Search

Whole-genome sequencing (WGS) is the gold standard for fully characterizing genetic variation but is still prohibitively expensive for large samples. To reduce costs, many studies sequence only a subset of individuals or genomic regions, and genotype imputation is used to infer genotypes for the remaining individuals or regions without sequencing data. However, not all variants can be well imputed, and the current state-of-the-art imputation quality metric, denoted as standard Rsq, is poorly calibrated for lower-frequency variants. Here, we propose MagicalRsq, a machine-learning-based method that integrates variant-level imputation and population genetics statistics, to provide a better calibrated imputation quality metric. Leveraging WGS data from the Cystic Fibrosis Genome Project (CFGP), and whole-exome sequence data from UK BioBank (UKB), we performed comprehensive experiments to evaluate the performance of MagicalRsq compared to standard Rsq for partially sequenced studies. We found that MagicalRsq aligns better with true R

There are many scholarly works focusing on organized crime and violence in Latin America. Scholars have shown empirically that tough on crime strategies have had collateral damages and have not been effective. By conducting logistic regression models using individual country survey data, this work seeks to analyze why tough on crime policies remain popular in some Latin American countries despite the decades of research criticizing these strategies. This article explores the cases of Colombia and Brazil, which have long histories of gang activity, organized crime, and violence. These countries also have elected presidential candidates who campaigned on iron fist strategies.

This article evaluates the factors impacting support for tough on crime policies in El Salvador. Examining theoretical and empirical scholarly work, we look at how fear, together with social and political contexts drive public appetite for punitive policies towards criminals. We show that President Nayib Bukele is responding to public opinion and has implemented tough on crime policies at the expense of human rights violations and democratic institutions. Society favors candidates who are the "toughest" against criminal actors. Political candidates from all sides of the ideological spectrum tap into the fear of the populace to win votes, leading to punitive Darwinism. We provide an empirical assessment of which theoretically relevant factors are statistically associated with punitivism in the Salvadoran context, using multiple regression analysis of high-quality public opinion survey data from LAPOP.

Is it possible to disengage from street gangs in communities and districts where gang organizations rule? We argue that disengagement is possible when this process does not alter the social order that allows street gangs to continue controlling and establishing the rules that govern economic activities and relationships in the barrios they control. We explore the process of gang disengagement under criminal governance in El Salvador, a country plagued by the powerful MS-13 and Barrio 18 gangs. We conducted a survey with nearly 1,200 people with a history of gang membership and 25 in-depth interviews with former gang members. We find that disengagement through religious conversion allows the gang to continue exerting power over the deserters, while at the same time enforcing religious commitment to the congregation. The religious community provides the normative framework that reassures the gang that its former associates will not act against it, consolidating its local authority.

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

This article examines how violence intervention programs are implemented in places governed by street gangs. It is based on focus groups conducted in communities impacted by gangs and gang-related violence in the countries of Northern Central America. We develop a typology for understanding the different mechanisms for interacting with gangs. In places where gangs rule, it is not possible for non-governmental workers to avoid gangs. Instead, we argue that community workers implementing programs in gang neighborhoods are required to acknowledge the power and presence of gangs and readapt their strategies to carry on implementing the programs.

AIMS: To describe the pain characteristics of five index chronic overlapping pain conditions (COPCs) and to assess each COPC separately in order to determine whether the presence of comorbid COPCs is associated with bodily pain distribution, pain intensity, pain interference, and high-impact pain of the index COPC. METHODS: Data were from a convenience sample of 655 US adults, of whom 388 had one or more of the five COPCs: painful temporomandibular disorders, headache, low back pain, irritable bowel syndrome, and/or fibromyalgia. Data were collected using pain location checklists and self-report questions regarding pain attributes. The contributions of the COPCs to reported pain intensity and interference were assessed using multivariable regression models. RESULTS/CONCLUSION: Heat maps from a pain body manikin illustrated that very little of the body was pain free within these COPCs. All pain attributes were the most severe for fibromyalgia and the least severe for irritable bowel syndrome. Within each index COPC, pain intensity, pain interference, and the proportion of participants with high-impact pain increased with each additional comorbid COPC up to four or more COPCs (including the index COPC) (P < .01). High-impact pain associated with an index COPC was influenced by type and number of comorbid COPCs, largely in a gradient-specific manner.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Previous genome-wide association studies (GWAS) of hematological traits have identified over 10,000 distinct trait-specific risk loci, but the underlying causal mechanisms at these loci remain incompletely characterized. We performed a transcriptome-wide association study (TWAS) of 29 hematological traits in 399,835 UK Biobank (UKB) participants of European ancestry using gene expression prediction models trained from whole blood RNA-seq data in 922 individuals. We discovered 557 TWAS signals associated with hematological traits distinct from previously discovered GWAS variants, including 10 completely novel gene-trait pairs corresponding to 9 unique genes. Among the 557 associations, 301 were available for replication in a cohort of 141,286 participants of European ancestry from the Million Veteran Program (MVP). Of these 301 associations, 199 replicated at a nominal threshold (α = 0.05) and 108 replicated at a strict Bonferroni adjusted threshold (α = 0.05/301). Using our TWAS results, we systematically assigned 4,261 out of 16,900 previously identified hematological trait GWAS variants to putative target genes. Compared to coloc, our TWAS results show reduced specificity and increased sensitivity to assign variants to target genes.

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Also, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including N=229 African American and N=381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, N = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (N = 27,955) and Hispanic/Latino (N = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1×10^(-4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (N=802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Hematological measures are important intermediate clinical phenotypes for many acute and chronic diseases. Hematological measures are highly heritable, and although genome-wide association studies (GWAS) have identified thousands of loci containing trait-associated variants, the causal genes underlying these associations are often uncertain. To better understand the underlying genetic regulatory mechanisms, we performed a transcriptome-wide association study (TWAS) using PrediXcan to systematically investigate the association between genetically-predicted gene expression and hematological measures in 54,542 individuals of European ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We found 239 significant gene-trait associations with hematological measures. Among this set of 239 associations, we replicated 71 at p < 0.05 with same direction of effect for the blood cell trait in a meta-analysis of TWAS results consisting of up to 35,900 European ancestry individuals from the Women’s Health Initiative (WHI), the Atherosclerosis Risk in Communities Study (ARIC), and BioMe Biobank. We further attempted to refine this list of candidate genes by performing conditional analyses, adjusting for individual variants previously associated with these hematological measures, and performed further fine-mapping of TWAS loci. To assist with the interpretation of TWAS findings, we designed an R Shiny application to interactively visualize TWAS results, one genomic locus at a time, by integrating our TWAS results with additional genetic data sources (GWAS, TWAS from other gene expression reference panels, conditional analyses, known GWAS variants, etc.). Our results and R Shiny application highlight frequently overlooked challenges with TWAS and illustrate the complexity of TWAS fine-mapping efforts.Author SummaryTranscriptome-wide association studies (TWAS) have shown great promise in furthering our understanding of the genetic regulatory mechanisms underlying complex trait variation. However, interpreting TWAS results can be incredibly complex, especially in large-scale analyses where hundreds of signals appear throughout the genome, with multiple genes often identified in a single chromosomal region. Our research demonstrates this complexity through real data examples from our analysis of hematological traits, and we provide a useful web application to visualize TWAS results in a broadly approachable format. Together, our results and web application illustrate the importance of interpreting TWAS studies in context and highlight the need to carefully examine results in a region-wide context to draw reasonable conclusions and formulate mechanistic hypotheses.

This chapter focuses on the war on drugs in Colombia. It begins by examining the linkages between cocaine trafficking between Colombia and South Florida, which elevated the drug trade on the security agenda of the United States. This chapter then examines the Medellin and Cali cartels and their role in drug trafficking and organized crime. It also analyzes Plan Colombia, a multi-billion-dollar foreign aid package designed to combat drug production and trafficking. This chapter explores how the goals of Plan Colombia evolved over time and the consequences of this policy. The chapter focuses on recent trends in coca production and the evolution of criminal groups, such as the criminal bands. Finally, it examines the impact of the peace process and the return to the war on drugs during the Duque administration.

This chapter examines drug trafficking and organized crime in Mexico. It begins with a history of drug trafficking and how it has evolved over time. It focuses on the 71-year rule by a single political party and the transition to democracy in 2000, which had an impact on the relationship between the state and organized crime. This chapter then examines Felipe Calderon’s war on drugs and the Merida Initiative, a U.S.-funded plan, to help the Mexican government combat drug trafficking and organized crime. It then examines recent trends in drug trafficking, organized crime, and counternarcotic policies, focusing on the Pena Nieto and Lopez Obrador governments. It examines opium production and the evolution of organized crime in the State of Guerrero. Finally, this chapter analyzes the impact of the Coronavirus on organized crime and the challenges combating corruption and impunity.

This chapter focuses on the issue of drug addiction as well as the trafficking of drugs through Mexico en route to the United States. It begins with an examination of OxyContin and the Sackler family. It focuses on the role that marketing played in the opioid crisis in the United States. This chapter also provides stories of addiction, focusing on the real-world impact that the opioid epidemic has had on people. It then turns to the case of fentanyl and Philadelphia, analyzing not only drug trafficking but also alternative policies, such as safe injection sites. Finally, it explains how drugs are trafficked through the border from Mexico.

Lineage-specific epigenomic changes during human corticogenesis have remained elusive due to challenges with sample availability and tissue heterogeneity. For example, previous studies used single-cell RNA sequencing to identify at least nine major cell types and up to 26 distinct subtypes in the dorsal cortex alone1,2. Here, we characterize cell type-specific cis-regulatory chromatin interactions, open chromatin peaks, and transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, and interneurons isolated from mid-gestational human cortex samples. We show that chromatin interactions underlie multiple aspects of gene regulation, with transposable elements and disease-associated variants enriched at distal interacting regions in a cell type-specific manner. In addition, promoters with significantly increased levels of chromatin interactivity, termed super interactive promoters, are enriched for lineage-specific genes, suggesting that interactions at these loci contribute to the fine-tuning of transcription. Finally, we develop CRISPRview, a novel technique integrating immunostaining, CRISPRi, RNAscope, and image analysis for validating cell type-specific cis-regulatory elements in heterogeneous populations of primary cells. Our study presents the first cell type-specific characterization of 3D epigenomes in the developing human cortex, advancing our understanding of gene regulation and lineage specification during this critical developmental window.