Concentrated incarceration and the public-housing-to-prison pipeline in New York City neighborhoods

Using public housing developments as a strategic site, our research documents a distinct pathway linking disadvantaged context to incarceration-the public-housing-to-prison pipeline. Focusing on New York City Housing Authority (NYCHA) housing developments as a case study, we find that incarceration rates in NYCHA tracts are 4.6 times higher than those in non-NYCHA tracts. More strikingly, 94% of NYCHA tracts report rates above the median value for non-NYCHA tracts. Moreover, 17% of New York State\u27s incarcerated population originated from just 372 NYCHA tracts. Compared with non-NYCHA tracts, NYCHA tracts had higher shares of Black residents and were significantly more disadvantaged. This NYCHA disadvantage in concentrated incarceration is also robust at different spatial scales. Our findings have implications for policies and programs to disrupt community-based pipelines to prison

A genome-integrated massively parallel reporter assay reveals DNA sequence determinants of cis-regulatory activity in neural cells

Recent large-scale genomics efforts to characterize the cis-regulatory sequences that orchestrate genome-wide expression patterns have produced impressive catalogues of putative regulatory elements. Most of these sequences have not been functionally tested, and our limited understanding of the non-coding genome prevents us from predicting which sequences are bona fide cis-regulatory elements. Recently, massively parallel reporter assays (MPRAs) have been deployed to measure the activity of putative cis-regulatory sequences in several biological contexts, each with specific advantages and distinct limitations. We developed LV-MPRA, a novel lentiviral-based, massively parallel reporter gene assay, to study the function of genome-integrated regulatory elements in any mammalian cell type; thus, making it possible to apply MPRAs in more biologically relevant contexts. We measured the activity of 2,600 sequences in U87 glioblastoma cells and human neural progenitor cells (hNPCs) and explored how regulatory activity is encoded in DNA sequence. We demonstrate that LV-MPRA can be applied to estimate the effects of local DNA sequence and regional chromatin on regulatory activity. Our data reveal that primary DNA sequence features, such as GC content and dinucleotide composition, accurately distinguish sequences with high activity from sequences with low activity in a full chromosomal context, and may also function in combination with different transcription factor binding sites to determine cell type specificity. We conclude that LV-MPRA will be an important tool for identifying cis-regulatory elements and stimulating new understanding about how the non-coding genome encodes information

IgG Responses to Tissue-Associated Antigens as Biomarkers of Immunological Treatment Efficacy

We previously demonstrated that IgG responses to a panel of 126 prostate tissue-associated antigens are common in patients with prostate cancer. In the current report we questioned whether changes in IgG responses to this panel might be used as a measure of immune response, and potentially antigen spread, following prostate cancer-directed immune-active therapies. Sera were obtained from prostate cancer patients prior to and three months following treatment with androgen deprivation therapy (n = 34), a poxviral vaccine (n = 31), and a DNA vaccine (n = 21). Changes in IgG responses to individual antigens were identified by phage immunoblot. Patterns of IgG recognition following three months of treatment were evaluated using a machine-learned Bayesian Belief Network (ML-BBN). We found that different antigens were recognized following androgen deprivation compared with vaccine therapies. While the number of clinical responders was low in the vaccine-treated populations, we demonstrate that ML-BBN can be used to develop potentially predictive models

Synthetic and genomic regulatory elements reveal aspects of cis-regulatory grammar in mouse embryonic stem cells

In embryonic stem cells (ESCs), a core transcription factor (TF) network establishes the gene expression program necessary for pluripotency. To address how interactions between four key TFs contribute t

Developmental enhancers revealed by extensive DNA methylome maps of zebrafish early embryos

DNA methylation undergoes dynamic changes during development and cell differentiation. Recent genome-wide studies discovered that tissue-specific differentially methylated regions (DMRs) often overlap tissue-specific distal cis-regulatory elements. However, developmental DNA methylation dynamics of the majority of the genomic CpGs outside gene promoters and CpG islands has not been extensively characterized. Here we generate and compare comprehensive DNA methylome maps of zebrafish developing embryos. From these maps we identify thousands of developmental stage-specific DMRs (dsDMR) across zebrafish developmental stages. The dsDMRs contain evolutionarily conserved sequences, are associated with developmental genes, and are marked with active enhancer histone post-translational modifications. Their methylation pattern correlates much stronger than promoter methylation with expression of putative target genes. When tested in vivo using a transgenic zebrafish assay, 20 out of 20 selected candidate dsDMRs exhibit functional enhancer activities. Our data suggest that developmental enhancers are a major target of DNA methylation changes during embryogenesis

Functional cis-regulatory modules encoded by mouse-specific endogenous retrovirus

Cis-regulatory modules contain multiple transcription factor (TF)-binding sites and integrate the effects of each TF to control gene expression in specific cellular contexts. Transposable elements (TEs) are uniquely equipped to deposit their regulatory sequences across a genome, which could also contain cis-regulatory modules that coordinate the control of multiple genes with the same regulatory logic. We provide the first evidence of mouse-specific TEs that encode a module of TF-binding sites in mouse embryonic stem cells (ESCs). The majority (77%) of the individual TEs tested exhibited enhancer activity in mouse ESCs. By mutating individual TF-binding sites within the TE, we identified a module of TF-binding motifs that cooperatively enhanced gene expression. Interestingly, we also observed the same motif module in the in silico constructed ancestral TE that also acted cooperatively to enhance gene expression. Our results suggest that ancestral TE insertions might have brought in cis-regulatory modules into the mouse genome

Assessment of the impact of the COVID-19 pandemic on health services use

OBJECTIVES: The coronavirus disease of 2019 (COVID-19) pandemic declared by the World Health Organization on March 11, 2020 impacted healthcare services with provider and patient cancellations, delays, and patient avoidance or delay of emergency department or urgent care. Limited data exist on the population proportion affected by delayed healthcare, which is important for future healthcare planning efforts. Our objective was to evaluate the impact of the COVID-19 pandemic on healthcare service cancellations or delays and delays/avoidance of emergency/urgent care overall and by population characteristics. STUDY DESIGN: This was a cross-sectional study. METHODS: Our sample (n = 2314) was assembled through a phone survey from 8/12/2020-10/27/2020 among non-institutionalized St. Louis County, Missouri, USA residents ≥18 years. We asked about provider and patient-initiated cancellations or delays of appointments and pandemic-associated delays/avoidance of emergency/urgent care overall and by participant characteristics. We calculated weighted prevalence estimates by select resident characteristics. RESULTS: Healthcare services cancellations or delays affected ∼54% (95% CI 50.6%-57.1%) of residents with dental (31.1%, 95% CI 28.1%-34.0%) and primary care (22.1%, 95% CI 19.5%-24.6%) being most common. The highest prevalences were among those who were White, ≥65 years old, female, in fair/poor health, who had health insurance, and who had ≥1 medical condition. Delayed or avoided emergency/urgent care impacted ∼23% (95% CI 19.9%-25.4%) of residents with a higher prevalence in females than males. CONCLUSIONS: Healthcare use disruptions impacted a substantial proportion of residents. Future healthcare planning efforts should consider these data to minimize potential morbidity and mortality from delayed care

Modifications to student quarantine policies in K-12 schools implementing multiple COVID-19 prevention strategies restores in-person education without increasing SARS-CoV-2 transmission risk, January-March 2021

OBJECTIVE: To determine whether modified K-12 student quarantine policies that allow some students to continue in-person education during their quarantine period increase schoolwide SARS-CoV-2 transmission risk following the increase in cases in winter 2020-2021. METHODS: We conducted a prospective cohort study of COVID-19 cases and close contacts among students and staff (n = 65,621) in 103 Missouri public schools. Participants were offered free, saliva-based RT-PCR testing. The projected number of school-based transmission events among untested close contacts was extrapolated from the percentage of events detected among tested asymptomatic close contacts and summed with the number of detected events for a projected total. An adjusted Cox regression model compared hazard rates of school-based SARS-CoV-2 infections between schools with a modified versus standard quarantine policy. RESULTS: From January-March 2021, a projected 23 (1%) school-based transmission events occurred among 1,636 school close contacts. There was no difference in the adjusted hazard rates of school-based SARS-CoV-2 infections between schools with a modified versus standard quarantine policy (hazard ratio = 1.00; 95% confidence interval: 0.97-1.03). DISCUSSION: School-based SARS-CoV-2 transmission was rare in 103 K-12 schools implementing multiple COVID-19 prevention strategies. Modified student quarantine policies were not associated with increased school incidence of COVID-19. Modifications to student quarantine policies may be a useful strategy for K-12 schools to safely reduce disruptions to in-person education during times of increased COVID-19 community incidence

A study of local and regional gene regulatory features in the human genome

Gene expression is driven by specific combinations of transcription factors binding to regulatory sequences to define cell type expression profiles. Changes in DNA sequence alter transcription factor binding affinities and gene expression, and DNA methylation is an additional source of variation that is maintained throughout cellular division. Numerous genomic studies are underway to determine which genes are abnormally regulated by DNA methylation in disease. However, we have a poor understanding of how disease-specific methylation variation affects expression. Global DNA demethylation agents have been clinically approved for use in cancer, which has spurred interest in identifying genes which would be most susceptible for targeted demethylation therapies. In this work, I developed multiple tools to increase our knowledge about the relationship between methylation and gene expression in both tissue specificity and disease.I first developed a computational strategy to identify amplifications and deletions from restriction enzyme-based methylation datasets. In a model of endocrine therapy resistant breast cancer, I identify ESR1 as the most amplified genomic region in response to estrogen deprivation. I develop a qPCR-based assay to probe the amplification in cell lines, formalin-fixed paraffin embedded samples, patient tumors, and xenograft samples. This data is consistent with the hypothesis that in a subset of patients, the ESR1 amplification results in increased levels of ERα. These are produced in response to estrogen deprivation to sensitize breast cancer to low available quantities of estrogen for cellular growth.Next, to explain specific variation in methylation that associates with expression change in both disease and tissue-specificity, I developed an integrative analysis tool, Methylation-based Gene Expression Classification (ME-Class). This model captures the complexity of methylation changes around a gene promoter. Using whole-genome bisulfite sequencing and RNA-seq datasets from different tissue samples, ME-Class significantly outperforms published methods using methylation to predict differential gene expression change. To demonstrate its utility, I used ME-Class to analyze different hematopoietic cell types, and identified that expression-associated methylation changes were predominantly found when comparing cells from distantly related lineages, implying that changes in the cell\u27s transcriptional program precede associated methylation changes. Training ME-Class on normal-tumor pairs indicated that cancer-specific expression-associated methylation changes differ from tissue-specific changes. I further show that ME-Class can detect functionally relevant cancer-specific, expression-associated methylation changes that are reversed upon the removal of methylation in a model of colon cancer.Lastly, I extended ME-Class to incorporate 5-hydroxymethylcytosine and uncovered gene regulatory logic involving 5hmC and 5mC in mammalian development and disease. As more large-scale, genome-wide, differential DNA methylation studies become available, tools such as ME-class will prove invaluable to understand how specific methylation changes affect transcription. Our results show this toolset can identify genes that are dysregulated by methylation in disease, and could be used to facilitate the identification of patients who may benefit from clinically-approved demethylating therapeutics