Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Northwestern Argentina: a center of genetic diversity of Lemon Verbena (Aloysia citriodora Paláu, Verbenaceae)

The aerial parts of lemon verbena (Aloysia citriodora Paláu) are worldwide used due to their medicinal and aromatic properties. The essential‐oil and acteoside contents have been proposed as the main quality markers for their pharmacological and organoleptic features. The northwestern region of Argentina has been repeatedly proposed as the place of origin for this species. For this reason, the essential‐oil yields and chemical compositions of leaves of 25 populations of lemon verbena from both wild collections and experimental crops from this region were studied. Plants from six different collections were subsequently grown on the same experimental parcel located at Cerrillos, Salta province, during more than seven years. In addition, the acteoside contents determined in all the samples collected in 2010 showed significant variations (from 0.5 to 4.0%). Large differences were observed in the essential‐oil composition and yields, which ranged from 0.4 to 2.1% (v/w). Nevertheless, most of the samples complied with the European Pharmacopoeia specifications. A remarkable chemical diversity with at least four clearly defined chemotypes was detected in this region. Therefore, it would be urgent to encourage actions to protect these genotypes of lemon verbena in the northwestern Argentina.EEA SaltaFil: Di Leo Lira, Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; ArgentinaFil: van Baren, Catalina María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; ArgentinaFil: López, Simón. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Molina, Ana C. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Heit, Cecilia I. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Viturro, Carmen Ines. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Perotti de Lampasona, Marina Elvira. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; ArgentinaFil: Catalan, Cesar Atilio Nazareno. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Química del Noroeste. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia. Instituto de Química del Noroeste; ArgentinaFil: Bandoni, Arnaldo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; Argentin

Essential oil chemotypes of Aloysia citrodora (Verbenaceae) in Northwestern Argentina

Chemical biodiversity of essential oils of natural populations of Aloysia citrodora Palau (“lemon verbena”, “cedrón”) in Northwestern Argentina was assessed by collecting in the same sites through different years. A total of 36 samples were collected in the Provinces of Salta (El Maray, La Paya, El Sunchal, El Alisal, Chorrillos), Jujuy (Chilcayo, San Roque), Catamarca (Mutquin, Colana) and Tucumán (Amaicha del Valle) in Argentina. Essential oils were obtained by hydrodistillation (Clevenger) of naturally air-dried plant material. Yields ranged from 0.16% to 1.93% (v/w), being the highest those of the collections of Mutquin. More than 65 compounds were identified by CG-FID-MS. Only 19 of these constituents, accounting from 77.3 to 98.9% of the total oil, present in more than 4.0% in at least one sample, were considered as variables for statistical analysis. Agglomerative Hierarchical Cluster analysis was conducted, showing at 65% of similarity, five groups. This grouping was in direct accordance to the biosynthetic pathways of main compounds (chemotypes). In the two sites of Jujuy, 21 collections evidenced four different chemotypes, named after the dominant component as follows: thujones, citronellal, carvone, and citral (neral + geranial). In the populations of Salta and Catamarca, linalool appeared as a new different chemotype. Though cedron is considered as a citral-bearing plant, curiously, in the 36 samples collected in the NW of Argentina, only two samples contained citral as main constituent. On the other hand, a dominance of citronellal and thujones compositions were found in the bulk of the samples collected, while others had very high content of linalool or carvone and its derivatives. Northwestern Argentina has repeatedly been mentioned as the center of biodiversity of this species. The new evidences found on the chemical biodiversity of essential oils of Aloysia citrodora in natural populations in this region, reinforce firmly this idea.Instituto de Recursos BiológicosFil: Elechosa, Miguel Angel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Di Leo Lira, Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; ArgentinaFil: Juarez, Miguel Angel. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Viturro, Carmen Ines. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Heit, Cecilia I.. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Molina, Ana C. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Martinez, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: López, Simón. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Molina, Ana Maria. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: van Baren, Catalina María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; ArgentinaFil: Bandoni, Arnaldo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Química y Metabolismo del Fármaco. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Química y Metabolismo del Fármaco; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Farmacología. Cátedra de Farmacognosia; Argentin

Characterization of large structural genetic mosaicism in human autosomes

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.Some individuals, studies, and centers received individual support. The grant numbers are: Addiction (U01HG004422, NIAAA: U10AA008401, NCI: P01CA089392, NIDA: R01DA013423, R01DA019963); Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (U.S. Public Health Service contracts: N01-CN-45165, N01-RC-45035, N01-RC-37004, NCI contract: HHSN261201000006C); Birth weight (U01HG004415); Blood clotting (R37 HL 039693); Broad Center for Genotyping and Analysis (U01HG04424); Cancer Prevention Study-II (American Cancer Society); Center for Inherited Disease Research (U01HG004438, HHSN268200782096C); Cleft lip/palate (NIDCR: U01DE018993 and R01DE016148, NIH contract: HHSN268200782096C); Dental Caries (NIDCR:U01DE018903 and R01DE014899, NIH CIDR contract: HHSN268200-782096C); Endometrial cancer (R01 CA134958); Fudan Lung Cancer Study (Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); National S&T Major Special Project (2011ZX09102-010-01); China National High-Tech Research and Development Program (2012AA02A517, 2012AA02A518); National Science Foundation of China (30890034); National Basic Research Program (2012CB944600); Scientific and Technological Support Plans from Jiangsu Province (BE2010715)); Gene-Environment Association Studies (Coordinating Center :U01 HG004446, Manuscript preparation: P01-GM099568); Genes and Environment in Lung Cancer, Singapore Study (National Medical Research Council Singapore grant (NMRC/0897/2004, NMRC/1075/2006); Agency for Science, Technology and Research (A*STAR) of Singapore); Genetic Epidemiological Study of Lung Adenocarcinoma (National Research Program on Genomic Medicine in Taiwan (DOH98-TD-G-111-015); National Research Program for Biopharmaceuticals in Taiwan (DOH 100-TD-PB-111-TM013); National Science Council,Taiwan (NSC 100-2319-B-400-001)); Glaucoma (NHGRI: U01HG004728, NEI: R01EY015473, NEI: R01EY015872, Harvard Medical School Distinguished Ophthalmology Scholar Award: Louis Pasquale); Guangdong Study (Foundation of Guangdong Science and Technology Department (2006B60101010, 2007A032000002, 2011A030400010); Guangzhou Science and Information Technology Bureau (2011Y2-00014); Chinese Lung Cancer Research Foundation; National Natural Science Foundation of China (81101549); Natural Science Foundation of Guangdong Province (S2011010000792)); Health Professionals Follow-up Study (UM1 CA167552, R01 HL35464); Hong Kong Study (General Research Fund of Research Grant Council, Hong Kong (781511M)); Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH; Intramural Research Program of the NIH, National Library of Medicine; Intramural Research Program of the National Institute for Occupational Safety and Health; Japanese Female Lung Cancer Collaborative Study (Grants-in-Aid from the Ministry of Health, Labor, and Welfare for Research on Applying Health Technology and for the 3rd-term Comprehensive 10-year Strategy for Cancer Control; National Cancer Center Research and Development Fund; Grant-in-Aid for Scientific Research on Priority Areas and on Innovative Area from the Ministry of Education, Science, Sports, Culture and Technology of Japan; NCI (R01-CA121210)); Lung cancer (Z01CP010200); Lung health (U01HG004738); Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); Melanoma (NCI R29CA70334, R01CA100264, P50CA093459); NLCS (China National High-Tech Research and Development Program Grant (2009AA022705); Priority Academic Program Development of Jiangsu Higher Education Institution; National Key Basic Research Program Grant (2011CB503805)); Nurses’ Health Study (P01 CA87969, R01 CA49449); Nurses’ Health Study II (UM1 CA176726, R01, 67262); OpPancreatic cancer (Mayo Clinic SPORE in Pancreatic Cancer: P50CA102701); Prematurity (U01HG004423); Prostate cancer (U01HG004726, NCI: CA63464, CA54281, CA1326792, RC2 CA148085); Shanghai Women’s Health Cohort Study (National Institutes of Health (R37 CA70867); National Cancer Institute intramural research program; NCI Intramural Research Program contract (N02 CP1101066)); Shenyang Lung Cancer Study (National Nature Science Foundation of China (81102194); Liaoning Provincial Department of Education (LS2010168); China Medical Board (00726)); Singapore Chinese Health Study (NIH grants: NCI R01 CA55069, R35 CA53890, R01 CA80205, and R01 CA144034); South Korea Multi-Center Lung Cancer Study (National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2011-0016106); National R&D Program for Cancer Control, Ministry of Health &Welfare, Republic of Korea (0720550-2); (A010250)); Tianjin Lung Cancer Study (Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT); China (IRT1076), Tianjin Cancer Institute and Hospital, National Foundation for Cancer Research US); Venous thromboembolism (U01HG004735); Wuhan lung cancer study (National Key Basic Research and Development Program (2011CB503800)) and Yunnan Lung Cancer Study (Intramural program of U.S. National Institutes of Health; National Cancer Institute). Additionally, K.C.B. was supported in part by the Mary Beryl Patch Turnbull Scholar Program. The GENEVA consortium thanks the participants and the staff of all GENEVA studies for their important contributions. Support for the GENEVA genome-wide association studies was provided through the NIH Genes, Environment and Health Initiative (GEI)

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits