scholarly journals Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs

2020 ◽  
Vol 7 ◽  
Author(s):  
Apurva Shrivastava ◽  
Tina Haase ◽  
Tanja Zeller ◽  
Christian Schulte
Keyword(s):  
Heart Failure ◽  
Cardiac Function ◽  
Clinical Application ◽  
Complex Disease ◽  
Disease Risk ◽  
High Sensitivity ◽  
Risk Scores ◽  
Circular Rnas ◽  
True Value ◽  
Non Coding Rnas

Heart failure (HF) is a complex disease in which cardiomyocyte injury leads to a cascade of inflammatory and fibrosis pathway activation, thereby causing decrease in cardiac function. As a result, several biomolecules are released which can be identified easily in circulating body fluids. The complex biological processes involved in the development and worsening of HF require an early treatment strategy to stop deterioration of cardiac function. Circulating biomarkers provide not only an ideal platform to detect subclinical changes, their clinical application also offers the opportunity to monitor disease treatment. Many of these biomarkers can be quantified with high sensitivity; allowing their clinical application to be evaluated beyond diagnostic purposes as potential tools for HF prognosis. Though the field of biomarkers is dominated by protein molecules, non-coding RNAs (microRNAs, long non-coding RNAs, and circular RNAs) are novel and promising biomarker candidates that encompass several ideal characteristics required in the biomarker field. The application of genetic biomarkers as genetic risk scores in disease prognosis, albeit in its infancy, holds promise to improve disease risk estimation. Despite the multitude of biomarkers that have been available and identified, the majority of novel biomarker candidates are not cardiac-specific, and instead may simply be a readout of systemic inflammation or other pathological processes. Thus, the true value of novel biomarker candidates in HF prognostication remains unclear. In this article, we discuss the current state of application of protein, genetic as well as non-coding RNA biomarkers in HF risk prognosis.

scholarly journals CircRNAs and their regulatory roles in cancers

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Mei Tao ◽  
Ming Zheng ◽  
Yanhua Xu ◽  
Shuo Ma ◽  
Weiwei Zhang ◽  
...  
Keyword(s):  
Nuclear Export ◽  
Mrna Translation ◽  
High Sensitivity ◽  
Detection Methods ◽  
Circular Rnas ◽  
Rnase L ◽  
Circular Structure ◽  
Dynamic Modification ◽  
Non Coding Rnas

AbstractCircular RNAs (circRNAs), a novel type of non-coding RNAs (ncRNAs), have a covalently closed circular structure resulting from pre-mRNA back splicing via spliceosome and ribozymes. They can be classified differently in accordance with different criteria. As circRNAs are abundant, conserved, and stable, they can be used as diagnostic markers in various diseases and targets to develop new therapies. There are various functions of circRNAs, including sponge for miR/proteins, role of scaffolds, templates for translation, and regulators of mRNA translation and stability. Without m7G cap and poly-A tail, circRNAs can still be degraded in several ways, including RNase L, Ago-dependent, and Ago-independent degradation. Increasing evidence indicates that circRNAs can be modified by N-6 methylation (m6A) in many aspects such as biogenesis, nuclear export, translation, and degradation. In addition, they have been proved to play a regulatory role in the progression of various cancers. Recently, methods of detecting circRNAs with high sensitivity and specificity have also been reported. This review presents a detailed overview of circRNAs regarding biogenesis, biomarker, functions, degradation, and dynamic modification as well as their regulatory roles in various cancers. It’s particularly summarized in detail in the biogenesis of circRNAs, regulation of circRNAs by m6A modification and mechanisms by which circRNAs affect tumor progression respectively. Moreover, existing circRNA detection methods and their characteristics are also mentioned.

scholarly journals Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jiangming Sun ◽  
Yunpeng Wang ◽  
Lasse Folkersen ◽  
Yan Borné ◽  
Inge Amlien ◽  
...  
Keyword(s):  
Risk Prediction ◽  
Complex Disease ◽  
Disease Risk ◽  
Disease Status ◽  
Risk Scores ◽  
Correct Prediction ◽  
Confidence Bounds ◽  
Conformal Prediction ◽  
Polygenic Risk ◽  
Individual Level

AbstractA promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease research. However, the application of PRS as a tool for predicting an individual’s disease susceptibility in a clinical setting is challenging because PRS typically provide a relative measure of risk evaluated at the level of a group of people but not at individual level. Here, we introduce a machine-learning technique, Mondrian Cross-Conformal Prediction (MCCP), to estimate the confidence bounds of PRS-to-disease-risk prediction. MCCP can report disease status conditional probability value for each individual and give a prediction at a desired error level. Moreover, with a user-defined prediction error rate, MCCP can estimate the proportion of sample (coverage) with a correct prediction.

scholarly journals Utility of polygenic embryo screening for disease depends on the selection strategy

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Todd Lencz ◽  
Daniel Backenroth ◽  
Einat Granot-Hershkovitz ◽  
Adam Green ◽  
Kyle Gettler ◽  
...  
Keyword(s):  
Complex Disease ◽  
Disease Risk ◽  
Threshold Model ◽  
Absolute Risk ◽  
Risk Scores ◽  
Selection Strategy ◽  
Case Control Studies ◽  
Disease Case ◽  
The Impact

Polygenic risk scores (PRSs) have been offered since 2019 to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. Here we predict, based on the liability threshold model, the expected reduction in complex disease risk following polygenic embryo screening for a single disease. A strong determinant of the potential utility of such screening is the selection strategy, a factor that has not been previously studied. When only embryos with a very high PRS are excluded, the achieved risk reduction is minimal. In contrast, selecting the embryo with the lowest PRS can lead to substantial relative risk reductions, given a sufficient number of viable embryos. We systematically examine the impact of several factors on the utility of screening, including: variance explained by the PRS, number of embryos, disease prevalence, parental PRSs, and parental disease status. We consider both relative and absolute risk reductions, as well as population-averaged and per-couple risk reductions, and also examine the risk of pleiotropic effects. Finally, we confirm our theoretical predictions by simulating ‘virtual’ couples and offspring based on real genomes from schizophrenia and Crohn’s disease case-control studies. We discuss the assumptions and limitations of our model, as well as the potential emerging ethical concerns.

scholarly journals Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories

2020 ◽  
Author(s):  
Ricky Lali ◽  
Michael Chong ◽  
Arghavan Omidi ◽  
Pedrum Mohammadi-Shemirani ◽  
Ann Le ◽  
...  
Keyword(s):  
Rare Variant ◽  
Genetic Risk ◽  
Complex Disease ◽  
Rare Variants ◽  
Disease Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Considerable Proportion ◽  
Asian Populations ◽  
Artery Disease

ABSTRACTRare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesized that rare variant burden over a large number of genes can be combined into predictive rare variant genetic risk score (RVGRS). We propose a novel method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A RVGRS was found to strongly associate with coronary artery disease (CAD) in European and South Asian populations. Calibrated RVGRS capture the aggregate effect of rare variants through a polygenic model of inheritance, identifies 1.5% of the population with substantial risk of early CAD, and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and common variant gene scores.

Abstract 13386: Individualized Risk Score Interpretation to Aid Clinical Decisions and Transitions of Care for Acute Heart Failure Patients

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Claire Y Zhao
Keyword(s):  
Heart Failure ◽  
Decision Making ◽  
Acute Heart Failure ◽  
Risk Score ◽  
Complex Disease ◽  
Adverse Outcomes ◽  
Transitions Of Care ◽  
Risk Scores ◽  
Clinical Decisions ◽  
Clinical Measurements

Acute heart failure (AHF) is a complex disease with heterogeneous manifestations and adverse outcomes. The interpretation of machine-learning risk scores is vital to support clinical decisions. Individualized Feature Importance (IFI) was designed to attribute changes in risk scores to clinical features and help contrast decision trajectory for a patient against those of patient subgroups that received distinct clinical decisions. Score Confidence Interval (SCI) was developed to quantify certainty in the prediction, which further encourages clinicians’ interpretation. Study was based on retrospective data from 25 hospitals in the US of 20,640 adult patients, with 87% discharged home (Class 0) and 13% transferred to the ICU or died in hospital (Class 1). IFI is based on Shapley Value, based on which SCI was designed to capture the variation in score if input features are missing. These methods were applied to previously developed risk score for AHF patients in the wards; however, they can be applied to any risk score. The SCI is wide at the beginning of the stay and narrows down towards the end as more clinical measurements become available, indicating the risk score is relatively certain at the end (Fig. 1a). IFI values (Fig. 1b) show how selected features drive changes in the risk score. To aid decision-making at the latest time, top missing features are prompted (Fig. 1c). Decision trajectories show the way top features drive the risk score (Fig. 1d), that this patient is at higher risk to discharge (Fig. 1e) and is more similar to ICU-transfers (Fig. 1f). Fig. 1g shows SCI improves risk score performance by abstaining uncertain cases from decision-making. IFI apportions risk score to clinical measurements. SCI reduces false alarm rates. By providing clinical context, they have the potential to enhance incorporation of risk scores in the clinical workflow to aid medical decisions by identifying patients at risk for deterioration and determining appropriate levels of care.

scholarly journals Significance of non-coding circular RNAs and micro RNAs in the pathogenesis of cardiovascular diseases

2018 ◽  
Vol 55 (11) ◽  
pp. 713-720 ◽  
Author(s):  
Guoan Zhao
Keyword(s):  
Heart Failure ◽  
Cardiovascular Diseases ◽  
Regulation Of Gene Expression ◽  
Renin Angiotensin System ◽  
Genomic Research ◽  
Circular Rnas ◽  
Surgical Interventions ◽  
Novel Treatments ◽  
Micro Rnas ◽  
Non Coding Rnas

Heart failure, coronary artery disease and myocardial infarction are the most prominent cardiovascular diseases contributing significantly to death worldwide. In the majority of situations, except for surgical interventions and transplantation, there are no reliable therapeutic approaches available to address these health problem. Despite several advances that led to the development of biomarkers and therapies based on the renin–angiotensin system, adrenergic pathways, etc, more definitive and consistent biomarkers and specific target based molecular therapies are still being sought. Recent advances in the field of genomic research has helped in identifying non-coding RNAs, including circular RNAs, piRNAs, micro RNAs, and long non-coding RNAs, that play a significant role in the regulation of gene expression and function and have direct impact on pathophysiological mechanisms. This new knowledge is currently being explored with much hope for the development of novel treatments and biomarkers. Circular RNAs and micro RNAs have been described in myocardium and aortic valves and were shown to be involved in the regulation of pathophysiological processes that potentially contribute to cardiovascular diseases. Approximately 32 000 human exonic circular RNAs have been catalogued and their functions are still being ascertained. In the heart, circular RNAs were shown to bind micro RNAs in a specific manner and regulate the expression of transcription factors and stress response genes, and expression of these non-coding RNAs were found to change in conditions such as cardiac hypertrophy, heart failure and cardiac remodelling, reflecting their significance as diagnostic and prognostic biomarkers. In this review, we address the present state of understanding on the biogenesis, regulation and pathophysiological roles of micro and circular RNAs in cardiovascular diseases, and on the potential future perspectives on their use as biomarkers and therapeutic agents.

scholarly journals Urinary Levels of the Acrolein Conjugates of Carnosine Are Associated with Cardiovascular Disease Risk

2021 ◽  
Vol 22 (3) ◽  
pp. 1383
Author(s):  
Timothy E. O’Toole ◽  
Xiaohong Li ◽  
Daniel W. Riggs ◽  
David J. Hoetker ◽  
Shahid P. Baba ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cardiovascular Disease ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Density Lipoprotein ◽  
High Sensitivity ◽  
Cvd Risk ◽  
Reactive Protein ◽  
Heart Study ◽  
Urinary Levels

Carnosine is a naturally occurring dipeptide (β-alanine-L-histidine) which supports physiological homeostasis by buffering intracellular pH, chelating metals, and conjugating with and neutralizing toxic aldehydes such as acrolein. However, it is not clear if carnosine can support cardiovascular function or modify cardiovascular disease (CVD) risk. To examine this, we measured urinary levels of nonconjugated carnosine and its acrolein conjugates (carnosine-propanal and carnosine-propanol) in participants of the Louisville Healthy Heart Study and examined associations with indices of CVD risk. We found that nonconjugated carnosine was significantly associated with hypertension (p = 0.011), heart failure (p = 0.015), those categorized with high CVD risk (p < 0.001), body mass index (BMI; p = 0.007), high sensitivity C-reactive protein (hsCRP; p = 0.026), high-density lipoprotein (HDL; p = 0.007) and certain medication uses. Levels of carnosine-propanal and carnosine-propanol demonstrated significant associations with BMI, blood glucose, HDL and diagnosis of diabetes. Carnosine-propanal was also associated with heart failure (p = 0.045) and hyperlipidemia (p = 0.002), but no associations with myocardial infarction or stroke were identified. We found that the positive associations of carnosine conjugates with diabetes and HDL remain statistically significant (p < 0.05) in an adjusted, linear regression model. These findings suggest that urinary levels of nonconjugated carnosine, carnosine-propanal and carnosine-propanol may be informative biomarkers for the assessment of CVD risk—and particularly reflective of skeletal muscle injury and carnosine depletion in diabetes.

scholarly journals Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ricky Lali ◽  
Michael Chong ◽  
Arghavan Omidi ◽  
Pedrum Mohammadi-Shemirani ◽  
Ann Le ◽  
...  
Keyword(s):  
Rare Variant ◽  
Risk Score ◽  
Genetic Risk ◽  
Complex Disease ◽  
Rare Variants ◽  
Disease Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Considerable Proportion ◽  
Asian Populations

AbstractRare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score.

Abstract P164: Cognitive Impairment Among Adults With Incident Heart Failure

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Madeline R Sterling ◽  
Deanna Jannat-Khah ◽  
Leslie McClure ◽  
Virginia Wadley ◽  
Frederick W Unverzgat ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Racial Differences ◽  
Disease Risk ◽  
Cognitive Status ◽  
Community Dwelling ◽  
Risk Scores ◽  
Clinical Criteria ◽  
Chd Risk

Background: Cognitive impairment is as high as 70% among adults with heart failure (HF) and its prevalence increases with the duration and severity of HF. However, little is known about the prevalence of cognitive impairment early in the course of HF. This is important, as high cognitive impairment at diagnosis would suggest that earlier screening would be warranted. We examined the prevalence and correlates of cognitive impairment among adults with incident HF. Methods: We used data from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study, an observational, longitudinal cohort study of 30,239 community-dwelling adults > 45 recruited from 2003 to 2007. Blacks and residents of the stroke belt were oversampled. Global cognitive status was assessed annually by telephone with the Six-item Screener (SIS) and the diagnosis of incident HF was validated by physicians using medical records and standard clinical criteria. Participants who were hospitalized for incident HF from 2004 until 2016 with a SIS completed > 1 month but < 18 months before the index hospitalization were included. After determining the prevalence of cognitive impairment among this cohort, we identified which of their baseline characteristics were independently associated with cognitive impairment using multivariable logistic regression. We then compared the prevalence of cognitive impairment among adults with incident HF to the prevalence of cognitive impairment among age, sex, and race matched participants without HF, stratifying by 10-year Framingham Coronary Heart Disease Risk Scores (FRS) (<10%, 10-20%, and > 20%). Results: Of the 436 participants with incident HF, 14.9% had cognitive impairment. In an age-adjusted model, older age (OR 1.04 [95% CI 1.01 - 1.08], black race (OR 1.88 [95% 1.08-3.28]), < high school education (OR 1.89 [95% 1.02-3.51]), and anticoagulation (OR 3.01 [95% 1.05 - 8.63]) were independently associated with higher odds of cognitive impairment, whereas female sex (OR 0.54 [95% 0.31 - 0.94]) was associated with lower odds of cognitive impairment. The prevalence of cognitive impairment among participants with incident HF was higher than the prevalence of cognitive impairment among controls with low FRS (9.4%) but was less than the prevalence of cognitive impairment among controls with high FRS (21.9%). Conclusion: The prevalence of cognitive impairment among adults with incident HF was greater than the prevalence of cognitive impairment among matched participants with low CHD risk, but less than the prevalence of cognitive impairment among matched participants with the highest CHD risk. This suggests that the majority of cognitive decline in HF may occur later in the course of the disease. Increased awareness of cognitive impairment among newly diagnosed patients, as well as ways to mitigate cognitive decline in the context of HF management, are warranted.

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