Dataset Information

GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

ABSTRACT: BACKGROUND AND PURPOSE:Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack. Clinical scores do not predict the whole vascular recurrence risk; therefore, we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. METHODS:We analyzed 256 polymorphisms from 115 candidate genes in 3 patient cohorts comprising 4482 IS or transient ischemic attack patients. The discovery cohort was prospectively recruited and included 1494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score [Genotyping Reurrence Risk of Stroke]) and generated risk groups using a classification tree method. RESULTS:The analyses revealed that rs1800801 in the MGP gene (hazard ratio, 1.33; P=9×10-03), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305); however, it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS (P=3.2×10-09) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared with previous Stroke Prognosis Instrument-II score (P=0.03). CONCLUSIONS:The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population.

SUBMITTER: Fernandez-Cadenas I

PROVIDER: S-EPMC5473776 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

Fernández-Cadenas Israel I Mendióroz Maite M Giralt Dolors D Nafria Cristina C Garcia Elena E Carrera Caty C Gallego-Fabrega Cristina C Domingues-Montanari Sophie S Delgado Pilar P Ribó Marc M Castellanos Mar M Martínez Sergi S Freijo Marimar M Jiménez-Conde Jordi J Rubiera Marta M Alvarez-Sabín José J Molina Carlos A CA Font Maria Angels MA Grau Olivares Marta M Palomeras Ernest E Perez de la Ossa Natalia N Martinez-Zabaleta Maite M Masjuan Jaime J Moniche Francisco F Canovas David D Piñana Carlos C Purroy Francisco F Cocho Dolores D Navas Inma I Tejero Carlos C Aymerich Nuria N Cullell Natalia N Muiño Elena E Serena Joaquín J Rubio Francisco F Davalos Antoni A Roquer Jaume J Arenillas Juan Francisco JF Martí-Fábregas Joan J Keene Keith K Chen Wei-Min WM Worrall Bradford B Sale Michele M Arboix Adrià A Krupinski Jerzy J Montaner Joan J

Stroke 20170414 5

<h4>Background and purpose</h4>Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack. Clinical scores do not predict the whole vascular recurrence risk; therefore, we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS.<h4>Methods</h4>We analyzed 256 polymorphisms from 115 candidate genes in 3 patient cohorts comprising 4482 IS or transient ischemic attack patients. ...[more]

PMID: 28411264

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Project description:Background and purposeFor survivors of oral anticoagulation therapy (OAT)-associated intracerebral hemorrhage (OAT-ICH) who are at high risk for thromboembolism, the benefits of OAT resumption must be weighed against increased risk of recurrent hemorrhagic stroke. The ε2/ε4 alleles of the apolipoprotein E (APOE) gene, MRI-defined cortical superficial siderosis, and cerebral microbleeds are the most potent risk factors for recurrent ICH. We sought to determine whether combining MRI markers and APOE genotype could have clinical impact by identifying ICH survivors in whom the risks of OAT resumption are highest.MethodsJoint analysis of data from 2 longitudinal cohort studies of OAT-ICH survivors: (1) MGH-ICH study (Massachusetts General Hospital ICH) and (2) longitudinal component of the ERICH study (Ethnic/Racial Variations of Intracerebral Hemorrhage). We evaluated whether MRI markers and APOE genotype predict ICH recurrence. We then developed and validated a combined APOE-MRI classification scheme to predict ICH recurrence, using Classification and Regression Tree analysis.ResultsCortical superficial siderosis, cerebral microbleed, and APOE ε2/ε4 variants were independently associated with ICH recurrence after OAT-ICH (all P<0.05). Combining APOE genotype and MRI data resulted in improved prediction of ICH recurrence (Harrell C: 0.79 versus 0.55 for clinical data alone, P=0.033). In the MGH (training) data set, CSS, cerebral microbleed, and APOE ε2/ε4 stratified likelihood of ICH recurrence into high-, medium-, and low-risk categories. In the ERICH (validation) data set, yearly ICH recurrence rates for high-, medium-, and low-risk individuals were 6.6%, 2.5%, and 0.9%, respectively, with overall area under the curve of 0.91 for prediction of recurrent ICH.ConclusionsCombining MRI and APOE genotype stratifies likelihood of ICH recurrence into high, medium, and low risk. If confirmed in prospective studies, this combined APOE-MRI classification scheme may prove useful for selecting individuals for OAT resumption after ICH.

Project description:Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P<0.001), higher mitotic score (1 versus 3, P<0.001), and lower Allred scores for estrogen and progesterone receptors (P = 0.002, 0.008). High Ki67 indices were also significantly correlated with higher Oncotype DX risk-of-recurrence group (low versus high, P<0.001). Ki67 index was the major contributor to a machine learning model which, when trained solely on clinico-pathological data and Ki67 scores, identified Oncotype DX high- and low-risk patients with 97% accuracy, 98% sensitivity and 80% specificity. Automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy, in a manner that integrates readily into the workflow of a pathology laboratory. Furthermore, automated Ki67 scores contribute significantly to models that predict risk of recurrence in breast cancer.

Dataset Information

GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

Publications

GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

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