Assessment of model based (input) impedance, pulse wave velocity, and wave reflection in the Asklepios Cohort

Objectives : Arterial stiffness and wave reflection parameters assessed from both invasive and non-invasive pressure and flow readings are used as surrogates for ventricular and vascular load. They have been reported to predict adverse cardiovascular events, but clinical assessment is laborious and may limit widespread use. This study aims to investigate measures of arterial stiffness and central hemodynamics provided by arterial tonometry alone and in combination with aortic root flows derived by echocardiography against surrogates derived by a mathematical pressure and flow model in a healthy middle-aged cohort. Methods : Measurements of carotid artery tonometry and echocardiography were performed on 2226 ASKLEPIOS study participants and parameters of systemic hemodynamics, arterial stiffness and wave reflection based on pressure and flow were measured. In a second step, the analysis was repeated but echocardiography derived flows were substituted by flows provided by a novel mathematical model. This was followed by a quantitative method comparison. Results : All investigated parameters showed a significant association between the methods. Overall agreement was acceptable for all parameters (mean differences: -0.0102 (0.033 SD) mmHg*s/ml for characteristic impedance, 0.36 (4.21 SD) mmHg for forward pressure amplitude, 2.26 (3.51 SD) mmHg for backward pressure amplitude and 0.717 (1.25 SD) m/s for pulse wave velocity). Conclusion : The results indicate that the use of model-based surrogates in a healthy middle aged cohort is feasible and deserves further attention

Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet

Aging; Arteriosclerosis; HemodynamicsEnvelliment; Arteriosclerosi; HemodinàmicaEnvejecimiento; Arteriosclerosis; HemodinámicaArterial pulse waves (PWs) such as blood pressure and photoplethysmogram (PPG) signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review the possibilities, limitations, complementarity, and differences of reduced-order, biophysical models of arterial PW propagation, as well as theoretical and empirical methods for analyzing PW signals and extracting clinically relevant information for vascular age assessment. We provide detailed mathematical derivations of these models and theoretical methods, showing how they are related to each other. Finally, we outline directions for future research to realize the potential of modeling and analysis of PW signals for accurate assessment of vascular age in both the clinic and in daily life.This article is based upon work from COST Action “Network for Research in Vascular Ageing” (VascAgeNet, CA18216), supported by COST (European Cooperation in Science and Technology, www.cost.eu). This work was supported by British Heart Foundation Grants PG/15/104/31913 (to J.A. and P.H.C.), FS/20/20/34626 (to P.H.C.), and AA/18/6/34223, PG/17/90/33415, SPG 2822621, and SP/F/21/150020 (to A.D.H.); Kaunas University of Technology Grant INP2022/16 (to B.P.); European Research Executive Agency, Marie-Sklodowska Curie Actions Individual Fellowship Grant 101038096 (to S.P.); Istinye University, BAP Project Grant 2019B1 (to S.P.); “la Caixa” Foundation Grant LCF/BQ/PR22/11920008 (to A.G.); and National Institute for Health and Care Research Grant AI AWARD02499 and EU Horizon 2020 Grant H2020 848109 (to A.D.H.)

Arterial pulse wave modelling and analysis for vascular age studies: a review from VascAgeNet

Arterial pulse waves (PWs) such as blood pressure and photoplethysmogram (PPG) signals contain a wealth of information on the cardiovascular (CV) system that can be exploited to assess vascular age and identify individuals at elevated CV risk. We review the possibilities, limitations, complementarity, and differences of reduced-order, biophysical models of arterial PW propagation, as well as theoretical and empirical methods for analyzing PW signals and extracting clinically relevant information for vascular age assessment. We provide detailed mathematical derivations of these models and theoretical methods, showing how they are related to each other. Finally, we outline directions for future research to realize the potential of modeling and analysis of PW signals for accurate assessment of vascular age in both the clinic and in daily life

Covid-19 effects on ARTErial StIffness and vascular AgeiNg: CARTESIAN study rationale and protocol

In December 2019, an outbreak of pneumonia caused by a novel Coronavirus (COVID-19) spread rapidly worldwide. Although the clinical manifestations of COVID-19 are dominated by respiratory symptoms, the cardiovascular system is extensively affected at multiple levels. Due to the unprecedented consequences of the COVID-19 pandemic, the ARTERY society decided to launch the Covid-19 effects on ARTErial StIffness and vascular AgeiNg (CARTESIAN) study — the first international multicentre study into the effects of COVID-19 on non-invasive biomarkers of vascular ageing. The main study objective is to evaluate the presence of Early Vascular Ageing (EVA) 6 and 12 months after COVID-19 infection. Secondary objectives are to study the effect of COVID-19 disease severity on EVA, to investigate the role of psychosocial factors in COVID-19 induced EVA, and to investigate the potential modifying effect of comorbidities and chronic treatments. In the CARTESIAN study, a broad array of cardiovascular measurements, including carotid-femoral pulse wave velocity, central blood pressure, carotid ultrasound, brachial flow-mediated dilatation, will be performed. To date, 43 centres from 21 countries have agreed to participate, with an expected study population of >2500 individuals. To our knowledge, CARTESIAN will be the first study to provide insight into the relationship between COVID-19, its severity, and early vascular ageing in a large cohort, potentially enabling future care and diagnostics to be more focused on the most vulnerable

Effect of Monthly, High‐Dose, Long‐Term Vitamin D Supplementation on Central Blood Pressure Parameters: A Randomized Controlled Trial Substudy

Background: The effects of monthly, high‐dose, long‐term (≥1‐year) vitamin D supplementation on central blood pressure (BP) parameters are unknown. Methods and Results: A total of 517 adults (58% male, aged 50–84 years) were recruited into a double‐blinded, placebo‐controlled trial substudy and randomized to receive, for 1.1 years (median; range: 0.9–1.5 years), either (1) vitamin D3 200 000 IU (initial dose) followed 1 month later by monthly 100 000‐IU doses (n=256) or (2) placebo monthly (n=261). At baseline (n=517) and follow‐up (n=380), suprasystolic oscillometry was undertaken, yielding aortic BP waveforms and hemodynamic parameters. Mean deseasonalized 25‐hydroxyvitamin D increased from 66 nmol/L (SD: 24) at baseline to 122 nmol/L (SD: 42) at follow‐up in the vitamin D group, with no change in the placebo group. Despite small, nonsignificant changes in hemodynamic parameters in the total sample (primary outcome), we observed consistently favorable changes among the 150 participants with vitamin D deficiency (<50 nmol/L) at baseline. In this subgroup, mean changes in the vitamin D group (n=71) versus placebo group (n=79) were −5.3 mm Hg (95% confidence interval [CI], −11.8 to 1.3) for brachial systolic BP (P=0.11), −2.8 mm Hg (95% CI, −6.2 to 0.7) for brachial diastolic BP (P=0.12), −7.5 mm Hg (95% CI, −14.4 to −0.6) for aortic systolic BP (P=0.03), −5.7 mm Hg (95% CI, −10.8 to −0.6) for augmentation index (P=0.03), −0.3 m/s (95% CI, −0.6 to −0.1) for pulse wave velocity (P=0.02), −8.6 mm Hg (95% CI, −15.4 to −1.9) for peak reservoir pressure (P=0.01), and −3.6 mm Hg (95% CI, −6.3 to −0.8) for backward pressure amplitude (P=0.01). Conclusions: Monthly, high‐dose, 1‐year vitamin D supplementation lowered central BP parameters among adults with vitamin D deficiency but not in the total sample. Clinical Trial Registration URL: http://www.anzctr.org.au. Unique identifier: ACTRN12611000402943

Twenty-Four-Hour Central (Aortic) Systolic Blood Pressure: Reference Values and Dipping Patterns in Untreated Individuals.

Central (aortic) systolic blood pressure (cSBP) is the pressure seen by the heart, the brain, and the kidneys. If properly measured, cSBP is closer associated with hypertension-mediated organ damage and prognosis, as compared with brachial SBP (bSBP). We investigated 24-hour profiles of bSBP and cSBP, measured simultaneously using Mobilograph devices, in 2423 untreated adults (1275 women; age, 18-94 years), free from overt cardiovascular disease, aiming to develop reference values and to analyze daytime-nighttime variability. Central SBP was assessed, using brachial waveforms, calibrated with mean arterial pressure (MAP)/diastolic BP (cSBPMAP/DBPcal), or bSBP/diastolic blood pressure (cSBPSBP/DBPcal), and a validated transfer function, resulting in 144 509 valid brachial and 130 804 valid central measurements. Averaged 24-hour, daytime, and nighttime brachial BP across all individuals was 124/79, 126/81, and 116/72 mm Hg, respectively. Averaged 24-hour, daytime, and nighttime values for cSBPMAP/DBPcal were 128, 128, and 125 mm Hg and 115, 117, and 107 mm Hg for cSBPSBP/DBPcal, respectively. We pragmatically propose as upper normal limit for 24-hour cSBPMAP/DBPcal 135 mm Hg and for 24-hour cSBPSBP/DBPcal 120 mm Hg. bSBP dipping (nighttime-daytime/daytime SBP) was -10.6 % in young participants and decreased with increasing age. Central SBPSBP/DBPcal dipping was less pronounced (-8.7% in young participants). In contrast, cSBPMAP/DBPcal dipping was completely absent in the youngest age group and less pronounced in all other participants. These data may serve for comparison in various diseases and have potential implications for refining hypertension diagnosis and management. The different dipping behavior of bSBP versus cSBP requires further investigation

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Implementation of a one-dimensional blood flow model using the finite element method

Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in engl. SpracheIn vielen hochentwickelten Ländern stellen Erkrankungen des Herzkreislaufsystems die häufigste Todesursache dar. Daher ist die Forschungsarbeit auf diesem Gebiet von großer Bedeutung. Die Modellbildung und Simulation des Herzkreislaufsystems nimmt dabei eine wichtige Rolle ein.Diese Arbeit beschäftigt sich mit der Herleitung und Simulation eines Blutflussmodells für größere Arterien, die einen wesentlichen Bestandteil des menschlichen Blutkreislaufsystems darstellen.Den Ausgangspunkt der Betrachtungen bilden die Navier-Stokes-Gleichungen für inkompressible Flüssigkeiten. Unter verschiedenen Annahmen, wie die zylindrische Form der Arterien, wird daraus ein Modell in einer Raumdimension abgeleitet. Dieses Blutflussmodell beinhaltet als Zustandsgrößen die Gefäßquerschnittsfläche und den Volumenfluss. Es kann als hyperbolische partielle Differentialgleichung erster Ordnung in Erhaltungsform angeschrieben werden.Um das Differentialgleichungssystem numerisch zu lösen, wird die Finite Elemente Methode benutzt. Dabei wird ein Taylor-Galerkin Verfahren zweiter Ordnung angewendet. Die Bestimmung der Randwerte geschieht mit Hilfe der charakteristischen Variablen des Systems.Die Implementierung erfolgt in Matlab. Sie stützt sich auf eine Vorgehensweise für stationäre Probleme, das um die zeitliche Komponente, insbesondere um die Berechnung der Randwerte, erweitert wird.Zur Verifizierung werden verschiedene Simulationsexperimente durchgeführt. Dabei werden unterschiedliche Druckkurven als Testeingänge verwendet, um die Ergebnisse mit verfügbaren Resultaten in der Literatur zu vergleichen. Mit diesem Modell kann der Blutfluss in größeren Arterien beschrieben werden, und es soll daher als Teilmodell in ein dynamisches, regulierbares und identifizierbares Herzkreislaufmodell des menschlichen Körpers einfließen, mit dem die Auswirkungen physiologischer Veränderungen des Gefäßsystems auf das globale Verhalten des Blutkreislaufs simuliert und untersucht werden können.In many developed countries diseases of the cardiovascular system are the most common cause of death. Therefore research work in this area is of great importance. In particular, modelling and simulation of the cardiovascular system plays an important role.\\ In this work a model for blood flow in major arteries, which are a fundamental component of the human blood circuit, will be derived and simulated. The derivation starts with the Navier-Stokes equations for incompressible fluids. After stating various assumptions like a cylindrical shape of arteries, a one-dimensional model is derived. The state variables in this blood flow model are the cross-sectional area and the averaged volume flux. The system can be written as a hyperbolic partial differential equation of first order in conservation form.To solve the system of differential equations numerically, the finite element method is used. More precisely a second-order Taylor-Galerkin scheme is applied. The characteristic variables are used to obtain the boundary conditions.The implementation is done in Matlab, based on a method for stationary problems, which will be extended by the time component, especially by the calculations of the boundary conditions.For verification purposes, several simulation experiments are performed.Different pressure functions are used as test inputs and the results are compared to those available in literature.This model can be used to describe the blood flow in the major arteries, and therefore it might be a part of a dynamical, controlled and identifiable model for the cardiovascular system of the human body, which can be used to simulate and analyse impacts of physiological changes of the vascular system to the global characteristics of the blood circuit.8