scholarly journals Polygenic Risk Scores for Predicting Adverse Outcomes After Coronary Revascularization

Author(s):  
Jenni Aittokallio ◽  
Anni Kauko ◽  
Felix Vaura ◽  
Veikko Salomaa ◽  
Tuomas Kiviniemi ◽  
...  
2012 ◽  
Vol 15 (3) ◽  
pp. 164 ◽  
Author(s):  
Miralem Pasic ◽  
Stephan Dreysse ◽  
Evgenij Potapov ◽  
Axel Unbehaun ◽  
Semih Buz ◽  
...  

We report on successful emergency transcatheter aortic valve implantation combined with percutaneous coronary revascularization in a polymorbid and preterminal patient in profound cardiogenic shock and with multiorgan failure. The risk scores were almost unbelievably high (Society of Thoracic Surgeons mortality score, 83.9%; Society of Thoracic Surgeons morbidity and mortality score, 96.8%; logistic EuroSCORE, 96.7%). Two and a half years after the procedure, the patient is doing very well.


Author(s):  
Leah Zilversmit Pao ◽  
Emily W. Harville ◽  
Jeffrey K. Wickliffe ◽  
Arti Shankar ◽  
Pierre Buekens

Metals, stress, and sociodemographics are commonly studied separately for their effects on birth outcomes, yet often jointly contribute to adverse outcomes. This study analyzes two methods for measuring cumulative risk to understand how maternal chemical and nonchemical stressors may contribute to small for gestational age (SGA). SGA was calculated using sex-specific fetal growth curves for infants of pregnant mothers (n = 2562) enrolled in the National Institute of Child Health and Human Development (NICHD) Fetal Growth Study. The exposures (maternal lead, mercury, cadmium, Cohen’s perceived stress, Edinburgh depression scores, race/ethnicity, income, and education) were grouped into three domains: metals, psychosocial stress, and sociodemographics. In Method 1 we created cumulative risk scores using tertiles. Method 2 employed weighted quantile sum (WQS) regression. For each method, logistic models were built with three exposure domains individually and race/ethnicity, adjusting for age, parity, pregnancy weight gain, and marital status. The adjusted effect of overall cumulative risk with three domains, was also modeled using each method. Sociodemographics was the only exposure associated with SGA in unadjusted models ((odds ratio) OR: 1.35, 95% (confidence interval) CI: 1.08, 1.68). The three cumulative variables in adjusted models were not significant individually, but the overall index was associated with SGA (OR: 1.17, 95% CI: 1.02, 1.35). In the WQS model, only the sociodemographics domain was significantly associated with SGA. Sociodemographics tended to be the strongest risk factor for SGA in both risk score and WQS models.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 286-286
Author(s):  
Anatoliy Yashin ◽  
Dequing Wu ◽  
Konstantin Arbeev ◽  
Arseniy Yashkin ◽  
Galina Gorbunova ◽  
...  

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.


2021 ◽  
Author(s):  
Alexander S. Hatoum ◽  
Emma C. Johnson ◽  
David A. A. Baranger ◽  
Sarah E. Paul ◽  
Arpana Agrawal ◽  
...  

2021 ◽  
pp. 1-8
Author(s):  
Michael Wainberg ◽  
Peter Zhukovsky ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
Aristotle Voineskos ◽  
...  

Abstract Background Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. Methods This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or ‘symptom dimensions’ via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. Results Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. Conclusions An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.


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