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Sandra Sanchez-Roige

Bio: Sandra Sanchez-Roige is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Genome-wide association study & Medicine. The author has an hindex of 28, co-authored 79 publications receiving 2904 citations. Previous affiliations of Sandra Sanchez-Roige include Autonomous University of Barcelona & Vanderbilt University Medical Center.


Papers
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Journal ArticleDOI
TL;DR: The largest genome-wide association study to date of DSM-IV-diagnosed AD found loci associated with AD and characterized the relationship between AD and other psychiatric and behavioral outcomes, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Abstract: Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

434 citations

Journal ArticleDOI
Richard Karlsson Linnér1, Richard Karlsson Linnér2, Pietro Biroli3, Edward Kong4, S. Fleur W. Meddens2, S. Fleur W. Meddens1, Robbee Wedow, Mark Alan Fontana5, Mark Alan Fontana6, Maël Lebreton7, Stephen P. Tino8, Abdel Abdellaoui1, Anke R. Hammerschlag1, Michel G. Nivard1, Aysu Okbay1, Cornelius A. Rietveld2, Pascal Timshel9, Pascal Timshel10, Maciej Trzaskowski11, Ronald de Vlaming1, Ronald de Vlaming2, Christian L. Zund3, Yanchun Bao12, Laura Buzdugan3, Laura Buzdugan13, Ann H. Caplin, Chia-Yen Chen4, Chia-Yen Chen14, Peter Eibich15, Peter Eibich16, Peter Eibich17, Pierre Fontanillas, Juan R. González18, Peter K. Joshi19, Ville Karhunen20, Aaron Kleinman, Remy Z. Levin21, Christina M. Lill22, Gerardus A. Meddens, Gerard Muntané18, Gerard Muntané23, Sandra Sanchez-Roige21, Frank J. A. van Rooij2, Erdogan Taskesen1, Yang Wu11, Futao Zhang11, Adam Auton, Jason D. Boardman24, David W. Clark19, Andrew Conlin20, Conor C. Dolan1, Urs Fischbacher25, Patrick J. F. Groenen2, Kathleen Mullan Harris26, Gregor Hasler27, Albert Hofman4, Albert Hofman2, Mohammad Arfan Ikram2, Sonia Jain21, Robert Karlsson28, Ronald C. Kessler4, Maarten Kooyman, James MacKillop29, James MacKillop30, Minna Männikkö20, Carlos Morcillo-Suarez18, Matthew B. McQueen24, Klaus M. Schmidt31, Melissa C. Smart12, Matthias Sutter16, Matthias Sutter32, Matthias Sutter33, Roy Thurik2, André G. Uitterlinden2, Jon White34, Harriet de Wit35, Jian Yang11, Lars Bertram22, Lars Bertram36, Dorret I. Boomsma1, Tõnu Esko37, Ernst Fehr3, David A. Hinds, Magnus Johannesson38, Meena Kumari12, David Laibson4, Patrik K. E. Magnusson28, Michelle N. Meyer39, Arcadi Navarro18, Arcadi Navarro40, Abraham A. Palmer21, Tune H. Pers9, Tune H. Pers10, Danielle Posthuma1, Daniel Schunk41, Murray B. Stein21, Rauli Svento20, Henning Tiemeier2, Paul R. H. J. Timmers19, Patrick Turley4, Patrick Turley14, Patrick Turley42, Robert J. Ursano43, Gert G. Wagner15, Gert G. Wagner16, James F. Wilson19, James F. Wilson44, Jacob Gratten11, Jacob Gratten45, James J. Lee46, David Cesarini47, Daniel J. Benjamin48, Daniel J. Benjamin42, Philipp Koellinger15, Philipp Koellinger1, Jonathan P. Beauchamp8 
TL;DR: This paper found evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of their other GWAS, and general risk-tolerance is genetically correlated with a range of risky behaviors.
Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

395 citations

Journal ArticleDOI
TL;DR: A GWAS of lifetime cannabis use reveals new risk loci, shows that cannabis use has genetic overlap with smoking and alcohol use, and indicates that the likelihood of initiating cannabis use is causally influenced by schizophrenia.
Abstract: Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

365 citations

Journal ArticleDOI
TL;DR: In this article, a genome-wide association analysis was performed to identify genetic variants associated with alcohol use disorders, which are common conditions that have enormous social and economic consequences, such as high blood cholesterol, obesity, and heart disease.
Abstract: Objective:Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated wi...

259 citations

Journal ArticleDOI
TL;DR: A genetic study of problematic alcohol use in 435,563 individuals, including data from the Million Veteran Program, Psychiatric Genomics Consortium and UK Biobank, found many novel risk loci and provided new insights into trait biology.
Abstract: Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.

195 citations


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01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

4,409 citations

01 Jan 2010
TL;DR: In this paper, the authors show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait, revealing patterns with important implications for genetic studies of common human diseases and traits.
Abstract: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

1,751 citations

Journal ArticleDOI
TL;DR: While ACE2 is essential for viral invasion, there is no evidence that ACE inhibitors or angiotensin receptor blockers (ARBs) worsen prognosis, Hence, patients should not discontinue their use.
Abstract: The novel coronavirus disease (COVID-19) outbreak, caused by SARS-CoV-2, represents the greatest medical challenge in decades. We provide a comprehensive review of the clinical course of COVID-19, its comorbidities, and mechanistic considerations for future therapies. While COVID-19 primarily affects the lungs, causing interstitial pneumonitis and severe acute respiratory distress syndrome (ARDS), it also affects multiple organs, particularly the cardiovascular system. Risk of severe infection and mortality increase with advancing age and male sex. Mortality is increased by comorbidities: cardiovascular disease, hypertension, diabetes, chronic pulmonary disease, and cancer. The most common complications include arrhythmia (atrial fibrillation, ventricular tachyarrhythmia, and ventricular fibrillation), cardiac injury [elevated highly sensitive troponin I (hs-cTnI) and creatine kinase (CK) levels], fulminant myocarditis, heart failure, pulmonary embolism, and disseminated intravascular coagulation (DIC). Mechanistically, SARS-CoV-2, following proteolytic cleavage of its S protein by a serine protease, binds to the transmembrane angiotensin-converting enzyme 2 (ACE2) -a homologue of ACE-to enter type 2 pneumocytes, macrophages, perivascular pericytes, and cardiomyocytes. This may lead to myocardial dysfunction and damage, endothelial dysfunction, microvascular dysfunction, plaque instability, and myocardial infarction (MI). While ACE2 is essential for viral invasion, there is no evidence that ACE inhibitors or angiotensin receptor blockers (ARBs) worsen prognosis. Hence, patients should not discontinue their use. Moreover, renin-angiotensin-aldosterone system (RAAS) inhibitors might be beneficial in COVID-19. Initial immune and inflammatory responses induce a severe cytokine storm [interleukin (IL)-6, IL-7, IL-22, IL-17, etc.] during the rapid progression phase of COVID-19. Early evaluation and continued monitoring of cardiac damage (cTnI and NT-proBNP) and coagulation (D-dimer) after hospitalization may identify patients with cardiac injury and predict COVID-19 complications. Preventive measures (social distancing and social isolation) also increase cardiovascular risk. Cardiovascular considerations of therapies currently used, including remdesivir, chloroquine, hydroxychloroquine, tocilizumab, ribavirin, interferons, and lopinavir/ritonavir, as well as experimental therapies, such as human recombinant ACE2 (rhACE2), are discussed.

1,060 citations

Journal ArticleDOI
TL;DR: This Review comprehensively assess the benefits and limitations of GWAS in human populations and discusses the relevance of performing more GWAS, with a focus on the cardiometabolic field.
Abstract: Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype–phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS. Despite the success of human genome-wide association studies (GWAS) in associating genetic variants and complex diseases or traits, criticisms of the usefulness of this study design remain. This Review assesses the pros and cons of GWAS, with a focus on the cardiometabolic field.

1,002 citations