,424 individuals met the study inclusion criteria. Among individuals with controlled hypertension, the likelihood of maintaining control was lower during the pandemic versus the prepandemic (relative risk: 0.93; 95% CI: 0.93, 0.93). Longer follow-up intervals were associated with a decreasing likelihood of maintaining controlled hypertension in both periods. Accounting for follow-up intervals, the likelihood of maintaining control was 2% lower during the pandemic versus the prepandemic. For uncontrolled hypertension, the likelihood of gaining control was modestly higher during the pandemic versus the prepandemic (relative risk: 1.01; 95% CI: 1.01, 1.01). The likelihood of gaining control decreased with follow-up length during the prepandemic but not pandemic. CONCLUSIONS: During the pandemic, longer follow-up between measurements contributed to the lower likelihood of maintaining control. Those with uncontrolled hypertension were modestly more likely to gain control in the pandemic.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants.

BACKGROUND: Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity. METHODS: 169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP. RESULTS: Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP. CONCLUSIONS: These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

Global patterns of rebound to normal RSV dynamics following COVID-19 suppression.

BACKGROUND: Annual epidemics of respiratory syncytial virus (RSV) had consistent timing and intensity between seasons prior to the SARS-CoV-2 pandemic (COVID-19). However, starting in April 2020, RSV seasonal activity declined due to COVID-19 non-pharmaceutical interventions (NPIs) before re-emerging after relaxation of NPIs. We described the unusual patterns of RSV epidemics that occurred in multiple subsequent waves following COVID-19 in different countries and explored factors associated with these patterns. METHODS: Weekly cases of RSV from twenty-eight countries were obtained from the World Health Organisation and combined with data on country-level characteristics and the stringency of the COVID-19 response. Dynamic time warping and regression were used to cluster time series patterns and describe epidemic characteristics before and after COVID-19 pandemic, and identify related factors. RESULTS: While the first wave of RSV epidemics following pandemic suppression exhibited unusual patterns, the second and third waves more closely resembled typical RSV patterns in many countries. Post-pandemic RSV patterns differed in their intensity and/or timing, with several broad patterns across the countries. The onset and peak timings of the first and second waves of RSV epidemics following COVID-19 suppression were earlier in the Southern than Northern Hemisphere. The second wave of RSV epidemics was also earlier with higher population density, and delayed if the intensity of the first wave was higher. More stringent NPIs were associated with lower RSV growth rate and intensity and a shorter gap between the first and second waves. CONCLUSION: Patterns of RSV activity have largely returned to normal following successive waves in the post-pandemic era. Onset and peak timings of future epidemics following disruption of normal RSV dynamics need close monitoring to inform the delivery of preventive and control measures.

Mapping partner drug resistance to guide antimalarial combination therapy policies in sub-Saharan Africa.

Resistance to artemisinin-based combination therapies (ACTs) threatens the global control of Plasmodium falciparum malaria. ACTs combine artemisinin-derived compounds with partner drugs to enable multiple mechanisms of clearance. Although ACTs remain widely effective in sub-Saharan Africa, long-standing circulation of parasite alleles associated with reduced partner drug susceptibility may contribute to the development of clinical resistance. We fitted a hierarchical Bayesian spatial model to data from over 500 molecular surveys to predict the prevalence and frequency of four key markers in transporter genes (pfcrt 76T and pfmdr1 86Y, 184F, and 1246Y) in first-level administrative divisions in sub-Saharan Africa from the uptake of ACTs (2004 to 2009) to their widespread usage (2010 to 2018). Our models estimated that the pfcrt 76T mutation decreased in prevalence in 90% of regions; the pfmdr1 N86 and D1246 wild-type genotypes increased in prevalence in 96% and 82% of regions, respectively; and there was no significant directional selection at the pfmdr1 Y184F locus. Rainfall seasonality was the strongest predictor of the prevalence of wild-type genotypes, with other covariates, including first-line drug policy and transmission intensity more weakly associated. We lastly identified regions of high priority for enhanced surveillance that could signify decreased susceptibility to the local first-line ACT. Our results can be used to infer the degree of molecular resistance and magnitude of wild-type reversion in regions without survey data to inform therapeutic policy decisions.

Air pollution interacts with genetic risk to influence cortical networks implicated in depression.

Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.

Placental genomic risk scores and early neurodevelopmental outcomes.

Tracing the early paths leading to developmental disorders is critical for prevention. In previous work, we detected an interaction between genomic risk scores for schizophrenia (GRSs) and early-life complications (ELCs), so that the liability of the disorder explained by genomic risk was higher in the presence of a history of ELCs, compared with its absence. This interaction was specifically driven by loci harboring genes highly expressed in placentae from normal and complicated pregnancies [G. Ursini et al., Nat. Med. 24, 792-801 (2018)]. Here, we analyze whether fractionated genomic risk scores for schizophrenia and other developmental disorders and traits, based on placental gene-expression loci (PlacGRSs), are linked with early neurodevelopmental outcomes in individuals with a history of ELCs. We found that schizophrenia's PlacGRSs are negatively associated with neonatal brain volume in singletons and offspring of multiple pregnancies and, in singletons, with cognitive development at 1 y and, less strongly, at 2 y, when cognitive scores become more sensitive to other factors. These negative associations are stronger in males, found only with GRSs fractionated by placental gene expression, and not found in PlacGRSs for other developmental disorders and traits. The relationship of PlacGRSs with brain volume persists as an anlage of placenta biology in adults with schizophrenia, again selectively in males. Higher placental genomic risk for schizophrenia, in the presence of ELCs and particularly in males, alters early brain growth and function, defining a potentially reversible neurodevelopmental path of risk that may be unique to schizophrenia.

Potential Impact of Higher-Valency Pneumococcal Conjugate Vaccines Among Adults in Different Localities in Germany.

Next-generation pneumococcal conjugate vaccines (PCVs) have been approved for use. The serotype distribution of pneumococcal isolates can vary between regions. To understand the potential impacts of new PCVs, we evaluated trends in invasive pneumococcal disease (IPD) among adults in Germany at a local level using Bayesian hierarchical logistic regression. There was little spatial variation in IPD cases caused by PCV13 serotypes, which dropped from 60% of IPD cases in 2006 to 30% in 2018. Over half of IPD cases in 2018 were attributable to serotypes covered by new PCVs (PCV15, PCV20), which suggests they could further reduce the burden of IPD.

Year-Round Respiratory Syncytial Virus Transmission in The Netherlands Following the COVID-19 Pandemic: A Prospective Nationwide Observational and Modeling Study.

We initiated a nationwide prospective study to monitor respiratory syncytial virus (RSV)-related pediatric hospitalizations in 46 hospitals throughout the Netherlands between May 2021 and August 2022. We showed year-round RSV transmission in the Netherlands after an initial 2021 summer outbreak. The pattern was unprecedented and distinct from neighboring countries. We extended a dynamic simulation model to evaluate the impact of waning immunity on pediatric RSV hospitalizations in the Netherlands using 4 different scenarios. Our results suggest that the observed continuous RSV transmission pattern could be associated with waning immunity due to the period of very low RSV circulation during the COVID-19 pandemic.

Waning Effectiveness of the BNT162b2 Vaccine Against Infection in Adolescents in Israel.

BACKGROUND: The short-term effectiveness of a 2-dose regimen of the BioNTech/Pfizer BNT162b2 vaccine for adolescents has been demonstrated. However, little is known about the long-term effectiveness in this age group. It is known, however, that waning of vaccine-induced immunity against infection in adult populations is evident within a few months. METHODS: Leveraging the database of Maccabi Healthcare Services (MHS), we conducted a matched case-control design for evaluating the association between time since vaccination and the incidence of infections, where 2 outcomes were evaluated: documented SARS-CoV-2 infection (regardless of symptoms) and symptomatic infection (COVID-19). Cases were defined as individuals aged 12-16 with a positive polymerase chain reaction (PCR) test occurring between 15 June and 8 December 2021, when the Delta variant was dominant in Israel. Controls were adolescents who had not tested positive previously. RESULTS: We estimated a peak vaccine effectiveness between 2 weeks and 3 months following receipt of the second dose, with 85% (95% confidence interval [CI]: 84-86%) and 90% (95% CI: 89-91%) effectiveness against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19), respectively. However, in line with findings for adults, waning effectiveness was evident. Long-term protection was reduced to 73% (95% CI: 68-77%) against infection and 79% (95% CI: 73-83%) against COVID-19 3-5 months after the second dose and waned to 53% (95% CI: 46-60%) against infection and 66% (95% CI: 59-72%) against COVID-19 after 5 months. CONCLUSIONS: Although vaccine-induced protection against both infection and COVID-19 continues over time in adolescents, the protection wanes with time since vaccination, starting 3 months after inoculation and continuing for more than 5 months.

Characterizing the nuclear and cytoplasmic transcriptomes in developing and mature human cortex uncovers new insight into psychiatric disease gene regulation.

Transcriptome compartmentalization by the nuclear membrane provides both stochastic and functional buffering of transcript activity in the cytoplasm, and has recently been implicated in neurodegenerative disease processes. Although many mechanisms regulating transcript compartmentalization are also prevalent in brain development, the extent to which subcellular localization differs as the brain matures has yet to be addressed. To characterize the nuclear and cytoplasmic transcriptomes during brain development, we sequenced both RNA fractions from homogenate prenatal and adult human postmortem cortex using poly(A)+ and Ribo-Zero library preparation methods. We find that while many genes are differentially expressed by fraction and developmental expression changes are similarly detectable in nuclear and cytoplasmic RNA, the compartmented transcriptomes become more distinct as the brain matures, perhaps reflecting increased utilization of nuclear retention as a regulatory strategy in adult brain. We examined potential mechanisms of this developmental divergence including alternative splicing, RNA editing, nuclear pore composition, RNA-binding protein motif enrichment, and RNA secondary structure. Intron retention is associated with greater nuclear abundance in a subset of transcripts, as is enrichment for several splicing factor binding motifs. Finally, we examined disease association with fraction-regulated gene sets and found nuclear-enriched genes were also preferentially enriched in gene sets associated with neurodevelopmental psychiatric disorders. These results suggest that although gene-level expression is globally comparable between fractions, nuclear retention of transcripts may play an underappreciated role in developmental regulation of gene expression in brain, particularly in genes whose dysregulation is related to neuropsychiatric disorders.