Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross... Show morePrevious genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). 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 analysis(3), 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 approach(4), 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 ancestry(5). 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. Show less
Roessel, S. van; Strijker, M.; Steyerberg, E.W.; Groen, J.V.; Mieog, J.S.; Groot, V.P.; ... ; Besselink, M.G. 2020
Background: The objective of this study was to validate and update the Amsterdam prediction model including tumor grade, lymph node ratio, margin status and adjuvant therapy, for prediction of... Show moreBackground: The objective of this study was to validate and update the Amsterdam prediction model including tumor grade, lymph node ratio, margin status and adjuvant therapy, for prediction of overall survival (OS) after pancreatoduodenectomy for pancreatic cancer.Methods: We included consecutive patients who underwent pancreatoduodenectomy for pancreatic cancer between 2000 and 2017 at 11 tertiary centers in 8 countries (USA, UK, Germany, Italy, Sweden, the Netherlands, Korea, Australia). Model performance for prediction of OS was evaluated by calibration statistics and Uno's C-statistic for discrimination. Validation followed the TRIPOD statement.Results: Overall, 3081 patients (53% male, median age 66 years) were included with a median OS of 24 months, of whom 38% had N2 disease and 77% received adjuvant chemotherapy. Predictions of 3-year OS were fairly similar to observed OS with a calibration slope of 0.72. Statistical updating of the model resulted in an increase of the C-statistic from 0.63 to 0.65 (95% CI 0.64-0.65), ranging from 0.62 to 0.67 across different countries. The area under the curve for the prediction of 3 -year OS was 0.71 after updating. Median OS was 36, 25 and 15 months for the low, intermediate and high risk group, respectively (P < 0.001).Conclusions: This large international study validated and updated the Amsterdam model for survival prediction after pancreatoduodenectomy for pancreatic cancer. The model incorporates readily available variables with a fairly accurate model performance and robustness across different countries, while novel markers may be added in the future. The risk groups and web-based calculator www pancreascalculaior. corn may facilitate use in daily practice and future trials. (C) 2019 Elsevier Ltd, BASO The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved. Show less
Zhang, Y.; Wester, L.; He, J.; Geiger, T.; Moerkens, M.; Siddappa, R.; ... ; Water, B. van de 2018
Antiestrogen resistance in estrogen receptor positive (ER+) breast cancer is associated with increased expression and activity of insulin-like growth factor 1 receptor (IGF1R). Here, a kinome siRNA... Show moreAntiestrogen resistance in estrogen receptor positive (ER+) breast cancer is associated with increased expression and activity of insulin-like growth factor 1 receptor (IGF1R). Here, a kinome siRNA screen has identified 10 regulators of IGF1R-mediated antiestrogen with clinical significance. These include the tamoxifen resistance suppressors BMPR1B, CDK10, CDK5, EIF2AK1, and MAP2K5, and the tamoxifen resistance inducers CHEK1, PAK2, RPS6KC1, TTK, and TXK. The p21-activated kinase 2, PAK2, is the strongest resistance inducer. Silencing of the tamoxifen resistance inducing genes, particularly PAK2, attenuates IGF1R-mediated resistance to tamoxifen and fulvestrant. High expression of PAK2 in ER+ metastatic breast cancer patients is correlated with unfavorable outcome after first-line tamoxifen monotherapy. Phospho-proteomics has defined PAK2 and the PAK-interacting exchange factors PIXα/β as downstream targets of IGF1R signaling, which are independent from PI3K/ATK and MAPK/ERK pathways. PAK2 and PIXα/β modulate IGF1R signaling-driven cell scattering. Targeting PIXα/β entirely mimics the effect of PAK2 silencing on antiestrogen re-sensitization. These data indicate PAK2/PIX as an effector pathway in IGF1R-mediated antiestrogen resistance. Show less
Background Whether triglyceride-mediated pathways are causally relevant to coronary heart disease is uncertain. We studied a genetic variant that regulates triglyceride concentration to help judge... Show moreBackground Whether triglyceride-mediated pathways are causally relevant to coronary heart disease is uncertain. We studied a genetic variant that regulates triglyceride concentration to help judge likelihood of causality. Methods We assessed the -1131T>C (rs662799) promoter polymorphism of the apolipoprotein A5 (APOA5) gene in relation to triglyceride concentration, several other risk factors, and risk of coronary heart disease. We compared disease risk for genetically-raised triglyceride concentration (20 842 patients with coronary heart disease, 35 206 controls) with that recorded for equivalent differences in circulating triglyceride concentration in prospective studies (302 430 participants with no history of cardiovascular disease; 12 785 incident cases of coronary heart disease during 2.79 million person-years at risk). We analysed -1131T>C in 1795 people without a history of cardiovascular disease who had information about lipoprotein concentration and diameter obtained by nuclear magnetic resonance spectroscopy. Findings The minor allele frequency of -1131T>C was 8% (95% CI 7-9). -1131T>C was not significantly associated with several non-lipid risk factors or LDL cholesterol, and it was modestly associated with lower HDL cholesterol (mean difference per C allele 3.5% [95% CI 2.6-4.6]; 0.053 mmol/L [0.039-0.068]), lower apolipoprotein AI (1.3% [0.3-2.3]; 0.023 g/L [0.005-0.041]), and higher apolipoprotein B (3.2% [1.3-5.1]; 0.027 g/L [0.011-0.043]). By contrast, for every C allele inherited, mean triglyceride concentration was 16.0% (95% CI 12.9-18.7), or 0.25 mmol/L (0.20-0.29), higher (p=4.4x10(-24)). The odds ratio for coronary heart disease was 1.18 (95% CI 1.11-1.26; p=2.6x10(-7)) per C allele, which was concordant with the hazard ratio of 1.10 (95% CI 1.08-1.12) per 16% higher triglyceride concentration recorded in prospective studies. -1131T>C was significantly associated with higher VLDL particle concentration (mean difference per C allele 12.2 nmol/L [95% CI 7.7-16.7]; p=9.3x10(-8)) and smaller HDL particle size (0.14 nm [0.08-0.20]; p=7.0x10(-5)), factors that could mediate the effects of triglyceride. Interpretation These data are consistent with a causal association between triglyceride-mediated pathways and coronary heart disease. Show less
