RESUMEN

Airborne radioactivity from fossil fuel production systems is poorly characterized, but a recent study showed elevated ambient levels with proximity to oil and gas production wells. Here, we report year-long, high temporal resolution monitoring results of airborne alpha radioactivity from both radon gas and radon progeny attached to particulates immediately northeast of an oil refinery in Commerce City, Colorado, USA, in an environmental justice community of concern. Gas and particle-associated radioactivity contributed nearly evenly to the total alpha radioactivity. Total radioactivity levels of 30-40 Bq m-3 were 2-3 times higher than background levels (~10-15 Bq m-3) when winds were light and southwesterly, suggesting the refinery as the geographic origin. Furthermore, elevated airborne radioactivity tracked most closely with the light hydrocarbon and natural gas tracer ethane. Thus, the data imply natural gas as the radon emission carrier, possibly from flaring. However, this could not explain all our particle-associated radioactivity observations. Our findings are unique and suggest a need for further investigations of radon emissions from oil and gas infrastructure such as natural gas processing plants, compressor stations, petrochemical plants, and oil refineries that process oil and natural gas from unconventional production.Implications Statement: Regulatory agencies currently do not mandate or conduct monitoring of radioactivity releases and public exposure from petroleum industry air emissions. This study reports elevated radioactivity from radon gas and nonvolatile radon decay products attached to particulate matter, at about 2-3 times above background levels in proximity to Colorado's largest oil refinery. Observations were within an environmental justice community of concern that experiences well above-average exposure to many other harmful atmospheric pollutants, suggesting potential adverse health effects from this cumulative exposure. Our findings offer actionable insights for policymakers, industry stakeholders, and affected communities alike.

RESUMEN

PURPOSE: Brain metastases represent the most common intracranial tumors in adults and are associated with a poor prognosis. We used a personalized in vitro drug screening approach to characterize individual therapeutic vulnerabilities in brain metastases. METHODS: Short-term cultures of cancer cells isolated from brain metastasis patients were molecularly characterized using next-generation sequencing and functionally evaluated using high-throughput in vitro drug screening to characterize pharmacological treatment sensitivities. RESULTS: Next-generation sequencing identified matched genetic alterations in brain metastasis tissue samples and corresponding short-term cultures, suggesting that short-term cultures of brain metastases are suitable models for recapitulating the genetic profile of brain metastases that may determine their sensitivity to anti-cancer drugs. Employing a high-throughput in vitro drug screening platform, we successfully screened the cultures of five brain metastases for response to 267 anticancer compounds and related drug response to genetic data. Among others, we found that targeted treatment with JAK3, HER2, or FGFR3 inhibitors showed anti-cancer effects in individual brain metastasis cultures. CONCLUSION: Our preclinical study provides a proof-of-concept for combining molecular profiling with in vitro drug screening for predictive evaluation of therapeutic vulnerabilities in brain metastasis patients. This approach could advance the use of patient-derived cancer cells in clinical practice and might eventually facilitate decision-making for personalized drug treatment.

Asunto(s)

Antineoplásicos , Neoplasias Encefálicas , Humanos , Neoplasias Encefálicas/tratamiento farmacológico , Neoplasias Encefálicas/secundario , Neoplasias Encefálicas/patología , Neoplasias Encefálicas/genética , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Células Tumorales Cultivadas , Ensayos de Selección de Medicamentos Antitumorales/métodos , Secuenciación de Nucleótidos de Alto Rendimiento , Femenino , Masculino , Persona de Mediana Edad , Ensayos Analíticos de Alto Rendimiento/métodos

RESUMEN

The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics.

Asunto(s)

Microbioma Gastrointestinal , Trasplante de Células Madre Hematopoyéticas , Microbiota , Humanos , Microbioma Gastrointestinal/genética , Microbiota/genética , Bacterias/genética , Antibacterianos , Hongos/genética , ADN Ribosómico , Metagenómica/métodos

RESUMEN

Potato is one of the world's major staple crops, and like many important crop plants, it has a polyploid genome. Polyploid haplotype assembly poses a major computational challenge. We introduce a novel strategy for the assembly of polyploid genomes and present an assembly of the autotetraploid potato cultivar Altus. Our method uses low-depth sequencing data from an offspring population to achieve chromosomal clustering and haplotype phasing on the assembly graph. Our approach generates high-quality assemblies of individual chromosomes with haplotype-specific sequence resolution of whole chromosome arms and can be applied in common breeding scenarios where collections of offspring are available.

Asunto(s)

Solanum tuberosum , Tetraploidía , Humanos , Haplotipos , Análisis de Secuencia de ADN , Solanum tuberosum/genética , Fitomejoramiento , Poliploidía

RESUMEN

The efficacy of epitope vaccines depends on the included epitopes as well as the probability that the selected epitopes are presented by the major histocompatibility complex (MHC) proteins of a vaccinated individual. Designing vaccines that effectively immunize a high proportion of the population is challenging because of high MHC polymorphism, diverging MHC-peptide binding affinities, and physical constraints on epitope vaccine constructs. Here, we present HOGVAX, a combinatorial optimization approach for epitope vaccine design. To optimize population coverage within the constraint of limited vaccine construct space, HOGVAX employs a hierarchical overlap graph (HOG) to identify and exploit overlaps between selected peptides and explicitly models the structure of linkage disequilibrium in the MHC. In a SARS-CoV-2 case study, we demonstrate that HOGVAX-designed vaccines contain substantially more epitopes than vaccines built from concatenated peptides and predict vaccine efficacy in over 98% of the population with high numbers of presented peptides in vaccinated individuals.

Asunto(s)

COVID-19 , Vacunas , Humanos , SARS-CoV-2 , COVID-19/prevención & control , Epítopos de Linfocito T , Péptidos

RESUMEN

An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. OFraMP applied to paclitaxel (ATB ID 35922).

Asunto(s)

Programas Informáticos , Bases de Datos Factuales

RESUMEN

Protein coordinated iron-sulfur clusters drive electron flow within metabolic pathways for organisms throughout the tree of life. It is not known how iron-sulfur clusters were first incorporated into proteins. Structural analogies to iron-sulfide minerals present on early Earth, suggest a connection in the evolution of both proteins and minerals. The availability of large protein and mineral crystallographic structure data sets, provides an opportunity to explore co-evolution of proteins and minerals on a large-scale using informatics approaches. However, quantitative comparisons are confounded by the infinite, repeating nature of the mineral lattice, in contrast to metal clusters in proteins, which are finite in size. We address this problem using the Niggli reduction to transform a mineral lattice to a finite, unique structure that when translated reproduces the crystal lattice. Protein and reduced mineral structures were represented as quotient graphs with the edges and nodes corresponding to bonds and atoms, respectively. We developed a graph theory-based method to calculate the maximum common connected edge subgraph (MCCES) between mineral and protein quotient graphs. MCCES can accommodate differences in structural volumes and easily allows additional chemical criteria to be considered when calculating similarity. To account for graph size differences, we use the Tversky similarity index. Using consistent criteria, we found little similarity between putative ancient iron-sulfur protein clusters and iron-sulfur mineral lattices, suggesting these metal sites are not as evolutionarily connected as once thought. We discuss possible evolutionary implications of these findings in addition to suggesting an alternative proxy, mineral surfaces, for better understanding the coevolution of the geosphere and biosphere.

Asunto(s)

Proteínas Hierro-Azufre , Metaloproteínas , Minerales , Proteínas Hierro-Azufre/química , Proteínas Hierro-Azufre/metabolismo , Azufre/química , Azufre/metabolismo , Hierro/química

RESUMEN

An important challenge in genome assembly is haplotype phasing, that is, to reconstruct the different haplotype sequences of an individual genome. Phasing becomes considerably more difficult with increasing ploidy, which makes polyploid phasing a notoriously hard computational problem. We present a novel genetic phasing method for plant breeding with the aim to phase two deep-sequenced parental samples with the help of a large number of progeny samples sequenced at low depth. The key ideas underlying our approach are to (i) integrate the individually weak Mendelian progeny signals with a Bayesian log-likelihood model, (ii) cluster alleles according to their likelihood of co-occurrence, and (iii) assign them to haplotypes via an interval scheduling approach. We show on two deep-sequenced parental and 193 low-depth progeny potato samples that our approach computes high-quality sparse phasings and that it scales to whole genomes.

Asunto(s)

Dióxido de Carbono , Fósiles , Atmósfera , Radioisótopos de Carbono/análisis

RESUMEN

Recent genome-wide CRISPR-Cas9 loss-of-function screens have identified genetic dependencies across many cancer cell lines. Associations between these dependencies and genomic alterations in the same cell lines reveal phenomena such as oncogene addiction and synthetic lethality. However, comprehensive identification of such associations is complicated by complex interactions between genes across genetically heterogeneous cancer types. We introduce and apply the algorithm SuperDendrix to CRISPR-Cas9 loss-of-function screens from 769 cancer cell lines, to identify differential dependencies across cell lines and to find associations between differential dependencies and combinations of genomic alterations and cell-type-specific markers. These associations respect the position and type of interactions within pathways: for example, we observe increased dependencies on downstream activators of pathways, such as NFE2L2, and decreased dependencies on upstream activators of pathways, such as CDK6. SuperDendrix also reveals dozens of dependencies on lineage-specific transcription factors, identifies cancer-type-specific correlations between dependencies, and enables annotation of individual mutated residues.

RESUMEN

In the adult heart, the epicardium becomes activated after injury, contributing to cardiac healing by secretion of paracrine factors. Here, we analyzed by single-cell RNA sequencing combined with RNA in situ hybridization and lineage tracing of Wilms tumor protein 1-positive (WT1+) cells, the cellular composition, location, and hierarchy of epicardial stromal cells (EpiSC) in comparison to activated myocardial fibroblasts/stromal cells in infarcted mouse hearts. We identified 11 transcriptionally distinct EpiSC populations, which can be classified into three groups, each containing a cluster of proliferating cells. Two groups expressed cardiac specification markers and sarcomeric proteins suggestive of cardiomyogenic potential. Transcripts of hypoxia-inducible factor (HIF)-1α and HIF-responsive genes were enriched in EpiSC consistent with an epicardial hypoxic niche. Expression of paracrine factors was not limited to WT1+ cells but was a general feature of activated cardiac stromal cells. Our findings provide the cellular framework by which myocardial ischemia may trigger in EpiSC the formation of cardioprotective/regenerative responses.

Asunto(s)

Fibroblastos/metabolismo , Miocardio/metabolismo , Pericardio/fisiología , Células del Estroma/metabolismo , Transcriptoma , Animales , Perfilación de la Expresión Génica , Hibridación in Situ , Masculino , Ratones , Ratones Endogámicos C57BL , ARN , Análisis de Secuencia de ARN , Análisis de la Célula Individual , Proteínas WT1/metabolismo

RESUMEN

Genome assembly is one of the most important problems in computational genomics. Here, we suggest addressing an issue that arises in homology-based scaffolding, that is, when linking and ordering contigs to obtain larger pseudo-chromosomes by means of a second incomplete assembly of a related species. The idea is to use alignments of binned regions in one contig to find the most homologous contig in the other assembly. We show that ordering the contigs of the other assembly can be expressed by a new string problem, the longest run subsequence problem (LRS). We show that LRS is NP-hard and present reduction rules and two algorithmic approaches that, together, are able to solve large instances of LRS to provable optimality. All data used in the experiments as well as our source code are freely available. We demonstrate its usefulness within an existing larger scaffolding approach by solving realistic instances resulting from partial Arabidopsis thaliana assemblies in short computation time.

RESUMEN

BACKGROUND: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. METHODS: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. FINDINGS: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. INTERPRETATION: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. FUNDING: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Asunto(s)

Estudio de Asociación del Genoma Completo , Abuso de Marihuana/genética , Humanos , Polimorfismo de Nucleótido Simple , Riesgo

RESUMEN

Resolving genomes at haplotype level is crucial for understanding the evolutionary history of polyploid species and for designing advanced breeding strategies. Polyploid phasing still presents considerable challenges, especially in regions of collapsing haplotypes.We present WHATSHAP POLYPHASE, a novel two-stage approach that addresses these challenges by (i) clustering reads and (ii) threading the haplotypes through the clusters. Our method outperforms the state-of-the-art in terms of phasing quality. Using a real tetraploid potato dataset, we demonstrate how to assemble local genomic regions of interest at the haplotype level. Our algorithm is implemented as part of the widely used open source tool WhatsHap.

Asunto(s)

Haplotipos , Modelos Genéticos , Poliploidía , Algoritmos , Solanum tuberosum/genética

RESUMEN

The recent publication, "Assessing Agreement in Exposure Classification between Proximity-Based Metrics and Air Monitoring Data in Epidemiology Studies of Unconventional Resource Development" by Hess et al [...].

Asunto(s)

Contaminantes Atmosféricos/análisis , Directivas Anticipadas , Benchmarking , Exposición a Riesgos Ambientales/análisis , Estudios Epidemiológicos

RESUMEN

Numerous applications in psychological research require that a pool of elements is partitioned into multiple parts. While many applications seek groups that are well-separated, that is, dissimilar from each other, others require the different groups to be as similar as possible. Examples include the assignment of students to parallel courses, assembling stimulus sets in experimental psychology, splitting achievement tests into parts of equal difficulty, and dividing a data set for cross-validation. We present anticlust, an easy-to-use and free software package for solving these problems fast and in an automated manner. The package anticlust is an open source extension to the R programming language and implements the methodology of anticlustering. Anticlustering divides elements into similar parts, ensuring similarity between groups by enforcing heterogeneity within groups. Thus, anticlustering is the direct reversal of cluster analysis that aims to maximize homogeneity within groups and dissimilarity between groups. Our package anticlust implements 2 anticlustering criteria, reversing the clustering methods k-means and cluster editing, respectively. In a simulation study, we show that anticlustering returns excellent results and outperforms alternative approaches like random assignment and matching. In 3 example applications, we illustrate how to apply anticlust on real data sets. We demonstrate how to assign experimental stimuli to equivalent sets based on norming data, how to divide a large data set for cross-validation, and how to split a test into parts of equal item difficulty and discrimination. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

RESUMEN

Since advances in horizontal drilling and hydraulic fracturing technologies have opened oil and gas development in previously unreachable areas, air pollution emissions have increased from the burning (i.e., flaring) or releasing (i.e., venting) of natural gas at oil and gas extraction sites. While venting and flaring is a growing concern, accounting of how much gas is vented and flared, and where this occurs, remains limited. The purpose of this paper is to describe two methods for estimating venting and flaring volumes - self-reports required by state law and satellite imagery radiant heat measurements - and to compare these methods using the case of Texas Eagle Ford and Permian Basin venting and flaring practices from 2012 to 2015. First, we used data self-reported by companies to the Texas Railroad Commission (TxRRC), and National Oceanic and Atmospheric Administration (NOAA) data captured by satellite-based Visible Infrared Imaging Radiometer Suite sensors, to estimate the annual total volumes of gas vented and flared in the Eagle Ford and Permian Basin from 2012 to 2015. Next, we developed a method using a geographic information system to link and compare TxRRC and NOAA county-based and point-based volume estimates. Finally, we conducted case studies of two oil and gas fields to better understand how TxRRC and NOAA venting and flaring volumes differ. We find both TxRRC and NOAA estimated venting and/or flaring volumes steadily increased from 2012 to 2015. Additionally, TxRRC reports captured about half the volumes estimated by NOAA. This suggests that self-reported volumes significantly underestimate the volume of gas being vented or flared. However, this research is limited by the data currently available. As such, future research and policy should further develop methods to systemically capture the extent to which oil and gas extraction facilities vent and flare natural gas.

RESUMEN

Cannabis is the most frequently used illicit psychoactive substance worldwide; around one in ten users become dependent. The risk for cannabis use disorder (CUD) has a strong genetic component, with twin heritability estimates ranging from 51 to 70%. Here we performed a genome-wide association study of CUD in 2,387 cases and 48,985 controls, followed by replication in 5,501 cases and 301,041 controls. We report a genome-wide significant risk locus for CUD (P = 9.31 × 10-12) that replicates in an independent population (Preplication = 3.27 × 10-3, Pmeta-analysis = 9.09 × 10-12). The index variant (rs56372821) is a strong expression quantitative trait locus for cholinergic receptor nicotinic α2 subunit (CHRNA2); analyses of the genetically regulated gene expression identified a significant association of CHRNA2 expression with CUD in brain tissue. At the polygenic level, analyses revealed a significant decrease in the risk of CUD with increased load of variants associated with cognitive performance. The results provide biological insights and inform on the genetic architecture of CUD.

Asunto(s)

Abuso de Marihuana/genética , Proteínas del Tejido Nervioso/fisiología , Receptores Nicotínicos/fisiología , Edad de Inicio , Alelos , Trastorno por Déficit de Atención con Hiperactividad/genética , Encéfalo/metabolismo , Estudios de Casos y Controles , Cromosomas Humanos Par 8/genética , Cognición/fisiología , Estudios de Cohortes , Factores de Confusión Epidemiológicos , Dinamarca , Escolaridad , Femenino , Perfilación de la Expresión Génica , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Humanos , Islandia , Masculino , Herencia Multifactorial , Proteínas del Tejido Nervioso/biosíntesis , Proteínas del Tejido Nervioso/genética , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Receptores Nicotínicos/biosíntesis , Receptores Nicotínicos/genética , Esquizofrenia/genética , Fumar/genética , Transcriptoma

RESUMEN

A key factor in computational drug design is the consistency and reliability with which intermolecular interactions between a wide variety of molecules can be described. Here we present a procedure to efficiently, reliably and automatically assign partial atomic charges to atoms based on known distributions. We formally introduce the molecular charge assignment problem, where the task is to select a charge from a set of candidate charges for every atom of a given query molecule. Charges are accompanied by a score that depends on their observed frequency in similar neighbourhoods (chemical environments) in a database of previously parameterised molecules. The aim is to assign the charges such that the total charge equals a known target charge within a margin of error while maximizing the sum of the charge scores. We show that the problem is a variant of the well-studied multiple-choice knapsack problem and thus weakly NP -complete. We propose solutions based on Integer Linear Programming and a pseudo-polynomial time Dynamic Programming algorithm. We demonstrate that the results obtained for novel molecules not included in the database are comparable to the ones obtained performing explicit charge calculations while decreasing the time to determine partial charges for a molecule from hours or even days to below a second. Our software is openly available.

RESUMEN

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

Asunto(s)

Consumo de Bebidas Alcohólicas/genética , Fumar/genética , Tabaquismo/genética , Femenino , Variación Genética/genética , Estudio de Asociación del Genoma Completo/métodos , Humanos , Masculino , Persona de Mediana Edad , Fenotipo , Riesgo , Nicotiana/efectos adversos