RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study.

BACKGROUND: Whole-genome sequencing (WGS) is the gold standard diagnostic tool to identify and genetically characterise emerging pathogen mutations (variants), but cost, capacity, and timeliness limit its use when large populations need rapidly assessing. We assessed the potential of genotyping assays to provide accurate and timely variant information at scale by retrospectively examining surveillance for SARS-CoV-2 variants in England between March and September, 2021, when genotyping assays were used widely for variant detection. METHODS: We chose a panel of four RT-PCR genotyping assays to detect circulating variants of SARS-COV-2 in England and developed a decision algorithm to assign a probable SARS-CoV-2 variant to samples using the assay results. We extracted surveillance data from the UK Health Security Agency databases for 115 934 SARS-CoV-2-positive samples (March 1-Sept 6, 2021) when variant information was available from both genotyping and WGS. By comparing the genotyping and WGS variant result, we calculated accuracy metrics (ie, sensitivity, specificity, and positive predictive value [PPV]) and the time difference between the sample collection date and the availability of variant information. We assessed the number of samples with a variant assigned from genotyping or WGS, or both, over time. FINDINGS: Genotyping and an initial decision algorithm (April 10-May 11, 2021 data) were accurate for key variant assignment: sensitivities and PPVs were 0·99 (95% CI 0·99-0·99) for the alpha, 1·00 (1·00-1·00) for the beta, and 0·91 (0·80-1·00) for the gamma variants; specificities were 0·97 (0·96-0·98), 1·00 (1·00-1·00), and 1·00 (1·00-1·00), respectively. A subsequent decision algorithm over a longer time period (May 27-Sept 6, 2021 data) remained accurate for key variant assignment: sensitivities were 0·91 (95% CI 0·74-1·00) for the beta, 0·98 (0·98-0·99) for the delta, and 0·93 (0·81-1·00) for the gamma variants; specificities were 1·00 (1·00-1·00), 0·96 (0·96-0·97), and 1·00 (1·00-1·00), respectively; and PPVs were 0·83 (0·62-1·00), 1·00 (1·00-1·00), and 0·78 (0·59-0·97), respectively. Genotyping produced variant information a median of 3 days (IQR 2-4) after the sample collection date, which was faster than with WGS (9 days [8-11]). The flexibility of genotyping enabled a nine-times increase in the quantity of samples tested for variants by this method (from 5000 to 45 000). INTERPRETATION: RT-PCR genotyping assays are suitable for high-throughput variant surveillance and could complement WGS, enabling larger scale testing for known variants and timelier results, with important implications for effective public health responses and disease control globally, especially in settings with low WGS capacity. However, the choice of panels of RT-PCR assays is highly dependent on database information on circulating variants generated by WGS, which could limit the use of genotyping assays when new variants are emerging and spreading rapidly. FUNDING: UK Health Security Agency and National Institute for Health Research Health Protection Research Unit in Emergency Preparedness and Response.

Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing.

BACKGROUND: Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. RESULTS: We systematically investigate both dominance-here representing any non-additive within-locus interaction-and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. CONCLUSIONS: Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.

Swab pooling enables rapid expansion of high-throughput capacity for SARS-CoV-2 community testing.

BACKGROUND: The challenges of rapid upscaling of testing capacity were a major lesson from the COVID-19 pandemic response. The need for process adjustments in high-throughput testing laboratories made sample pooling a challenging option to implement. OBJECTIVE: This study aimed to evaluate whether pooling samples at source (swab pooling) was as effective as qRT-PCR testing of individuals in identifying cases of SARS-CoV-2 in real-world community testing conditions using the same high-throughput pipeline. METHODS: Two cohorts of 10 (Pool10: 1,030 participants and 103 pools) and 6 (Pool6: 1,284 participants and 214 pools) samples per pool were tested for concordance, sensitivity, specificity, and Ct value differences with individual testing as reference. RESULTS: Swab pooling allowed unmodified application of an existing high-throughput SARS-Cov-2 testing pipeline with only marginal loss of accuracy. For Pool10, concordance was 98.1% (95% Confidence interval: 93.3-99.8%), sensitivity was 95.7% (85.5-99.5%), and specificity was 100.0% (93.6-100.0%). For Pool6, concordance was 97.2% (94.0-99.0%), sensitivity was 97.5% (93.7-99.3%), and specificity was 96.4% (87.7-99.6%). Differences of outcomes measure between pool size were not significant. Most positive individual samples, which were not detected in pools, had very low viral concentration. If only individual samples with a viral concentration > 400 copies/ml (i.e. Ct value < 30) were considered positive, the overall sensitivity of pooling increased to 99.5%. CONCLUSION: The study demonstrated high sensitivity and specificity by swab pooling and the immediate capability of high-throughput laboratories to implement this method making it an option in planning of rapid upscaling of laboratory capacity for future pandemics.

2023 ESH Guidelines for the management of arterial hypertension The Task Force for the management of arterial hypertension of the European Society of Hypertension: Endorsed by the International Society of Hypertension (ISH) and the European Renal Association (ERA).

DOCUMENT REVIEWERS: Luis Alcocer (Mexico), Christina Antza (Greece), Mustafa Arici (Turkey), Eduardo Barbosa (Brazil), Adel Berbari (Lebanon), Luís Bronze (Portugal), John Chalmers (Australia), Tine De Backer (Belgium), Alejandro de la Sierra (Spain), Kyriakos Dimitriadis (Greece), Dorota Drozdz (Poland), Béatrice Duly-Bouhanick (France), Brent M. Egan (USA), Serap Erdine (Turkey), Claudio Ferri (Italy), Slavomira Filipova (Slovak Republic), Anthony Heagerty (UK), Michael Hecht Olsen (Denmark), Dagmara Hering (Poland), Sang Hyun Ihm (South Korea), Uday Jadhav (India), Manolis Kallistratos (Greece), Kazuomi Kario (Japan), Vasilios Kotsis (Greece), Adi Leiba (Israel), Patricio López-Jaramillo (Colombia), Hans-Peter Marti (Norway), Terry McCormack (UK), Paolo Mulatero (Italy), Dike B. Ojji (Nigeria), Sungha Park (South Korea), Priit Pauklin (Estonia), Sabine Perl (Austria), Arman Postadzhian (Bulgaria), Aleksander Prejbisz (Poland), Venkata Ram (India), Ramiro Sanchez (Argentina), Markus Schlaich (Australia), Alta Schutte (Australia), Cristina Sierra (Spain), Sekib Sokolovic (Bosnia and Herzegovina), Jonas Spaak (Sweden), Dimitrios Terentes-Printzios (Greece), Bruno Trimarco (Italy), Thomas Unger (The Netherlands), Bert-Jan van den Born (The Netherlands), Anna Vachulova (Slovak Republic), Agostino Virdis (Italy), Jiguang Wang (China), Ulrich Wenzel (Germany), Paul Whelton (USA), Jiri Widimsky (Czech Republic), Jacek Wolf (Poland), Grégoire Wuerzner (Switzerland), Eugene Yang (USA), Yuqing Zhang (China).

Cluster analysis of angiotensin biomarkers to identify antihypertensive drug treatment in population studies.

BACKGROUND: The recent progress in molecular biology generates an increasing interest in investigating molecular biomarkers as markers of response to treatments. The present work is motivated by a study, where the objective was to explore the potential of the molecular biomarkers of renin-angiotensin-aldosterone system (RAAS) to identify the undertaken antihypertensive treatments in the general population. Population-based studies offer an opportunity to assess the effectiveness of treatments in real-world scenarios. However, lack of quality documentation, especially when electronic health record linkage is unavailable, leads to inaccurate reporting and classification bias. METHOD: We present a machine learning clustering technique to determine the potential of measured RAAS biomarkers for the identification of undertaken treatments in the general population. The biomarkers were simultaneously determined through a novel mass-spectrometry analysis in 800 participants of the Cooperative Health Research In South Tyrol (CHRIS) study with documented antihypertensive treatments. We assessed the agreement, sensitivity and specificity of the resulting clusters against known treatment types. Through the lasso penalized regression, we identified clinical characteristics associated with the biomarkers, accounting for the effects of cluster and treatment classifications. RESULTS: We identified three well-separated clusters: cluster 1 (n = 444) preferentially including individuals not receiving RAAS-targeting drugs; cluster 2 (n = 235) identifying angiotensin type 1 receptor blockers (ARB) users (weighted kappa κw = 74%; sensitivity = 73%; specificity = 83%); and cluster 3 (n = 121) well discriminating angiotensin-converting enzyme inhibitors (ACEi) users (κw = 81%; sensitivity = 55%; specificity = 90%). Individuals in clusters 2 and 3 had higher frequency of diabetes as well as higher fasting glucose and BMI levels. Age, sex and kidney function were strong predictors of the RAAS biomarkers independently of the cluster structure. CONCLUSIONS: Unsupervised clustering of angiotensin-based biomarkers is a viable technique to identify individuals on specific antihypertensive treatments, pointing to a potential application of the biomarkers as useful clinical diagnostic tools even outside of a controlled clinical setting.

Impact of preeclampsia on cardiovascular events: An analysis of the Generation Scotland: Scottish family health study.

Preeclampsia is a recognised cause of an increased risk of major adverse cardiovascular events when compared to the background risk in women who did not have hypertensive disorders during pregnancy. The Generation Scotland: Scottish Family Health Study (GS:SFHS) is a population cohort of more than 20,000 members of the Scottish population. Using the Scottish Morbidity Records, we linked the women in the GS:SFHS cohort to validated maternity and inpatient admission data. This allowed us to robustly identify cardiovascular outcomes in the form of inpatient admission for cardiovascular events, We also aimed to explore the risk of pregnancy on future cardiovascular events, using data from nulliparous and parous women.In total, 9732 women were selected. 3693 women were nulliparous, and after study exclusion, 5253 women with 9583 pregnancies remained. Pregnancies from 1980 until the end of the study period of 1st of July 2013 were included. Cardiovascular events occurred in 9.0% of nulliparous women, 4.2% of women with pregnancies and in 7.6% of women with a history of preeclampsia. A total of 218 parous women experienced cardiovascular events, 25 in the preeclampsia group and 193 in the normotensive group.Survival analysis was undertaken, with index pregnancy taken as first pregnancy in normotensive controls and first preeclampsia pregnancy in cases. Endpoint of interest was admission to hospital with first cardiovascular event. After further exclusions a total of 169 cardiovascular events occurred in the normotensive pregnancy group and 20 in the preeclampsia group. Women with a history of preeclampsia were more likely to have cardiovascular events later in life than women with normotensive deliveries., This was statistically significantly different on Kaplan Meier survival analysis, (log rank Mantel-Cox p-value < 0.001). The women in our study were middle-aged, within 33 years of pregnancy, with a mean age of 53 years in the preeclampsia cardiovascular events group.Our study supports the urgent need for uniform guidelines and implementation to improve the health in women with this medical history. Increased awareness among the public of the cardiovascular risk associated with PE is vital to aid uptake of cardiovascular prevention programmes.

Cardiovascular precision medicine - A pharmacogenomic perspective.

Precision medicine envisages the integration of an individual's clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.

Role of Uromodulin in Salt-Sensitive Hypertension.

The exclusive expression of uromodulin in the kidneys has made it an intriguing protein in kidney and cardiovascular research. Genome-wide association studies discovered variants of uromodulin that are associated with chronic kidney diseases and hypertension. Urinary and circulating uromodulin levels reflect kidney and cardiovascular health as well as overall mortality. More recently, Mendelian randomization studies have shown that genetically driven levels of uromodulin have a causal and adverse effect on kidney function. On a mechanistic level, salt sensitivity is an important factor in the pathophysiology of hypertension, and uromodulin is involved in salt reabsorption via the NKCC2 (Na+-K+-2Cl- cotransporter) on epithelial cells of the ascending limb of loop of Henle. In this review, we provide an overview of the multifaceted physiology and pathophysiology of uromodulin including recent advances in its genetics; cellular trafficking; and mechanistic and clinical studies undertaken to understand the complex relationship between uromodulin, blood pressure, and kidney function. We focus on tubular sodium reabsorption as one of the best understood and pathophysiologically and clinically most important roles of uromodulin, which can lead to therapeutic interventions.

Unravelling the Distinct Effects of Systolic and Diastolic Blood Pressure Using Mendelian Randomisation.

A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent effect of SBP and DBP on a range of CV outcomes. Genetic predisposition to higher SBP and DBP was associated with increased risk of coronary artery disease (CAD), myocardial infarction (MI), stroke, heart failure (HF), atrial fibrillation (AF), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Genetically proxied SBP exclusively was associated with CAD (OR 1.18, 95% CI: 1.03-1.36, per 10 mmHg), stroke (1.44[1.28-1.62]), ischemic stroke (1.49[1.30-1.69]), HF (1.41[1.20-1.65]), AF (1.28[1.15-1.43]), and T2DM (1.2[1.13-1.46]). Genetically proxied DBP exclusively was associated with stroke (1.21[1.06-1.37], per 5 mmHg), ischemic stroke (1.24[1.09-1.41]), stroke small-vessel (1.35[1.10-1.65]) and CAD (1.19[1.00-1.41]). Multivariable MR using exclusive SBP and DBP instruments showed the predominant effect of SBP on CAD (1.23[1.05-1.44], per 10 mmHg), stroke (1.39[1.20-1.60]), ischemic stroke (1.44[1.25-1.67]), HF (1.42[1.18-1.71]), AF (1.26[1.10-1.43]) and T2DM (1.31[1.14-1.52]). The discrepancy between effects of SBP and DBP on outcomes warrants further studies on underpinning mechanisms which may be amenable to therapeutic targeting.

Mechanistic interactions of uromodulin with the thick ascending limb: perspectives in physiology and hypertension.

Hypertension is a significant risk factor for cardiovascular disease and mortality worldwide. The kidney is a major regulator of blood pressure and electrolyte homeostasis, with monogenic disorders indicating a link between abnormal ion transport and salt-sensitive hypertension. However, the association between salt and hypertension remains controversial. Thus, there is continued interest in deciphering the molecular mechanisms behind these processes. Uromodulin (UMOD) is the most abundant protein in the normal urine and is primarily synthesized by the thick ascending limb epithelial cells of the kidney. Genome-wide association studies have linked common UMOD variants with kidney function, susceptibility to chronic kidney disease and hypertension independent of renal excretory function. This review will discuss and provide predictions on the role of the UMOD protein in renal ion transport and hypertension based on current observational, biochemical, genetic, pharmacological and clinical evidence.

Echocardiography Predictors of Survival in Hypertensive Patients With Left Ventricular Hypertrophy.

BACKGROUND: Left ventricular hypertrophy (LVH) is a well-known target organ damage. Concentric hypertrophy is the strongest predictor of increased risk of cardiovascular events, but the predictive value of individual echocardiographic parameters remains unclear.The aim of this study was to search for echocardiographic and hemodynamic variables associated with concentric and eccentric remodeling and their association with long-term cardiovascular outcomes. METHODS: Patients with echocardiography performed within 1 year prior to the initial clinic visit were included into the study. Logistic regression and multivariable Cox-proportional hazards were calculated according to several risk factors and variables. Additionally, cubic spline interpolation was used. RESULTS: We observed 690 patients for 10 years. There was a total of 177 major adverse cardiac and cerebrovascular events (MACCE) and 90 deaths over a 10-year period. Left ventricular concentric hypertrophy is associated with worse outcomes than eccentric hypertrophy in hypertensive subjects. Interestingly, different echocardiographic parameters contributed to risk depending on type of hypertrophy. In concentric hypertrophy, relative wall thickness provides linear prediction of risk for all-cause mortality (ACM) and composite endpoint. Systolic blood pressure is a significant predictor of MACCE. Blood pressure variability also showed significant predictive value for MACCE and ACM. CONCLUSIONS: These data indicate risk stratification based on LVH need to consider different measures based on the type of remodeling.

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the global burden of the disease. Artificial intelligence and machine learning, which have made a substantial impact on our everyday lives over the last decade may be the route to this transformation. However, artificial intelligence in health care is still in its nascent stages and realizing its potential requires numerous challenges to be overcome. In this review, we provide a clinician-centric perspective on artificial intelligence and machine learning as applied to medicine and hypertension. We focus on the main roadblocks impeding implementation of this technology in clinical care and describe efforts driving potential solutions. At the juncture, there is a critical requirement for clinical and scientific expertise to work in tandem with algorithmic innovation followed by rigorous validation and scrutiny to realize the promise of artificial intelligence-enabled health care for hypertension and other chronic diseases.