Effectiveness of Coronavirus Disease 2019 (COVID-19) Vaccination Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection Among Residents of US Nursing Homes Before and During the Delta Variant Predominance, December 2020-November 2021.

BACKGROUND: Residents of nursing homes experience disproportionate morbidity and mortality related to coronavirus disease 2019 (COVID-19) and were prioritized for vaccine introduction. We evaluated COVID-19 vaccine effectiveness (VE) in preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among nursing home residents. METHODS: We used a retrospective cohort of 4315 nursing home residents during 14 December 2020-9 November 2021. A Cox proportional hazards model was used to estimate hazard ratios comparing residents with a completed vaccination series with unvaccinated among those with and without prior SARS-CoV-2 infection, by vaccine product, and by time period. RESULTS: Overall adjusted VE was 58% (95% confidence interval [CI], 44% to 69%) among residents without a history of SARS-CoV-2 infection. During the pre-Delta period, the VE within 150 days of receipt of the second dose of Pfizer-BioNTech (67%; 95% CI, 40% to 82%) and Moderna (75%; 95% CI, 32% to 91%) was similar. During the Delta period, VE measured >150 days after the second dose was 33% (95% CI, -2% to 56%) for Pfizer-BioNTech and 77% (95% CI, 48% to 91%) for Moderna. Rates of infection were 78% lower (95% CI, 67% to 85%) among residents with prior SARS-CoV-2 infection and completed vaccination series compared with unvaccinated residents without a history of SARS-CoV-2 infection. CONCLUSIONS: COVID-19 vaccines were effective in preventing SARS-CoV-2 infections among nursing home residents, and history of prior SARS-CoV-2 infection provided additional protection. Maintaining high coverage of recommended doses of COVID-19 vaccines remains a critical tool for preventing infections in nursing homes.

Sex Differences in the Human Brain Transcriptome of Cases With Schizophrenia.

BACKGROUND: While schizophrenia differs between males and females in the age of onset, symptomatology, and disease course, the molecular mechanisms underlying these differences remain uncharacterized. METHODS: To address questions about the sex-specific effects of schizophrenia, we performed a large-scale transcriptome analysis of RNA sequencing data from 437 controls and 341 cases from two distinct cohorts from the CommonMind Consortium. RESULTS: Analysis across the cohorts identified a reproducible gene expression signature of schizophrenia that was highly concordant with previous work. Differential expression across sex was reproducible across cohorts and identified X- and Y-linked genes, as well as those involved in dosage compensation. Intriguingly, the sex expression signature was also enriched for genes involved in neurexin family protein binding and synaptic organization. Differential expression analysis testing a sex-by-diagnosis interaction effect did not identify any genome-wide signature after multiple testing corrections. Gene coexpression network analysis was performed to reduce dimensionality from thousands of genes to dozens of modules and elucidate interactions among genes. We found enrichment of coexpression modules for sex-by-diagnosis differential expression signatures, which were highly reproducible across the two cohorts and involved a number of diverse pathways, including neural nucleus development, neuron projection morphogenesis, and regulation of neural precursor cell proliferation. CONCLUSIONS: Overall, our results indicate that the effect size of sex differences in schizophrenia gene expression signatures is small and underscore the challenge of identifying robust sex-by-diagnosis signatures, which will require future analyses in larger cohorts.

Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions. METHODS: A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene's surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues. RESULTS: Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR < 5%: N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR < 0.05): APOC1, EED, CD2AP, CEACAM19, CLPTM1, MTCH2, TREM2, and KNOP1. CONCLUSIONS: We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

The AD Knowledge Portal: A Repository for Multi-Omic Data on Alzheimer's Disease and Aging.

The AD Knowledge Portal (adknowledgeportal.org) is a public data repository that shares data and other resources generated by multiple collaborative research programs focused on aging, dementia, and Alzheimer's disease (AD). In this article, we highlight how to use the Portal to discover and download genomic variant and transcriptomic data from the same individuals. First, we show how to use the web interface to browse and search for data of interest using relevant file annotations. We demonstrate how to learn more about the context surrounding the data, including diagnostic criteria and methodological details about sample preparation and data analysis. We present two primary ways to download data-using a web interface, and using a programmatic method that provides access using the command line. Finally, we show how to merge separate sources of metadata into a comprehensive file that contains factors and covariates necessary in downstream analyses. © 2020 The Authors. Basic Protocol 1: Find and download files associated with a selected study Basic Protocol 2: Download files in bulk using the command line client Basic Protocol 3: Working with file annotations and metadata.

CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.

Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org .

Loss of Mitochondrial Ndufs4 in Striatal Medium Spiny Neurons Mediates Progressive Motor Impairment in a Mouse Model of Leigh Syndrome.

Inability of mitochondria to generate energy leads to severe and often fatal myoencephalopathies. Among these, Leigh syndrome (LS) is one of the most common childhood mitochondrial diseases; it is characterized by hypotonia, failure to thrive, respiratory insufficiency and progressive mental and motor dysfunction, leading to early death. Basal ganglia nuclei, including the striatum, are affected in LS patients. However, neither the identity of the affected cell types in the striatum nor their contribution to the disease has been established. Here, we used a mouse model of LS lacking Ndufs4, a mitochondrial complex I subunit, to confirm that loss of complex I, but not complex II, alters respiration in the striatum. To assess the role of striatal dysfunction in the pathology, we selectively inactivated Ndufs4 in the striatal medium spiny neurons (MSNs), which account for over 95% of striatal neurons. Our results show that lack of Ndufs4 in MSNs causes a non-fatal progressive motor impairment without affecting the cognitive function of mice. Furthermore, no inflammatory responses or neuronal loss were observed up to 6 months of age. Hence, complex I deficiency in MSNs contributes to the motor deficits observed in LS, but not to the neural degeneration, suggesting that other neuronal populations drive the plethora of clinical signs in LS.