Insights into Uromodulin and Blood Pressure.

PURPOSE OF REVIEW: We review the role of uromodulin, a protein exclusively expressed in the kidney, in blood pressure regulation and hypertension. RECENT FINDINGS: The last few years have seen a shift of focus from genetic association to mendelian randomisation and uromodulin-salt interaction studies, thus confirming the causal role of uromodulin in blood pressure regulation and hypertension. This work has been complemented by phenome-wide association studies in a wider range of ethnicities. Important recent molecular work elucidated uromodulin trafficking and secretion and provided more insights into the pathophysiological roles of circulating and urinary uromodulin. Uromodulin has a causal role in blood pressure regulation and hypertensin. Recent studies show utility of the uromodulin as a biomarker and a possible precision medicine application based on genetically determined differential responses to loop diuretics.

Assessing Machine Learning for Diagnostic Classification of Hypertension Types Identified by Ambulatory Blood Pressure Monitoring.

Background: Inaccurate blood pressure (BP) classification results in inappropriate treatment. We tested whether machine learning (ML), using routine clinical data, can serve as a reliable alternative to ambulatory BP monitoring (ABPM) in classifying BP status. Methods: This study employed a multicentre approach involving 3 derivation cohorts from Glasgow, Gdansk, and Birmingham, and a fourth independent evaluation cohort. ML models were trained using office BP, ABPM, and clinical, laboratory, and demographic data, collected from patients referred for hypertension assessment. Seven ML algorithms were trained to classify patients into 5 groups, named as follows: Normal/Target; Hypertension-Masked; Normal/Target-White-Coat (WC); Hypertension-WC; and Hypertension. The 10-year cardiovascular outcomes and 27-year all-cause mortality risks were calculated for the ML-derived groups using the Cox proportional hazards model. Results: Overall, extreme gradient boosting (using XGBoost open source software) showed the highest area under the receiver operating characteristic curve of 0.85-0.88 across derivation cohorts, Glasgow (n = 923; 43% female; age 50.7 ± 16.3 years), Gdansk (n = 709; 46% female; age 54.4 ± 13 years), and Birmingham (n = 1222; 56% female; age 55.7 ± 14 years). But accuracy (0.57-0.72) and F1 (harmonic mean of precision and recall) scores (0.57-0.69) were low across the 3 patient cohorts. The evaluation cohort (n = 6213; 51% female; age 51.2 ± 10.8 years) indicated elevated 10-year risks of composite cardiovascular events in the Normal/Target-WC and the Hypertension-WC groups, with heightened 27-year all-cause mortality observed in all groups, except the Hypertension-Masked group, compared to the Normal/Target group. Conclusions: ML has limited potential in accurate BP classification when ABPM is unavailable. Larger studies including diverse patient groups and different resource settings are warranted.

Contexte: Les erreurs dans la classification des valeurs de la pression artérielle (PA) entraînent une inadéquation du traitement. Nous avons tâché de déterminer si l'apprentissage machine, à l'aide de données cliniques routinières, constituait une solution de rechange fiable à la surveillance ambulatoire de la PA pour définir le statut de la PA. Méthodologie: Cette étude a utilisé une approche multicentrique incluant trois cohortes de dérivation de Glasgow, Gdansk et Birmingham, et une quatrième cohorte d'évaluation indépendante. Les modèles d'apprentissage machine ont été développés en analysant les données démographiques, les valeurs de la PA mesurée au cabinet, les données relatives à la surveillance ambulatoire de la PA et aux épreuves de laboratoire recueillies auprès de patients adressés pour une évaluation de l'hypertension. Sept algorithmes d'apprentissage machine ont été appliqués pour classer les patients en cinq groupes : Normale/Cible; Hypertension-Masquée; Normal/Cible-Blouse blanche; Hypertension-Blouse blanche; Hypertension. Les événements cardiovasculaires sur 10 ans et le risque de mortalité toutes causes confondues sur 27 ans ont été calculés dans les groupes dérivés de l'apprentissage machine à l'aide d'un modèle de risques proportionnels de Cox. Résultats: D'une manière générale, l'amplification de gradient extrême (à l'aide du logiciel ouvert XGBoost) a mis en évidence l'aire sous la courbe de la fonction d'efficacité du récepteur (courbe ROC pour Receiver Operating Characteristic) la plus haute, soit 0,85 à 0,88, pour toutes les cohortes de dérivation : Glasgow (n = 923; 43 % de femmes; âge : 50,7 ± 16,3 ans); Gdansk (n = 709; 46 % de femmes; âge : 54,4 ± 13 ans); Birmingham (n = 1 222; 56 % de femmes; âge : 55,7 ± 14 ans). La précision (0,57 ­ 0,72) et le score F1 (moyenne harmonique de la précision et du rappel) (0,57 ­ 0,69) ont été faibles dans les trois cohortes de patients. La cohorte d'évaluation (n = 6 213; 51 % de femmes; âge : 51,2 ± 10,8 ans) a indiqué un risque d'événements cardiovasculaires composites sur 10 ans élevé dans les groupes Normale/Cible-Blouse blanche et Hypertension-Blouse blanche, tandis qu'une hausse de la mortalité toutes causes confondues sur 27 ans a été observée dans tous les groupes, sauf dans le groupe Hypertension-Masquée, comparativement au groupe Normale/Cible. Conclusions: Le potentiel d'exactitude de la classification de la PA à l'aide de l'apprentissage machine lorsque la surveillance ambulatoire de la PA n'est pas possible est limité. Des études de plus grande envergure portant sur des groupes de patients et des niveaux de ressources diversifiés s'imposent.

UMOD Genotype-Blinded Trial of Ambulatory Blood Pressure Response to Torasemide.

BACKGROUND: UMOD (uromodulin) has been linked to hypertension through potential activation of Na+-K+-2Cl- cotransporter (NKCC2), a target of loop diuretics. We posited that hypertensive patients carrying the rs13333226-AA UMOD genotype would demonstrate greater blood pressure responses to loop diuretics, potentially mediated by this UMOD/NKCC2 interaction. METHODS: This prospective, multicenter, genotype-blinded trial evaluated torasemide (torsemide) efficacy on systolic blood pressure (SBP) reduction over 16 weeks in nondiabetic, hypertensive participants uncontrolled on ≥1 nondiuretic antihypertensive for >3 months. The primary end point was the change in 24-hour ambulatory SBP (ABPM SBP) and SBP response trajectories between baseline and 16 weeks by genotype (AA versus AG/GG) due to nonrandomized groups at baseline (ClinicalTrials.gov: NCT03354897). RESULTS: Of 251 enrolled participants, 222 received torasemide and 174 demonstrated satisfactory treatment adherence and had genotype data. The study participants were middle-aged (59±11 years), predominantly male (62%), obese (body mass index, 32±7 kg/m2), with normal eGFR (92±17 mL/min/1.73 m²) and an average baseline ABPM of 138/81 mm Hg. Significant reductions in mean ABPM SBP were observed in both groups after 16 weeks (AA, -6.57 mm Hg [95% CI, -8.44 to -4.69]; P<0.0001; AG/GG, -3.22 [95% CI, -5.93 to -0.51]; P=0.021). The change in mean ABPM SBP (baseline to 16 weeks) showed a difference of -3.35 mm Hg ([95% CI, -6.64 to -0.05]; P=0.048) AA versus AG/GG genotypes. The AG/GG group displayed a rebound in SBP from 8 weeks, differing from the consistent decrease in the AA group (P=0.004 for difference in trajectories). CONCLUSIONS: Our results confirm a plausible interaction between UMOD and NKCC2 and suggest a potential role for genotype-guided use of loop diuretics in hypertension management. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03354897.

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.

Evaluating transition in Turner syndrome in the West of Scotland.

BACKGROUND: A Turner Syndrome (TS) Transition clinic, Royal Hospital for Children Glasgow (RHCG), with paediatric and adult endocrinology/gynaecology teams was established in 1998 with an aim of improving health outcomes in TS throughout the lifespan. OBJECTIVE: To evaluate the success of our TS transition service, focussing on evaluating established follow-up after transfer to adult services. METHODS: Girls attending the TS Transition clinic at Royal Hospital for Children Glasgow, 1998-2017, were identified. Attendance data were obtained from patient records and an electronic appointment system. We assessed good and late early attendance in our cohort of TS patients as well as established endocrine follow-up, defined as those still attending adult endocrine services 3 years after transfer. Success of TS transition was determined by the proportion of girls in established endocrine follow-up. RESULTS: Forty-six girls (median age 18.3 yrs) were identified. Thirty-six, 36/46 girls transferred prior to 2015 and 26 of those (72%) were in established follow-up at 3 years, 22/36 girls had met with an Adult specialist prior to transfer and 14/36 had not met with an adult specialist prior to transfer. Twenty-one (80.7%) were good early attenders (p = 0.10). In the early attenders' cohort, there was no significant difference between those that had and had not met an adult specialist prior to transfer. CONCLUSION: A significant proportion of girls with TS are currently lost to endocrine follow-up following transfer to adult clinics. Early attendance at an adult clinic appears to predict established long-term follow-up. Strategies to improve early attendance and long-term endocrine follow-up are needed to ensure lifelong health needs are addressed.