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Träfflista för sökning "WFRF:(Chong S S) srt2:(2015-2019)"

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1.	Thomas, HS, et al. (author) 2019 swepub:Mat__t
2.	Bhangu, A, et al. (author) Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study 2018 In: The Lancet. Infectious diseases. - : Elsevier. - 1474-4457 .- 1473-3099. ; 18:5, s. 516-525 Journal article (peer-reviewed)
3.	Bhangu, A, et al. (author) Mortality of emergency abdominal surgery in high-, middle- and low-income countries 2016 In: The British journal of surgery. - : Oxford University Press (OUP). - 1365-2168 .- 0007-1323. ; 103:8, s. 971-988 Journal article (peer-reviewed)
4.	Franceschini, N., et al. (author) GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes 2018 In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1 Journal article (peer-reviewed)abstract Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans. © 2018, The Author(s).
5.	2019 Journal article (peer-reviewed)
6.	Ruderfer, DM, et al. (author) Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes 2018 In: Cell. - : Elsevier BV. - 1097-4172 .- 0092-8674. ; 173:7, s. 1705- Journal article (peer-reviewed)
7.	Klionsky, Daniel J, et al. (author) Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition). 2016 In: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 12:1, s. 1-222 Journal article (peer-reviewed)
8.	Bancroft, EK, et al. (author) Psychosocial impact of undergoing prostate cancer screening for men with BRCA1 or BRCA2 mutations 2019 In: BJU international. - : Wiley. - 1464-410X .- 1464-4096. ; 123:2, s. 284-292 Journal article (peer-reviewed)
9.	Aung, T, et al. (author) Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci 2017 In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 49:7, s. 993- Journal article (peer-reviewed)
10.	Chauhan, G., et al. (author) Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting 2019 In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 92:5 Journal article (peer-reviewed)abstract ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 x 10(-8); and LINC00539/ZDHHC20, p = 5.82 x 10(-9). Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p([BI]) = 9.38 x 10(-25); p([SSBI]) = 5.23 x 10(-14) for hypertension), smoking (p([BI]) = 4.4 x 10(-10); p([SSBI]) = 1.2 x 10(-4)), diabetes (p([BI]) = 1.7 x 10(-8); p([SSBI]) = 2.8 x 10(-3)), previous cardiovascular disease (p([BI]) = 1.0 x 10(-18); p([SSBI]) = 2.3 x 10(-7)), stroke (p([BI]) = 3.9 x 10(-69); p([SSBI]) = 3.2 x 10(-24)), and MRI-defined white matter hyperintensity burden (p([BI]) = 1.43 x 10(-157); p([SSBI]) = 3.16 x 10(-106)), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

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Type of publication: journal article (68); conference paper (11)

Type of content: peer-reviewed (78); other academic/artistic (1)

Author/Editor: Stefansson, K (8); Qi, Chong (8); Dichgans, M (7); Trompet, S (7); Grahn, T. (7); Julin, R. (7); show more...; Juutinen, S. (7); Pakarinen, J. (7); Rahkila, P. (7); Sarén, J. (7); Scholey, C. (7); Uusitalo, J. (7); Salomaa, V (7); Rosand, J. (7); Sharma, P. (6); Seshadri, S (6); Chauhan, G (6); Rundek, T (6); Amouyel, P (6); Gudnason, V (6); Hofman, A (6); Schmidt, R (6); Fornage, M (6); Debette, S (6); Lemmens, R. (6); Malik, R (6); Lindgren, Arne (6); Leino, M. (6); Traylor, M (6); Greenlees, P. T. (6); Sorri, J. (6); Slowik, A. (6); Williams, S. (5); Hassan, A (5); Jern, Christina, 196 ... (5); Melander, Olle (5); Smart, NJ (5); Pellino, G (5); Psaty, BM (5); Tzourio, C (5); Launer, LJ (5); Qi, Chong, 1983- (5); Sandzelius, M. (5); Rice, K. (5); Taylor, A (5); Lee, P. (5); Thorleifsson, G (5); Page, R. D. (5); Kato, N. (5); Sargurupremraj, M. (5); show less...

University: Karolinska Institutet (37); Royal Institute of Technology (20); Lund University (16); University of Gothenburg (11); Umeå University (10); Uppsala University (7); show more...; Linköping University (6); Chalmers University of Technology (5); Örebro University (4); Stockholm University (2); Jönköping University (2); University of Skövde (2); Swedish University of Agricultural Sciences (2); Luleå University of Technology (1); Halmstad University (1); Högskolan Dalarna (1); show less...

Language: English (80)

Research subject (UKÄ/SCB): Medical and Health Sciences (34); Natural sciences (27); Engineering and Technology (11); Agricultural Sciences (1); Social Sciences (1)

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