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Archive for the ‘Cardiovascular Research’ Category


Regulatory MicroRNAs in Aberrant Cholesterol Transport and Metabolism

Curator: Marzan Khan, B.Sc

Aberrant levels of lipids and cholesterol accumulation in the body lead to cardiometabolic disorders such as atherosclerosis, one of the leading causes of death in the Western World(1). The physical manifestation of this condition is the build-up of plaque along the arterial endothelium causing the arteries to constrict and resist a smooth blood flow(2). This obstructive deposition of plaque is merely the initiation of atherosclerosis and is enriched in LDL cholesterol (LDL-C) as well foam cells which are macrophages carrying an overload of toxic, oxidized LDL(2). As the condition progresses, the plaque further obstructs blood flow and creates blood clots, ultimately leading to myocardial infarction, stroke and other cardiovascular diseases(2). Therefore, LDL is referred to as “the bad cholesterol”(2).

Until now, statins are most widely prescribed as lipid-lowering drugs that inhibit the enzyme 3-hydroxy-3methylgutaryl-CoA reductase (HMGCR), the rate-limiting step in de-novo cholesterol biogenesis (1). But some people cannot continue with the medication due to it’s harmful side-effects(1). With the need to develop newer therapeutics to combat cardiovascular diseases, Harvard University researchers at Massachusetts General Hospital discovered 4 microRNAs that control cholesterol, triglyceride, and glucose homeostasis(3)

MicroRNAs are non-coding, regulatory elements approximately 22 nucleotides long, with the ability to control post-transcriptional expression of genes(3). The liver is the center for carbohydrate and lipid metabolism. Stringent regulation of endogenous LDL-receptor (LDL-R) pathway in the liver is crucial to maintain a minimal concentration of LDL particles in blood(3). A mechanism whereby peripheral tissues and macrophages can get rid of their excess LDL is mediated by ATP-binding cassette, subfamily A, member 1 (ABCA1)(3). ABCA1 consumes nascent HDL particles- dubbed as the “good cholesterol” which travel back to the liver for its contents of triglycerides and cholesterol to be excreted(3).

Genome-wide association studies (GWASs) meta-analysis carried out by the researchers disclosed 4 microRNAs –(miR-128-1, miR-148a, miR-130b, and miR-301b) to lie close to single-nucleotide polymorphisms (SNPs) associated with abnormal metabolism and transport of lipids and cholesterol(3) Experimental analyses carried out on relevant cell types such as the liver and macrophages have proven that these microRNAs bind to the 3’ UTRs of both LDL-R and ABCA1 transporters, and silence their activity. Overexpression of miR-128-1 and miR148a in mice models caused circulating HDL-C to drop. Corroborating the theory under investigation further, their inhibition led to an increased clearance of LDL from the blood and a greater accumulation in the liver(3).

That the antisense inhibition of miRNA-128-1 increased insulin signaling in mice, propels us to hypothesize that abnormal expression of miR-128-1 might cause insulin resistance in metabolic syndrome, and defective insulin signaling in hepatic steatosis and dyslipidemia(3)

Further examination of miR-148 established that Liver-X-Receptor (LXR) activation of the Sterol regulatory element-binding protein 1c (SREBP1c), the transcription factor responsible for controlling  fatty acid production and glucose metabolism, also mediates the expression of miR-148a(4,5) That the promoter region of miR-148 contained binding sites for SREBP1c was shown by chromatin immunoprecipitation combined with massively parallel sequencing (ChIP-seq)(4). More specifically, SREBP1c attaches to the E-box2, E-box3 and E-box4 elements on miR-148-1a promoter sites to control its expression(4).

Earlier, the same researchers- Andres Naars and his team had found another microRNA called miR-33 to block HDL generation, and this blockage to reverse upon antisense targeting of miR-33(6).

These experimental data substantiate the theory of miRNAs being important regulators of lipoprotein receptors and transporter proteins as well as underscore the importance of employing antisense technologies to reverse their gene-silencing effects on LDL-R and ABCA1(4). Such a therapeutic approach, that will consequently lower LDL-C and promote HDL-C seems to be a promising strategy to treat atherosclerosis and other cardiovascular diseases(4).

References:

1.Goedeke L1,Wagschal A2,Fernández-Hernando C3, Näär AM4. miRNA regulation of LDL-cholesterol metabolism. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):. Biochim Biophys Acta. 2016 Dec;1861(12 Pt B):2047-2052

https://www.ncbi.nlm.nih.gov/pubmed/26968099

2.MedicalNewsToday. Joseph Nordgvist. Atherosclerosis:Causes, Symptoms and Treatments. 13.08.2015

http://www.medicalnewstoday.com/articles/247837.php

3.Wagschal A1,2, Najafi-Shoushtari SH1,2, Wang L1,2, Goedeke L3, Sinha S4, deLemos AS5, Black JC1,6, Ramírez CM3, Li Y7, Tewhey R8,9, Hatoum I10, Shah N11, Lu Y11, Kristo F1, Psychogios N4, Vrbanac V12, Lu YC13, Hla T13, de Cabo R14, Tsang JS11, Schadt E15, Sabeti PC8,9, Kathiresan S4,6,8,16, Cohen DE7, Whetstine J1,6, Chung RT5,6, Fernández-Hernando C3, Kaplan LM6,10, Bernards A1,6,16, Gerszten RE4,6, Näär AM1,2. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. . Nat Med.2015 Nov;21(11):1290

https://www.ncbi.nlm.nih.gov/pubmed/26501192

4.Goedeke L1,2,3,4, Rotllan N1,2, Canfrán-Duque A1,2, Aranda JF1,2,3, Ramírez CM1,2, Araldi E1,2,3,4, Lin CS3,4, Anderson NN5,6, Wagschal A7,8, de Cabo R9, Horton JD5,6, Lasunción MA10,11, Näär AM7,8, Suárez Y1,2,3,4, Fernández-Hernando C1,2,3,4. MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels. Nat Med. 2015 Nov;21(11):1280-9.

https://www.ncbi.nlm.nih.gov/pubmed/26437365

5.Eberlé D1, Hegarty B, Bossard P, Ferré P, Foufelle F. SREBP transcription factors: master regulators of lipid homeostasis. Biochimie. 2004 Nov;86(11):839-48.

https://www.ncbi.nlm.nih.gov/pubmed/15589694

6.Harvard Medical School. News. MicoRNAs and Metabolism.

https://hms.harvard.edu/news/micrornas-and-metabolism

7. MGH – Four microRNAs identified as playing key roles in cholesterol, lipid metabolism

http://www.massgeneral.org/about/pressrelease.aspx?id=1862

 

Other related articles published in this Open Access Online Scientific Journal include the following:

 

  • Cardiovascular Diseases, Volume Three: Etiologies of Cardiovascular Diseases: Epigenetics, Genetics and Genomics,

on Amazon since 11/29/2015

http://www.amazon.com/dp/B018PNHJ84

 

HDL oxidation in type 2 diabetic patients

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/27/hdl-oxidation-in-type-2-diabetic-patients/

 

HDL-C: Target of Therapy – Steven E. Nissen, MD, MACC, Cleveland Clinic vs Peter Libby, MD, BWH

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/11/07/hdl-c-target-of-therapy-steven-e-nissen-md-macc-cleveland-clinic-vs-peter-libby-md-bwh/

 

High-Density Lipoprotein (HDL): An Independent Predictor of Endothelial Function & Atherosclerosis, A Modulator, An Agonist, A Biomarker for Cardiovascular Risk

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/03/31/high-density-lipoprotein-hdl-an-independent-predictor-of-endothelial-function-artherosclerosis-a-modulator-an-agonist-a-biomarker-for-cardiovascular-risk/

 

Risk of Major Cardiovascular Events by LDL-Cholesterol Level (mg/dL): Among those treated with high-dose statin therapy, more than 40% of patients failed to achieve an LDL-cholesterol target of less than 70 mg/dL.

Reporter: Aviva Lev-Ari, PhD., RN

https://pharmaceuticalintelligence.com/2014/07/29/risk-of-major-cardiovascular-events-by-ldl-cholesterol-level-mgdl-among-those-treated-with-high-dose-statin-therapy-more-than-40-of-patients-failed-to-achieve-an-ldl-cholesterol-target-of-less-th/

 

LDL, HDL, TG, ApoA1 and ApoB: Genetic Loci Associated With Plasma Concentration of these Biomarkers – A Genome-Wide Analysis With Replication

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/12/18/ldl-hdl-tg-apoa1-and-apob-genetic-loci-associated-with-plasma-concentration-of-these-biomarkers-a-genome-wide-analysis-with-replication/

 

Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/04/15/two-mutations-in-a-pcsk9-gene-eliminates-a-protein-involve-in-controlling-ldl-cholesterol/

Artherogenesis: Predictor of CVD – the Smaller and Denser LDL Particles

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/11/15/artherogenesis-predictor-of-cvd-the-smaller-and-denser-ldl-particles/

 

A Concise Review of Cardiovascular Biomarkers of Hypertension

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/04/25/a-concise-review-of-cardiovascular-biomarkers-of-hypertension/

 

Triglycerides: Is it a Risk Factor or a Risk Marker for Atherosclerosis and Cardiovascular Disease ? The Impact of Genetic Mutations on (ANGPTL4) Gene, encoder of (angiopoietin-like 4) Protein, inhibitor of Lipoprotein Lipase

Reporters, Curators and Authors: Aviva Lev-Ari, PhD, RN and Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/03/13/triglycerides-is-it-a-risk-factor-or-a-risk-marker-for-atherosclerosis-and-cardiovascular-disease-the-impact-of-genetic-mutations-on-angptl4-gene-encoder-of-angiopoietin-like-4-protein-that-in/

 

Excess Eating, Overweight, and Diabetic

Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/15/excess-eating-overweight-and-diabetic/

 

Obesity Issues

Larry H. Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/2015/11/12/obesity-issues/

 

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Cheetah Medical Introduces New Algorithm for Fluid Management

Reporter: Lawrence J Mulligan, PhD

 

Cheetah Medical Advances the Science of Fluid Management

Cheetah Medical is the pioneer and leading global provider of 100% noninvasive hemodynamic monitoring technologies that are designed for use in critical care, OR and emergency department settings. The CHEETAH NICOM™ and STARLING™ SV technologies use a proprietary algorithm to calculate parameters related to the volume of blood and the functioning of patients’ circulatory systems. Medical professionals use this information to assess patients’ unique volume requirements, guide volume management decisions and maintain adequate organ perfusion. Cheetah Medical technologies are designed to enable more confident, informed therapy decisions that support clinical goals of improving patient outcomes and driving economic efficiencies.

NEWTON, Mass. –(BUSINESS WIRE)– Cheetah Medical announced today that its eighth abstract on fluid management will be presented at Society of Critical Care Medicine meeting in January. Building on previous work, this abstract demonstrates a strong association between large volume fluid administration in septic shock and increased risk of death in more than 23,000 patients.

Each year, millions of patients require hemodynamic monitoring to ensure optimal volume and perfusion management. While intravenous fluid is typical first-line therapy for many critical care situations, volume management has been a challenge for the healthcare community. It is often difficult for a clinician to know the right amount of fluid to administer to patients, and there are serious complications associated with both under and over resuscitation.

“Ever since we’ve been using intravenous fluid, clinicians have been asking, ‘What is the right amount?’” said Doug Hansell, MD and Cheetah’s Chief Physician Executive. “Today, with non-invasive Cheetah technology, we have new tools to answer this question, and we are learning that getting this question right is more important than ever.”

Cheetah Medical has been working with leading researchers using a large U.S. dataset to better understand the risks and benefits of fluid administration. During the past two years, researchers have now released eight clinical abstracts on the importance of fluid management.

  • FLUID ADMINISTRATION IN SEPSIS AND SEPTIC SHOCK – PATTERNS AND OUTCOMES: Sepsis and septic shock is a huge national priority, as it is the most expensive condition to treat, at $24 billion per year (AHRQ). This study identified a strong association between large fluid administration (more than five liters) and excess mortality in septic shock patients. As expected, sicker patients received more fluid. However, even after accounting for the severity of illness, these patients had an increased risk of dying. (Society of Critical Care Medicine Annual Conference, January 2017)
  • FLUID ADMINISTRATION IN OPEN AND LAPAROSCOPIC ABDOMINAL SURGERY: The study looked at the relationship between intraoperative fluid therapy and complications following abdominal surgery.Based on data from 18,633 patients, an increase in complications was found with day-of-surgery fluid use above five liters for open abdominal procedures. The study recommended individualized fluid therapy to reduce potentially negative effects from over/under resuscitation with intravenous fluids. (American Society of Anesthesiologists [ASA] 2016 Annual Meeting)
  • FLUID PRESCRIPTIONS IN HOSPITALIZED PATIENTS WITH RENAL FAILURE: The implication of volume resuscitation and potential complications among patients with acute kidney injuries (AKIs) has been widely debated. This study examined the relationship between fluid administration and outcomesamong 62,695 AKI patients. It found the potential for both under and over resuscitation in those who received treatments with vasopressors. A better understanding of individual fluid needs was seen for patients requiring pressor and mechanical ventilation support. (European Society of Intensive Care Medicine [ESICM] Annual Congress, 2016)
  • EFFECTS OF FLUIDS ADMINISTRATION IN PATIENTS WITH SEPTIC SHOCK WITH OR WITHOUT HEART FAILURE (HF): The study examined the relationship between indications of fluid overload in sepsis patients (with or without diastolic HF) and outcomes. For 29,098 patients, mortality was the highest among those who received the highest volumes of fluid. It also noted that patients with diagnosed diastolic HF received less fluids and exhibited a significantly lower mortality than predicted. These lower mortality rates could be a result of a more conservative fluid treatment strategy applied in patients known to be at risk for fluid overload. (American Thoracic Society [ATS] 2016 International Conference)
  • WIDE PRACTICE VARIABILITY IN FLUID RESUSCITATION OF CRITICALLY ILL PATIENTS WITH ARDS: The study looked at how variable fluid resuscitation testing and treatments impacted the outcomes of patients with acute respiratory distress syndrome (ARDS). An analysis of 1,052 patients highlighted a highly variable fluid resuscitation. The findings suggest a widespread variability in provider decision-making regarding fluid resuscitation, which may be detrimental to quality and costs, lowering the overall value of care. (American Thoracic Society [ATS] 2016 International Conference)
  • POTENTIAL HARM ASSOCIATED WITH SEVERITY-ADJUSTED TREATMENT VARIABILITY IN FLUID RESUSCITATION OF CRITICALLY ILL SEPTIC PATIENTS: The study set out to determine treatment variability for patients with severe sepsis and how it may impact mortality. Retrospectively analyzing 77,032 patients, a high degree of treatment variability was found for fluid resuscitation, with a range of 250 ml to more than 7L of fluid administered. For patients who received less fluid, there was no increased risk of mortality. In those who received the most fluid, there was a strong association with worse hospital mortality. (American Thoracic Society [ATS] 2016 International Conference)
  • ASSOCIATION OF FLUIDS AND OUTCOMES IN EMERGENCY DEPARTMENT PATIENTS HOSPITALIZED WITH COMMUNITY-ACQUIRED PNEUMONIA (CAP): Analyzing 192,806 CAP patients, the study looked at the correlation between fluid-volume overload, hospital mortality and ventilator-free days (VFDs). A significant association was found between the amount of fluid administered on day one, increased mortality and decreased VFDs. The study may have also identified a subset of CAP patients who could benefit from a more restrictive fluid strategy. (36thInternational Symposium on Intensive Care and Emergency Medicine)
  • FLUID ADMINISTRATION IN COMMUNITY-ACQUIRED SEPSISEXAMINATION OF A LARGE ADMINISTRATIVE DATABASE: The study looked at variation in fluid administration practices and compliance with “Surviving Sepsis” guidelines, which recommend a minimum initial fluid administration of 30cc/kg in sepsis-induced tissue hypoperfusion patients. It found that a substantial proportion of patients (47.4 %) with community-acquired sepsis received less than the recommended guidelines within the first 24 hours. (Society of Critical Care Medicine Annual Conference, 2016)

“We are very proud to have supported this work – we are advancing the science of fluid management and helping to improve our understanding of how better fluid management may improve patient outcomes,” said Chris Hutchison, CEO of Cheetah Medical.

 

SOURCE

https://www.cheetah-medical.com/cheetah-medical-advances-science-fluid-management/

 

Other related articles published in this Open Access On-line Scientific Journal includes the following:

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Thriving Three Groups on LinkedIn

Groups Launcher and Group Manager: Aviva Lev-Ari, PhD, RN

 

Cardiovascular Biotech & Pharma UK & US Networking Group

906 members

https://www.linkedin.com/groups/4357927

 

 

Leaders in Pharmaceutical Business Intelligence

336 members

https://www.linkedin.com/groups/4346921

 

 

Innovation in Israel

172 members

https://www.linkedin.com/groups/2987122

 

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Lysyl Oxidase (LOX) gene missense mutation causes Thoracic Aortic Aneurysm and Dissection (TAAD) in Humans because of inadequate cross-linking of collagen and elastin in the aortic wall

Mutation carriers may be predisposed to vascular diseases because of weakened vessel walls under stress conditions.

 

Reporting: Aviva Lev-Ari, PhD, RN

 

Loss of function mutation in LOX causes thoracic aortic aneurysm and dissection in humans

  1. Vivian S. Leea,
  2. Carmen M. Halabia,b,
  3. Erin P. Hoffmanc,1,
  4. Nikkola Carmichaelc,d,
  5. Ignaty Leshchinerc,d,
  6. Christine G. Liand,e,
  7. Andrew J. Bierhalsf,
  8. Dana Vuzmanc,d,
  9. Brigham Genomic Medicine2,
  10. Robert P. Mechama,
  11. Natasha Y. Frankc,d,g,3, and
  12. Nathan O. Stitzielh,i,j,3

Edited by J. G. Seidman, Harvard Medical School, Boston, MA, and approved June 7, 2016 (received for review January 27, 2016)

  • Author contributions: V.S.L., R.P.M., N.Y.F., and N.O.S. designed research; V.S.L., C.M.H., and N.O.S. performed research; E.P.H., N.C., C.G.L., D.V., B.G.M.P., R.P.M., and N.Y.F. contributed new reagents/analytic tools; V.S.L., C.M.

Significance

The mechanical integrity of the arterial wall is dependent on a properly structured ECM. Elastin and collagen are key structural components of the ECM, contributing to the stability and elasticity of normal arteries. Lysyl oxidase (LOX) normally cross-links collagen and elastin molecules in the process of forming proper collagen fibers and elastic lamellae. Here, using whole-genome sequencing in humans and genome engineering in mice, we show that a missense mutation in LOX causes aortic aneurysm and dissection because of insufficient elastin and collagen cross-linking in the aortic wall. These findings confirm mutations in LOX as a cause of aortic disease in humans and identify LOX as a diagnostic and potentially therapeutic target.

Abstract

Thoracic aortic aneurysms and dissections (TAAD) represent a substantial cause of morbidity and mortality worldwide. Many individuals presenting with an inherited form of TAAD do not have causal mutations in the set of genes known to underlie disease. Using whole-genome sequencing in two first cousins with TAAD, we identified a missense mutation in the lysyl oxidase (LOX) gene (c.893T > G encoding p.Met298Arg) that cosegregated with disease in the family. Using clustered regularly interspaced short palindromic repeats (CRISPR)/clustered regularly interspaced short palindromic repeats-associated protein-9 nuclease (Cas9) genome engineering tools, we introduced the human mutation into the homologous position in the mouse genome, creating mice that were heterozygous and homozygous for the human allele. Mutant mice that were heterozygous for the human allele displayed disorganized ultrastructural properties of the aortic wall characterized by fragmented elastic lamellae, whereas mice homozygous for the human allele died shortly after parturition from ascending aortic aneurysm and spontaneous hemorrhage. These data suggest that a missense mutation in LOX is associated with aortic disease in humans, likely through insufficient cross-linking of elastin and collagen in the aortic wall. Mutation carriers may be predisposed to vascular diseases because of weakened vessel walls under stress conditions. LOX sequencing for clinical TAAD may identify additional mutation carriers in the future. Additional studies using our mouse model of LOX-associated TAAD have the potential to clarify the mechanism of disease and identify novel therapeutics specific to this genetic cause.

SOURCE

http://www.pnas.org/content/early/2016/07/15/1601442113.abstract

Missense LOX Mutation Linked to Aortic Rupture, Aneurysm

NEW YORK (GenomeWeb) – Researchers from Washington University School of Medicine have linked a LOX gene variant with aortic rupture and aneurysm.

As they reported in the online early edition of the Proceedings of the National Academy of Sciences yesterday, the researchers sequenced two first cousins from a family with a history of aortic ruptures and aneurysms to uncover a missense mutation in the lysyl oxidase (LOX) gene, which encodes a protein that cross-links elastin and collagen. When they used CRISPR/Cas9 genome engineering to introduce the mutation into a mouse model, mice heterogeneous for the mutation had disorganized aortic walls, while mice homozygous for the mutation died shortly after birth of ascending aneurysm and spontaneous hemorrhage, suggesting that the LOX variant might be causal.

Read more @ the Source

SOURCE

https://www.genomeweb.com/sequencing/missense-lox-mutation-linked-aortic-rupture-aneurysm

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Entire Family of Impella Abiomed Impella® Therapy Left Side Heart Pumps: FDA Approved To Enable Heart Recovery

Reporter: Aviva Lev-Ari, PhD, RN

 

Abiomed Impella® Therapy Receives FDA Approval for Cardiogenic Shock After Heart Attack or Heart Surgery

Entire Family of Impella Left Side Heart Pumps FDA Approved To Enable Heart Recovery

DANVERS, Mass., April 07, 2016 (GLOBE NEWSWIRE) — Abiomed, Inc. (NASDAQ:ABMD), a leading provider of breakthrough heart support technologies, today announced that it has received U.S. Food and Drug Administration (FDA) Pre-Market Approval (PMA) for its Impella 2.5™, Impella CP®, Impella 5.0™ and Impella LD™ heart pumps to provide treatment of ongoing cardiogenic shock. In this setting, the Impella heart pumps stabilize the patient’s hemodynamics, unload the left ventricle, perfuse the end organs and allow for recovery of the native heart.  This latest approval adds to the prior FDA indication of Impella 2.5 for high risk percutaneous coronary intervention (PCI), or Protected PCI™, received in March 2015.

With this approval, these are the first and only percutaneous temporary ventricular support devices that are FDA-approved as safe and effective for the cardiogenic shock indication, as stated below:

The Impella 2.5, Impella CP, Impella 5.0 and Impella LD catheters, in conjunction with the Automated Impella Controller console, are intended for short-term use (<4 days for the Impella 2.5 and Impella CP and <6 days for the Impella 5.0 and Impella LD) and indicated for the treatment of ongoing cardiogenic shock that occurs immediately (<48 hours) following acute myocardial infarction (AMI) or open heart surgery as a result of isolated left ventricular failure that is not responsive to optimal medical management and conventional treatment measures with or without an intra-aortic balloon pump.  The intent of the Impella system therapy is to reduce ventricular work and to provide the circulatory support necessary to allow heart recovery and early assessment of residual myocardial function.

The product labeling also allows for the clinical decision to leave Impella 2.5, Impella CP, Impella 5.0 and Impella LD in place beyond the intended duration of four to six days due to unforeseen circumstances.

The Impella products offer the unique ability to both stabilize the patient’s hemodynamics before or during a PCI procedure and unload the heart, which allows the muscle to rest and potentially recover its native function. Heart recovery is the ideal option for a patient’s quality of life and as documented in several clinical papers, has the ability to save costs for the healthcare system1,2,3.

Cardiogenic shock is a life-threatening condition in which the heart is suddenly unable to pump enough blood and oxygen to support the body’s vital organs. For this approval, it typically occurs during or after a heart attack or acute myocardial infarction (AMI) or cardiopulmonary bypass surgery as a result of a weakened or damaged heart muscle. Despite advancements in medical technology, critical care guidelines and interventional techniques, AMI cardiogenic shock and post-cardiotomy cardiogenic shock (PCCS) carry a high mortality risk and has shown an incremental but consistent increase in occurrence in recent years in the United States.

“This approval sets a new standard for the entire cardiovascular community as clinicians continue to seek education and new approaches to effectively treat severely ill cardiac patients with limited options and high mortality risk,” said William O’Neill, M.D., medical director of the Center for Structural Heart Disease at Henry Ford Hospital. “The Impella heart pumps offer the ability to provide percutaneous hemodynamic stability to high-risk patients in need of rapid and effective treatment by unloading the heart, perfusing the end organs and ultimately, allowing for the opportunity to recover native heart function.”

“Abiomed would like to recognize our customers, physicians, nurses, scientists, regulators and employees for their last fifteen years of circulatory support research and clinical applications. This FDA approval marks a significant milestone in the treatment of heart disease. The new medical field of heart muscle recovery has begun,” said Michael R. Minogue, President, Chairman and Chief Executive Officer of Abiomed. “Today, Abiomed only treats around 5% of this AMI cardiogenic shock patient population, which suffers one of the highest mortality risks of any patient in the heart hospital. Tomorrow, Abiomed will be able to educate and directly partner with our customers and establish appropriate protocols to improve the patient outcomes focused on native heart recovery.”

Abiomed Data Supporting FDA Approval

The data submitted to the FDA in support of the PMA included an analysis of 415 patients from the RECOVER 1 study and the U.S. Impella registry (cVAD Registry™), as well as an Impella literature review including 692 patients treated with Impella from 17 clinical studies. A safety analysis reviewed over 24,000 Impella treated patients using the FDA medical device reporting (“MDR”) database, which draws from seven years of U.S. experience with Impella.

In addition, the Company also provided a benchmark analysis of Impella patients in the real-world Impella cVAD registry vs. these same patient groups in the Abiomed AB5000/BVS 5000 Registry. The Abiomed BVS 5000 product was the first ventricular assist device (VAD) ever approved by the FDA in 1991 based on 83 patient PMA study. In 2003, the AB5000 Ventricle received FDA approval and this also included a PMA study with 60 patients.

For this approval, the data source for this benchmark analysis was a registry (“AB/BVS Registry”) that contained 2,152 patients that received the AB5000 and BVS 5000 devices, which were originally approved for heart recovery. The analysis examined by the FDA used 204 patients that received the AB5000 device for the same indications. This analysis demonstrated significantly better outcomes with Impella in these patients.

The Company believes this is the most comprehensive review ever submitted to the FDA for circulatory support in the cardiogenic shock population.

  1. Maini B, Gregory D, Scotti DJ, Buyantseva L. Percutaneous cardiac assist devices compared with surgical hemodynamic support alternatives: Cost-Effectiveness in the Emergent Setting.Catheter Cardiovasc Interv. 2014 May 1;83(6):E183-92.
  2. Cheung A, Danter M, Gregory D. TCT-385 Comparative Economic Outcomes in Cardiogenic Shock Patients Managed with the Minimally Invasive Impella or Extracorporeal Life Support. J Am Coll Cardiol. 2012;60(17_S):. doi:10.1016/j.jacc.2012.08.413.
  3. Gregory D, Scotti DJ, de Lissovoy G, Palacios I, Dixon, Maini B, O’Neill W. A value-based analysis of hemodynamic support strategies for high-risk heart failure patients undergoing a percutaneous coronary intervention. Am Health Drug Benefits. 2013 Mar;6(2):88-99


ABOUT IMPELLA

Impella 2.5 received FDA PMA approval for high risk PCI in March 2015, is supported by clinical guidelines, and is reimbursed by the Centers for Medicare & Medicaid Services (CMS) under ICD-9-CM code 37.68 for multiple indications. The Impella RP® device received Humanitarian Device Exemption (HDE) approval in January 2015. The Impella product portfolio, which is comprised of Impella 2.5, Impella CP, Impella 5.0, Impella LD, and Impella RP, has supported over 35,000 patients in the United States.

The ABIOMED logo, ABIOMED, Impella, Impella CP, and Impella RP are registered trademarks of Abiomed, Inc. in the U.S.A. and certain foreign countries.  Impella 2.5, Impella 5.0, Impella LD, and Protected PCI are trademarks of Abiomed, Inc.

ABOUT ABIOMED
Based in Danvers, Massachusetts, Abiomed, Inc. is a leading provider of medical devices that provide circulatory support.  Our products are designed to enable the heart to rest by improving blood flow and/or performing the pumping of the heart.  For additional information, please visit: www.abiomed.com

FORWARD-LOOKING STATEMENTS
This release includes forward-looking statements.  These forward-looking statements generally can be identified by the use of words such as “anticipate,” “expect,” “plan,” “could,” “may,” “will,” “believe,” “estimate,” “forecast,” “goal,” “project,” and other words of similar meaning.  These forward-looking statements address various matters including, the Company’s guidance for fiscal 2016 revenue. Each forward-looking statement contained in this press release is subject to risks and uncertainties that could cause actual results to differ materially from those expressed or implied by such statement.  Applicable risks and uncertainties include, among others, uncertainties associated with development, testing and related regulatory approvals, including the potential for future losses, complex manufacturing, high quality requirements, dependence on limited sources of supply, competition, technological change, government regulation, litigation matters, future capital needs and uncertainty of additional financing, and the risks identified under the heading “Risk Factors” in the Company’s Annual Report on Form 10-K for the year ended March 31, 2015 and the Company’s Quarterly Report on Form 10-Q for the quarter ended September 30, 2015, each filed with the Securities and Exchange Commission, as well as other information the Company files with the SEC.  We caution investors not to place considerable reliance on the forward-looking statements contained in this press release.  You are encouraged to read our filings with the SEC, available at www.sec.gov, for a discussion of these and other risks and uncertainties.  The forward-looking statements in this press release speak only as of the date of this release and the Company undertakes no obligation to update or revise any of these statements.  Our business is subject to substantial risks and uncertainties, including those referenced above.  Investors, potential investors, and others should give careful consideration to these risks and uncertainties.

For more information, please contact: Aimee Genzler Director, Corporate Communications 978-646-1553 agenzler@abiomed.com Ingrid Goldberg Director, Investor Relations igoldberg@abiomed.com

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Cancer detection and therapeutics

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Kurzweill Reports

http://kurzweilai.us1.list-manage.com/track/click

Machine learning rivals human skills in cancer detection

Two announcements yesterday (April 21) suggest that deep learning algorithms rival human skills in detecting cancer from ultrasound images and in identifying cancer in pathology reports.

Samsung Medison RS80A ultrasound imaging system (credit: Samsung)

Samsung Medison, a global medical equipment company and an affiliate of Samsung Electronics, has just updated its RS80A ultrasound imaging system with a deep learning algorithm for breast-lesion analysis.

The “S-Detect for Breast” feature uses big data collected from breast-exam cases and recommends whether the selected lesion is benign or malignant. It’s used in in lesion segmentation, characteristic analysis, and assessment processes, providing “more accurate results.”

“We saw a high level of conformity from analyzing and detecting lesion in various cases by using the S-Detect,” said professor Han Boo Kyung, a radiologist at Samsung Medical Center.

“Users can reduce taking unnecessary biopsies and doctors-in-training will likely have more reliable support in accurately detecting malignant and suspicious lesions.”

Deep learning is better than humans in extracting meaning from cancer pathology reports

Meanwhile, researchers from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University-Purdue University Indianapolis say they’ve found that open-source machine learning tools are as good as — or better than — humans in extracting crucial meaning from free-text (unstructured) pathology reports and detecting cancer cases. The computer tools are also faster and less resource-intensive.

(U.S. states require cancer cases to be reported to statewide cancer registries for disease tracking, identification of at-risk populations, and recognition of unusual trends or clusters. This free-text information can be difficult for health officials to interpret, which can further delay health department action, when action is needed.)

“We think that its no longer necessary for humans to spend time reviewing text reports to determine if cancer is present or not,” said study senior author Shaun Grannis*, M.D., M.S., interim director of the Regenstrief Center of Biomedical Informatics.

Awash in oceans of data

“We have come to the point in time that technology can handle this. A human’s time is better spent helping other humans by providing them with better clinical care. Everything — physician practices, health care systems, health information exchanges, insurers, as well as public health departments — are awash in oceans of data. How can we hope to make sense of this deluge of data? Humans can’t do it — but computers can.”

This is especially relevant for underserved nations, where a majority of clinical data is collected in the form of unstructured free text, he said.

The researchers sampled 7,000 free-text pathology reports from over 30 hospitals that participate in the Indiana Health Information Exchange and used open source tools, classification algorithms, and varying feature selection approaches to predict if a report was positive or negative for cancer. The results indicated that a fully automated review yielded results similar or better than those of trained human reviewers, saving both time and money.

Major infrastructure advance

“We found that artificial intelligence was as least as accurate as humans in identifying cancer cases from free-text clinical data. For example the computer ‘learned’ that the word ‘sheet’ or ‘sheets’ signified cancer as ‘sheet’ or ‘sheets of cells’ are used in pathology reports to indicate malignancy.

“This is not an advance in ideas; it’s a major infrastructure advance — we have the technology, we have the data, we have the software from which we saw accurate, rapid review of vast amounts of data without human oversight or supervision.”

The study was published in the April 2016 issue of the Journal of Biomedical Informatics. It was conducted with support from the Centers for Disease Control and Prevention.

Co-authors of the study include researchers at the IU Fairbanks School of Public Health, the IU School of Medicine and the School of Science at IUPUI.

* Grannis, a Regenstrief Institute investigator and an associate professor of family medicine at the IU School of Medicine, is the architect of the Regenstrief syndromic surveillance detector for communicable diseases and led the technical implementation of Indiana’s Public Health Emergency Surveillance System — one of the nation’s largest. Studies over the past decade have shown that this system detects outbreaks of communicable diseases seven to nine days earlier and finds four times as many cases as human reporting while providing more complete data.

Yann Lecun is Director of AI Research, Facebook and a noted deep-learning expert. 

 

Toward better public health reporting using existing off the shelf approaches: A comparison of alternative cancer detection approaches using plaintext medical data and non-dictionary based feature selection

Suranga N. Kasthurirathnea, , Brian E. Dixonb, cJudy GichoyadHuiping XucYuni XiadBurke Mamlinb, dShaun J. Grannisb, d

Highlights

• Cancer cases can be identified in unstructured clinical data to support public health reporting.
• Such cancer detection methods do not require complex external ontologies or human intervention.
• Such approaches can identify cases with sensitivity, specificity, PPV, accuracy, and AUC exceeding 80–90%.
• Automated cancer detection methods perform as well as approaches that require costly clinician input.
• These approaches may be generalized for other health analytics applications and healthcare domains.

Abstract

Objectives

Increased adoption of electronic health records has resulted in increased availability of free text clinical data for secondary use. A variety of approaches to obtain actionable information from unstructured free text data exist. These approaches are resource intensive, inherently complex and rely on structured clinical data and dictionary-based approaches. We sought to evaluate the potential to obtain actionable information from free text pathology reports using routinely available tools and approaches that do not depend on dictionary-based approaches.

Materials and methods

We obtained pathology reports from a large health information exchange and evaluated the capacity to detect cancer cases from these reports using 3 non-dictionary feature selection approaches, 4 feature subset sizes, and 5 clinical decision models: simple logistic regression, naïve bayes, k-nearest neighbor, random forest, and J48 decision tree. The performance of each decision model was evaluated using sensitivity, specificity, accuracy, positive predictive value, and area under the receiver operating characteristics (ROC) curve.

Results

Decision models parameterized using automated, informed, and manual feature selection approaches yielded similar results. Furthermore, non-dictionary classification approaches identified cancer cases present in free text reports with evaluation measures approaching and exceeding 80–90% for most metrics.

Conclusion

Our methods are feasible and practical approaches for extracting substantial information value from free text medical data, and the results suggest that these methods can perform on par, if not better, than existing dictionary-based approaches. Given that public health agencies are often under-resourced and lack the technical capacity for more complex methodologies, these results represent potentially significant value to the public health field.

Graphical abstract
 Image for unlabelled figure

Scientists shoot anticancer drugs deep into tumors

Ultrasonic vibrations cause gas microbubbles to explode, releasing nanoparticles containing anticancer drugs

Schematic of a magnetic microbubble used in the study, containing gas core (blue) and shell of magnetic iron-oxide nanoparticles (red) that form a dense shell (center) around drug-containing nanoparticles. When stimulated by ultrasound at resonant frequencies, the microbubbles explode, releasing the nanoparticles, which can travel hundreds of micrometers into tumor tissue to deliver anticancer drugs and can also be imaged on an MRI machine. (credit: Yu Gao et al./NPG Asia Materials)    http://www.kurzweilai.net/images/magnetic-microbubble.jpg

 

Scientists at Nanyang Technological University (NTU Singapore) have invented a new way to deliver cancer drugs deep into tumor cells.

They created micro-sized gas bubbles coated with anticancer drug particles embedded in iron oxide nanoparticles and used MRI or other magnetic sources to direct these microbubbles to gather around a specific tumor. Then they used ultrasound to vibrate the microbubbles, providing the energy to direct the drug particles into a targeted kill zone in the tumor. The magnetic nanoparticles also allow for imaging in an MRI machine.

The microbubbles were successfully tested in mice and the study has been published by the Nature Publishing Group in Asia Materials.

Overcoming limitations of chemotherapy

This innovative technique was developed by a multidisciplinary team of scientists led by Asst Prof C. J. Xu from the School of Chemical and Biomedical Engineering and Assoc. Prof Claus-Dieter Ohl from the School of Physical and Mathematical Sciences.

Xu, who is also a researcher at the NTU-Northwestern Institute for Nanomedicine, said their new method may solve some of the most pressing problems faced in chemotherapy used to treat cancer.

The main problem is that current chemotherapy drugs cannot be easily targeted. The drug particles flow in the bloodstream, damaging both healthy and cancerous cells. Typically, these drugs are flushed away quickly in organs such as the lungs and liver, limiting their effectiveness.

The remaining drugs are also unable to penetrate deep into the core of the tumor, leaving some cancer cells alive, which could lead to a resurgence in tumor growth.

Delivering anticancer drugs deep into tumors

Schematic of the apparatus used to investigate magnetic microbubble oscillation and nanoparticle release (credit: Yu Gao et al./NPG Asia Materials)
http://www.kurzweilai.net/images/magnetic-microbubble-nanoparticle-release-setup.jpg

The microbubbles are magnetic, so after injecting them into the bloodstream, they can be clustered around the tumor using magnets to ensure that they don’t kill the healthy cells, explains Xu, who has been working on cancer diagnosis and drug delivery systems since 2004.

“More importantly, our invention is the first of its kind that allows drug particles to be directed deep into a tumor in a few milliseconds. They can penetrate a depth of 50 cell layers or more (about 200 micrometers) — twice the width of a human hair. This helps to ensure that the drugs can reach the cancer cells on the surface and also inside the core of the tumor.”

According to Clinical Associate Professor Chia Sing Joo, a Senior Consultant at the Tan Tock Seng Hospital’s Endoscopy Centre and the Urology & Continence Clinic, “For anticancer drugs to achieve their best effectiveness, they need to penetrate into the tumor efficiently in order to reach the cytoplasm of all the cancer cells that are being targeted without affecting the normal cells.

“Currently, this can [only] be achieved by means of a direct injection into the tumor or by administering a large dosage of anticancer drugs, which can be painful, expensive, impractical and might have various side effects. If successful, I envisage [the new drug-delivery system] can be a good alternative treatment in the future, one which is low cost and yet effective for the treatment of cancers involving solid tumors, as it might minimize the side effects of drugs.” Joo is a surgeon experienced in the treatment of prostate, bladder and kidney cancer and a consultant for this study.

According to Ohl, an expert in biophysics who has published previous studies involving drug delivery systems and bubble dynamics, “most prototype drug delivery systems on the market face three main challenges before they can be commercially successful: they have to be non-invasive, patient-friendly, and yet cost-effective. We were able to come up with our solution that addresses these three challenges.”

The 12-person study team included scientists from City University of Hong Kong and Technion – Israel Institute of Technology (Technion). The team plans to use this new drug delivery system in studies on lung and liver cancer using animal models, and eventually clinical studies.

They estimate that it will take another eight to ten years before it reaches human clinical trials.

 

Abstract of Controlled nanoparticle release from stable magnetic microbubble oscillations

Magnetic microbubbles (MMBs) are microbubbles (MBs) coated with magnetic nanoparticles (NPs). MMBs not only maintain the acoustic properties of MBs, but also serve as an important contrast agent for magnetic resonance imaging. Such dual-modality functionality makes MMBs particularly useful for a wide range of biomedical applications, such as localized drug/gene delivery. This article reports the ability of MMBs to release their particle cargo on demand under stable oscillation. When stimulated by ultrasound at resonant frequencies, MMBs of 450 nm to 200 μm oscillate in volume and surface modes. Above an oscillation threshold, NPs are released from the MMB shell and can travel hundreds of micrometers from the surface of the bubble. The migration of NPs from MMBs can be described with a force balance model. With this technology, we deliver doxorubicin-containing poly(lactic-co-glycolic acid) particles across a physiological barrier bothin vitro and in vivo, with a 18-fold and 5-fold increase in NP delivery to the heart tissue of zebrafish and tumor tissue of mouse, respectively. The penetration of released NPs in tissues is also improved. The ability to remotely control the release of NPs from MMBs suggests opportunities for targeted drug delivery through/into tissues that are not easily diffused through or penetrated.

 

 

Artificial protein controls first self-assembly of C60 fullerenes

New discovery expected to lead to new materials with properties such as higher strength, lighter weight, and greater chemical reactivity, resulting in applications ranging from medicine to energy and electronics
Buckminsterfullerene (C60), aka fullerene and buckyball (credit: St Stev via Foter.com / CC BY-NC-ND)   http://www.kurzweilai.net/images/Dartmouth-Artificial-Protein-Study.jpg

A Dartmouth College scientist and his collaborators* have created the first high-resolution co-assembly between a protein and buckminsterfullerene (C60), aka fullerene and buckyball (a sphere-like molecule composed of 60 carbon atoms and shaped like a soccer ball).

“This is a proof-of-principle study demonstrating that proteins can be used as effective vehicles for organizing nanomaterials by design,” says senior author Gevorg Grigoryan, an assistant professor of computer science at Dartmouth and senior author of a study discussed in an open-access paper in the journal in Nature Communications.

Proteins organize and orchestrate essentially all molecular processes in our cells. The goal of the new study was to create a new artificial protein that can direct the self-assembly of fullerene into ordered superstructures.

COP, a stable tetramer (a polymer derived from four identical single molecule) in isolation, interacts with C60 (fullerene) molecules via a surface-binding site and further self-assembles into a co-crystalline array called C60Sol–COP (credit: Kook-Han Kim et al./Nature Communications)   http://www.kurzweilai.net/images/self-assembly-with-fullernene.jpg

Grigoryan and his colleagues show that that their artificial protein organizes a fullerene into a lattice called C60Sol–COP. COP, a protein that is a stable tetramer (a polymer derived from four identical single molecules), interacted with fullerene molecules via a surface-binding site and further self-assembled into an ordered crystalline superstructure. Interestingly, the superstructure exhibits high charge conductance, whereas both the protein-alone crystal and amorphous C60 are electrically insulating.

Grigoryan says that if we learn to do the programmable self-assembly of precisely organized molecular building blocks more generally, it will lead to a range of new materials with properties such as higher strength, lighter weight, and greater chemical reactivity, resulting in a host of applications, from medicine to energy and electronics.

Fullerenes are currently used in nanotechnology because of their high heat resistance and electrical superconductivity (when doped), but the molecule has been difficult to organize in useful ways.

* The study also included researchers from Dartmouth College, Sungkyunkwan University, the New Jersey Institute of Technology, the National Institute of Science Education and Research, the University of California-San Francisco, the University of Pennsylvania, and the Institute for Basic Science.

Abstract of Protein-directed self-assembly of a fullerene crystal

Learning to engineer self-assembly would enable the precise organization of molecules by design to create matter with tailored properties. Here we demonstrate that proteins can direct the self-assembly of buckminsterfullerene (C60) into ordered superstructures. A previously engineered tetrameric helical bundle binds C60 in solution, rendering it water soluble. Two tetramers associate with one C60, promoting further organization revealed in a 1.67-Å crystal structure. Fullerene groups occupy periodic lattice sites, sandwiched between two Tyr residues from adjacent tetramers. Strikingly, the assembly exhibits high charge conductance, whereas both the protein-alone crystal and amorphous C60 are electrically insulating. The affinity of C60 for its crystal-binding site is estimated to be in the nanomolar range, with lattices of known protein crystals geometrically compatible with incorporating the motif. Taken together, these findings suggest a new means of organizing fullerene molecules into a rich variety of lattices to generate new properties by design.

 

Protein-directed self-assembly of a fullerene crystal

Kook-Han KimDong-Kyun KoYong-Tae KimNam Hyeong Kim,….., Yong Ho Kim Gevorg Grigoryan
Nature Communications 2016;7,(11429)
               http://www.nature.com/ncomms/2016/160426/ncomms11429/full/ncomms11429.html

Programmable self-assembly of molecular building blocks is a highly desirable way of achieving bottom-up control over novel functions and materials. Applications of molecular assemblies are well explored in the literature, ranging from optoelectronic1, 2, magnetic3, and photovoltaic4 devices to chemical and bioanalytical sensing5, and medicine6. However, it has been a daunting challenge to quantitatively describe and control the driving forces that govern self-assembly, particularly given the broad range of molecular building blocks one would like to organize. In this respect, nature’s self-assembling macromolecules hold considerable promise as standard chassis for encoding precise organization. By learning to engineer the assembly of these molecules, myriad other molecular building blocks can be co-organized in desired ways through non-covalent or covalent attachment. The protein polymer is a particularly attractive candidate for a standard assembly chassis given its rich chemical alphabet, diversity of available assembly geometries, broad ability to engage other molecular moieties, and the possibility of engineered function. Considerable progress has been made in the area of engineering protein assemblies7, 8, using either computational9, 10,11, 12, 13, 14 or rational approaches15, 16, 17, 18, but the problem remains a grand challenge. A major difficulty lies in accounting for the enormous continuum of possible assembly geometries available to proteins to engineer a sequence that predictably prefers just one. General design principles, which provide predictive rules of assembly, are thus of enormous utility in limiting the geometric search space and enabling robust design11, 19.

In this work, we demonstrate the first ever high-resolution structure of co-assembly between a protein and buckminsterfullerene (C60), which suggests a simple structural mode for protein–fullerene co-organization. Three separate crystal structures, resolved to 1.67, 1.76 and 2.35Å, reveal a protein lattice with C60 groups occupying periodic sites wedged between two helical segments, each donating a Tyr residue. A half site of the motif is estimated to have nM-scale affinity for C60, such that binding of fullerene appears to direct the organization of protein units in the co-crystal. The assembly exhibits a nm-spaced helical arrangement of fullerenes along a crystallographic axis, endowing the crystal with electrical conductance properties. We closely investigate the interfacial geometry of the C60-binding motif, finding it to be common among protein crystal lattices. C60 and its derivatives have been previously reported to interact with several proteins20, 21, 22, 23, 24, 25, although a high-resolution structure of a protein–C60 has been lacking. Still, prior evidence of interaction indicates that fullerenes and proteins are compatible as materials. This, together with the simple (and naturally recurrent) geometry of the C60-binding motif we discover, suggests that it may be possible to use the structural principles emergent from our study to generate a variety of C60–protein co-assemblies to further explore and exploit the properties of fullerenes26.

 

The aim of programmable self-assembly is to anticipate and harness unique collective properties that arise from precisely organized molecular building blocks. To this end, achieving atomic-level precision is crucial. This work demonstrates the first atomic resolution structures of a fullerene–protein assembly, establishing the feasibility of creating such objects, and further suggests a possible design principle for engineering such assemblies in general. How robust the discovered C60-binding motif is towards designing novel assemblies will need to be tested through a number of future design studies. However, the straightforward manner in which self-organization arose in our case, the simplicity of the C60-organizing motif in the lattice, together with its high affinity and the ubiquity of associated interfaces in natural protein lattices, are certainly promising with respect to the general applicability of the design principle. Our work also demonstrates the potential utility of exploring C60/protein co-organization, as derived supercrystals already showed synergistic charge conductance properties. Taken together, these results point to an exciting direction of inquiry towards generating protein–fullerene assemblies for the study and design of novel properties.

 

Scientists turn skin cells into heart and brain cells using only drugs — no stem cells required

Closer to the natural regeneration that happens in animals like newts and salamanders and no medical-safety and embryo concerns
Neurons created from chemically induced neural stem cells. The cells were created from skin cells that were reprogrammed into neural stem cells using a cocktail of only nine chemicals. This is the first time cellular reprogramming has been accomplished without adding external genes to the cells. (credit: Mingliang Zhang, PhD, Gladstone Institutes)   http://www.kurzweilai.net/images/Neurons-Created-From-Chemically-Induced-Neural-Stem-Cells.jpg

Scientists at the Gladstone Institutes have used chemicals to transform skin cells into heart cells and brain cells, instead of adding external genes — making this accomplishment a breakthrough, according to the scientists.

The research lays the groundwork for one day being able to regenerate lost or damaged cells directly with pharmaceutical drugs — a more efficient and reliable method to reprogram cells and one that avoids medical concerns surrounding genetic engineering.

Instead, in two studies published in an open-access paper in Science and in Cell Stem Cell, the team of scientists at the Roddenberry Center for Stem Cell Biology and Medicine at Gladstone used chemical cocktails to gradually coax skin cells to change into organ-specific stem-cell-like cells and ultimately into heart or brain cells.

“This method brings us closer to being able to generate new cells at the site of injury in patients,” said Gladstone senior investigator Sheng Ding, PhD, the senior author on both studies. “Our hope is to one day treat diseases like heart failure or Parkinson’s disease with drugs that help the heart and brain regenerate damaged areas from their own existing tissue cells. This process is much closer to the natural regeneration that happens in animals like newts and salamanders, which has long fascinated us.”

Chemically Repaired Hearts

A human heart cell that was chemically reprogrammed from a human skin cell (credit: Nan Cao/Gladstone Institutes)  http://www.kurzweilai.net/images/chemically-programmed-heart-cell.jpg

Transplanted adult heart cells do not survive or integrate properly into the heart and few stem cells can be coaxed into becoming heart cells.

Instead, in the Science study, the researchers used a cocktail of nine chemicals to change human skin cells into beating heart cells. By trial and error, they found the best combination of chemicals to begin the process by changing the cells into a state resembling multipotent stem cells (cells that can turn into many different types of cells in a particular organ). A second cocktail of chemicals and growth factors then helped transition the cells to become heart muscle cells.

With this method, more than 97% of the cells began beating, a characteristic of fully developed, healthy heart cells. The cells also responded appropriately to hormones, and molecularly, they resembled heart muscle cells, not skin cells. What’s more, when the cells were transplanted into a mouse heart early in the process, they developed into healthy-looking heart muscle cells within the organ.

“The ultimate goal in treating heart failure is a robust, reliable way for the heart to create new muscle cells,” said Srivastava, co-senior author on the Science paper. “Reprogramming a patient’s own cells could provide the safest and most efficient way to regenerate dying or diseased heart muscle.”

Rejuvenating the brain with neural stem cell-like cells

In the second study, authored by Gladstone postdoctoral scholar Mingliang Zhang, PhD, and published in Cell Stem Cell, the scientists created neural stem-cell-like cells from mouse skin cells using a similar approach.

The chemical cocktail again consisted of nine molecules, some of which overlapped with those used in the first study. Over ten days, the cocktail changed the identity of the cells, until all of the skin-cell genes were turned off and the genes of the neural stem-cell-like cells were gradually turned on.

When transplanted into mice, the neural stem-cell-like cells spontaneously developed into the three basic types of brain cells: neurons, oligodendrocytes, and astrocytes. The neural stem-cell-like cells were also able to self-replicate, making them ideal for treating neurodegenerative diseases or brain injury.

With their improved safety, these neural stem-cell-like cells could one day be used for cell replacement therapy in neurodegenerative diseases like Parkinson’s disease and Alzheimer’s disease, according to co-senior author Yadong Huang, MD, PhD, a senior investigator at Gladstone. “In the future, we could even imagine treating patients with a drug cocktail that acts on the brain or spinal cord, rejuvenating cells in the brain in real time.”

 

Gladstone Institutes | Chemically Reprogrammed Beating Heart Cell

Abstract of Conversion of human fibroblasts into functional cardiomyocytes by small molecules

Reprogramming somatic fibroblasts into alternative lineages would provide a promising source of cells for regenerative therapy. However, transdifferentiating human cells to specific homogeneous, functional cell types is challenging. Here we show that cardiomyocyte-like cells can be generated by treating human fibroblasts with a combination of nine compounds (9C). The chemically induced cardiomyocyte-like cells (ciCMs) uniformly contracted and resembled human cardiomyocytes in their transcriptome, epigenetic, and electrophysiological properties. 9C treatment of human fibroblasts resulted in a more open-chromatin conformation at key heart developmental genes, enabling their promoters/enhancers to bind effectors of major cardiogenic signals. When transplanted into infarcted mouse hearts, 9C-treated fibroblasts were efficiently converted to ciCMs. This pharmacological approach for lineage-specific reprogramming may have many important therapeutic implications after further optimization to generate mature cardiac cells.


Abstract of Pharmacological Reprogramming of Fibroblasts into Neural Stem Cells by Signaling-Directed Transcriptional Activation

Cellular reprogramming using chemically defined conditions, without genetic manipulation, is a promising approach for generating clinically relevant cell types for regenerative medicine and drug discovery. However, small-molecule approaches for inducing lineage-specific stem cells from somatic cells across lineage boundaries have been challenging. Here, we report highly efficient reprogramming of mouse fibroblasts into induced neural stem cell-like cells (ciNSLCs) using a cocktail of nine components (M9). The resulting ciNSLCs closely resemble primary neural stem cells molecularly and functionally. Transcriptome analysis revealed that M9 induces a gradual and specific conversion of fibroblasts toward a neural fate. During reprogramming specific transcription factors such as Elk1 and Gli2 that are downstream of M9-induced signaling pathways bind and activate endogenous master neural genes to specify neural identity. Our study provides an effective chemical approach for generating neural stem cells from mouse fibroblasts and reveals mechanistic insights into underlying reprogramming processes.

 

Ultrafast laser technique identifies brain tumors in real time

04/19/2016  Associate Editor, BioOptics World

A research group at VU University Amsterdam (The Netherlands) has shown that an ultrafast laser technique can reveal exactly where brain tumors are, producing images in less than a minute and enabling surgeons to removetumors without compromising healthy tissue.

Related: OCT-based approach facilitates brain cancer surgery

Pathologists typically use staining methods, in which chemicals like hematoxylin and eosin turn different tissue components blue and red, revealing its structure and whether there are any tumor cells. But for a definitive diagnosis, this process can take up to 24 hours—which means surgeons may not realize some cancerous tissue has escaped from their attention until after surgery, requiring a second operation and more risk.

But the research team’s new ultrafast laser technique is label-free—instead, they fire short, 20-fs-long laser pulses into the tissue, and when three photons converge at the same time and place, the photons interact with the nonlinear optical properties of the tissue. Through well-known phenomena in optics called second- and third-harmonic generation, these interactions produce a single photon.

The key is that the incoming and outgoing photons have different wavelengths. The incoming photons are at 1200 nm, long enough to penetrate deep into the tissue. The single photon that is produced, however, is at 600 or 400 nm, depending on if it’s second- or third-harmonic generation. The shorter wavelengths mean the photon can scatter in the tissue. The scattered photon thus contains information about the tissue, and when it reaches a detector—in this case, a high-sensitivity gallium arsenide phosphide (GaAsP) photomultiplier tube—it reveals what the tissue looks like inside.

Tissue from a patient diagnosed with low-grade glioma. The green image is taken with the new method, while the pink uses conventional hematoxylin and eosin staining. Going from the upper left to the lower right, both images show increasing cell density because of more tumor tissue. The insets reveal the high density of tumor cells. (Credit: N.V. Kuzmin et al, VU University Amsterdam, The Netherlands)

The research team used the technique to analyze glial brain tumors, which are particularly deadly because it’s hard to get rid of tumor cells by surgery, irradiation, and chemotherapy without substantial collateral damage to the surrounding brain tissue. They tested their method on samples of glial brain tumors from humans, finding that the histological detail in these images was as good—if not better—than those made with conventional staining techniques. They were able to make most images in under a minute. The smaller ones took less than a second, while larger images of a few square millimeters took five minutes—making it possible to do it in real time in the operating room, according to Marloes Groot of VU University Amsterdam, who led the work.

Now that they’ve shown their approach works, the researchers are developing a handheld device that a surgeon can use to identify a tumor’s border during surgery. The incoming laser pulses can only reach a depth of about 100 µm into the tissue. To reach farther, Groot envisions attaching a needle that can pierce the tissue and deliver photons deeper, allowing diagnosis during an operation and possibly before surgery begins.

Full details of the work appear in the journal Biomedical Optics Express; for more information, please visit http://dx.doi.org/10.1364/boe.7.001889.

Third harmonic generation imaging for fast, label-free pathology of human brain tumors

N. V. Kuzmin, P. Wesseling, P. C. de Witt Hamer, D. P. Noske, G. D. Galgano, H. D. Mansvelder, J. C. Baayen, and M. L. Groot
Biomedical Optics Express > Volume 7 > Issue 5 > Page 1889

In brain tumor surgery, recognition of tumor boundaries is key. However, intraoperative assessment of tumor boundaries by the neurosurgeon is difficult. Therefore, there is an urgent need for tools that provide the neurosurgeon with pathological information during the operation. We show that third harmonic generation (THG) microscopy provides label-free, real-time images of histopathological quality; increased cellularity, nuclear pleomorphism, and rarefaction of neuropil in fresh, unstained human brain tissue could be clearly recognized. We further demonstrate THG images taken with a GRIN objective, as a step toward in situ THG microendoscopy of tumor boundaries. THG imaging is thus a promising tool for optical biopsies.

 

 

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A Concise Review of Cardiovascular Biomarkers of Hypertension

Curator: Larry H. Bernstein, MD, FCAP

LPBI

Revised 5/25/2016

 

Introduction

While a large body of work had been done on cholesterol synthesis, HDL and LDL cholesterol, triglycerides, and lipoproteins for a quarter century, and the concept of metabolic syndrome was emerging, there was neither a unifying concept nor a sufficient multivariable approach to apply the use of laboratory markers to clinical practice.  The mathematical foundation for such an evaluation of the biological markers and the computational tools were maturing at the turn of the 20th century, and the interest in outcomes research for improved healthcare practice was maturing. In addition, there was now heavy investment in health information systems that would support emerging health networks of a rapidly consolidating patient base.  This has become important for the pharmaceutical industry and for allied health sciences to enable a suitable method of measuring the effectiveness of drug and of lifestyle changes to improve the population health.

The importance of finding biomarkers for hypertension is significant as stated above. I refer to observations in a lecture by Teresa Seeman, Ph.D., Professor, UCLA Geffen School of Medicine (1).
The missed cased of hypertension in the U.S. alone has been examined by the NHANES studies. Table  I
shows the poor identification of this serious chronic condition. The next table (Table II)*, also from NHANES  (Seeman study) looks at Allostatic Load for biomarkers using component biomarker measurement criterion cutpoints.  Table III* gives the odds ratios for mortality by Allostatic Load Score.

An explanatory problem for our difficulty with diagnosis of a number of hypertension disease “subsets” is that there is peripheral hypertension that might be idiopathic, or it might be related to coexisting diseases with both inflammatory and vascular structural dynamics nature.  In addition, this may be concurrent with pulmonary hypertension, systemic hypertension, and progressive renal disease.  This discussion is reserved for later.  As stated, the late or missed diagnosis of systemic or essential idiopathic hypertension is illustrated in the three Seeman tables (1).

 

Table 1

Table 2

Table 3

 

 

 

 

Table 1*. Missed cases by “self report”

Self-reports

vs undiagnosed

study NHANES 88-94 NHANES 99-2004 NHANES 2005-08
Hypertension %unaware  BP > 140/90 42.7 43.5 39.06
SR-controlled
SR-high

Unaware

  7.45

10

13.88

8.35

10.85

16.12

6.5

10.18

19.98

High cholesterol Chol > 220 g/dl 55.93 49.3 47.05
SR-controlled
SR- high
Unaware
  11.02
8.68
12.12
8.47
8.72
18.5
7.22
8.12
23.46
Diabetes HgA1C > 6.4%      
SR-controlled

SR- high

Unaware

  2.41

3.43

1.64

1.76

5.01

3.09

2.11
5.51
3.09

*modified from Seeman

 

 

 

 

 

 

 

 

 

Table II* USHANES: Allostatic Load – component cutpoints

Biomarker Total N High Risk Percent (%) Cutpoint
DBP (mm Hg) 15,489 1,180   7.62    90
SBP (mm Hg) 15,491 3,461 22.34  140
Pulse Rate 15,117 1,009   6.67    90
HgA1C (%) 15,441 1,482   9.60    6.4
WHR 14,824 6,778 45.72    0.94
HDL Cholesterol (mg/dl) 15,187 3,440 22.65     40
Total Cholesterol

(mg/dl)

15,293 3,196  20.90    240

*From  T. Seaman, UCLA Geffen SOM

 

Table III*. Odds of mortality by Allostatic Load Score.

ALS Odds Ratio
7-8 5
6 2.6
5 2.3
4 2.1
3 1.8
2 1.5
1 1.4

 

*From  T. Seaman, UCLA Geffen SOM

 

I refer to cardiovascular diseases in reference to an aggregate of diseases affecting the heart, the circulatory system from large artery to the capillary, the lungs and kidneys, excluding the lymphatics.
These major disease entities are both separate and interrelated, not necessarily found in the same combinations. However, they account for a growing proportion of illness, apart from cancers, that affect the aging population of western societies. In the discussion that follows, I shall construct a picture of the pathophysiology of cardiovascular diseases, describe the major biomarkers for the assessment of these, point out the relationship of these to hypertension, and try to develop a more targeted approach to the assessment of hypertension and related disorders.

Chronic kidney disease (CKD) is defined as persistent kidney damage accompanied by a reduction in the glomerular filtration rate (GFR) and the presence of albuminuria. The rise in incidence of CKD is attributed to an aging populace and increases in hypertension (HTN), diabetes, and obesity within the U.S. population. CKD is associated with a host of complications including electrolyte imbalances, mineral and bone disorders, anemia, dyslipidemia, and HTN. It is well known that CKD is a risk factor for cardiovascular disease (CVD), and that a reduced GFR and albuminuria are independently associated with an increase in cardiovascular and all-cause mortality.

The relationship between CKD and HTN is cyclic, as CKD can contribute to or cause HTN (3). Elevated BP leads to damage of blood vessels within the kidney, as well as throughout the body. This damage impairs the kidney’s ability to filter fluid and waste from the blood, leading to an increase of fluid volume in the blood—thus causing an increase in BP.

 

A cursory description of the blood circulation

The full circulation involves the heart as a pump, and the arteries and veins, comprising small and large vessels, and capillaries at the point of delivery of oxygen and capture of carbon dioxide, and of transfer of substrates to tissues.  The brain, liver, pancreas and spleen, and endocrines are not further considered here, except for a consideration on neuro-humoral peptides that have emerged in the regulation of blood pressure and are essential to the stress response. The lung and the liver are both important with respect to the exchange of air and metabolites, and both have secondary circulations, the pulmonary and the portal vascular circulations.  In the case of the lungs, the vena cava flows into the right atrium, which delivers unoxygenated blood to the lungs via the right ventricle and right pulmonary artery, which returns to the left atrium by way of the right pulmonary vein.  The blood from the left atrium that flows into the left ventricle is ejected into the aorta.  The coronary arteries that nourish the heart are at the base of the aorta.  The heart muscle is a syncytium, unlike striated muscle, and it is densely packed with mitochondria, suitable for continuous contraction under vasovagal control. This is the anatomical construct, but the physiology is still being clarified because normal function and disease are both a matter of regulatory control.

In order to understand hypertension, we have to view the heart functioning over a long period of time.
In a still frame picture, we envision the left ventricle contracts emptying the oxygenated blood into the circulation. The ejection of blood into the aorta is called systole, by which the blood is delivered by the force of contraction into the circulation.  The filling pressure is called diastole.  So we have a filling and an emptying, and heard by the stethoscope is a lub-dub, synchronously repeated.   A normal systolic blood pressure is below 120. A systolic blood pressure of 120 to 139 means you have prehypertension, or borderline high blood pressure. Even people with prehypertension are at a higher risk of developing heart disease. A systolic blood pressure number of 140 or higher is considered to be hypertension, or high blood pressure. The diastolic blood pressure number or the bottom number indicates the pressure in the arteries when the heart rests between beats. A normal diastolic blood pressure number is less than 80. A diastolic blood pressure between 80 and 89 indicates prehypertension. A diastolic blood pressure number of 90 or higher is considered to be hypertension or high blood pressure. So now we have identified a systolic and a diastolic high blood pressure. Systolic pressure increases with vigorous activity, and becomes normal when the activity resides.  The systolic blood pressure increases with age. Over time, consistently high blood pressure weakens and damages the blood vessels so affected. Moreover, changes in the body’s normal functions may cause high blood pressure, including changes to kidney fluid and salt balances, the renin-angiotensin-aldosterone system, sympathetic nervous system activity, and blood vessel structure and function.

 

Starling’s Law of the Heart

Two principal intrinsic mechanisms, namely the Frank-Starling mechanism and rate induced regulation, enable the myocardium to adapt to changes in hemodynamic conditions. The Frank-Starling mechanism (also referred to as Starling’s law of the heart), is invoked in response to changes in the resting length of the myocardial fibers. Rate-induced regulation is invoked in response to changes in the frequency of the heartbeat.  (3-9).

Frank and Starling (3, 4) showed that an increase in diastolic volume caused an increase in systolic performance. The stretch effect persists across a range of myocardial contractile states, but during exercise it plays only a lesser role augmenting ventricular function maximal exercise. This is because in healthy human subjects adrenergic reflex mechanisms modulate myocardial performance, heart rate, vascular impedance and coronary flow during exercise and changes in these variables can overshadow the effect of fiber stretch or even prevent an increase in end-diastolic volume during stress (5). (See you- tube (6).

According to Lakatta muscle length modulates the extent of myofilament calcium ion (Ca2+) activation (7-9).   Similarly, the fiber length during a contraction, which is determined in part by the load encountered during shortening, also determines the extent of myofilament Ca2+ activation. Therefore, the terms preload, afterload and myocardial contractile state lose part of their significance in light of current knowledge.

 

Biology and High Blood Pressure

Researchers continue to study how various changes in normal body functions cause high blood pressure. The key functions affected in high blood pressure include (10):

Kidney Fluid and Salt Balances

The kidneys normally regulate the body’s salt balance by retaining sodium and water and excreting potassium. Imbalances in this kidney function can expand blood volumes, which can cause high blood pressure.

Renin-Angiotensin-Aldosterone System

The renin-angiotensin-aldosterone system makes angiotensin and aldosterone hormones. Angiotensin narrows or constricts blood vessels, which can lead to an increase in blood pressure. Aldosterone controls how the kidneys balance fluid and salt levels. Increased aldosterone levels or activity may change this kidney function, leading to increased blood volumes and high blood pressure.

Sympathetic Nervous System Activity

The sympathetic nervous system has important functions in blood pressure regulation, including heart rate, blood pressure, and breathing rate. Researchers are investigating whether imbalances in this system cause high blood pressure.

Blood Vessel Structure and Function

Changes in the structure and function of small and large arteries may contribute to high blood pressure. The angiotensin pathway and the immune system may stiffen small and large arteries, which can affect blood pressure.

Two or more types of hypertension

Systemic hypertension

Idiopathic hypertension

Hypertension from chronic renal disease

Pulmonary artery hypertension

Hypertension associated with systemic chronic inflammatory disease (rheumatoid arthritis and other collagen vascular diseases)

Genetic Causes of High Blood Pressure

Much of the understanding of the body systems involved in high blood pressure has come from genetic studies. High blood pressure often runs in families. Years of research have identified many genes and other mutations associated with high blood pressure, some in the renal salt regulatory and renin-angiotensin-aldosterone pathways. However, these known genetic factors only account for 2 to 3 percent of all cases. Emerging research suggests that certain DNA changes during fetal development also may cause the development of high blood pressure later in life.

Environmental Causes of High Blood Pressure

Environmental causes of high blood pressure include unhealthy lifestyle habits, being overweight or obese, and medicines.

Other medical causes of high blood pressure include other medical conditions such as chronic kidney disease, sleep apnea, thyroid problems, or certain tumors.

The common complications of hypertension and their signs and symptoms include:

http://www.nhlbi.nih.gov/health/health-topics/topics/hbp/causes10

 

Pulse Pressure and Stroke Volume

The  pulse pressure is the difference between systolic (the upper number) and diastolic (the lower number) (11).

Systemic pulse pressure = Psystolic – Pdiastolic

The pulse pressure is 40 mmHg for a typical blood pressure reading of 120/80 mmHg.

Pulse pressure (PP) is proportional to stroke volume (SV), the amount of blood pumped from the heart in one beat, and inversely proportional to the compliance or flexibility of the blood vessels, mainly the aorta.

A low (also called narrow) pulse pressure means that not much blood is being expelled from the heart, and can be caused by a number of factors, including severe blood loss due to trauma, congestive heart failure, shock, a narrowing of the valve leading from the heart to the aorta (stenosis), and fluid accumulating around the heart (tamponade).

High (or wide) pulse pressures occur during exercise, as stroke volume increases and the overall resistance to blood flow decreases. It can also occur for many reasons, such as hardening of the arteries (which can have numerous causes), various deficiencies in the aorta (mainly) or other arteries, including leaksfistulas, and a usually-congenital condition known as AVM, pain/anxiety, fever, anemia, pregnancy, and more. Certain medications for high blood pressure can widen pulse pressure, while others narrow it. A chronic increase in pulse pressure is a risk factor for heart disease, and can lead to the type of arrhythmia called atrial fibrillation or A-Fib.

 

Hypertension Background and Definition

The prevalence of CKD has steadily increased over the past two decades, and was reported to affect over 13% of the U.S. population in 2004.  In 2009, more than 570,000 people in the United States were classified as having end-stage renal disease (ESRD), including nearly 400,000 dialysis patients and over 17,000 transplant recipients.  A patient is determined to have ESRD when he or she requires replacement therapy, including dialysis or kidney transplantation. A National Health Examination Survey (NHANES) spanning 2005-2006 showed that 29% of US adults 18 years of age and older were hypertensive, and of those with high blood pressure (BP), 78% were aware they were hypertensive, 68% were being treated with antihypertensive agents, and only 64% of treated individuals had controlled hypertension (12, 13). In addition, data from NHANES 1999-2006 estimated that 30% of adults 20 years of age and older have prehypertension, defined as an untreated SBP of 120-139 mm Hg or untreated DBP of 80-89 mmHg (12, 13).

Hypertension is the most important modifiable risk factor for coronary heart disease (the leading cause of death in North America), stroke (the third leading cause), congestive heart failure, end-stage renal disease, and peripheral vascular disease. The 2010 Institute for Clinical Systems Improvement (ICSI) guideline (14) on the diagnosis and treatment of hypertension indicates that systolic blood pressure (SBP) should be the major factor to detect, evaluate, and treat hypertension In adults aged 50 years and older. The 2013 joint European Society of Hypertension (ESH) (15) and the European Society of Cardiology (ESC) (16) guidelines recommend that ambulatory blood-pressure monitoring (ABPM) be incorporated into the assessment of cardiovascular risk factors and hypertension.

The JNC 7 (17) identifies the following as major cardiovascular risk factors:

  • Hypertension: component of metabolic syndrome
  • Tobacco use, particularly cigarettes, including chewing tobacco
  • Elevated LDL cholesterol (or total cholesterol ≥240 mg/dL) or low HDL cholesterol: component of metabolic syndrome
  • Diabetes mellitus: component of metabolic syndrome
  • Obesity (BMI ≥30 kg/m 2): component of metabolic syndrome
  • Age greater than 55 years for men or greater than 65 years for women: increased risk begins at the respective ages; the Adult Treatment Panel III used earlier age cut points to suggest the need for earlier action
  • Estimated glomerular filtration rate less than 60 mL/min
  • Microalbuminuria
  • Family history of premature cardiovascular disease (men < 55 years; women < 65 years)
  • Lack of exercise

The Eighth Report of the JNC (JNC 8), released in December 2013 no longer recommends just thiazide-type diuretics as initial therapy in most patients. In essence, the JNC 8 recommends treating to 150/90 mm Hg in patients over age 60 years; for everybody else, the goal BP is 140/90 (18).

Biomarkers Associated with Hypertension

The biomarkers associated with hypertension are for the most part derived from features that characterize the disordered physiology. We might first consider the measurement of blood pressure. Then it becomes necessary to analyze the physiological elements that largely contribute to blood pressure. Finally, there are several biomarkers that have loomed large as measures are myocardial function or myocardial cell death, and are also not independent of renal function, that are indicators of short term and long term cardiovascular status. Having already indicated the importance of measurement of pulse, diastolic and systolic blood pressure in the routine examination of physical status, which is related to cardiac output we shall pay attention to the pulse pressure and pulse wave velocity.    These were defined in the preceding discussion.  They are critically related to the development of hypertension and in the long term, they emerge significantly earlier than either congestive heart failure, chronic kidney disease, acute coronary syndrome, stroke, or cardio-renal syndrome.

Even though cardiovascular disease (CVD), the leading cause of death in developed countries, is not predicted by classic risk factors, there are elements of the risk factor association that need further exploration and will be dissected, such as activity level, obesity, lipids, diabetes mellitus, family history and stress.  Further analysis will point to endocrine and/or metabolic factors that drive cardiovascular risk.

In taking into account the blood pressure measurements, we consider the pulse pressure (PP) and the pulse wave velocity (PWV).  If we refer back to the stroke volume and the Law of the Heart, the systolic blood pressure (SBP) is increased with increased left ventricular output that raises the left ventricular (LV) afterload. This coincides with a decrease in diastolic pressure (DBP) that accompanies a change in coronary artery perfusion (CAP).  Thus, many studies point to increased SBP as a strong risk factor for stroke and CVD.  However, there are sufficient studies that indicate the brachial artery pulse pressure (PP) is a strong determinant of CVD and stroke, and these two elements, SBP and brachial artery PP, may be an indicator of increased arterial stiffness in hypertensive patients and the general population. Brachial PP is also a determinant of recurrent events after acute coronary syndrome (ACS) or with left ventricular hypertrophy (LVH), or the risk of CHF in the aging population, and of all-cause-mortality in the general population.  In addition, the aortic PWV calculated from the Framingham equations was a suitable predictor of CVD risk. In a classic study of arterial stiffness and of CVD and all-cause mortality in an essential hypertension cohort at the Broussais Hospital between 1980 and 1996 (19), the carotid-femoral PWV was measured as an indicator of aortic stiffness, and it was found to be significantly associated with all-cause and CVD mortality independent of previous CVD, age, and diabetes. They tested the hypothesis that aortic stiffness is a predictor of cardiovascular and all-cause mortality in hypertensive patients based on the consideration that the elastic properties of the aorta and central arteries are the major determinants of systemic arterial impedance, and the PWV measured along the aortic and aorto-iliac pathway is the most clinically relevant. They assessed arterial stiffness by measuring the PWV using  the Moens-Korteweg equation based on the increase of the square root of the elasticity modulus in stiffer arteries (20).

PWV as a Diagnostic Test

To assess the performance of PWV considered as a diagnostic test, with the use of receiver operating characteristic (ROC) curves, they calculated sensitivities, specificities, positive predictive values, and negative predictive values of PWV at different cutoff values, first to detect the presence of AA in the overall population and second to detect patients with high 10-year cardiovascular mortality risk in the subgroup of 462 patients without AA with age range from 30 to 74 years. Optimal cutoff values of PWV were defined as the maximization of the sum of sensitivity and specificity.

The main finding of the study was that PWV was a strong predictor of cardiovascular risks as determined by the Framingham equations in a population of treated or untreated subjects with essential hypertension (21). They measured the PWV from foot-to-foot transit time in the aorta for a noninvasive evaluation of regional aortic stiffness, which allows an estimate of the distance traveled by the pulse. The presence of a PWV > 13 m/s, taken alone, appeared as a strong predictor of cardiovascular mortality with high performance values (21). Their work and other studies (22, 23) established increased pulse pressure, the major hemodynamic consequence of increased aortic PWV, as a strong independent predictor of cardiac mortality, mainly MI, in populations of normotensive and hypertensive subjects.

In addition to the findings above, the PWV was found to be an independent predictor of future increase in SBP and of incident hypertension in the Baltimore study (21). The authors reported that in a subset of 306 subjects who were normotensive at baseline, hypertension developed in 105 (34%) during a median follow-up of 4.3 years (range 2 to 12 years). PWV was also an independent predictor of incident hypertension (hazard ratio 1.10 per 1 m/s increase in PWV, 95% confidence interval 1.00 to 1.30, p = 0.03) in individuals with a follow-up duration greater than the median. The authors (21) concluded that carotid-femoral PWV measured using nondirectional transcutaneous Doppler probes (model 810A, 9 to 10-Mhz probes, Parks Medical Electronics, Inc., Aloha, Oregon) could be done to identify normotensive individuals who should be targeted for the implementation of interventions aimed at preventing or delaying the progression of subclinical arterial stiffening and the onset of hypertension.  They reported that age, BMI, and MAP were independently associated with higher SBP on the last visit (Table IV); in addition, PWV was also independently associated with higher SBP on the last visit, and explained 4% of its variance. As shown in Table V, age, BMI, and MAP (p = 0.09, p = 0.009, p < 0.0001 respectively for the interaction terms with time) were predictors of the longitudinal changes in SBP. In addition, PWV was also an independent predictor of the longitudinal increase in SBP (p = 0.003 for the interaction term with time).

In addition, they report that in the group with follow-up duration greater than the median (in which all subjects remained normotensive for the first 4.3 years), beyond age (hazard ratio [HR] 1.02 per 1 year, 95% confidence interval [CI] 0.99 to 1.04, p = 0.2) and SBP (HR 1.05 per 1 mm Hg, 95% CI 1.01 to 1.09, p = 0.006), both HDL (HR 0.96 per 1 mg/dl, 95% CI 0.93 to 0.99, p = 0.02) and PWV (HR 1.10 per 1 m/s, 95% CI 1.00 to 1.30, p = 0.03) (Fig. 1) were independent predictors of incident HTN.

Their findings in a longitudinal projection indicate that PWV, a marker of central arterial stiffening, is an independent determinant of longitudinal SBP increase in healthy BLSA volunteers, and an independent risk factor for incident hypertension among normotensive subjects followed up for longer than 4 years. The study was accompanied by a commentary in the same journal that states: “Pulse wave velocity (PWV) is a simple measure of the time taken by the pressure wave to travel over a specific distance. By virtue of its intrinsic relation to the mechanical properties of the artery by the Moens–Kortweg formula (PWV=√(Eh/2)Rρ; where E is the Young’s Modulus of the arterial wall, h the wall thickness, R the end- diastolic radius and ρ is the density of blood)(20), and buoyed a number of longitudinal studies that reported on the independent predictive value of PWV measurement for cardiovascular events and mortality in various populations, PWV is now widely accepted as the ‘gold standard’ measure of arterial stiffness.

 

 

 

Table IV Multiple Regression Analysis Evaluating the Predictors of Last Visit SBP 21

Variable Parameter
Estimate
Standard
Error
p Value
Age (yrs) 0.32 0.06 <0.0001
Gender (men) 0.65 1.78 0.71
Race (white) −1.22 2.00 0.54
Smoking (ever) 2.48 1.61 0.12
BMI (kg/m2)* 0.61 0.22 0.006
MAP (mm Hg)* 0.60 0.08 <0.0001
PWV (m/s)* 1.56 0.38 <0.0001
Heart rate (beats/min) 0.08 0.06 0.20
Total cholesterol (mg/dl) −0.005 0.02 0.83
Triglycerides (mg/dl) −0.009 0.01 0.50
HDL cholesterol (mg/dl) −0.001 0.07 0.98
Glucose (mg/dl) −0.02 0.06 0.75

 

 

 

 

 

 

 

 

Table V Predictors of Longitudinal SBP Derived From a Linear Mixed-Effects Regression Model 21

Variable Coefficient Standardized

Coefficient

95% Confidence

Interval

p Value
Time (yrs) 3.14 0.14 0.61 to 5.66 0.02
Age (yrs) −0.37 0.25 −0.68 to −0.06 0.02
Age2 (yrs2)* 0.006 0.08 0.002 to 0.008 <0.0001
Gender (men) 0.61 0.03 −1.26 to 2.47 0.52
BMI (kg/m2)* 0.25 0.11 −0.01 to 0.50 0.06
MAP (mmHg)* 1.03 0.47 0.93 to 1.12 <0.0001
PWV (m/s) 0.29 0.12 −0.16 to 0.74 0.21
Time × age* 0.02 0.04 −0.002 to 0.038 0.09
Time × BMI* 0.10 0.06 0.02 to 0.183 0.009
Time × MAP* −0.08 −0.12 −0.11 to −0.05 <0.0001
Time × PWV* 0.22 0.08 0.07 to 0.36 0.003

 

 

Figure 1 21

http://content.onlinejacc.org/data/Journals/JAC/23115/10065_gr1.jpeg

Figure 2.21

http://content.onlinejacc.org/data/Journals/JAC/23115/10065_gr2.jpeg

The interest in this physiological measure is illustrated by the increasing number and diversity of research publications in this arena related to human hypertension, relating PWV to pathophysiological processes (for example, homocysteine, inflammation and extracellular matrix turnover and disorders related to hypertension, such as sleep apnea). The epidemiology, genetic associations and prognostic implications of PWV (and arterial stiffness) have also been reported as has the relationship to hemodynamics, cardiac structure and function.” (24) Furthermore, arterial stiffening may be “characterized by an increase in (central) PP and changes in the morphology of the arterial waveform, both of which can now be measured non-invasively using tonometers from commercially available devices. Wave reflection is typically characterized by aortic pressure augmentation (ΔP) and the augmentation index (ΔP/PP) (Figure 3)(24). Higher augmented pressure, as an index of wave reflection, has been linked to adverse clinical outcomes in different populations.

Figure 3.24

Analysis of the pressure waveform. The initial systolic pressure is labelled as P1 and augmented pressure ( P) is typically measured as the difference between peak pressure (P2) and P1. Augmentation index is  P/PP. PP, pulse pressure.    http://www.nature.com/jhh/journal/v22/n10/images/jhh200847f1.gif 24

A review by Payne et al. (25) states that aortic stiffness and arterial pulse wave reflections determine elevated central systolic pressure and are associated with risk of adverse cardiovascular outcomes. This is because an impaired compensatory mechanism through matrix metalloproteinases of remodeling to compensate for changes in wall stress, possibly related to angiotensin II and inhibition of the vascular adhesion protein semicarbazide-sensitive amine oxidase, related to reduced elastin fiber cross-linking. This has implications for pharmacological agents that target age-related advanced glycation end-product cross-links. This also brings into consideration NO playing a considerable role. But they caution that the endogenous NO synthase inhibitors asymmetric dimethylarginine and L-NG-monomethyl arginine associated with clinical atherosclerosis don’t appear to be associated with arterial stiffening. The matter leaves much to be explained.  The mechanisms underlying arterial stiffness could well require insights into inflammation, calcification, vascular growth and remodeling, and endothelial dysfunction. Nevertheless, arterial stiffness is independently associated with cardiovascular outcome in most of the situations where it has been examined.  Given this train of thinking, O’Rourke (26) considers a progressive arterial dilatation with repeated cycles of stress that leads to degeneration of the arterial wall and increases the pressure wave impulse and wave velocity, augmenting the pressure in late systole. Drugs may reduce wave reflection, but have no direct effect on arterial stiffness.  However, reduction in wave reflection decreases aortic systolic pressure augmentation.  DK Arnett (26) depicts the effect of persistently elevated blood pressure in the following diagram (Figure 4).

 

Figure 4.26  Both transient and sustained stiffening of the artery are likely to be present in hypertension.

An initial elevation in blood pressure may establish a positive feedback in which hypertension biomechanically increases arterial stiffness without any structural change. This elevated blood pressure   might later lead to additional vascular hypertrophy and hyperplasia, collagen deposition, and atherosclerosis, and fixed elevations in arterial stiffness.  As to a genetic factor, she refers to a gene contributing to pulse pressure on chromosome 8 located at 32 cM, which also contains the lipoprotein lipase (LPL) gene which has been associated with hypertension. LPL may be an important candidate gene for pulse pressure.  She specifically identifies a relationship between genetic regions contributing to aortic compliance in African American sibships ascertained for hypertension in Figure 5 (27).  These results suggest there may be influential genetic regions contributing to aortic compliance in African American sibships ascertained for hypertension (27). Collectively, these two studies, the first to our knowledge, indicate the presence of genetic factors influencing hypertension.

Other authors state that PWV has a direct relationship to intrinsic elasticity of the arterial wall, and it is an independent predictor of CVD related morbidity and mortality, but it is not associated with classical risk factors for atherosclerosis (28).  They point out that PWV doesn’t increase during early stages of atherosclerosis, as measured by intima-media thickness and non-calcified atheroma, but it does increase in the presence of aortic calcification that occurs with advanced atherosclerotic plaque. Age-related
PWV measurement. Carotid-to-femoral PWV is calculated by dividing the distance (d) between the two arterial sites by the difference in time of pressure wave arrival between the carotid (t1) and femoral artery (t2) referenced to the R wave of the electrocardiogram.

Figure 5. Linkage of arterial compliance on chromosome 2: HyperGEN27

Widening of the pulse pressure is the major cause of age-related increase in prevalence of hypertension and is related to arterial stiffening. (28)  Commonly used points for measuring the PWV are the carotid and femoral artery because they are superficial and easy to access. Arterial distensibility is measured by the Bramwell and Hill equation (29): PWV = √(V × ΔP/ρ × ΔV), where ρ is blood density. This is shown in Figure 6.

 

Figure 6 28

 

View larger version:

 

Furthermore, these authors (28) report arterial stiffness increases with age by approximately 0.1 m/s/y in East Asian populations with low prevalences of atherosclerosis, but some authors have found accelerated stiffening between 50 and 60 years of age. In contrast, stiffness of peripheral arteries increases less or not at all with increasing age. Again, ageing of the arterial media is associated with increased expression of matrix metalloproteinases (MMP), which are members of the zinc-dependent endopeptidase family and are involved in degradation of vascular elastin and collagen fibers. Several different types of MMP exist in the vascular wall, but in relation to arterial stiffness, much interest has focused on MMP-2 and MMP-9.  This concludes the discussion of PP and PWV in the evolution of hypertension.

 

Diagnostic Biomarkers of essential hypertension.

Ioannidis and Tzoulaki (30) reviewed the literature on 10 popular ‘‘new’’ biomarkers and found that each one had accrued more than 6000 publications.1 The predictive effects of these popular blood biomarkers for coronary heart disease in the general population are listed in Table VI (31).

 

Table VI.* Predictive Value of New Biomarkers 30,31

Biomarker Adjusted Relative Risk (95% C.I.)
Triglycerides 0.99 (0.94–1.05)
C-reactive protein 1.39 (1.32–1.47)
Fibrinogen 1.45 (1.34–1.57)
Interleukin 6 1.27 (1.19–1.35)
BNP or NT-proBNP 1.42 (1.24–1.63)
Serum albumin 1.2 (1.1–1.3)
ICAM-1 (0.75–1.64)
Homocysteine 1.05 (1.03–1.07)
Uric acid 1.09 (1.03–1.16)

*Ionnidis and Tzoulaki from Giles
The majority of these biomarkers show small effects, if any, even in combination.  Giles (31) points out that an elevated homocysteine level might be of great importance to a young person with a myocardial infarction and a positive family history of similar occurrences. Emerging biomarkers, eg, asymmetric and symmetric dimethylarginine and galectin-3, are promising more specific biomarkers based on pathophysiologies for cardiovascular disease. Even then, blood pressure remains the biomarker par excellence for hypertension and for many other cardiovascular entities.

The importance of blood pressure was highlighted by the report of the cardiovascular lifetime risk pooling project.(10) Starting at 55 years of age, 61,585 men and women were followed over an average of 14 years, ie, 700,000 person-years. Individuals who maintained or decreased their blood pressure to normal levels had the lowest remaining lifetime risk for cardiovascular disease (22–41%) compared with individuals who had or developed hypertension by 55 years of age (42–69%). The study indicated that efforts should continue to emphasize the importance of lowering blood pressure and avoiding or delaying the incidence of hypertension to reduce the lifetime risk for cardiovascular disease

A small study involving 120 hypertensive patients with or without heart failure tried to establish a multi-biomarker approach to heart failure (HF) in hypertensive patients using N-terminal pro BNP (32). The following biomarkers were included in the study: Collagen III N-terminal propeptide (PIIINP), cystatin C (CysC), lipocalin-2/NGAL, syndecan-4, tumor necrosis factor-α (TNF-α), interleukin 1 receptor type I (IL1R1), galectin-3, cardiotrophin-1 (CT-1), transforming growth factor β (TGF-β) and N-terminal pro-brain natriuretic peptide (NT-proBNP). The highest discriminative value for HF was observed for NT-proBNP (area under the receiver operating characteristic curve (AUC) = 0.873) and TGF-β (AUC = 0.878). On the basis of ROC curve analysis they found that CT-1 > 152 pg/mL, TGF-β < 7.7 ng/mL, syndecan > 2.3 ng/mL, NT-proBNP > 332.5 pg/mL, CysC > 1 mg/L and NGAL > 39.9 ng/mL were significant predictors of overt HF. There was only a small improvement in predictive ability of the multi-biomarker panel including the four biomarkers with the best performance in the detection of HF (NT-proBNP, TGF-β, CT-1, CysC) compared to the panel with NT-proBNP, TGF-β and CT-1 (absent  CysC). The biomarkers with different pathophysiological backgrounds (NT-proBNP, TGF-β, CT-1) give additive prognostic value for incident compared to NT-proBNP alone.

Inflammation has been associated with pathophysiology of hypertension and vascular damage. Resistant hypertensive patients (RHTN) have unfavorable prognosis due to poor blood pressure control and higher prevalence of target organ damage. Endothelial dysfunction and arterial stiffness are involved in such condition. Previous studies showed that RHTN patients have higher arterial stiffness and endothelial dysfunction than controlled hypertensive and normotensive subjects. The relationship between high blood pressure levels and arterial stiffness may be explained in part, by inflammatory pathways. Previous studies also found that hypertensive subjects have higher levels of inflammatory cytokines including TNF-α, IL-10, IL-1β and CRP. Moreover, IL-1β correlates with arterial stiffness and levels of blood pressure, which are particularly high in patients with resistant hypertension. Increased inflammatory cytokines levels might be related to the development of vascular damage and to the higher cardiovascular risk of resistant hypertensive patients. Elevated BP may cause cardiovascular structural and functional alterations leading to organ damage such as left ventricular hypertrophy, arterial and renal dysfunction. TNF-α inhibition reduced systolic BP and endothelial inflammation in SHR [33]. They also found that IL-1β correlates with arterial stiffness and levels of blood pressure, even after adjust for age and glucose [33]. These investigators then demonstrated that isoprostane levels, an oxidative stress marker, were associated with endothelial dysfunction in these patients [33].

Chao et al. carried out studies of kallistatin (34-36). Kallistatin is an endogenous protein in human plasma as a tissue Kallikrein-Binding Protein (KBP). Tissue kallikrein is a serine protease that releases vasodilating kinin peptides from kininogen substrate. The tissue kallikrein-kinin system is involved in mediating beneficial effects in hypertension as well as cardiac, cerebral and renal injury. KBP was later identified as a serine protease inhibitor (serpin) because of its ability to inhibit tissue kallikrein activity, and was subsequently named “kallistatin”. Kallistatin is mainly expressed in the liver, but is also present in the heart, kidney and blood vessel. Kallistatin protein contains two structural elements: an active site and a heparin-binding domain. The active site of kallistatin is crucial for complex formation with tissue kallikrein, and thus tissue kallikrein inhibition.

Kallistatin is expressed in tissues relevant to cardiovascular function, and has consequently been shown to have vasodilating properties.  Kallistatin has pleiotropic effects in vasodilation and inhibition of inflammation, angiogenesis, oxidative stress, fibrosis, and cancer progression. Injection of a neutralizing Kallistatin antibody into hypertensive rats aggravates cardiovascular and renal injury in association with increased inflammation, oxidative stress and tissue remodeling.  Neither the blood pressure-lowering effect nor the vasorelaxation ability of kallistatin is abolished by icatibant (Hoe140, a kinin B2 receptor antagonist), indicating that kallistatin-mediated vasodilation is unrelated to the tissue kallikrein-kinin system.

The findings reported indicate that kallistatin exerts beneficial effects against hypertension and organ damage. Kallistatin levels in circulation, body fluids or tissues were lower in patients with liver disease, septic syndrome, diabetic retinopathy, severe pneumonia, inflammatory bowel disease, and cancer of the colon and prostate. In addition, reduced plasma kallistatin levels are associated with adiposity and metabolic risk in apparently healthy African American youths. Considered a negative acute-phase protein, circulating kallistatin levels as well as hepatic expression are rapidly reduced within 24 hours after Lipopolysaccharide (LPS) induced endotoxemia in mice. Similarly, circulating kallistatin levels are markedly decreased in patients with septic syndrome and liver disease. Taking together, the studies indicate that kallistatin exhibits potent anti-inflammatory activity.

The pathogenesis of hypertension and cardiovascular and renal diseases is tightly linked to increased oxidative stress and reduced NO bioavailability (37-39). Time-dependent elevation of circulating oxygen species are associated with reduced kallistatin levels in animal models of hypertension and cardiovascular and renal injury. Stimulation of NO formation by kallistatin may lead to inhibition of oxidative stress and thus multi-organ damage. On the other hand, endogenous kallistatin depletion by neutralizing antibody increased oxidative stress and aggravated cardiovascular and renal damage.

A human kallistatin gene polymorphism has been shown to correlate with a decreased risk of developing acute kidney injury during septic shock. Kallistatin levels are markedly reduced in both humans and mice with sepsis syndrome. However, kallistatin administration protects against lethality and organ injury in animal models of toxic septic shock. Moreover, kallistatin levels are decreased in patients with liver disease, septic shock, inflammatory bowel disease, severe pneumonia and acute respiratory distress syndrome. Taken together, the results indicate that kallistatin has the potential to be a molecular biomarker for patients with sepsis, cardiovascular and metabolic disorders.

Pulmonary hypertension (PH) is defined as a mean pulmonary artery pressure of .25 mmHg at rest or .30 mmHg with exercise. Right heart catheterization is required for the definitive diagnosis. Subsequent investigations are instituted to further characterize the disease. The 6-min walk test (6MWT), a measure of exercise capacity, and the New York Heart Association (NYHA)/World Health Organization (WHO) functional classification, a measure of severity, are used to follow the clinical course while receiving treatment, and these both correlate with disease severity and prognosis (43).

Pulmonary arterial hypertension (PAH) is a progressive disease of the pulmonary vasculature that leads to exercise limitation, right heart failure, and death. There is a need for biomarkers that can aid in early detection, disease surveillance, and treatment monitoring in PAH. Several potential molecules have been investigated; however, only brain natriuretic peptide is currently recommended at diagnosis and for follow-up of PAH patients.

ANP is released from storage granules in atrial tissue, while BNP is secreted from ventricular tissue in a constitutive fashion. ANP secretion is stimulated by atrial stretch caused by atrial volume overload; BNP is released in response to ventricular stretch. Natriuretic peptides act on the kidney, causing natriuresis and diuresis, and relax vascular smooth muscle, causing arterial and venous dilatation, leading to reduced blood pressure and ventricular preload. ANP and BNP are released as prohormones and then cleaved into the active peptide and an inactive N-terminal fragment (43).

Natriuretic peptide precursors are released in response to atrial and ventricular stretch, cleaved into active molecules and inactive precursors and convert guanosine 59-triphosphate (GTP) to cyclic guanosine monophosphate (cGMP), leading to their various physiological actions.

There are a number of confounding factors in the interpretation of natriuretic peptide levels, including left heart disease, sex, age and renal dysfunction. Since most studies exclude patients with left heart disease and renal dysfunction, it becomes problematic extrapolating these results to an unselected population (43).

Endothelin-1 (ET-1) is a peptide found in abundance in the human lung and, through action of endothelin receptors (ETA and ETB) on vascular smooth muscle cells, is implicated in the pathogenesis of PAH. Endothelin receptor antagonists are approved for the treatment of PAH. Levels of circulating ET-1 and related molecules are logical biomarkers of interest in PAH. ET-1 is elevated in PAH compared to controls, and correlates with pulmonary hemodynamic parameters. In addition, higher ET-1 levels are associated with increased mortality in patients treated for PAH. ET-1’s precursor, big-ET-1, has a longer half-life and hence is more stable than ET-1.

Endothelin-1 ET-1 is a potent endogenous vasoconstrictor and proliferative cytokine. The ET-1 gene is translated to prepro-ET-1 which is then cleaved, by the action of an intracellular endopeptidase, to form the biologically inactive big ET-1. ET-converting enzymes further cleave this to form functional ET-1 . There are two ET receptor isoforms, termed type A (ETA), located predominantly on vascular smooth muscle cells, and type B (ETB), predominantly expressed on vascular endothelial cells but also on arterial smooth muscle. Activation of both receptor subtypes, when located on vascular smooth muscle, results in vasoconstriction and cell proliferation. In addition, the endothelial ETB receptor mediates vasodilatation and clearance of ET-1 (43).

Prepro-ET-1 is cleaved to inactive big ET-1 and then further cleaved to form active ET-1. This acts on vascular smooth muscle via the ETA and ETB receptors, causing vasoconstriction and cell proliferation, and on endothelial cells via ETB receptors, releasing nitric oxide (NO) and prostacyclin (PGI2), causing vasorelaxation.

As a biomarker, ADMA has been evaluated in several different classes of PH (43, 44). In IPAH, plasma levels are significantly higher than in healthy, matched controls. In such patients, plasma ADMA correlates positively with right atrial pressure, and negatively with mixed venous oxygen saturation, stroke volume, cardiac index and survival. On stepwise multiple regression analysis, ADMA is an independent predictor of mortality and, using Kaplan–Meier survival curves, patients with supramedian ADMA levels have significantly worse survival than those with inframedian levels.

Patients with idiopathic PAH, plasma levels of Ang-1 and Ang-2 were higher in PAH patients as compared to healthy controls.  Moreover, higher plasma levels of Ang-2 were associated with lower CI and mixed venous oxygen saturation (SvO2) and higher PVR, and, with therapy initiation, changes in Ang-2 correlated with changes in hemodynamics (45, 46).

Endostatin is an antiangiogenic peptide. It is synthesized by myocardium, is detectable in the peripheral circulation of patients with decompensated heart failure, and predicts mortality.48 In PAH, reduced RV myocardial oxygen delivery is felt to contribute to a transition from RV adaptation to failure (46).

Cyclic guanosine monophosphate (cGMP) is an intracellular second messenger of nitric oxide and an indirect marker of natriuretic peptide production (46).

Human pentraxin 3 (PTX3) is a protein synthesized by vascular cells that regulates angiogenesis, inflammation, and cell proliferation (46).

N-terminal propeptide of procollagen III (PIIINP), carboxy-terminal telopeptide of collagen I (CITP), matrix metalloproteinase-9 (MMP-9), and tissue inhibitor of metalloproteinase I (TIMP-1)(46).

Osteopontin (OPN) is a matricellular protein that mediates cell migration, adhesion, remodeling, and survival of the vascular and inflammatory cells (46).

F2-isoprostane is a marker of lipid peroxidation of arachidonic acid, which stimulates endothelial cell proliferation and ET-1 synthesis and may play a role in the pathogenesis of PAH (46).

Circulating fibrocytes are bone marrow-derived cells (CD45 /collagen I ) that contribute to organ fibrosis and extracellular matrix deposition (46).

Circulating miRs (46)

Despite many other substances being investigated as potential biomarkers in PAH, more research is needed to validate the results of small studies and assess their clinical utility. Widespread clinical use of current investigational biomarkers will require validated clinical laboratory techniques and increased knowledge of levels in the healthy population as well as other disease states.

Here are important tests in clinical practice (47):

 

6-min walk distance

Cardiac index

WHO FC

PIIINP

Higher tertiles associated with worse disease

worse renal function

higher right atrial pressure (RAP)

CITP – vascular remodeling

 

Recent guidelines (17, 18) encourage the use of screening examinations, such as an echocardiogram (UCG), in high-risk populations for the early detection of PAH . To detect PAH in patients with connective tissue disease (CTD), the obvious screening tests are an UCG and spirometry, including assessment of the diffusing capacity of the lung for carbon monoxide (DLCO). Previous studies have suggested that B-type natriuretic peptide (BNP) and its N-terminal prohormone (NT-proBNP) are potential biomarkers for PAH. However, neither BNP nor NT-pro BNP are specific biomarkers of the degeneration of the pulmonary artery; rather, they are biomarkers of cardiac burden resulting from right heart failure.

Human pentraxin 3 (PTX3) is a specific biomarker for PAH, reflecting pulmonary vascular proteins. They are divided into short and long pentraxins on the basis of their primary structure.
C-Reactive protein (CRP) and serum amyloid P are the classic short pentraxins that are produced in the liver in response to systemic inflammatory cytokines (48). In contrast, PTX3 is one of the long pentraxins. It is synthesized by local vascular cells, such as smooth muscle cells, endothelial cells and fibroblasts, as well as innate immunity cells at sites of inflammation. PTX3 plays a key role in the regulation of cell proliferation and angiogenesis (49).

Increased plasma PTX3 levels have been reported in patients with acute myocardial injury in the
24 h after admission to hospital, with levels returning to normal after 3 days. Similarly, PTX3 levels are higher in patients with unstable angina pectoris, with the changes in PTX3 levels found to be independent of other coronary risk factors, such as obesity and diabetes mellitus. Finally, high serum PTX3 levels have been reported in patents with vasculitis, such as small-vessel vasculitis  and Takayasu aortitis.

Mean plasma PTX3 concentrations in the CTD-PAH and CTD patients were 5.02+0.69 ng/mL (range 1.82–12.94 ng/mL) and 2.40+0.14 ng/mL (range 0.70–4.29 ng/mL), respectively (Table 2). Log transformation of the data revealed significantly higher PTX3 levels in CTD-PAH than in CTD patients (1.49+0.12 vs. 0.82+0.06 log ng/mL, respectively; P = 0.001).(not shown)(50)

Figure 1. Serum pentraxin 3 (PTX3) concentrations in 50 patients with pulmonary arterial hypertension (PAH) and 100 healthy controls, and their correlation with serum concentrations of other biomarkers. A: Comparison of PTX3 concentrations in PAH patients and healthy controls. Mean plasma PTX3 concentrations were 4.4060.37 and 1.94+0.09 ng/mL in the controls and PAH patients, respectively. B: Distribution of log-transformed PTX3 concentrations in PAH patients and healthy controls. C: Log-transformed PTX3 concentrations were significantly higher in patients with PAH than in healthy controls (1.34+0.07 vs. 0.55+0.05 log ng/mL, respectively; P,0.001). D, E: There was no correlation between plasma concentrations of PTX3 and either B-type natriuretic peptide (BNP; r=0.33, P=0.02) or C-reactive protein (CRP; r=0.21, P=0.14) in PAH patients. (not shown) (50)

 

Table 2. Clinical characteristics and biomarkers in patients with connective tissue disease, with or without pulmonary arterial hypertension.

CTD-PAH ( n =17)                CTD alone ( n =34)       P -value

Age (years)                                 56.3+4.6                                 56.3+2.7               0.990

No. women (%)                         15 (88)                                      31(91)                  0.745

No. with SSc (%)                       10 (59)                                      20 (59)                    1

No. with heart failure (%)          1 (6)                                         0                            –

No. being treated for PAH (%)   17 (100)                                  0                           –

Serum PTX3 (mg/dL)                   5.02+0.69                          2.40+0.14             0.001

Serum CRP (mg/dL)                   0.24+0.09                            0.22+0.04             0.936

Serum BNP (pg/mL)                 189.3+74.                            4 49.3+12.1            0.014

…..  CTD, connective tissue disease; PAH, pulmonary arterial hypertension; SSc, scleroderma;

Figure 3. Receiver operating characteristic (ROC) curves for pentraxin 3 (PTX3) and other biomarkers in patients with connective tissue disease (CTD). The areas under the ROC curve (AUCROC) for PTX3 was 0.866 (95% confidence interval (CI) 0.757–0.974). The star indicates the threshold concentration of 2.85 ng/mL PTX3 that maximized true-positive and false-negative results (sensitivity 94.1%, specificity 73.5%). The AUCROC for C-reactive protein (CRP) was 0.518 (95% CI 0.333–0.704), whereas that for B-type natriuretic peptide (BNP) was 0.670 (95% CI 0.497–0.842). (50)  http://dx.doi.org:/10.1371/journal.pone.0045834.g003

This study was to determine whether PTX3, the regulation of which is independent of that of the systemic inflammatory marker CRP, is a useful biomarker for diagnosing PAH. The investigators found that PTX3 may be a more sensitive biomarker for PAH than BNP, which is, to date, the most established biomarker for PAH, especially in patients with CTD-PAH. Their findings suggest that PTX3 does not reflect the cardiac burden due to the pulmonary hypertension, but rather the activity of pulmonary vascular degeneration because PTX3 levels were significantly decreased after active treatment specifically for PAH (50). PLoS ONE 7(9): e45834. http://dx.doi.org:/10.1371/journal.pone.0045834.

Pharmacologic treatment for pulmonary arterial hypertension (PAH) remains suboptimal and mortality rates are still high, even with pulmonary vasodilator therapy. In addition, we have only an incomplete understanding of the pathobiology of PAH, which is characterized at the tissue level by fibrosis, hypertrophy and plexiform remodeling of the distal pulmonary arterioles. Novel therapeutic approaches that might target pulmonary vascular remodeling, rather than pulmonary vaso-reactivity, require precise patient phenotyping both in terms of clinical status and disease subtype. However, current risk stratification models are cumbersome and not precise enough for choosing or assessing the results of therapeutic intervention. Biomarkers used in patients with left heart failure, such as troponin-T and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are elevated in PAH patients but tend to simply reflect increased circulating plasma volumes and elevated right heart pressure, rather than conveying information about disease mechanism.

In this issue of Heart, Calvier and colleagues (see page 390) (51)propose galectin-3 as a useful biomarker in PAH. The rationale for this hypothesis is that elevated aldosterone levels induce an increase in serum levels of galectin-3, a β-galactoside-binding lectin expressed by circulating myocytes, endothelial cells and other cardiovascular cell types. Among other effects, activation of the aldosterone/galactin-3 pathway promotes fibrosis (51), suggesting that elevated levels will correlate with the severity of PAH due to increased pulmonary arteriolar remodeling. To test this hypothesis, serum levels were measured in a total of 57 patients – 41 with idiopathic PAH (iPAH) and 16 with PAH associated with a connective tissue disorder (CTD). The magnitude of elevation in serum levels of aldosterone, galectin-3 and NT-proBNP each correlated with the severity of PAH. However, as shown in figure 1, although serum levels of galectin-3 were elevated in both iPAH and PAH-CTD patients, aldosterone was elevated only in those with iPAH.

In addition, elevated vascular cell adhesion molecule 1 (VCAM-1) and proinflammatory, anti-angiogenic interleukin 12 (IL-12) in were elevated only in PAH-CTD patients, not in those in iPAH. These data suggest that aldosterone and galectin-3 can be used as biomarkers “in tandem” that reflect both the severity and cause of PAH (52).

In the accompanying editorial, Maron (see page 335) summarizes the knowledge gaps in PAH and concludes: “Taken together, Calvier and colleagues provide a key contribution to an underdeveloped area of pulmonary vascular medicine and in doing so identify galectin-3/aldosterone as promising biomarker(s) for informing both disease pathobiology and clinical status in PAH. The rationale of this pursuit in PAH was based, in part, on lessons earned from left heart failure in which the importance of systemically circulating vasoactive factors to clinical trajectory is well established. In this regard, the current work not only develops a novel scientific avenue worthy of further investigation, but also adds to the evolving body of evidence implicating a role for neurohumoral activation in the pathophysiology of PAH”.

Rheumatoid arthritis (RA) affects about 1% of the population and is known to be a significant risk factor for cardiovascular disease, with a 3-fold increased risk of myocardial infarction, a 2-fold increased risk of sudden death and a 50% increase in cardiovascular mortality rates. However, outcomes after PCI in RA patients have not been well characterized and there is little data on the possible effects of disease modifying therapy for RA on risk of restenosis after percutaneous coronary intervention (PCI). In a single center retrospective cohort study, Sintek and colleagues (53)(see page 363) compared the primary endpoint of repeat target vessel revascularization (TVR) in 143 RA patients matched to 541 other.

Pathophysiological targets of differing imaging modalities, demonstrate targets for tracers/contrast agents/pharmacotherapy used in SPECT, PET, MRI and echocardiography to assess myocardial viability.  (Not shown. Adapted from Schuster et al., J Am Coll Cardiol 2012; 59:359–70.)

Ischemic cardiomyopathy implies significant left ventricular systolic dysfunction with an underlying pathophysiology that includes myocardial scarring, hibernation and stunning, or a combination of these disease states. The role of imaging in assessment of myocardial viability is emphasized (not shown) (54) with brief summaries of the role of echocardiography, single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). The effects of revascularization in patients with ischemic cardiomyopathy remain controversial. Instead, the key elements of evidence based therapy for ischemic cardiomyopathy are standard medical therapy for heart failure combined with implantable cardiac defibrillation (ICD) and/or biventricular pacing device therapy in appropriate patients.

The relationship between the heart and the kidney in hypertension and heart failure

Hypertension is undoubtedly a factor in the treatment of chronic kidney disease because of the relationship between kidney function and BP components that have been studied in people with CKD, diabetes, and hypertension.  Cystatin C was used to evaluate the association between kidney function and both SBP and DBP and 24-h creatinine clearance (CrCl) among 906 participants in the Heart and Soul Study.  (56).  The study investigators hypothesized that although both creatinine and cystatin C are freely filtered at the glomerulus, a major difference between them is that creatinine is secreted by renal tubules, whereas cystatin C is metabolized by the proximal tubule and only a small fraction appears in the urine. In addition, Cystatin C has also been shown to be a stronger predictor of adverse outcomes than serum creatinine. Based on the more linear relationship of cystatin C with GFR, they hypothesized that cystatin C would have a stronger association with SBP than conventional measures of kidney function. Their results found that SBP was linearly associated with cystatin C concentrations (1.19 ± 0.55 mm Hg increase per 0.4 mg/L cystatin C, P = .03) across the range of kidney functions, but only in subjects with CrCl <60 mL/min (6.4 ± 2.13 mm Hg increase per 28 mL/min, P = .003), not >60 mL/min. Further, the DBP was not associated with cystatin C or CrCl. However, PP was linearly associated with both cystatin C (1.28 ± 0.55 mm Hg per 0.4 mg/L cystatin, P = .02) and CrCl <60 mL/min (7.27 ± 2.16 mm Hg per 28 mL/min, P = .001). The relationship between SBP and cystatin C by decile is shown in Figure 7 and Table 3.

Figure 7.

Mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) by decile of kidney function measured as cystatin C. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2771570/bin/nihms-153474-f0001.jpg

 

 

Table 3

Linear regression of systolic blood pressure by kidney function (N = 906)

Age-adjusted Multivariable adjusted*
Measure N β coefficient P β coefficient P
Cystatin-C (per 0.4 mg/L [SD] increase) 1.75 ± 0.72 .01 1.19 ± 0.55 .03
    Overall
    >1.0 551 2.23 ± 0.07 .03 1.23 ± 0.03 .04
    <1.0 355 1.59 ± 0.04 .71 0.54 ± 0.01 .87
Spline P value for difference in slopes .85
24-h CrCl (per 28 mL/min [SD] decrease)
    Overall 1.96 ± 0.76 .01 0.91 ± 0.61 .14
    <60 222 11.20 ± 2.74 <.001 6.40 ± 2.13 .003
    >60 684 0.31 ± 0.99 .42 0.36 ± 0.77 .64
    Spline P-value for difference in slopes .01

The results for both Cystatin C and for eGFR are in agreement with incidence rates for heart failure (57)categorized by ejection fraction (EF) and kidney function over 1992−2000 in the Cardiovascular Health Study. Estimated glomerular filtration rate (mL/min per 1.73 m2) is labeled as “eGFR”. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2258307/bin/nihms-39968-f0002.jpg).

The association of cystatin C with risk for SHF appeared linear across quartiles of cystatin C (57) and slightly stronger at the highest categories of cystatin C, whereas the lower three quartiles of cystatin C had similar risks for DHF. Participants with an estimated GFR ≥ 60 mL/min per 1.73 m2 had an equal likelihood of developing DHF or SHF, whereas participants with an estimated GFR < 60 mL/min per 1.73 m2 had a greater likelihood of developing SHF.

When an interaction term for HF type (SHF or DHF) was inserted into a fully adjusted standard Cox proportional hazards model with HF with either type of EF as the outcome, the association of continuous cystatin C with SHF was significantly greater than the association of cystatin C with DHF ( P value for interaction < 0.001). The association of estimated GFR and SHF compared with DHF was weaker (P value for interaction = 0.06 for the fully adjusted model).

Ascending quartiles of cystatin C were associated with increasing adjusted risk for the development of “unclassified” HF, defined by the absence of a point-of-care EF measurement. The magnitude of the fully adjusted hazard ratios for the association between cystatin C and risk of unclassified HF were intermediate between those described for DHF and SHF [hazard ratios (95% confidence intervals) for each higher quartile of cystatin C 1.00 (reference), 1.12 (0.80−1.57), 1.84 (1.34−2.51), 2.18 (1.58−3.00)]. The authors state that increased left atrial filling pressures trigger the release of atrial natriuretic peptide and inhibition of vasopressin, which leads to decreased renal sympathetic tone and diuresis early in the pathogenesis of HF (57).  They suggest that even relatively small decrements in k58idney function contribute to the risk of SHF.

Aldosterone plays a key role in homeostatic control and maintenance of blood pressure (BP) by regulation of extracellular volume, vascular tone, and cardiac output. Taking this assumption further, a study unrelated to that above explored the magnitude of the effect of relative aldosterone excess in predicting peripheral as well as aortic blood pressure in a cohort of patients undergoing coronary angiography.  (58) They found that mean peripheral systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the entire cohort were 141 ± 24 mm Hg and 81 ± 11 mm Hg, respectively. Median SBP and aortic SBP increased steadily and significantly from aldosterone/renin ratio (ARR), respectively; p < 0.0001 for both) after multivariate adjustment for parameters potentially influencing BP. ARR emerged as the second most significant independent predictor (after age) of mean SBP and as the most important predictor of mean DBP in this patient cohort.  The authors stress the importance of the ARR in modulating BP over a much wider range than is currently appreciated, as it was already known that the ARR was positively associated with pulse wave velocity in young normotensive healthy adults, indicating that relative aldosterone excess might affect arterial remodeling and precede BP rise as a result of increased vascular stiffness. In this study the ARR was calculated as the PAC/PRC ratio (pg/ml/pg/ml). An ARR >50 pg/ml had a sensitivity and specificity of ARR of 89% and 96%, respectively, for primary aldosteronism. The ARR was modeled as a continuous ratio (with log-transformed values).  The study carried out a multivariate stepwise regression analysis for predictors of BP (not shown). They illustrate (not shown) that marked increases in PRC are a major characteristic of lower ARR categories, and that  across a broad range of ARR values, inappropriately elevated aldosterone levels exert a strong effect on BP values and constitute the most important and second-most important predictor of DBP and SBP, respectively.

Cystatin C may be ordered when a health practitioner is not satisfied with the results of other tests, such as a creatinine or creatinine clearance, or wants to check for early kidney dysfunction, particularly in the elderly, and/or wants to monitor known impairment over time. In diverse populations it has been found to improve the estimate of GFR when combined in an equation with blood creatinine. A high level in the blood corresponds to a decreased glomerular filtration rate (GFR) and hence to kidney dysfunction. Since cystatin C is produced throughout the body at a constant rate and removed and broken down by the kidneys, it should remain at a steady level in the blood if the kidneys are working efficiently and the GFR is normal.

Chronic kidney disease (CKD) is defined as the presence of: persistent and usually progressive reduction in GFR (GFR <60 mL/min/1.73 m2) and/or albuminuria (>30 mg of urinary albumin per gram of urinary creatinine), regardless of GFR. Cystatin C is an index of GFR, especially in patients where serum creatinine may be misleading (eg, very obese, elderly, or malnourished patients); for such patients, use of CKD-EPI cystatin C equation is recommended to estimate GFR. Cystatin C eGFR may have advantages over creatinine eGFR in certain patient groups in whom muscle mass is abnormally high or low (for example quadriplegics, very elderly, or malnourished individuals). Blood levels of cystatin C also equilibrate more quickly than creatinine, and therefore, serum cystatin C may be more accurate than serum creatinine when kidney function is rapidly changing (59) (for example amongst hospitalized individuals).

It is a low molecular weight (13,250 kD) cysteine proteinase inhibitor that is produced by all nucleated cells and found in body fluids, including serum. Since it is formed at a constant rate and freely filtered by the kidneys, its serum concentration is inversely correlated with the glomerular filtration rate (GFR); that is, high values indicate low GFRs while lower values indicate higher GFRs, similar to creatinine. While both cystatin C and creatinine are freely filtered by glomeruli, cystatin C is reabsorbed and metabolized by proximal renal tubules. Thus, under normal conditions, cystatin C does not enter the final excreted urine to any significant degree, and the serum concentration is unaffected by infections, inflammatory or neoplastic states, or by body mass, diet, or drugs.  GFR can be estimated (eGFR) from serum cystatin C utilizing an equation which includes the age and gender of the patient (CKD-EPI cystatin C equation, developed by Inker et al. (59) It demonstrated good correlation with measured iothalamate clearance in patients with all common causes of kidney disease, including kidney transplant recipients.

According to the National Kidney Foundation Kidney Disease Outcome Quality Initiative (K/DOQI) classification, among patients with CKD, irrespective of diagnosis, the stage of disease should be assigned based on the level of kidney function:

Table 4

Stage Description GFR mL/min/BSA
1 Kidney damage with normal or  increased GFR 90
2 Kidney damage with mild decrease in  GFR 60-89
3 Moderate decrease in GFR 30-59
4 Severe decrease in GFR 15-29
5 Kidney failure <15 (or dialysis)

(http://www2.kidney.org/professionals/kdoqi/guidelines_ckd/p4_class_g1.htm)

In a study to evaluate cystatin C as a measure of renal function in comparison to serum creatinine, 500 patients had cystatin C measured by nephelometry and glomerular filtration rate (GFR) measured by nonradiolabeled iothalamate clearance (59). In addition, serum creatinine was measured and the patients’ medical records reviewed. The correlation of 1/cystatin C with GFR (r=0.90) was significantly superior than 1/creatinine (r=0.82, p<0.05) with GFR. The superior correlation of 1/cystatin C with GFR was observed in the various clinical subgroups of patients studied (ie, subjects with no suspected renal disease, renal transplant patients, recipients of some other transplant, patients with glomerular disease, and patients with non-glomerular renal disease). The findings indicated that cystatin C may be superior to serum creatinine for the assessment of GFR in a wide spectrum of patients (59). Others have similarly found that cystatin C correlates better than serum creatinine for assessment of GFR. (60)

Patients were screened for 3 chronic kidney disease (CKD) studies in the United States (n = 2,980) and a clinical population in Paris, France (n = 438)(61).   GFR was measured by using urinary clearance of iodine125-iothalamate in the US studies and chromium51-EDTA in the Paris study. GFR was calculated using the 4 new equations based on serum cystatin C alone, serum cystatin C, serum creatinine, or both with age, sex, and race. New equations were developed by using linear regression with log GFR as the outcome in two thirds of data from US studies. Internal validation was performed in the remaining one third of data from US CKD studies; external validation was performed in the Paris study.

Mean mGFR, serum creatinine, and serum cystatin C values were 48 mL/min/1.73 m2 (5th to 95th percentile, 15 to 95), 2.1 mg/dL, and 1.8 mg/L, respectively. For the new equations, coefficients for age, sex, and race were significant in the equation with serum cystatin C, but 2- to 4-fold smaller than in the equation with serum creatinine (62, 63). Measures of performance in new equations were consistent across the development and internal and external validation data sets. Percentages of estimated GFR within 30% of mGFR for equations based on serum cystatin C alone, serum cystatin C, serum creatinine, or both levels with age, sex, and race were 81%, 83%, 85%, and 89%, respectively. The equation using serum cystatin C level alone yields estimates with small biases in age, sex, and race subgroups, which are improved in equations including these variables. It is concluded that Serum cystatin C level alone provides GFR estimates not linked to muscle mass, and that an equation including serum cystatin C level in combination with serum creatinine level, age, sex, and race provides the most accurate estimates.
The authors report that absence of urinary excretion has made it difficult to rigorously evaluate cystatin C as a filtration marker and to examine its non-GFR determinants. They also point out that a high level of variation in the cystatin C assay (64, 65), and standardization and calibration of clinical laboratories will be important to obtain accurate GFR estimation using cystatin C, as has been shown for creatinine.

The study reported above was followed by a major study by Inker LA, et al. (59). Their findings are summarized as follows. Mean measured GFRs were 68 and 70 ml per minute per 1.73 m2 of body-surface area in the development and validation data sets, respectively. In the validation data set, the creatinine–cystatin C equation performed better than equations that used creatinine or cystatin C alone. Bias was similar among the three equations, with a median difference between measured and estimated GFR of 3.9 ml per minute per 1.73 m2 with the combined equation, as compared with 3.7 and 3.4 ml per minute per 1.73 m2 with the creatinine equation and the cystatin C equation (P=0.07 and P=0.05), respectively. Precision was improved with the combined equation (interquartile range of the difference, 13.4 vs. 15.4 and 16.4 ml per minute per 1.73 m2, respectively [P=0.001 and P<0.001]), and the results were more accurate (percentage of estimates that were >30% of measured GFR, 8.5 vs. 12.8 and 14.1, respectively [P<0.001 for both comparisons]). In participants whose estimated GFR based on creatinine was 45 to 74 ml per minute per 1.73 m2, the combined equation improved the classification of measured GFR as either less than 60 ml per minute per 1.73 m2 or greater than or equal to 60 ml per minute per 1.73 m2 (net reclassification index, 19.4% [P<0.001]) and correctly reclassified 16.9% of those with an estimated GFR of 45 to 59 ml per minute per 1.73 m2 as having a GFR of 60 ml or higher per minute per 1.73 m2.

Other studies have established the importance of cystatin C levels(66, 67) and the factors influencing cystatin C levels on renal function measurement (68), including an implication that cystatin C, an alternative measure of kidney function, was a stronger predictor of the risk of cardiovascular events and death than either creatinine or the estimated GFR (69). This includes the Dallas Heart Study (30) finding that cystatin C was independently associated with a specific cardiac phenotype of concentric hypertrophy, including increased LV mass, concentricity, and wall thickness, but it was not associated with LV systolic function or volume. This association was particularly robust in hypertensives and blacks. The Cystatin C concentrations within stages of CKD are shown in Table 5 (70).

Table 5

      Cystatin C level
Stage a Description GFR range a (ml/min/1.73 m2) Native kidney disease b Transplant recipient c
1 Normal or increased GFR 90 0.80 0.87
2 Mildly decreased GFR 60 to 89 0.80 to 1.09 0.87 to 1.23
3 Moderately decreased GFR 30 to 59 1.10 to 1.86 1.24 to 2.24
4 Severely decreased GFR 15 to 29 1.87 to 3.17 2.25 to 4.10
5 Kidney Failure <15 >3.17 >4.10

a GFR estimates and CKD stage will be inaccurate if there is a calibration difference with the Dade-Behring BN II Nephelometer assay used in this study.

b Using the prediction equation: GFR=66.8 (cystatin C)-1.30.

c Using the prediction equation: GFR=76.6 (cystatin C)-1.16.

 

Copeptin, a novel marker

Urinary albumin excretion is a powerful predictor of progressive cardiovascular and renal disease. Copeptin is the inactive C-terminal fragment of the vasopressin precursor. It is a reliable marker of vasopressin secretion serves as a useful substitute for circulating vasopressin concentration. This allows  for the indirect measurement of vasopressin in epidemiological studies. Moreover, it has been shown that copeptin is a candidate biomarker for pneumonia 32), a predictor of outcome in heart failure, and is a powerful predictor of renal disease associated with albumin excretion (71).  Figure 8 shows the association between copeptin and 24-hour urinary volume, 24-h urinary osmolality and osmolality (71).

 

Figure 8

 

Association between quintiles of copeptin and median 24-h UAE (upper panel) and prevalence of microalbuminuria (lower panel) for males and females. Differences between the quintiles were tested by Kruskal–Wallis test. UAE, urinary albumin excretion.

 

 

Table 6 shows the association between copeptin concentration and urinary albumin excretion (UAE) in a log-log plot (71).

 

Model Corrected for β 95% CI for β P
Males        
 1 − (Crude) 0.25 0.20–0.30 <0.001
 2 As 1+age 0.21 0.16–0.26 <0.001
 3 As 2+MAP, BMI, smoking, glucose, cholesterol, CRP, and eGFR 0.10 0.05–0.16 <0.001
 4 As 3+diuretics and ACEi/ARB. 0.09 0.04–0.15 0.001
         
Females
 1 − (Crude) 0.19 0.15–0.23 <0.001
 2 As 1+age 0.17 0.14–0.22 <0.001
 3 As 2+MAP, BMI, smoking, glucose, cholesterol, CRP, and eGFR 0.16 0.11–0.21 <0.001
 4 As 3+diuretics and ACEi/ARB. 0.17 0.12–0.21 <0.001

ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin-II-receptor blocker; BMI, body mass index; CHD, coronary heart disease; CI, confidence interval; CRP, C-reactive protein; eGFR, estimated glomerular filtration rate; MAP, mean arterial pressure.

Log copeptin concentration was entered in the regression analyses as independent and log UAE as the dependent variable. Copeptin was associated with UAE in all age groups, but this association is the strongest when subjects are older. Twenty-four-hour urinary volume and 24-h urinary osmolarity were significantly different, with 24-h urinary volume being higher and 24-h urinary osmolarity being lower in the oldest age group when compared with the youngest age group. In both males and females, high copeptin concentration (a surrogate for vasopressin) is associated with low 24-h urinary volume and high 24-h urinary osmolarity. However, urinary osmolarity was independently associated with UAE, but it was weaker than that between copeptin and UAE.  This might indicate that induction of specific glomerular hyperfiltration or decreased tubular albumin reabsorption are associated with this relationship. In addition, subjects with higher levels of copeptin had lower renal function.  These investigators concluded that copeptin (a reliable substitute for vasopressin) is associated with UAE and microalbuminuria, consistent with the hypothesis that vasopressin induces UAE (72).  Other studies indicated that copeptin levels are increased in patients with pulmonary artery hypertension (73), and
higher serum copeptin levels, a surrogate for arginine vasopressin (AVP) release, are associated not only with systolic and diastolic blood pressure but also with several components of metabolic syndrome (74) including obesity, elevated concentration of triglycerides, albuminuria, and serum uric acid level.

 

 

Natriuretic peptides in the evaluation of heart failure

The brain type natriuretic peptide (BNP) and the N-terminal pro B-type natriuretic peptide (NT proBNP), but not yet the atrial natriuretic peptide have gained prominence in the evaluation of patients with CHF, which may be with or without preserved ejection fraction . Richards et al. (75)  make the following points.

 

  • Threshold values of B-type natriuretic peptide (BNP) and N-terminal prohormone B-type natriuretic peptide (NT-proBNP) validated for diagnosis of undifferentiated acutely decompensated heart failure (ADHF) remain useful in patients with heart failure with preserved ejection fraction (HFPEF), with minor loss of diagnostic performance.

 

  • BNP and NT-proBNP measured on admission with ADHF are powerfully predictive of in-hospital mortality in both HFPEF and heart failure with reduced EF (HFREF), with similar or greater risk in HFPEF as in HFREF associated with any given level of either peptide.

 

  • In stable treated heart failure, plasma natriuretic peptide concentrations often fall below cut-point values used for the diagnosis of ADHF in the emergency department; in HFPEF, levels average approximately half those in HFREF.

 

  • BNP and NT-proBNP are powerful independent prognostic markers in both chronic HFREF and chronic HFPEF, and the risk of important clinical adverse outcomes for a given peptide level is similar regardless of left ventricular ejection fraction.

 

  • Serial measurement of BNP or NT-proBNP to monitor status and guide treatment in chronic heart failure may be more applicable in HFREF than in HFPEF.

 

In addition, they point out the following:

 

BNP and NT-proBNP fall below ADHF thresholds in stable HFREF in approximately 50% and 20% of cases, respectively. Levels in stable HFPEF are even lower, approximately half those in HFREF.

 

Whereas BNPs have 90% sensitivity for asymptomatic LVEF of less than 40% in the community (a precursor state for HFREF), they offer no clear guide to the presence of early community based HFPEF.

 

Guidelines recommend BNP and NT-proBNP as adjuncts to the diagnosis of acute and chronic HF and for risk stratification. Refinements for application to HFPEF are needed.

 

The prognostic power of NPs is similar in HFREF and HFPEF. Defined levels of BNP and NT-proBNP correlate with similar short-term and long-term risks of important clinical adverse outcomes in both HFREF and HFPEF.

 

They provide a diagnostic algorithm for suspected heart failure (75)(Figure 9).

 

Figure 9

Diagnostic algorithm for suspected heart failure presenting either acutely or nonacutely

 

 

Diagnostic algorithm for suspected heart failure presenting either acutely or nonacutely. a In the acute setting, mid-regional pro–atrial natriuretic peptide may also be used (cutoff point 120 pmol/L; ie, <120 pmol/L 5 heart failure unlikely). b Other causes of elevated natriuretic peptide levels in the acute setting are an acute coronary syndrome, atrial or ventricular arrhythmias, pulmonary embolism, and severe chronic obstructive pulmonary disease with elevated right heart pressures, renal failure, and sepsis. Other causes of an elevated natriuretic level in the nonacute setting are old age (>75 years), atrial arrhythmias, left ventricular hypertrophy, chronic obstructive pulmonary disease, and chronic kidney disease. c Exclusion cutoff points for natriuretic peptides are chosen to minimize the false-negative rate while reducing unnecessary referrals for echocardiography. Treatment may reduce natriuretic peptide concentration, and natriuretic peptide concentrations may not be markedly elevated in patients with heart failure with preserved ejection fraction.

 

Patients with acute pulmonary symptoms and with acute myocardial infarct present with dyspnea to the Emergency Department.  The evaluation is made particularly difficult in a patient for whom there is no prior history. Maisel et al. (76) presented the utility of the midregion proadrenomedullin (MR-proADM) in all patients presenting with acute shortness of breath.  They found that MR-proADM was superior to BNP or troponin for predicting 90-day all-cause mortality in patients presenting with acute dyspnea (c index = 0.755, p < 0.0001). Furthermore, MR-proADM added significantly to all clinical variables (all adjusted hazard ratios: HR=3.28), and it was also superior to all other biomarkers.

 

There is a large body of recent work that has enlarged our view of hypertension, kidney disease, cardiovascular disease, including heart failure with (HFpEF) or without preserved ejection fraction. I shall here refer to my review in Leaders in Pharmaceutical Innovation  (78).  The piece contains a study that I published  (79) with collaborators in Brooklyn, Bridgeport and Philadelphia that is no longer available from the publisher.

 

The natriuretic peptides, B-type natriuretic peptide (BNP) and NT-proBNP that have emerged as tools for diagnosing congestive heart failure (CHF) are affected by age and renal insufficiency (RI).  NTproBNP is used in rejecting CHF and as a marker of risk for patients with acute coronary syndromes. This observational study was undertaken to evaluate the reference value for interpreting NT-proBNP concentrations. The hypothesis is that increasing concentrations of NT-proBNP are associated with the effects of multiple co-morbidities, not merely CHF,

resulting in altered volume status or myocardial filling pressures.

 

NT-proBNP was measured in a population with normal trans-thoracic echocardiograms
(TTE) and free of anemia or renal impairment. Exclusion conditions were the following
co-morbidities:

 

 

  • anemia as defined by WHO,
  • atrial fibrillation (AF),
  • elevated troponin T exceeding 0.070 mg/dl,
  • systolic or diastolic blood pressure exceeding 140 and 90 respectively,
  • ejection fraction less than 45%,
  • left ventricular hypertrophy (LVH),
  • left ventricular wall relaxation impairment, and
  • renal insufficiency (RI) defined by creatinine clearance < 60ml/min using
    the MDRD formula .

Study participants were seen in acute care for symptoms of shortness of breath suspicious for CHF requiring evaluation with cardiac NTproBNP assay. The median NT-proBNP for patients under 50 years is 60.5 pg/ml with an upper limit of 462 pg/ml, and for patients over 50 years the median was 272.8 pg/ml with an upper limit of 998.2 pg/ml.

We suggested that NT-proBNP levels can be more accurately interpreted only after removal of the major co-morbidities that affect an increase in this  peptide in serum. The PRIDE study guidelines (http://www.pridestudy.org/)  should be applied until presence or absence of comorbidities is diagnosed. With no comorbidities, the reference range for normal over 50 years of age remains steady at ~1000 pg/ml. The effect shown in previous papers likely is due to increasing concurrent comorbidity with age.

We observed the following changes with respect to NTproBNP and age:

(i) Sharp increase in NT-proBNP at over age 50

(ii) Increase in NT-proBNP at 7% per decade over 50

(iii) Decrease in eGFR at 4% per decade over 50

(iv) Slope of NT-proBNP increase with age is related to proportion of patients with eGFR less than 90

(v) NT-proBNP increase can be delayed or accelerated based on disease comorbidities

The mean and 95% CI of NTproBNP (CHF removed) by the National Kidney Foundation staging for eGFR interval (eGFR scale: 0, > 120; 1, 90 to 119;2, 60 to 89; 3, 40 to 59; 4, 15 to 39; 5, under 15 ml/min). We created a new variable to minimize the effects of age and eGFR variability by correcting these large effects in the whole sample population.

Adjustment of the NT-proBNP for  both eGFR and for age over 50 differences. We have carried out a normalization to adjust for both eGFR and for age over 50:

(i) Take Log of NT-proBNP and multiply by 1000
(ii) Divide the result by eGFR (using MDRD9 or Cockroft Gault10)
(iii) Compare results for age under 50, 50-70, and over 70 years
(iv) Adjust to age under 50 years by multiplying by 0.66 and 0.56.

Figure 10

 

 

NKF staging by GFRe interval and NT-proBNP (CHF removed).

 

 

The equation does not require weight because the results are reported normalized

to 1.73 m2 body surface area, which is an accepted average adult surface area.

 

This is illustrated in Figure 11.

Figure 11

 

Plot of 1000*log (NT-proBNP)/GFR vs age at  eGFR over 90  and 60 ml/min

Figure 12 compares the reference ranges for NTproBNP before and after adjustment.

  • before adjustment; b) after adjustment. c) the scatterplot for 1000xlog(NT proBNP) versus 1000xlog(NT-proBNP/eGFR). Superimposed scatterplot and regression line with centroid and

confidence interval for 1000*log(NT-proBNP)/eGFR vs age (anemia removed)

at eGFR over 40 and 90 ml/min. (Black: eGFR > 90, Blue:  eGFR > 40)

 

More recent work is enlightening.  Hijazi et al. (80) studied the incremental value of measuring N-terminal pro–B-type natriuretic peptide (NT-proBNP) levels in addition to established risk factors (including the CHA2DS2VASc [heart failure, hypertension, age 75 years and older, diabetes, and previous stroke or transient ischemic attack, vascular disease, age 65 to 74 years, and sex category) for the prediction of cardiovascular and bleeding events. They concluded that NT-proBNP levels are often elevated in atrial fibrillation (AF) and it is independently associated with an increased risk for stroke and mortality. NT-proBNP improves risk stratification beyond the CHA2DS2VASc score and might be a novel tool for improved stroke prediction in AF. The

efficacy of apixaban compared with warfarin was independent of the NT-proBNP level. Moreover, natriuretic peptides are regulatory hormones associated with cardiac remodeling, namely, left ventricular hypertrophy and systolic/diastolic dysfunction. Another study reported that the risk of death of patients with plasma NT-proBNP 133 pg/mL (third tertile of the distribution) was 3.3 times that of patients with values 50.8 pg/mL (first tertile; hazard ratio: 3.30 [95% CI: 0.90 to 12.29]). This predictive value was independent of, and superior to, that of 2 ECG indexes of left ventricular hypertrophy, the Sokolov-Lyon index and the amplitude of the R wave in lead aVL and it persisted in patients without ECG left ventricular hypertrophy (81).
Many patients presenting with acute dyspnea (including those with ADHF) have multiple coexisting medical disorders that may complicate their diagnosis and management. These patients presenting with acute dyspnea may have longer hospital length of stay and are at high risk for repeat hospitalization or death. In this presentation testing for brain natriuretic peptide (BNP) or NT-proBNP has been shown to be valuable for an accurate and efficient diagnosis and prognostication of HF (82).

 

The biological activity of BNP, the product of an intracellular peptide (proBNP108) that is converted to NT-proBNP, includes stimulation of natriuresis and vasorelaxation; inhibition of renin, aldosterone, and sympathetic nervous activity; inhibition of fibrosis; and improvement in myocardial relaxation.

 

Figure 13

 

Biology of the natriuretic peptide system. BNP indicates brain natriuretic peptide; NT-proBNP, amino-terminal pro-B-type natriuretic peptide; and DPP-IV, dipeptidyl peptidase-4.

The authors remind us that approximately 20% of patients with acute dyspnea have BNP or NT-proBNP levels that are above the cutoff point to exclude HF but too low to definitively identify it (82). Knowledge of the differential diagnosis of non-HF elevation of NP, as well as interpretation of the BNP or NT-proBNP value in the context of a clinical assessment is essential.  Across all stages of HF, elevated BNP or NT-proBNP concentrations are at least comparable prognostic predictors of mortality and cardiovascular events relative to traditional predictors of outcome in this setting, with increasing NP concentrations predicting worse prognosis in a linear fashion. This prognostic value may be used to stratify patients at the highest risk of adverse outcomes (see Figure 2 In this page). Age-adjusted Kaplan-Meier survival curve of mortality at 1 year associated with an elevated amino-terminal pro-B-type natriuretic peptide    (NT-proBNP) concentration at emergency department presentation with dyspnea in those with acutely decompensated heart failure. Reproduced from Januzzi et al22. (82)

The importance of determining diastolic and systolic function and for measurement of pulmonary artery pressure by echocardiography is clear, as NT-proBNP levels may be increased with increase in pulmonary pressure as well as conditions that increase cardiac output. Although Hijazi et al. used the Cockcroft-Gault (CG) equation to determine the glomerular filtration rate (GFR) the CG equation may find higher eGFR in older individuals (80). In addition, elevated NT-proBNP independently predicts all-cause mortality and morbidity of patients with AF. A prominent disease with elevated NT-proBNP is a respiratory system disease, such as chronic obstructive pulmonary disease, pulmonary embolism, and interstitial lung disease, in which B-type natriuretic peptide levels are elevated in response to the pressure of the right side of the heart. The authors conclude that one should keep in mind that NT-proBNP alone may be inadequate.

NT-proBNP level is used for the detection of acute CHF and as a predictor of survival. However, a number of factors, including renal function, may affect the NT-proBNP levels. This study aims to provide a more precise way of interpreting NT-proBNP levels based on GFR, independent of age. This study includes 247 pts in whom CHF and known confounders of elevated NT-proBNP were excluded, to show the relationship of GFR in association with age. The effect of eGFR on NT-proBNP level was adjusted by dividing 1000 x log(NT-proBNP) by eGFR then further adjusting for age in order to determine a normalized NT-proBNP value. The normalized NT-proBNP levels were affected by eGFR independent of the age of the patient. A normalizing function based on eGFR eliminates the need for an age-based reference ranges for NT-proBNP (79).

The routine use of natiuretic peptides in severely dyspneic patients has recently been called into question. We hypothesized that the diagnostic utility of Amino Terminal pro Brain Natiuretic Peptide (NT-proBNP) is diminished in a complex elderly population (83)

We studied 502 consecutive patients in whom NT-proBNP values were obtained to evaluate severe dyspnea in the emergency department (84). The diagnostic utility of NT-proBNP for the diagnosis of congestive heart failure (CHF) was assessed utilizing several published guidelines, as well as the manufacturer’s suggested age dependent cut-off points. The area under the receiver operator curve (AUC) for NT-proBNP was 0.70. Using age-related cut points, the diagnostic accuracy of NT-proBNP for the diagnosis of CHF was below prior reports (70% vs. 83%). Age and estimated creatinine clearance correlated directly with NT-proBNP levels, while hematocrit correlated inversely. Both age > 50 years and to a lesser extent hematocrit < 30% affected the diagnostic accuracy of NT-proBNP, while renal function had no effect. In multivariate analysis, a prior history of CHF was the best predictor of current CHF, odds ratio (OR) = 45; CI: 23-88.

The diagnostic accuracy of NT-proBNP for the evaluation of CHF appears less robust in an elderly population with a high prevalence of prior CHF. Age and hematocrit levels, may adversely affect the diagnostic accuracy off NT-proBNP (85).

Obesity and hypertension.

Obesity is associated with an increased risk of hypertension. In the past 5 years there have been dramatic advances into the genetic and neurobiological mechanisms of obesity with the discovery of leptin and novel neuropeptide pathways regulating appetite and metabolism. In this brief review, we argue that these mounting advances into the neurobiology of obesity have and will continue to provide new insights into the regulation of arterial pressure in obesity. We focus our comments on the sympathetic, vascular, and renal mechanisms of leptin and melanocortin receptor agonists and on the regulation of arterial pressure in rodent models of genetic obesity. Three concepts are proposed (86).

First, the effect of obesity on blood pressure may depend critically on the genetic-neurobiological mechanisms underlying the obesity. Second, obesity is not consistently associated with increased blood pressure, at least in rodent models. Third, the blood pressure response to obesity may be critically influenced by modifying alleles in the genetic background.

Leptin plays an important role in regulation of body weight through regulation of food intake and sympathetically mediated thermogenesis. The hypothalamic melanocortin system, via activation of the melanocortin-4 receptor (MC4-R), decreases appetite and weight, but its effects on sympathetic nerve activity (SNA) are unknown. In addition, it is not known whether sympathoactivation to leptin is mediated by the melanocortin system.

The following study (87) tested the interactions between these systems in regulation of brown adipose tissue (BAT) and renal and lumbar SNA in anesthetized Sprague-Dawley rats. Intracerebroventricular administration of the MC4-R agonist MT-II (200 to 600 pmol) produced a dose-dependent sympathoexcitation affecting BAT and renal and lumbar beds. This response was completely blocked by the MC4-R antagonist SHU9119 (30 pmol ICV). Administration of leptin (1000 m g/kg IV) slowly increased BAT SNA (baseline, 4166 spikes/s; 6 hours, 196628 spikes/s; P50.001) and renal SNA (baseline, 116616 spikes/s; 6 hours, 169626 spikes/s; P50.014).

Intracerebroventricular administration of SHU9119 did not inhibit leptin-induced BAT sympathoexcitation (baseline, 3567 spikes/s; 6 hours, 158634 spikes/s; P50.71 versus leptin alone). However, renal sympathoexcitation to leptin was completely blocked by SHU9119 (baseline, 142617 spikes/s; 6 hours, 146625 spikes/s; P50.007 versus leptin alone). The study (87) demonstrates that the hypothalamic melanocortin system can act to increase sympathetic nerve traffic to thermogenic BAT and other tissues. Our data also suggest that leptin increases renal SNA through activation of hypothalamic melanocortin receptors. In contrast, sympathoactivation to thermogenic BAT by leptin appears to be independent of the melanocortin system.

Troponins

The introduction of the first generation troponins T and I was an important event leading to the declining use of creatine kinase isoenzyme MB because of the short half-life in the circulation of CKMB and the possibility of missing a late presenting ACS. The situation then would call for the measurement of lactate dehydrogenase isoenzyme 1 (H-type), which had a decline in use.  The troponins T and I are proteins associated with the muscle contractile element with high specificity for the cardiomyocyte apparatus, which increased rapidly after ACS and which had estimated diagnostic cutoffs of 0.08 mg/dl and 1 mg/dl respectively.  The choice of marker was largely dependent of the instrument platform.  These biomarkers went through several generations of improvement to improve the diagnostic sensitivity to a cutoff at 2 SD of the lower limit of detection, magnifying confusion in interpretation that had always existed. These cardiospecific markers are elevated in patients with hypertension and specifically, long term CKD. This was clarified by introducing the terms Type 1 and Type 2 myocardial infarct, designating the classic ACS due to plaque rupture as Type 1.  However, the type 2 class might well be non-homogeneous. In any case, these are the best we have in detecting myocardial ischemic damage with biomarker release.

 

Discussion

This discussion has covered a large body of research involving hypertension, the kidney, and cardiovascular humoral mechanisms of control with a broad brush.  The work that has been done is far more than is cited.  There are several biomarkers that we have considered. They are not only laboratory based measurements.  They are: PWV, cystatin C, eGFR, copeptin, BNP or NT-BNP, Midregional prohormone adrenomedullin (MR-ADM), urinary albumin excretion, and the aldosterone/renin ratio.

The preceding discussion reminds us of the story of the blind men palpating an elephant, set in a poem by John Godfrey Saxe. These blind men were asked to tell of their experiences palpating different parts of an elephant, without seeing the entire animal Figure 1. Each of the blind men was able to palpate one part of the elephant, and thus was able to describe it in terms that were “partly in the right.” However, because none of them was able to encompass the entire elephant in their hands, they were also “in the wrong,” in that they failed to identify the whole elephant (88).
The blind men and the elephant. Poem by John Godfrey Saxe (Cartoon originally copyrighted by the authors (88); G. Renee Guzlas, artist). http://www.nature.com/ki/journal/v62/n5/thumbs/4493262f1bth.gif

These authors advanced the “elephant” as the increased oxidative burden in the uremic milieu of patients with chronic kidney disease. I introduce the concept in the diagnostic dilemma about what biomarkers are diagnostically informative in hypertension and ischemic CVD poses a conundrum. In reviewing the full gamut of biomarkers, we have a replay of the Lone Ranger and the silver bullet.  The problem is that there is no “silver” bullet.  We are accustomed to rely on clinical observations that are themselves weak covariates in actual experience.  The studies that have been done to validate the effectiveness of key biomarkers are well designed and show relevance in the populations studied.  However, they are insufficient by themselves in the emergent care population.
 

Impediments to a solution to the problem

Tests are ordered by physicians based on the findings in a clinical history and physical examination. Test that are ordered are reimbursed by insurance carriers, Medicare and Medicaid based on a provisional diagnosis.  The provisional diagnosis generates an ICD10 code, which has been most recently revised with a weighted input from the insurers that is not in favor of considered clinical evidence.  Moreover, the provider of care is graded based on the number of patients seen and the tests performed on a daily basis over any period.  Given this situation, and in addition, the requirement to interact with an outmoded information system that is more helpful to the insurer and less helpful to the provider, it is not surprising that there is a large burnout of the nursing and physician practitioner workforce.  If the diagnosis is inconclusive at the time of patient examination, then the work is not reimbursable based on ICD10 coding requirements that are disease specific.   This problem breaks down into a workload and a reimbursement inconsistency, neither of which makes sense in terms of the original studies on Diagnosis Related Groups (89) at Yale by Robert Fetter’s group.  The problem is made worse by the design and selection of healthcare information systems.

Many have pointed out the flaws in current EHR design that impede the optimum use of data and hinder workflow. Researchers have suggested that EHRs can be part of a learning health system to better capture and use data to improve clinical practice, create new evidence, educate, and support research efforts. The health care system suffers from both inefficient and ineffective use of data. Data are suboptimally displayed to users, undernetworked, underutilized, and wasted. Errors, inefficiencies, and increased costs occur on the basis of unavailable data in a system that does not coordinate the exchange of information, or adequately support its use (90). Clinicians’ schedules are stretched to the limit and yet the system in which they work exerts little effort to streamline and support carefully engineered care processes. Information for decision-making is difficult to access in the context of hurried real-time workflows(91)

 

 

The solution to the problem

The current design of the Electronic Medical Record (EMR) is a linear presentation of portions of the record by services, by diagnostic method, and by date, to cite examples.  This allows perusal through a graphical user interface (GUI) that partitions the information or necessary reports in a workstation entered by keying to icons.  This requires that the medical practitioner finds the history, medications, laboratory reports, cardiac imaging and EKGs, and radiology in different workspaces.  The introduction of a DASHBOARD has allowed a presentation of drug reactions, allergies, primary and secondary diagnoses, and critical information about any patient the care giver needing access to the record.  The advantage of this innovation is obvious.  The startup problem is what information is presented and how it is displayed, which is a source of variability and a key to its success.

Gil David and Larry Bernstein have developed, in consultation with Prof. Ronald Coifman, in the Yale University Applied Mathematics Program, a software system that is the equivalent of an intelligent Electronic Health Records Dashboard (92)( that provides empirical medical reference and suggests quantitative diagnostics options.

The most commonly ordered test used for managing patients worldwide is the hemogram that often incorporates the review of a peripheral smear.  While the hemogram has undergone progressive modification of the measured features over time the subsequent expansion of the panel of tests has provided a window into the cellular changes in the production, release or suppression of the formed elements from the blood-forming organ to the circulation.  In the hemogram one can view data reflecting the characteristics of a broad spectrum of medical conditions.

How we frame our expectations is so important that it determines the data we collect to examine the process.   In the absence of data to support an assumed benefit, there is no proof of validity at whatever cost.   This has meaning for hospital operations, for nonhospital laboratory operations, for companies in the diagnostic business, and for planning of health systems.

In 1983, a vision for creating the EMR was introduced by Lawrence Weed, expressed by McGowan and Winstead-Fry (93)

The data presented has to be comprehended in context with vital signs, key symptoms, and an accurate medical history.  Consequently, the limits of memory and cognition are tested in medical practice on a daily basis.  We deal with problems in the interpretation of data presented to the physician, and how through better design of the software that presents this data the situation could be improved.  The computer architecture that the physician uses to view the results is more often than not presented as the designer would prefer, and not as the end-user would like.

Eugene Rypka contributed greatly to clarifying the extraction of features (94) in a series of articles, which set the groundwork for the methods used today in clinical microbiology.  The method he describes is termed S-clustering, and will have a significant bearing on how we can view hematology data.  He describes S-clustering as extracting features from endogenous data that amplify or maximize structural information to create distinctive classes.  The method classifies by taking the number of features with sufficient variety to map into a theoretic standard. The mapping is done by a truth table, and each variable is scaled to assign values for each: message choice.  The number of messages and the number of choices forms an N-by N table.  He points out that the message choice in an antibody titer would be converted from 0 + ++ +++ to 0 1 2 3.

Bernstein and colleagues had a series of studies using Kullback-Liebler Distance  (effective information) for clustering to examine the latent structure of the elements commonly used for diagnosis of myocardial infarction (95-97)(CK-MB, LD and the isoenzyme-1 of LD),  protein-energy malnutrition (serum albumin, serum transthyretin, condition associated with protein malnutrition (see Jeejeebhoy and subjective global assessment), prolonged period with no oral intake), prediction of respiratory distress syndrome of the newborn (RDS), and prediction of lymph nodal involvement of prostate cancer, among other studies.   The exploration of syndromic classification has made a substantial contribution to the diagnostic literature, but has only been made useful through publication on the web of calculators and nomograms (such as Epocrates and Medcalc) accessible to physicians through an iPhone.  These are not an integral part of the EMR, and the applications require an anticipation of the need for such processing.

Gil David et al. (90, 92) introduced an AUTOMATED processing of the data available to the ordering physician and can anticipate an enormous impact in diagnosis and treatment of perhaps half of the top 20 most common causes of hospital admission that carry a high cost and morbidity.  For example: anemias (iron deficiency, vitamin B12 and folate deficiency, and hemolytic anemia or myelodysplastic syndrome); pneumonia; systemic inflammatory response syndrome (SIRS) with or without bacteremia; multiple organ failure and hemodynamic shock; electrolyte/acid base balance disorders; acute and chronic liver disease; acute and chronic renal disease; diabetes mellitus; protein-energy malnutrition; acute respiratory distress of the newborn; acute coronary syndrome; congestive heart failure; disordered bone mineral metabolism; hemostatic disorders; leukemia and lymphoma; malabsorption syndromes; and cancer(s)[breast, prostate, colorectal, pancreas, stomach, liver, esophagus, thyroid, and parathyroid]. The same approach has also been applied to the problem of hospital malnutrition, but it has not been sufficiently applied to hypertension, cardiovascular diseases, acute coronary syndrome, chronic renal failure.

We have developed (David G, Bernstein L, and Coifman) (92) a software system that is the equivalent of an intelligent Electronic Health Records Dashboard that provides empirical medical reference and suggests quantitative diagnostics options. The primary purpose is to gather medical information, generate metrics, analyze them in realtime and provide a differential diagnosis, meeting the highest standard of accuracy. The system builds its unique characterization and provides a list of other patients that share this unique profile, therefore utilizing the vast aggregated knowledge (diagnosis, analysis, treatment, etc.) of the medical community. The main mathematical breakthroughs are provided by accurate patient profiling and inference methodologies in which anomalous subprofiles are extracted and compared to potentially relevant cases. As the model grows and its knowledge database is extended, the diagnostic and the prognostic become more accurate and precise. We anticipate that the effect of implementing this diagnostic amplifier would result in higher physician productivity at a time of great human resource limitations, safer prescribing practices, rapid identification of unusual patients, better assignment of patients to observation, inpatient beds, intensive care, or referral to clinic, shortened length of patients ICU and bed days.

The main benefit is a real time assessment as well as diagnostic options based on comparable cases, flags for risk and potential problems as illustrated in the following case acquired on 04/21/10. The patient was diagnosed by our system with severe SIRS at a grade of 0.61 .

Method for data organization and classification via characterization metrics.

The database is organized to enable linking a given profile to known profiles. This is achieved by associating a patient to a peer group of patients having an overall similar profile, where the similar profile is obtained through a randomized search for an appropriate weighting of variables. Given the selection of a patients’ peer group, we build a metric that measures the dissimilarity of the patient from its group. This is achieved through a local iterated statistical analysis in the peer group.

This characteristic metric is used to locate other patients with similar unique profiles, for each of whom we repeat the procedure described above. This leads to a network of patients with similar risk condition. Then, the classification of the patient is inferred from the medical known condition of some of the patients in the linked network.

How do we organize the data and linkages provided in the first place?

Predictors: PWV, cystatin C, creatinine, urea, eGFR, copeptin, BNP or NT-BNP, TnI or TnT, Midregional prohormone adrenomedullin (MR-ADM), urinary albumin excretion, and the aldosterone/renin ratio, homocysteine, transthyretin, glucose, albumin, chol/LDL, LD, Na+, K+,  Cl, HCO3, pH.

Conditions: AMI, CRF, ARF, hypertension, HFpEF, HFcEF, ADHF, obesity, PHT, RVHF, pulmonary edema, PEM

Other variables: sex (M,F), age, BMI. …

Conditioning data: take log transform for large ascending values, OR take deciles of variables, if necessary.  This could apply to NT-proBNP, BNP, TnI, TnT, CK and LD.

Arrange predictor variables in columns and patient-sequence in rows.  This is a bidimentional table.  The problem is to assign diagnoses to each patient-in sequence. There can be more than one diagnosis.

In reality the patient-sequence or identifier is not relevant. Only the condition assignment is.  The condition assignments are made in a column adjacent to the patient, and they fall into rows.
The construct appears to be a 2×2, but it is actually an n-dimensional  matrix.  Each patient position has one or more diagnoses.

Multivariate statistical analysis is used to extend this analysis to two or more predictors.   In this case a multiple linear regression or a linear discriminant function would be used to predict a dependent variable from two or more independent variables.   If there is linear association dependency of the variables is assumed and the test of hypotheses requires that the variances of the predictors are normally distributed.  A method using a log-linear model circumvents the problem of the distributional dependency in a method called ordinal regression.    There is also a relationship of analysis of variance, a method of examining differences between the means of  two or more groups.  Then there is linear discriminant analysis, a method by which we examine the linear separation between groups rather than the linear association between groups.  Finally, the neural network is a nonlinear, nonparametric model for classifying data with several variables into distinct classes. In this case we might imagine a curved line drawn around the groups to divide the classes. The focus of this discussion will be the use of linear regression  and explore other methods for classification purposes (98).

The real issue is how a combination of variables falls into a table with meaningful information.  We are concerned with accurate assignment into uniquely variable groups by information in test relationships. One determines the effectiveness of each variable by its contribution to information gain in the system.  The reference or null set is the class having no information.  Uncertainty in assigning to a classification is only relieved by providing sufficient information.  One determines the effectiveness of each variable by its contribution to information gain in the system.  The possibility for realizing a good model for approximating the effects of factors supported by data used for inference owes much to the discovery of Kullback-Liebler distance or “information” (99), and Akaike (100) found a simple relationship between K-L information and Fisher’s maximized log-likelihood function. A solid foundation in this work was elaborated by Eugene Rypka (101).  Of course, this was made far less complicated by the genetic complement that defines its function, which made more accessible the study of biochemical pathways.  In addition, the genetic relationships in plant genetics were accessible to Ronald Fisher for the application of the linear discriminant function.    In the last 60 years the application of entropy comparable to the entropy of physics, information, noise, and signal processing, has been fully developed by Shannon, Kullback, and others,  and has been integrated with modern statistics, as a result of the seminal work of Akaike, Leo Goodman, Magidson and Vermunt, and unrelated work by Coifman. Dr. Magidson writes about Latent Class Model evolution:

The recent increase in interest in latent class models is due to the development of extended algorithms which allow today’s computers to perform LC analyses on data containing more than just a few variables, and the recent realization that the use of such models can yield powerful improvements over traditional approaches to segmentation, as well as to cluster, factor, regression and other kinds of analysis.

Perhaps the application to medical diagnostics had been slowed by limitations of data capture and computer architecture as well as lack of clarity in definition of what are the most distinguishing features needed for diagnostic clarification.  Bernstein and colleagues (102-104) had a series of studies using Kullback-Liebler Distance  (effective information) for clustering to examine the latent structure of the elements commonly used for diagnosis of myocardial infarction (CK-MB, LD and the isoenzyme-1 of LD),  protein-energy malnutrition (serum albumin, serum transthyretin, condition associated with protein malnutrition (see Jeejeebhoy and subjective global assessment), prolonged period with no oral intake), prediction of respiratory distress syndrome of the newborn (RDS), and prediction of lymph nodal involvement of prostate cancer, among other studies.   The exploration of syndromic classification has made a substantial contribution to the diagnostic literature, but has only been made useful through publication on the web of calculators and nomograms (such as Epocrates and Medcalc) accessible to physicians through an iPhone.  These are not an integral part of the EMR, and the applications require an anticipation of the need for such processing.

Gil David et al. introduced an AUTOMATED processing of the data (104) available to the ordering physician and can anticipate an enormous impact in diagnosis and treatment of perhaps half of the top 20 most common causes of hospital admission that carry a high cost and morbidity.  For example: anemias (iron deficiency, vitamin B12 and folate deficiency, and hemolytic anemia or myelodysplastic syndrome); pneumonia; systemic inflammatory response syndrome (SIRS) with or without bacteremia; multiple organ failure and hemodynamic shock; electrolyte/acid base balance disorders; acute and chronic liver disease; acute and chronic renal disease; diabetes mellitus; protein-energy malnutrition; acute respiratory distress of the newborn; acute coronary syndrome; congestive heart failure; disordered bone mineral metabolism; hemostatic disorders; leukemia and lymphoma; malabsorption syndromes; and cancer(s)[breast, prostate, colorectal, pancreas, stomach, liver, esophagus, thyroid, and parathyroid].

Our database organized to enable linking a given profile to known profiles(102-104). This is achieved by associating a patient to a peer group of patients having an overall similar profile, where the similar profile is obtained through a randomized search for an appropriate weighting of variables. Given the selection of a patients’ peer group, we build a metric that measures the dissimilarity of the patient from its group. This is achieved through a local iterated statistical analysis in the peer group.

We then use this characteristic metric to locate other patients with similar unique profiles, for each of whom we repeat the procedure described above. This leads to a network of patients with similar risk condition. Then, the classification of the patient is inferred from the medical known condition of some of the patients in the linked network. Given a set of points (the database) and a newly arrived sample (point), we characterize the behavior of the newly arrived sample, according to the database. Then, we detect other points in the database that match this unique characterization. This collection of detected points defines the characteristic neighborhood of the newly arrived sample. We use the characteristic neighborhood in order to classify the newly arrived sample. This process of differential diagnosis is repeated for every newly arrived point.   The medical colossus we have today has become a system out of control and beset by the elephant in the room – an uncharted complexity.

 

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  12. Parag C. Patel, Colby R. Ayers, Sabina A. Murphy, et al. Association of Cystatin C with Left Ventricular Structure and Function (The Dallas Heart Study). Circulation: Heart Failure. 2009; 2: 98-104.  http://dx.doi.org:/10.1161/CIRCHEARTFAILURE.108.807271.
  13. Rule AD, Bergstralh EJ, Slezak JM, Bergert J, Larson TS. Glomerular filtraton rate estimated by cystatin C among different clinical presentations. Kidney Int. 2006; 69:399–405. http://dx.doi.org:/10.1038/sj.ki.5000073
  14. Muller B, Morgenthaler N, Stolz D, et al. Circulating levels of copeptin, a novel biomarker, in lower respiratory tract infections. Eur J Clin Invest 2007;37, 145–152.
  15. Stoiser B, Mortl D, Hulsmann M, et al. Copeptin, a fragment of the vasopressin precursor, as a novel predictor of outcome in heart failure.  Eur J Clin Invest Nov 2006; 36(11):771–778.
    http://dx.doi.org:/10.1111/j.1365-2362.2006.01724.x
  16. Meijer E, Bakker SJL, Helbesma N, et al. Copeptin, a surrogate marker of vasopressin, is associated with microalbuminuria in a large population cohort.  Kidney Intl 2010; 77:29–36.
    http://dx.doi.org:/10.1038/ki.2009.397
  17. Nickel NP, Lichtinghagen R, Golpon H, et al. Circulating levels of copeptin predict outcome in patients with pulmonary arterial hypertension. Respir Res. Nov 19, 2013; 14:130. http://dx.doi.org:/10.1186/1465-9921-14-130
  18. Tenderenda-Banasiuk E,  Wasilewska A, Filonowicz R, et al. Serum copeptin levels in adolescents with primary hypertension. Pediatr Nephrol. 2014; 29(3): 423–429.    doi:  10.1007/s00467-013-2683-5
  19. Richards M, Januzzi JL, and Troughton RW. Natriuretic Peptides in Heart Failure with Preserved Ejection Fraction.  Heart Failure Clin 2014; 10:453–470. http://dx.doi.org/10.1016/j.hfc.2014.04.006
  20. Maisel A, Mueller C, Nowak M and Peacock WF, et al. Midregion Prohormone Adrenomedullin and Prognosis in Patients Presenting with Acute Dyspnea Results from the BACH (Biomarkers in Acute Heart Failure) Trial. J Am Coll Cardiol 2011; 58(10):1057–67.  http://dx.doi.org:/10.1016/j.jacc.2011.06.006.
  21. Bernstein LH. Heart-Lung-Kidney: Essential Ties. Leaders in Pharmaceutical Innovation. http://pharmaceuticalinnovations.com
  22. Bernstein LH, Zions MY, Alam ME, et al.  What is the best approximation of reference normal for NT-proBNP? Clinical levels for enhanced assessment of NT-proBNP (CLEAN). J Med Lab and Diag 04/2011; 2:16-21. http://www.academicjournals.org/jmld
  23. Hijazi  Z., Wallentin  L., Siegbahn  A., et al; N-terminal pro-B-type natriuretic peptide for risk assessment in patients with atrial fibrillation: insights from the ARISTOTLE trial (Apixaban for the Prevention of Stroke in Subjects With Atrial Fibrillation. J Am Coll Cardiol. 2013; 61:2274-2284
  24. Paget V, Legedz L, Gaudebout N, et al. N-Terminal Pro-Brain Natriuretic Peptide A Powerful Predictor of Mortality in Hypertension. Hypertension. 2011; 57:702-709   http://hyper.ahajournals.org/content/57/4/702.full.pdf]
  25. Kim Han-Naand  Januzzi JL.  Natriuretic Peptide Testing in Heart Failure. Circulation 2011;  123: 2015-2019. http://dx.doi.org:/10.1161/CIRCULATIONAHA.110.979500
  26. Balta S, Demirkol S, Aydogan M, and Celik T. Higher N-Terminal Pro–B-Type Natriuretic Peptide May Be Related to Very Different Conditions.  J Am Coll Cardiol. 2013; 62(17):1634-1635.   http://dx.doi.org:/10.1016/j.jacc.2013.04.093
  27. Bernstein LH1, Zions MY, Haq SA, et al. Effect of renal function loss on NT-proBNP level variations. Clin Biochem. 2009 Jul; 42(10-11): 1091-8. http://dx.doi.org:/10.1016/j.clinbiochem.2009.02.027
  28. Afaq MA, Shoraki A, Oleg I, Bernstein L, and Stuart W. Zarich.  Validity of Amino Terminal pro-Brain Natiuretic Peptide in a Medically Complex Elderly Population. J Clin Med Res. 2011 Aug; 3(4): 156–163.   doi:  10.4021/jocmr606w
  29. Mark AL, Correia M, MorganDA, et al. New Concepts From the Emerging Biology of Obesity. Hypertension. 1999; 33[part II]:537-541.
  30. Himmelfarb J, Stenvinkel P, Ikizler TA and Hakim RM. The elephant in uremia: Oxidant stress as a unifying concept of cardiovascular disease in uremia. Kidney International (2002) 62, 1524–1538; http://dx.doi.org:/10.1046/j.1523-1755.2002.00600.x  http://www.nature.com/ki/journal/v62/n5/full/4493262a.html
  31. The blind men and the elephant. Poem by John Godfrey Saxe (Cartoon originally copyrighted by the authors; G. Renee Guzlas, artist). http://www.nature.com/ki/journal/v62/n5/thumbs/4493262f1bth.gif
  32. Fetter RB. Diagnosis Related Groups: Understanding Hospital Performance. Interfaces Jan. – Feb., 1991; 21(1), Franz Edelman Award Papers: 6-26
  33. Bernstein LH. Inadequacy of EHRs. Pharmaceutical Intelligence. https://pharmaceuticalintelligence.com/2015/11/05/inadequacy-of-ehrs/
  34. Celi LA,  Marshall JD, Lai Y, Stone DJ. Disrupting Electronic Health Records Systems: The Next Generation.  JMIR  Med Inform 2015 (23.10.15);  3(4) :e34
    http://dx.doi.org:/10.2196/medinform.4192
  35. Realtime Clinical Expert Support. Pharmaceutical Intelligence.  https://pharmaceuticalintelligence.com/2015/05/10/realtime-clinical-expert-support/
  36. McGowan JJ and Winstead-Fry P. Problem Knowledge Couplers: reengineering evidence-based medicine through interdisciplinary development, decision support, and research. Bull Med Libr Assoc. 1999 October;  87(4):462–470.)
  37. Rypka EW and Babb R. Automatic construction and use of an identification scheme. In MEDICAL RESEARCH ENGINEERING Apr 19709; (2):9-19. https://www.researchgate.net/publication/17720773_Automatic_construction_and_use_of_an_identification_scheme
  38. Rudolph, R. A., Bernstein, L. H. and Babb, J. Information induction for predicting acute myocardial infarction. Clinical Chemistry 1988; 34: 2031-2038.
  39. Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.
  40. Bernstein LH, Good IJ, Holtzman, Deaton ML, Babb J. Diagnosis of acute myocardial infarction from two measurements of creatine kinase isoenzyme MB with use of nonparametric probability estimation. Clin Chem 1989; 35(3):444-447.
  41. Bernstein LH. Regression: A richly textured method for comparison and classification of predictor variables. https://pharmaceuticalintelligence.com/2012/08/14/regression-a-richly-textured-method-for-comparison-and-classification-of-predictor-variables/
  42. Posada D and Buckley TR. Model Selection and Model Averaging in Phylogenetics: Advantages of Akaike Information Criterion and Bayesian Approaches over Likelihood Ratio Tests. Syst. Biol. 200; 53(5):793–808. http://dx.doi.org:/10.1080/10635150490522304
  1. Kullback S. and Leibler R. On Information and Sufficiency. Ann Math Statistics. Mar 1951; 22(1):79-86. http://www.csee.wvu.edu/~xinl/library/papers/math/statistics/Kullback_Leibler_1951.pdf
  2. Bernstein LH, David G, Rucinski J, Coifman RR. Converting Hematology Based Data Into an Inferential Interpretation. In INTECH Open Access Publisher, 2012. https://books.google.com/books/about/Converting_Hematology_Based_Data_Into_an.html
  3. Bernstein LH, David G, Coifman RR. Generating Evidence Based Interpretation of Hematology Screens via Anomaly Characterization. Open Clin Chem J 2011; 4:10-16
  4. Bernstein LH. Automated Inferential Diagnosis of SIRS, sepsis, septic shock. Medical Informatics View. https://pharmaceuticalintelligence.com/2012/08/01/automated-inferential-diagnosis-of-sirs-sepsis-septic-shock/
  5. Bernstein LH, David G, Coifman RR. The Automated Nutritional Assessment. Nutrition  2013; 29: 113-121

 

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