Posts Tagged ‘calcium signaling’

Lesson 4 Cell Signaling And Motility: G Proteins, Signal Transduction: Curations and Articles of reference as supplemental information: #TUBiol3373

Curator: Stephen J. Williams, Ph.D.

Below please find the link to the Powerpoint presentation for lesson #4 for #TUBiol3373.  The lesson first competes the discussion on G Protein Coupled Receptors, including how cells terminate cell signals.  Included are mechanisms of receptor desensitization.  Please NOTE that desensitization mechanisms like B arrestin decoupling of G proteins and receptor endocytosis occur after REPEATED and HIGH exposures to agonist.  Hydrolysis of GTP of the alpha subunit of G proteins, removal of agonist, and the action of phosphodiesterase on the second messenger (cAMP or cGMP) is what results in the downslope of the effect curve, the termination of the signal after agonist-receptor interaction.


Click below for PowerPoint of lesson 4

Powerpoint for lesson 4


Please Click below for the papers for your Group presentations

paper 1: Membrane interactions of G proteins and other related proteins

paper 2: Macaluso_et_al-2002-Journal_of_Cellular_Physiology

paper 3: Interactions of Ras proteins with the plasma membrane

paper 4: Futosi_et_al-2016-Immunological_Reviews


Please find related article on G proteins and Receptor Tyrosine Kinases on this Open Access Online Journal

G Protein–Coupled Receptor and S-Nitrosylation in Cardiac Ischemia and Acute Coronary Syndrome

Action of Hormones on the Circulation

Newer Treatments for Depression: Monoamine, Neurotrophic Factor & Pharmacokinetic Hypotheses

VEGF activation and signaling, lysine methylation, and activation of receptor tyrosine kinase



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Calcium Signaling, Cardiac Mitochondria and Metabolic Syndrome

Larry H Bernstein: Author 


Reporter: Aviva Lev-Ari, PhD, RN

Mitochondria, the cardiovascular system and metabolic syndrome

Start date
April 24, 2013
End date
April 24, 2013
London, UK / Kennedy Lecture Theatre, Institute of Child Health
London, UK
– Mitochondrial ROS metabolism in the heart
– Mitochondrial permeability transition pore
– Mitochondria in vascular smooth muscle
– Therapeutic targets for cardiac disease

Invited speakers

This event has now passed – please visit our Conference calendar for future Abcam events

Confirmed speakers:

Paolo Bernardi, University of Padova, Italy
‘The mitochondrial permeability transition pore: A mystery solved?’

Susan Chalmers, University of Strathclyde Glasgow
‘Mitochondria in vascular smooth muscle: from regulation of calcium signals to control of proliferation’

Andrew Hall, UCL
‘The role of sirtuin 3 in cardiac dysfunction’

Derek Hausenloy, UCL
‘Mitochondrial dynamics as a therapeutic target for cardiac disease’

Guy Rutter, Imperial College London
‘Mitochondria and insulin secretion – links to diabetes’ 

Michael Murphy, MRC Mitochondiral Biology Unit, Cambridge
‘Exploring mitochondrial ROS metabolism in the heart using targeted probes and bioactive molecules’

Toni Vidal Puig, Institute of Metabolic Science, University of Cambridge
‘Adipose tissue expandability, lipotoxicity and the metabolic syndrome’ 


It all happens in a heartbeat

Calcium signaling is instrumental for excitation-contraction coupling (ECC). The involvement of mitochondria  in establishing rapid cytosolic calcium transients in this process remain debated.

Two models have emerged:

  • slow integration versus rapid and
  • ample beat-to-beat changes of

cytosolic calcium transients into the mitochondria matrix.

a brief outline of cardiac calcium signaling » 

Mitochondrial Calcium transport mechanisms 

Calcium influx can be mediated by:

  • Mitochondrial Calcium Uniporter (MCU)
  • Mitochondrial Ryanodine receptor type 1 (mRyR1)
  • Leucine-zipper-EF-hand-containing transmembrane protein 1 (LETM1)
  • Proposed uptake by UCP2 and 3 and Coenzyme Q10

Calcium efflux can be mediated by:

  • Na-dependent calcium extrusion pathway, mNCX1
  • Mitochondrial permeability transistion pore (mPTP)

Inhibiting Calcium signaling 

Homeostasis of mitochondrial Ca2+ is crucial for balancing cell survival, death and energy production. Inhibitors of mitochondrial Ca2+ exchange are:

  1. CGP37157 – Selective mitochondrial Na+-Ca2+ exchange inhibitor
  2. Thapsigargin – Potent, cell-permeable Ca2+-ATPase inhibitor
  3. Ryanodine – Ca2+ release modulator

calcium signaling inhibitors (now available from Abcam Biochemicals)  » 

Quick tools for calcium detection 

You can now detect intracellular calcium mobilization directly in cultured cells in only 1 hour with Fluo-8 No Wash Calcium Assay Kit (ab112129):

  • increased signal with Fluo-8 – high affinity indicator (Kd = 389 nM)
  • no wash step needed
  • works on adherent and suspension cells

The Mitochondria, cardiovascular system and metabolic syndrome meeting took place on April 24 2013,  London, UK.

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Heroes in Medical Research: Dr. Carmine Paul Bianchi Pharmacologist, Leader, and Mentor

Writer/Curator: Stephen J. Williams, Ph.D.

Past articles in this Heroes in Medical Research series had focused on those seemingly small discoveries, sometimes gained serendipitously and through careful observation and experimentation, which led to some of our most important breakthroughs of our time.  I have tried to make the posts more about the people and less about the discoveries

However, though seminal discoveries are so important to the future of science (and should be celebrated), equally if not MORE IMPORTANT is the MENTORING of future scientists and the PROMOTION of fields of study.  One person who exemplified these values was Dr. Carmine Paul Bianchi, who had recently just passed away this August, and will be sorely missed in the field of pharmacology and toxicology.

For those who were not familiar with Dr. Bianchi I have curated some pertinent information about his work as a scientist, professor and Chairman in pharmacology, and leader and spokesperson for the field of pharmacology.  He was one of the founders of the Mid-Atlantic Pharmacology Society and was an advocate and influential in the careers of many pharmacologists and toxicologists.

Comments from fellow colleagues are very welcome (in comment section at end of post)

The following is separated in 3 sections:

  • An obituary from the Philadelphia Inquirer
  •  A section of the history of the Pharmacology Department at Thomas Jefferson University where Dr. Bianchi was Chairman
  • A few important textbooks and scientific articles he had authored


Carmine Paul Bianchi, 86, pharmacology professor

Paul Bianchi















Carmine Paul Bianchi

By Bonnie L. Cook, Inquirer Staff Writer

Posted: August 20, 2013

Carmine Paul Bianchi, 86, of Boothwyn, a professor of pharmacology in Philadelphia for many years, died Tuesday, Aug. 13, of a digestive ailment at Taylor Hospice House in Ridley Park.

Born in Newark, N.J., and raised in Maplewood, Dr. Bianchi served as an Army surgical technician in Tilton General Hospital at Fort Dix from 1945 to 1947.

He earned a bachelor’s degree in chemistry from Columbia University in 1950, a master’s in physiology and biochemistry from Rutgers University in 1953, and a doctorate in physiology and physical chemistry in 1956 from Rutgers.

In the 1950s, he did research at Rutgers and was a public health fellow and visiting scientist at the National Institutes of Health in Maryland.

From 1961 to 1976, he held a number of jobs in the department of pharmacology in the University of Pennsylvania School of Medicine. That culminated in his being named professor of pharmacology.

Dr. Bianchi left in 1976 for Jefferson Medical College of Thomas Jefferson University, where he became pharmacology professor and chairman of the pharmacology department from 1976 to 1987. In 1987, he stepped down from the chairmanship but remained professor of pharmacology. He retired in 1997 as professor emeritus.

Dr. Bianchi was a member of many professional groups, including the New York Academy of Sciences and the American Association for the Advancement of Science.

He was a leader and author in pharmacology, helping edit an industry journal and making himself available for consultation to medical examiners and experts in toxicology.

He wrote or contributed to three books and 200 scientific papers and lectured widely. He enjoyed mentoring medical and graduate students.

His family called Dr. Bianchi “a true renaissance man” who was as comfortable discussing English, history, and politics as he was the sciences.




The following was taken from a history of  Department of Pharmacology  at Thomas Jefferson University  and can be viewed at:



Carmine Paul Bianchi, Ph.D;

Third Chairman (1976-1986)

The new Chairman of the Department, effective

July 1, 1976, was Carmine Paul Bianchi, Ph.D.

(Figure 8-3) from the University of Pennsylvania

School of Medicine, where he had been Professor

of Pharmacology since [969 and a member of the

faculty of that Department since 1961.

Dr. Bianchi was born on April 9, [927, in

Newark, New Jersey. After receiving his diploma

at Columbia High School in 1945, he spent two

years in the Army Medical Corps as Technical Sgt.

Fourth Grade. He then attended Columbia

University, where he majored in chemistry and

obtained the B.A. degree in 1950. Like Dr.

Gruber, the first Chairman of the Pharmacology

Department at Jefferson, Bianchi earned his Ph.D.

in physiology. He pursued his graduate studies at

Rutgers University, supplementing his physiology

major with a biochemistry minor for the M.S.

degree in [953 and with a physical chemistry minor

for the Ph.D. degree in 1956. Dr. Bianchi then

spent several years at the National Institutes of

Health-two years as a Public Health Fellow and

one as a Visiting Scientist. Following that he was

Assistant Member of the Institute for Muscle

Disease in New York for one year. In 1961 Dr.

Bianchi became classified professionally as a

pharmacologist by becoming an Associate in the

Department of Pharmacology at the University of

Pennsylvania School of Medicine. There he

advanced to Professorship in 1969 and remained

until he came to Jefferson. The evolution of Dr.

Bianchi’s career from physiology to pharmacology

was the logical result of his investigations of the

effect of various drugs on the metabolism and

distribution of some of the important elements of

the body, notably calcium. His major field of

interest became classified and remained in

electrolyte pharmacology.

Throughout his career Dr. Bianchi has been

very active in the affairs of outside professional

organizations. He is a member of the American

Society for Pharmacology and Experimental

Therapeutics, the American Physiological Society,

the American Chemical Society, and the

International Society of Toxicology, to name

only a few. He served as President of both the

Philadelphia Physiological Society and the John

Morgan Society in the same year (1973-1974), and

of the Philadelphia Chapter of the Society for

Neuroscience (1979-1980). He gave much time

and valuable services as Field Editor for the

Journal of Pharmacology and Experimental

Therapeutics ([970-1979) and as a member of the

Pharmacology Section of the National Board of

Medical Examiners (1981-1985).

After Dr. Bianchi became Chairman no

immediate changes in the general structure and

activities of the Department took place. He

enlarged the Department and filled vacancies

occasioned by the retirement of some faculty

members. The didactic schedules and subject

matter offered to the medical and graduate

students underwent only minor annual changes.

Research activities were augmented by the

addition of Dr. Bianchi’s specialty in electrolyte

pharmacology and the appointments of new staff

members for investigations in that and related

flelds. Through the following decade there was a

marked change in the faculty structure of the

Department. The [975 Jefferson catalogue, for

example, listed 15 faculty appointments in

Pharmacology, of which eight were on a primary

full-time basis with offices and laboratories in the

Department. In 1985 there were 36 faculty

appointments of which eight were on a primary

full-time basis. The large increase in the total

number of faculty resulted from adjunct

appointments from outside organizations and from

secondary appointments of faculty members of the

Clinical Departments at Jefferson. This expansion

reflected a broadening of interests and interactions

on both the scientific and clinical fronts in clinical

pharmacology and clinical toxicology.

A notable addition to the faculty of the

Department in 1978 was Dr. Hyman Menduke

as Professor of Pharmacology

(Biostatistics). After receiving his Ph.D. in

Economic Statistics at the University of

Pennsylvania, Menduke came to Jefferson in 1953

as Assistant Professor of Biostatistics with no

official Departmental affiliation until 1963, when

he was appointed Professor of Preventive

Medicine (Biostatistics). When Dr. Menduke first

came to Jefferson he gave a ten-hour course in

biostatistics to the second-year medical students in

time provided during their pharmacology course.

Through the years his offerings expanded to a

12-hour course for freshman medical students and

introductory and advanced courses for graduate

students. An early and valuable contribution was a

series of individual conferences with graduate

students on the statistical planning of their

research problems and the later analysis of their



The interests and activities of the Department in

research in toxicology have been emphasized.

Toxicology continued as an important part of the

research program after Dr. Bianchi became

Chairman in 1976, although under his direction

the major emphasis in research became redirected

toward the general areas of cell pharmacology and


In accord with its continuing research and

teaching activities in toxicology, the Department

starting in 1977 organized a series of annual

workshops on Industrial Toxicology sponsored by

the College of Graduate Studies. These were

four-day symposia on important toxicologic

problems in industry and the general environment,

presented by toxicologically involved Jefferson

faculty and by invited experts from other

universities, industry, and government.

In 1979 the Department was awarded a training

grant in Industrial and Environmental Toxicology

by the National Institute of Environmental Health

Sciences. The purpose of this award was to

provide postdoctoral training in toxicology for

individuals who had previously received their

Ph.D. degrees in other sciences. Ten M.S. degrees

were subsequently awarded in this program

through the years from 1981 to 1986.

On December 14, 1978, a full day’s workshop

with outside invited experts was held to discuss

the formation of a Toxicology Center and the

establishment of a Chair in Toxicology-Pathology

to broaden the base of research and training in

toxicology at Jefferson. It was envisioned that the

Center would be an administrative Division within

the Department of Pharmacology, with research

participation from other basic science departments

and the Department of Medicine. Although funds

accumulated in support of a Toxicology Center,

disagreements developed relating to the

administrative base of the Center.


A few articles from Dr. Bianchi showing the diversity of his research interests including calcium mobilization, neurotoxicology, and cellular metabolism and physiology.

Muscle fatigue and the role of transverse tubules.

Bianchi CP, Narayan S.

Science. 1982 Jan 15;215(4530):295-6. No abstract available.


Effect of adenosine on oxygen uptake and electrolyte content of frog sartorius muscle.

Prosdocimi M, Bianchi CP.

J Pharmacol Exp Ther. 1981 Jul;218(1):92-6.


The effect of diazepam on tension and electrolyte distribution in frog muscle.

Degroof RC, Bianchi CP, Narayan S.

Eur J Pharmacol. 1980 Aug 29;66(2-3):193-9.


Steady state maintenance of electrolytes in the spinal cord of the frog.

Bianchi CP, Erulkar SD.

J Neurochem. 1979 Jun;32(6):1671-7. No abstract available.

An in-vitro model of anesthetic hypertonic hyperpyrexia, halothane–caffeine-induced muscle contractures: prevention of contracture by procainamide.

Strobel GE, Bianchi CP.

Anesthesiology. 1971 Nov;35(5):465-73. No abstract available.


The effects of psychoactive agents on calcium uptake by preparations of rat brain mitochondria.

Tjioe S, Haugaard N, Bianchi CP.

J Neurochem. 1971 Nov;18(11):2171-8. No abstract available.


The effect of veratridine on sodium-sensitive radiocalcium uptake in frog sartorius muscle.

Johnson P, Bianchi CP.

Eur J Pharmacol. 1971 Sep;16(1):90-9. No abstract available.


The function of ATP in Ca2+ uptake by rat brain mitochondria.

Tjioe S, Bianchi CP, Haugaard N.

Biochim Biophys Acta. 1970 Sep 1;216(2):270-3. No abstract availabl


The effects of pH gradients on the uptake and distribution of C14-procaine and lidocaine in intact and desheathed sciatic nerve trunks.

Strobel GE, Bianchi CP.

J Pharmacol Exp Ther. 1970 Mar;172(1):18-32. No abstract available



More articles by CP Bianchi  can be found at:[auth]

The following is one of the seminal books Dr. Bianchi authored:


Role of Calcium Channels of the Sarcolemma and the Sarcoplasmic Reticulum in Skeletal Muscle Functions


Advances in General and Cellular Pharmacology (1976)

Toshio Narahashi; Carmine Paul Bianchi

The author of the Advances in General and Cellular Pharmacology is Toshio Narahashi; Carmine Paul Bianchi – very good writer. You can download this e-book absolutely for free. This ebook’s ISBN number is 9781461582007. if you were searching for for free download of kindle books, google books, free pdf books, pdf ebooks, e-books, pdf files or pdf ebooks just stay here for a while, download what you wanted for free and enjoy!

Advances in General and Cellular Pharmacology – Toshio Narahashi; Carmine Paul Bianchi – PDF Free Download Ebook also for Kindle


Other articles in this series published on this site include:

Heroes in Medical Research: Dr. Robert Ting, Ph.D. and Retrovirus in AIDS and Cancer

Heroes in Medical Research: Barnett Rosenberg and the Discovery of Cisplatin

Volume Two: Interviews with Scientific Leaders



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Genetic Analysis of Atrial Fibrillation

Author and Curator: Larry H Bernstein, MD, FCAP  


Curator: Aviva-Lev Ari, PhD, RN

This article is a followup of the wonderful study of the effect of oxidation of a methionine residue in calcium dependent-calmodulin kinase Ox-CaMKII on stabilizing the atrial cardiomyocyte, giving protection from atrial fibrillation.  It is also not so distant from the work reviewed, mostly on the ventricular myocyte and the calcium signaling by initiation of the ryanodyne receptor (RyR2) in calcium sparks and the CaMKII d isoenzyme.

We refer to the following related articles published in pharmaceutical Intelligence:

Oxidized Calcium Calmodulin Kinase and Atrial Fibrillation
Author: Larry H. Bernstein, MD, FCAP and Curator: Aviva Lev-Ari, PhD, RN

Jmjd3 and Cardiovascular Differentiation of Embryonic Stem Cells

Author: Larry H. Bernstein, MD, FCAP and Curator: Aviva Lev-Ari, PhD, RN

Contributions to cardiomyocyte interactions and signaling
Author and Curator: Larry H Bernstein, MD, FCAP  and Curator: Aviva Lev-Ari, PhD, RN

Cardiac Contractility & Myocardium Performance: Therapeutic Implications for Ryanopathy (Calcium Release-related Contractile Dysfunction) and Catecholamine Responses
Editor: Justin Pearlman, MD, PhD, FACC, Author and Curator: Larry H Bernstein, MD, FCAP, and Article Curator: Aviva Lev-Ari, PhD, RN

Part I. Identification of Biomarkers that are Related to the Actin Cytoskeleton
Curator and Writer: Larry H Bernstein, MD, FCAP

Part II: Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility
Larry H. Bernstein, MD, FCAP, Stephen Williams, PhD and Aviva Lev-Ari, PhD, RN

Part IV: The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets
Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN

Part VI: Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD
Aviva Lev-Ari, PhD, RN

Part VII: Cardiac Contractility & Myocardium Performance: Ventricular Arrhythmias and Non-ischemic Heart Failure – Therapeutic Implications for Cardiomyocyte Ryanopathy (Calcium Release-related Contractile Dysfunction) and Catecholamine Responses
Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

Part VIII: Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and Cardiovascular Calcium Signaling Mechanism
Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

Part IX: Calcium-Channel Blockers, Calcium Release-related Contractile Dysfunction (Ryanopathy) and Calcium as Neurotransmitter Sensor
Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

Part X: Synaptotagmin functions as a Calcium Sensor: How Calcium Ions Regulate the fusion of vesicles with cell membranes during Neurotransmission
Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

The material presented is very focused, and cannot be found elsewhere in Pharmaceutical Intelligence with respedt to genetics and heart disease.  However, there are other articles that may be of interest to the reader.

Volume Three: Etiologies of Cardiovascular Diseases – Epigenetics, Genetics & Genomics

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

PART 3.  Determinants of Cardiovascular Diseases: Genetics, Heredity and Genomics Discoveries

3.2 Leading DIAGNOSES of Cardiovascular Diseases covered in Circulation: Cardiovascular Genetics, 3/2010 – 3/2013

The Diagnoses covered include the following – relevant to this discussion

  • MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis, diastolic dysfunction, and acute heart failure
  • Genomics of Ventricular arrhythmias, A-Fib, Right Ventricular Dysplasia, Cardiomyopathy
  • Heredity of Cardiovascular Disorders Inheritance

3.2.1: Heredity of Cardiovascular Disorders Inheritance

The implications of heredity extend beyond serving as a platform for genetic analysis, influencing diagnosis,

  1. prognostication, and
  2. treatment of both index cases and relatives, and
  3. enabling rational targeting of genotyping resources.

This review covers acquisition of a family history, evaluation of heritability and inheritance patterns, and the impact of inheritance on subsequent components of the clinical pathway.

SOURCE:   Circulation: Cardiovascular Genetics.2011; 4: 701-709.

3.2.2: Myocardial Damage MicroRNA in Serum as Biomarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis,  diastolic dysfunction, and acute heart failure

Increased MicroRNA-1 and MicroRNA-133a Levels in Serum of Patients With Cardiovascular Disease Indicate Myocardial Damage
Y Kuwabara, Koh Ono, T Horie, H Nishi, K Nagao, et al.
SOURCE:  Circulation: Cardiovascular Genetics. 2011; 4: 446-454 Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease

MF Corsten, R Dennert, S Jochems, T Kuznetsova, Y Devaux, et al.
SOURCE: Circulation: Cardiovascular Genetics. 2010; 3: 499-506. Large-Scale Candidate Gene Analysis in Whites and African Americans Identifies IL6R Polymorphism in Relation to Atrial Fibrillation

The National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource (CARe) Project
RB Schnabel, KF Kerr, SA Lubitz, EL Alkylbekova, et al.
SOURCE:  Circulation: Cardiovascular Genetics.2011; 4: 557-564

 Weighted Gene Coexpression Network Analysis of Human Left Atrial Tissue Identifies Gene Modules Associated With Atrial Fibrillation

N Tan, MK Chung, JD Smith, J Hsu, D Serre, DW Newton, L Castel, E Soltesz, G Pettersson, AM Gillinov, DR Van Wagoner and J Barnard
From the Cleveland Clinic Lerner College of Medicine (N.T.), Department of Cardiovascular Medicine (M.K.C., D.W.N.), and Department of Thoracic & Cardiovascular Surgery (E.S., G.P., A.M.G.); and Department of Cellular & Molecular Medicine (J.D.S., J.H.), Genomic Medicine Institute (D.S.), Department of Molecular Cardiology (L.C.), and Department of Quantitative Health Sciences (J.B.), Cleveland Clinic Lerner Research Institute, Cleveland, OH
Circ Cardiovasc Genet. 2013;6:362-371;   The online-only Data Supplement is available at

Background—Genetic mechanisms of atrial fibrillation (AF) remain incompletely understood. Previous differential expression studies in AF were limited by small sample size and provided limited understanding of global gene networks, prompting the need for larger-scale, network-based analyses.

Methods and Results—Left atrial tissues from Cleveland Clinic patients who underwent cardiac surgery were assayed using Illumina Human HT-12 mRNA microarrays. The data set included 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without coronary artery disease (n=64), coronary artery disease without MV disease (n=57), and lone AF (n=35). Weighted gene coexpression network analysis was performed in the MV group to detect modules of correlated genes. Module preservation was assessed in the other 2 groups. Module eigengenes were regressed on AF severity or atrial rhythm at surgery. Modules whose eigengenes correlated with either AF phenotype were analyzed for gene content. A total of 14 modules were detected in the MV group; all were preserved in the other 2 groups. One module (124 genes) was associated with AF severity and atrial rhythm across all groups. Its top hub gene, RCAN1, is implicated in calcineurin-dependent signaling and cardiac hypertrophy. Another module (679 genes) was associated with atrial rhythm in the MV and coronary artery disease groups. It was enriched with cell signaling genes and contained cardiovascular developmental genes including TBX5.

Conclusions—Our network-based approach found 2 modules strongly associated with AF. Further analysis of these modules may yield insight into AF pathogenesis by providing novel targets for functional studies. (Circ Cardiovasc Genet. 2013;6:362-371.)

Key Words: arrhythmias, cardiac • atrial fibrillation • bioinformatics • gene coexpression • gene regulatory networks • genetics • microarrays


trial fibrillation (AF) is the most common sustained car­diac arrhythmia, with a prevalence of ≈1% to 2% in the general population.1,2 Although AF may be an isolated con­dition (lone AF [LAF]), it often occurs concomitantly with other cardiovascular diseases, such as coronary artery disease (CAD) and valvular heart disease.1 In addition, stroke risk is increased 5-fold among patients with AF, and ischemic strokes attributed to AF are more likely to be fatal.1 Current antiarrhythmic drug therapies are limited in terms of efficacy and safety.1,3,4 Thus, there is a need to develop better risk pre­diction tools as well as mechanistically targeted therapies for AF. Such developments can only come about through a clearer understanding of its pathogenesis.

Family history is an established risk factor for AF. A Danish Twin Registry study estimated AF heritability at 62%, indicating a significant genetic component.5 Substantial progress has been made to elucidate this genetic basis. For example, genome-wide association studies (GWASs) have identified several susceptibil­ity loci and candidate genes linked with AF. Initial studies per­formed in European populations found 3 AF-associated genomic loci.6–9 Of these, the most significant single-nucleotide polymor-phisms (SNPs) mapped to an intergenic region of chromosome 4q25. The closest gene in this region, PITX2, is crucial in left-right asymmetrical development of the heart and thus seems promising as a major player in initiating AF.10,11 A large-scale GWAS meta-analysis discovered 6 additional susceptibility loci, implicating genes involved in cardiopulmonary development, ion transport, and cellular structural integrity.12

Differential expression studies have also provided insight into the pathogenesis of AF. A study by Barth et al13 found that about two-thirds of the genes expressed in the right atrial appendage were downregulated during permanent AF, and that many of these genes were involved in calcium-dependent signaling pathways. In addition, ventricular-predominant genes were upregulated in right atrial appendages of sub­jects with AF.13 Another study showed that inflammatory and transcription-related gene expression was increased in right atrial appendages of subjects with AF versus controls.14 These results highlight the adaptive responses to AF-induced stress and ischemia taking place within the atria.

Despite these advances, much remains to be discovered about the genetic mechanisms of AF. The AF-associated SNPs found thus far only explain a fraction of its heritability15; furthermore, the means by which the putative candidate genes cause AF have not been fully established.9,15,16 Additionally, previous dif­ferential expression studies in human tissue were limited to the right atrial appendage, had small sample sizes, and provided little understanding of global gene interactions.13,14 Weighted gene coexpression network analysis (WGCNA) is a technique to construct gene modules within a network based on correla­tions in gene expression (ie, coexpression).17,18 WGCNA has been used to study genetically complex diseases, such as meta­bolic syndrome,19 schizophrenia,20 and heart failure.21 Here, we obtained mRNA expression profiles from human left atrial appendage tissue and implemented WGCNA to identify gene modules associated with AF phenotypes.


Subject Recruitment

From 2001 to 2008, patients undergoing cardiac surgery at the Cleveland Clinic were prospectively screened and recruited. Informed consent for research use of discarded atrial tissues was ob­tained from each patient by a study coordinator during the presur­gical visit. Demographic and clinical data were obtained from the Cardiovascular Surgery Information Registry and by chart review. Use of human atrial tissues was approved by the Institutional Review Board of the Cleveland Clinic.

Table S1: Clinical definitions of cardiovascular phenotype groups

Criterion Type Mitral Valve (MV) Disease Coronary Artery Disease (CAD) Lone Atrial Fibrillation (LAF)
Inclusion Criteria Surgical indication – Surgical indication – History of atrial fibrillation
mitral valve repair or replacement coronary artery bypass graft
Surgical indication
– MAZE procedure
Preserved ejection fraction (≥50%)
Exclusion Criteria Significant coronary artery disease: Significant mitral valve disease: Significant
coronary artery
– Significant (≥50%) stenosis – Documented echocardiography disease:
 in at least finding of – Significant
one coronary artery  mitral regurgitation (≥3) or (≥50%) stenosis in
via cardiac catheterization mitral stenosis at least one
– History of revascularization – History of mitral valve coronary artery via
(percutaneous coronary intervention or coronary artery bypass graft surgery)  repair or replacement cardiac catheterization
– History of revascularization
(percutaneous coronary intervention or coronary artery bypass graft surgery)
Significant valvular heart disease:
-Documented echocardiography finding of valvular regurgitation (≥3) or stenosis
-History of valve repair or replacement

RNA Microarray Isolation and Profiling

Left atria appendage specimens were dissected during cardiac surgery and stored frozen at −80°C. Total RNA was extracted using the Trizol technique. RNA samples were processed by the Cleveland Clinic Genomics Core. For each sample, 250-ng RNA was reverse tran­scribed into cRNA and biotin-UTP labeled using the TotalPrep RNA Amplification Kit (Ambion, Austin, TX). cRNA was quantified using a Nanodrop spectrophotometer, and cRNA size distribution was as­sessed on a 1% agarose gel. cRNA was hybridized to Illumina Human HT-12 Expression BeadChip arrays (v.3). Arrays were scanned using a BeadArray reader.

Expression Data Preprocessing

Raw expression data were extracted using the beadarray package in R, and bead-level data were averaged after log base-2 transformation. Background correction was performed by fitting a normal-gamma deconvolution model using the NormalGamma R package.22 Quantile normalization and batch effect adjustment with the ComBat method were performed using R.23 Probes that were not detected (at a P<0.05 threshold) in all samples as well as probes with relatively lower vari­ances (interquartile range ≤log2[1.2]) were excluded.

The WGCNA approach requires that genes be represented as sin­gular nodes in such a network. However, a small proportion of the genes in our data have multiple probe mappings. To facilitate the representation of singular genes within the network, a probe must be selected to represent its associated gene. Hence, for genes that mapped to multiple probes, the probe with the highest mean expres­sion level was selected for analysis (which often selects the splice isoform with the highest expression and signal-to-noise ratio), result­ing in a total of 6168 genes.

Defining Training and Test Sets

Currently, no large external mRNA microarray data from human left atrial tissues are publicly available. To facilitate internal validation of results, we divided our data set into 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without CAD (MV group; n=64), CAD without MV disease (CAD group; n=57), and LAF (LAF group; n=35). LAF was defined as the presence of AF without concomitant structural heart disease, according to the guidelines set by the European Society of Cardiology.1 The MV group, which was the largest and had the most power for detecting significant modules, served as the training set for module derivation, whereas the other 2 groups were designated test sets for module reproducibility. To mini­mize the effect of population stratification, the data set was limited to white subjects. Differences in clinical characteristics among the groups were assessed using Kruskal–Wallis rank-sum tests for con­tinuous variables and Pearson x2 test for categorical variables.

Weight Gene Coexpression Network Analysis

WGCNA is a systems-biology method to identify and characterize gene modules whose members share strong coexpression. We applied previously validated methodology in this analysis.17 Briefly, pair-wise gene (Pearson) correlations were calculated using the MV group data set. A weighted adjacency matrix was then constructed. I is a soft-thresholding pa­rameter that provides emphasis on stronger correlations over weaker and less meaningful ones while preserving the continuous nature of gene–gene relationships. I=3 was selected in this analysis based on the criterion outlined by Zhang and Horvath17 (see the online-only Data Supplement).

Next, the topological overlap–based dissimilarity matrix was com­puted from the weighted adjacency matrix. The topological overlap, developed by Ravasz et al,24 reflects the relative interconnectedness (ie, shared neighbors) between 2 genes.17 Hence, construction of the net­work dendrogram based on this dissimilarity measure allows for the identification of gene modules whose members share strong intercon-nectivity patterns. The WGCNA cutreeDynamic R function was used to identify a suitable cut height for module identification via an adap­tive cut height selection approach.18 Gene modules, defined as branches of the network dendrogram, were assigned colors for visualization.

Network Preservation Analysis

Module preservation between the MV and CAD groups as well as the MV and LAF groups was assessed using network preservation statis­tics as described in Langfelder et al.25 Module density–based statistics (to assess whether genes in each module remain highly connected in the test set) and connectivity-based statistics (to assess whether con­nectivity patterns between genes in the test set remain similar com­pared with the training set) were considered in this analysis.25 In each comparison, a Z statistic representing a weighted summary of module density and connectivity measures was computed for every module (Zsummary). The Zsummary score was used to evaluate module preserva­tion, with values ≥8 indicating strong preservation, as proposed by Langfelder et al.25 The WGCNA R function network preservation was used to implement this analysis.25

Table S2: Network preservation analysis between the MV and CAD groups – size and Zsummary scores of gene modules detected.

Module Module Size


Black 275 15.52
Blue 964 44.79
Brown 817 12.80
Cyan 119 13.42
Green 349 14.27
Green-Yellow 215 19.31
Magenta 239 15.38
Midnight-Blue 83 15.92
Pink 252 23.31
Purple 224 16.96
Red 278 17.30
Salmon 124 13.84
Tan 679 28.48
Turquoise 1512 44.03

Table S3: Network preservation analysis between the MV and LAF groups – size and Zsummary scores of gene modules detected

Module Module Size ZSummary
Black 275 13.14
Blue 964 39.26
Brown 817 14.98
Cyan 119 11.46
Green 349 14.91
Green-Yellow 215 20.99
Magenta 239 18.58
Midnight-Blue 83 13.87
Pink 252 19.10
Purple 224 8.80
Red 278 16.62
Salmon 124 11.57
Tan 679 28.61
Turquoise 1512 42.07

Clinical Significance of Preserved Modules

Principal component analysis of the expression data for each gene module was performed. The first principal component of each mod­ule, designated the eigengene, was identified for the 3 cardiovascular disease groups; this served as a summary expression measure that explained the largest proportion of the variance of the module.26 Multivariate linear regression was performed with the module ei-gengenes as the outcome variables and AF severity (no AF, parox­ysmal AF, persistent AF, permanent AF) as the predictor of interest (adjusting for age and sex). A similar regression analysis was per­formed with atrial rhythm at surgery (no AF history, AF history in sinus rhythm, AF history in AF rhythm) as the predictor of interest. The false discovery rate method was used to adjust for multiple com­parisons. Modules whose eigengenes associated with AF severity and atrial rhythm were identified for further analysis.

In addition, hierarchical clustering of module eigengenes and se­lected clinical traits (age, sex, hypertension, cholesterol, left atrial size, AF state, and atrial rhythm) was used to identify additional module–trait associations. Clusters of eigengenes/traits were detected based on a dissimilarity measure D, as given by

D=1−cor(Vi,Vj),i≠j                                                                              (3)

where V=the eigengene or clinical trait.

Enrichment Analysis

Gene modules significantly associated with AF severity and atrial rhythm were submitted to Ingenuity Pathway Analysis (IPA) to determine enrichment for functional/disease categories. IPA is an application of gene set over-representation analysis; for each dis-ease/functional category annotation, a P value is calculated (using Fisher exact test) by comparing the number of genes from the mod­ule of interest that participate in the said category against the total number of participating genes in the background set.27 All 6168 genes in the current data set served as the background set for the enrichment analysis.

Hub Gene Analysis

Hub genes are defined as genes that have high intramodular connectivity17,20

Alternatively, they may also be defined as genes with high module membership21,25

Both definitions were used to identify the hub genes of modules associated with AF phenotype.

To confirm that the hub genes identified were themselves associ­ated with AF phenotype, the expression data of the top 10 hub genes (by intramodular connectivity) were regressed on atrial rhythm (ad­justing for age and sex). In addition, eigengenes of AF-associated modules were regressed on their respective (top 10) hub gene expres­sion profiles, and the model R2 indices were computed.

Membership of AF-Associated Candidate Genes From Previous Studies

Previous GWAS studies identified multiple AF-associated SNPs.8,9,12,15,28 We selected candidate genes closest to or containing these SNPs and identified their module locations as well as their clos­est within-module partners (absolute Pearson correlations).

Sensitivity Analysis of Soft-Thresholding Parameter

To verify that the key results obtained from the above analysis were robust with respect to the chosen soft-thresholding parameter (I=3), we repeated the module identification process using I=5. The eigen-genes of the detected modules were computed and regressed on atrial rhythm (adjusting for age and sex). Modules significantly associated with atrial rhythm in ≥2 groups of data set were compared with the AF phenotype–associated modules from the original analysis.


Subject Characteristics

Table 1 describes the clinical characteristics of the cardiac surgery patients who were recruited for the study. Subjects in the LAF group were generally younger and less likely to be a current smoker (P=2.0×10−4 and 0.032, respectively). Subjects in the MV group had lower body mass indices (P=2.7×10−6), and a larger proportion had paroxysmal AF compared with the other 2 groups (P=0.033).

Table 1. Clinical Characteristics of Study Subjects


MV Group (n=64)

CAD Group (n=57)

LAF Group (n=35)

P Value*

Age, median y (1st–3rd quartiles)

60 (51.75–67.25)

64 (58.00–70.00)

56 (45.50–60.50)


Sex, female (%) 19 (29.7) 6 (10.5)

7 (20.0)


BMI, median (1st–3rd quartiles)

25.97 (24.27–28.66)

29.01 (27.06–32.11)

29.71 (26.72–35.10)


Current smoker (%) 29 (45.3) 35 (61.4)

12 (21.1)


Hypertension (%) 21 (32.8) 39 (68.4)

16 (45.7)


AF severity (%)
No AF 7 (10.9) 7 (12.3)

0 (0.0)


Paroxysmal 19 (29.7) 10 (17.5)

7 (20.0)

Persistent 30 (46.9) 26 (45.6)

15 (42.9)

Permanent 8 (12.5) 14 (24.6)

13 (37.1)

Atrial rhythm at surgery (%)
No AF history in sinus rhythm 7 (10.9) 7 (12.3)

0 (0)


AF history in sinus rhythm 28 (43.8) 16 (28.1)

11 (31.4)

AF History in AF rhythm 29 (45.3) 34 (59.6)

24 (68.6)

Gene Coexpression Network Construction and Module Identificationsee document at

A total of 14 modules were detected using the MV group data set (Figure 1), with module sizes ranging from 83 genes to 1512 genes; 38 genes did not share similar coexpression with the other genes in the network and were therefore not included in any of the identified modules

Figure 1. Network dendrogram (top) and colors of identified modules (bottom).

Figure 1. Network dendrogram (top) and colors of identified modules (bottom). The dendrogram was constructed using the topological overlap matrix as the similarity measure. Modules corresponded to branches of the dendrogram and were assigned colors for visualization.

Network Preservation Analysis Revealed Strong Preservation of All Modules Between the Training and Test Sets

All 14 modules showed strong preservation across the CAD and LAF groups in both comparisons, with Z [summary]  scores of >10 in most modules (Figure 2). No major deviations in the Z [summary] score distributions for the 2 comparisons were noted, indicating that modules were preserved to a similar extent across the 2 groups

Figure 2. Preservation of mod-ules between mitral valve (MV) and coronary artery disease

Figure 2. Preservation of mod­ules between mitral valve (MV) and coronary artery disease (CAD) groups (left), and MV and lone atrial fibrillation (LAF) groups (right). A Zsummary sta­tistic was computed for each module as an overall measure of its preservation relating to density and connectivity. All modules showed strong pres­ervation in both comparisons with Zsummary scores >8 (red dot­ted line).

Regression Analysis of Module Eigengene Profiles Identified 2 Modules Associated With AF Severity and Atrial Rhythm

Table IV in the online-only Data Supplement summarizes the proportion of variance explained by the first 3 principal components for each module. On average, the first principal component (ie, the eigengene) explained ≈18% of the total variance of its associated module. For each group, the mod­ule eigengenes were extracted and regressed on AF severity (with age and sex as covariates). The salmon module (124 genes) eigengene was strongly associated with AF severity in the MV and CAD groups (P=1.7×10−6 and 5.2×10−4, respec­tively); this association was less significant in the LAF group (P=9.0×10−2). Eigengene levels increased with worsening AF severity across all 3 groups, with the greatest stepwise change taking place between the paroxysmal AF and per­sistent AF categories (Figure 3A). When the module eigen-genes were regressed on atrial rhythm, the salmon module eigengene showed significant association in all groups (MV: P=1.1×10−14; CAD: P=1.36×10−6; LAF: P=2.1×10−4). Eigen-gene levels were higher in the AF history in AF rhythm cat­egory (Figure 3B).

Table S4: Proportion of variance explained by the principal components for each module.












20.5% 22.2% 20.1% 21.8% 21.4% 22.8% 19.6%


4.1% 3.6% 4.8% 5.7% 4.5% 5.9% 3.9%


3.4% 3.1% 3.8% 4.4% 3.9% 3.7% 3.7%



12.5% 18.6% 7.1% 16.8% 12.2% 20.3% 12.8%


6.0% 5.5% 5.0% 7.0% 5.5% 6.1% 6.4%


4.9% 4.1% 4.4% 6.5% 4.8% 4.4% 4.8%



14.0% 16.6% 11.7% 14.3% 14.7% 20.8% 20.2%


8.9% 8.5% 7.6% 9.3% 7.3% 11.1% 6.9%


6.5% 6.3% 5.5% 8.2% 6.1% 5.3% 6.2%



Midnight- Blue









28.5% 22.6% 18.7% 20.5% 22.3% 19.0% 25.8%


4.6% 6.0% 4.7% 4.1% 6.9% 4.0% 3.5%


4.2% 4.2% 4.2% 3.5% 4.0% 3.6% 3.3%



23.4% 17.1% 15.5% 15.0% 18.0% 14.6% 18.2%


7.4% 8.6% 6.0% 6.4% 7.2% 5.8% 6.6%


5.1% 5.4% 5.3% 5.4% 6.2% 5.1% 4.5%



23.5% 18.4% 12.0% 15.9% 16.9% 13.7% 16.5%


7.9% 8.5% 9.8% 9.4% 9.5% 9.1% 9.6%


6.7% 7.0% 6.6% 6.0% 6.9% 6.8% 6.3%

Figure 3. Boxplots of salmon module eigengene expression levels with respect to atrial fibrillation (AF) severity (A) and atrial rhythm (B).

Figure 3. Boxplots of salmon module eigengene expression levels with respect to atrial fibrillation (AF) severity (A) and atrial rhythm (B).
A, Eigengene expression correlated positively with AF severity, with the largest stepwise increase between the paroxysmal AF and per­manent AF categories. B, Eigengene expression was highest in the AF history in AF rhythm category in all 3 groups. CAD indicates coro­nary artery disease; LAF, lone AF; and MV, mitral valve.

The regression analysis also revealed statistically significant associations between the tan module (679 genes) eigengene and atrial rhythm in the MV and CAD groups (P=5.8×10−4 and 3.4×10−2, respectively). Eigengene levels were lower in the AF history in AF rhythm category compared with the AF history in sinus rhythm category (Figure 4); this trend was also observed in the LAF group, albeit with weaker statistical evidence (P=0.15).

Figure 4. Boxplots of tan module eigengene expression levels with respect to atrial rhythm.

Figure 4. Boxplots of tan module eigengene expression levels with respect to atrial rhythm.
Eigengene expression levels were lower in the atrial fibrillation (AF) history in AF rhythm category compared with the AF history in sinus rhythm category. CAD indicates coronary artery disease; LAF, lone AF; and MV, mitral valve

Hierarchical Clustering of Eigengene Profiles With Clinical Traits

Hierarchical clustering was performed to identify relation­ships between gene modules and selected clinical traits. The salmon module clustered with AF severity and atrial rhythm; in addition, left atrial size was found in the same cluster, sug­gesting a possible relationship between salmon module gene expression and atrial remodeling (Figure 5A). Although the tan module was in a separate cluster from the salmon module, it was negatively correlated with both atrial rhythm and AF severity (Figure 5B).

Figure 5. Dendrogram (A) and correlation heatmap (B) of module eigengenes and clinical traits.

Figure 5. Dendrogram (A) and correlation heatmap (B) of module eigengenes and clinical traits

A, The salmon module eigengene but not the tan module eigengene clustered with atrial fibrillation (AF) severity, atrial rhythm, and left atrial size. B, AF severity and atrial rhythm at surgery correlated positively with the salmon module eigengene and negatively with the tan module eigengene. Arhythm indicates atrial rhythm at surgery; Chol, cholesterol; HTN, hypertension; and LASize, left atrial size.

IPA Enrichment Analysis of Salmon and Tan Modules

The salmon module was enriched in genes involved in cardio­vascular function and development (smallest P=4.4×10−4) and organ morphology (smallest P=4.4×10−4). In addition, the top disease categories identified included endocrine system disor­ders (smallest P=4.4×10−4) and cardiovascular disease (small­est P=2.59×10−3).

The tan module was enriched in genes involved in cell-to-cell signaling and interaction (smallest P=8.9×10−4) and cell death and survival (smallest P=1.5×10−3). Enriched disease categories included cancer (smallest P=2.2×10−4) and cardio­vascular disease (smallest P=4.5×10−4).

see document at

Hub Gene Analysis of Salmon and Tan Modules

We identified hub genes in the 2 modules based on intramod-ular connectivity and module membership. For the salmon module, the gene RCAN1 exhibited the highest intramodular connectivity and module membership. The top 10 hub genes (by intramodular connectivity) were significantly associated with atrial rhythm, with false discovery rate–adjusted P values ranging from 1.5×10−5 to 4.2×10−12. These hub genes accounted for 95% of the variation in the salmon module eigengene.

In the tan module, the top hub gene was CPEB3. The top 10 hub genes (by intramodular connectivity) correlated with atrial rhythm as well, although the statistical associations in the lower-ranked hub genes were relatively weaker (false discovery rate–adjusted P values ranging from 1.1×10−1 to 3.4×10−4). These hub genes explained 94% of the total varia­tion in the tan module eigengene.

The names and connectivity measures of the hub genes found in both modules are presented in Table 2.

Table 2. Top 10 Hub Genes in the Salmon (Left) and Tan (Right) Modules as Defined by Intramodular Connectivity and Module Membership

Salmon Module

Tan Module









RCAN1 8.2






DNAJA4 7.7






PDE8B 7.7












PTPN4 6.7






SORBS2 6.0






ADCY6 5.7






FHL2 5.7






BVES 5.4






TMEM173 5.3







A visualiza­tion of the salmon module is shown using the Cytoscape tool (Figure 6). A full list of the genes in the salmon and tan mod­ules is provided in the online-only Data Supplement.

Figure 6. Cytoscape visualization of genes in the salmon module.
Nodes representing genes with high intramodu-lar connectivities, such as RCAN1 and DNAJA4, appear larger in the network. Strong connections are visualized with darker lines, whereas weak connections appear more translucent

Figure 6. Cytoscape visualization of genes in the salmon module.

Membership of AF-Associated Candidate Genes From Previous Studies

The tan module contained MYOZ1, which was identified as a candidate gene from the recent AF meta-analysis. PITX2 was located in the green module (n=349), and ZFHX3 was located in the turquoise module (n=1512). The locations of other can­didate genes (and their closest partners) are reported in the online-only Data Supplement.

Sensitivity Analysis of Key Results

We repeated the WGCNA module identification approach using a different soft-thresholding parameter (β=5). One mod­ule (n=121) was found to be strongly associated with atrial rhythm at surgery across all 3 groups of data set, whereas another module (n=244) was associated with atrial rhythm at surgery in the MV and CAD groups. The first module over­lapped significantly with the salmon module in terms of gene membership, whereas most of the second modules’ genes were contained within the tan module. The top hub genes found in the salmon and tan modules remained present and highly connected in the 2 new modules identified with the dif­ferent soft-thresholding parameter.


To our knowledge, our study is the first implementation of an unbiased, network-based analysis in a large sample of human left atrial appendage gene expression profiles. We found 2 modules associated with AF severity and atrial rhythm in 2 to 3 of our cardiovascular comorbidity groups. Functional analy­ses revealed significant enrichment of cardiovascular-related categories for both modules. In addition, several of the hub genes identified are implicated in cardiovascular disease and may play a role in AF initiation and progression.

In our study, WGCNA was used to construct modules based on gene coexpression, thereby reducing the net-work’s dimensionality to a smaller set of elements.17,21 Relating modulewise changes to phenotypic traits allowed statistically significant associations to be detected at a lower false discovery rate compared with traditional differential expression studies. Furthermore, shared functions and path­ways among genes in the modules could be inferred via enrichment analyses.

We divided our data set into 3 groups to verify the repro­ducibility of the modules identified by WGCNA; 14 modules were identified in the MV group in our gene network. All were strongly preserved in the CAD and LAF groups, suggesting that gene coexpression patterns are robust and reproducible despite differences in cardiovascular comorbidities.

The use of module eigengene profiles as representative summary measures has been validated in a number of studies.20,26 Additionally, we found that the eigengenes accounted for a significant proportion (average 18%) of gene expression variability in their respective modules. Regression analysis of the module eigengenes found 2 modules associated with AF severity and atrial rhythm in ≥2 groups of data set. The association between the salmon module eigengene and AF severity was statistically weaker in the LAF group (adjusted P=9.0×10−2). This was probably because of its significantly smaller sample size compared with the MV and CAD groups. Despite this weaker association, the relationship between the salmon module eigengene and AF severity remained consistent among the 3 groups (Figure 3A). Similarly, the lack of statistical significance for the association between the tan module eigengene and atrial rhythm at surgery in the LAF group was likely driven by the smaller sample size and (by definition) lack of samples in the no AF category.

A major part of our analysis focused on the identifica­tion of module hub genes. Hubs are connected with a large number of nodes; disruption of hubs therefore leads to wide­spread changes within the network. This concept has powerful applications in the study of biology, genetics, and disease.29,30 Although mutations of peripheral genes can certainly lead to disease, gene network changes are more likely to be motivated by changes in hub genes, making them more biologically inter­esting targets for further study.17,29,31 Indeed,

  • the hub genes of the salmon and tan modules accounted for the vast majority of the variation in their respective module eigengenes, signaling their importance in driving gene module behavior.

The hub genes identified in the salmon and tan modules were significantly associated with AF phenotype overall. It was noted that this association was statistically weaker for the lower-ranked hub genes in the tan module. This highlights an important aspect and strength of WGCNA—to be able to capture module-wide changes with respect to disease despite potentially weaker associations among individual genes.

The implementation of WGCNA necessitated the selection of a soft-thresholding parameter 13. Unlike hard-thresholding (where gene correlations below a certain value are shrunk to zero), the soft-thresholding approach gives greater weight to stronger correlations while maintaining the continuous nature of gene–gene relationships. We selected a 13 value of 3 based on the criteria outlined by Zhang and Horvath.17 His team and other investigators have demonstrated that module identifica­tion is robust with respect to the 13 parameter.17,19–21 In our data, we were also able to reproduce the key findings reported with a different, larger 13 value, thereby verifying the stability of our results relating to 13.

The salmon module (124 genes) was associated with both AF phenotypes; furthermore, IPA analysis of its gene con­tents suggested enrichment in cardiovascular development as well as disease. Its eigengene increased with worsening AF severity, with the largest stepwise change occurring between the paroxysmal AF and persistent AF categories (Figure 3). Hence,

  • the gene expression changes within the salmon mod­ule may reflect the later stages of AF pathophysiology.

The top hub gene of the salmon module was RCAN1 (reg­ulator of calcineurin 1). Calcineurin is a cytoplasmic Ca2+/ calmodulin-dependent protein phosphatase that stimulates cardiac hypertrophy via its interactions with NFAT and L-type Ca2+ channels.32,33 RCAN1 is known to inhibit calcineurin and its associated pathways.32,34 However, some data suggest that RCAN1 may instead function as a calcineurin activator when highly expressed and consequently potentiate hypertrophic signaling.35 Thus,

  • perturbations in RCAN1 levels (attribut­able to genetic variants or mutations) may cause an aberrant switching in function, which in turn triggers atrial remodeling and arrhythmogenesis.

Other hub genes found in the salmon module are also involved in cardiovascular development and function and may be potential targets for further study.

  • DNAJA4 (DnaJ homolog, subfamily A, member 4) regulates the trafficking and matu­ration of KCNH2 potassium channels, which have a promi­nent role in cardiac repolarization and are implicated in the long-QT syndromes.36

FHL2 (four-and-a-half LIM domain protein 2) interacts with numerous cellular components, including

  1. actin cytoskeleton,
  2. transcription machinery, and
  3. ion channels.37

FHL2 was shown to enhance the hypertrophic effects of isoproterenol, indicating that

  • FHL2 may modulate the effect of environmental stress on cardiomyocyte growth.38
  • FHL2 also interacts with several potassium channels in the heart, such as KCNQ1, KCNE1, and KCNA5.37,39

Additionally, blood vessel epicardial substance (BVES) and other members of its family were shown to be highly expressed in cardiac pacemaker cells. BVES knockout mice exhibited sinus nodal dysfunction, suggesting that BVES regulates the development of the cardiac pacemaking and conduction system40 and may therefore be involved in the early phase of AF development.

The tan module (679 genes) eigengene was negatively correlated with atrial rhythm in the MV and CAD groups (Figure 4); this may indicate a general decrease in gene expres­sion of its members in fibrillating atrial tissue. IPA analysis revealed enrichment in genes involved in cell signaling as well as apoptosis. The top-ranked hub gene, cytoplasmic polyade-nylation element binding protein 3 (CPEB3), regulates mRNA translation and has been associated with synaptic plasticity and memory formation.41 The role of CPEB3 in the heart is currently unknown, so further exploration via animal model studies may be warranted.

Natriuretic peptide-precursor B (NPPB), another highly interconnected hub gene, produces a precursor peptide of brain natriuretic peptide, which

  • regulates blood pressure through natriuresis and vasodilation.42

(NPPB) gene variants have been linked with diabetes mellitus, although associations with cardiac phenotypes are less clear.42 TBX5 and GATA4, which play important roles in the embryonic heart development,43 were members of the tan module. Although not hub genes, they may also contribute toward developmental sus­ceptibility of AF. In addition, TBX5 was previously reported to be near an SNP associated with PR interval and AF in separate large-scale GWAS studies.12,28 MYOZ1, another candidate gene identified in the recent AF GWAS meta-analysis, was found to be a member as well; it associates with proteins found in the Z-disc of skeletal and cardiac muscle and may suppress calcineurin-dependent hypertrophic signaling.12

Some, but not all, of the candidate genes found in previous GWAS studies were located in the AF-associated modules. One possible explanation for this could be the difference in sample sizes. The meta-analysis involved thousands of indi­viduals, whereas the current study had <100 in each group of data set, which limited the power to detect significant differ­ences between levels of AF phenotype even with the module-wise approach. Additionally, transcription factors like PITX2 are most highly expressed during the fetal phase of develop­ment. Perturbations in these genes (attributable to genetic variants or mutations) may therefore initiate the development of AF at this stage and play no significant role in adults (when we obtained their tissue samples).

Limitations in Study

We noted several limitations in this study. First, no human left atrial mRNA data set of adequate size currently exists publicly. Hence, we were unable to validate our results with an external, independent data set. However, the network pres­ervation assessment performed within our data set showed strong preservation in all modules, indicating that our findings are robust and reproducible.

Although the module eigengenes captured a significant pro­portion of module variance, a large fraction of variability did remain unaccounted for, which may limit their use as repre­sentative summary measures.

We extracted RNA from human left atrial appendage tis­sue, which consists primarily of cardiomyocytes and fibro­blasts. Atrial fibrosis is known to occur with AF-associated remodeling.44 As such, the cardiomyocyte to fibroblast ratio is likely to change with different levels of AF severity, which in turn influences the amount of RNA extracted from each cell type. Hence, true differences in gene expression (and coexpression) within cardiomyocytes may be confounded by changes in cellular composition attributable to atrial remod­eling. Also, there may be significant regional heterogeneity in the left atrium with respect to structure, cellular composi­tion, and gene expression,45 which may limit the generaliz-ability of our results to other parts of the left atrium.

All subjects in the study were whites to minimize the effects of population stratification. However, it is recognized that the genetic basis of AF may differ among ethnic groups.9 Thus, our results may not be generalizable to other ethnicities.

Finally, it is possible for genes to be involved in multiple processes and functions that require different sets of genes. However, WGCNA does not allow for overlapping modules to be formed. Thus,

  • this limits the method’s ability to character­ize such gene interactions.


In summary, we constructed a weighted gene coexpression network based on RNA expression data from the largest collection of human left atrial appendage tissue specimens to date. We identified 2 gene modules significantly associated with AF severity or atrial rhythm at surgery. Hub genes within these modules may be involved in the initiation or progression of AF and may therefore be candidates for functional stud­ies.


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10. Clauss S, Kääb S. Is Pitx2 growing up? Circ Cardiovasc Genet. 2011;4:105–107.

11. Kirchhof P, Kahr PC, Kaese S, Piccini I, Vokshi I, Scheld HH, et al. PITX2c is expressed in the adult left atrium, and reducing Pitx2c expres­sion promotes atrial fibrillation inducibility and complex changes in gene expression. Circ Cardiovasc Genet. 2011;4:123–133.

12. Ellinor PT, Lunetta KL, Albert CM, Glazer NL, Ritchie MD, Smith AV, et al. Meta-analysis identifies six new susceptibility loci for atrial fibrillation. Nat Genet. 2012;44:670–675.

13. Barth AS, Merk S, Arnoldi E, Zwermann L, Kloos P, Gebauer M, et al. Reprogramming of the human atrial transcriptome in permanent atrial fi­brillation: expression of a ventricular-like genomic signature. Circ Res. 2005;96:1022–1029.

Continues to 45.  see


Atrial fibrillation is the most common sustained cardiac arrhythmias in the United States. The genetic and molecular mecha­nisms governing its initiation and progression are complex, and our understanding of these mechanisms remains incomplete despite recent advances via genome-wide association studies, animal model experiments, and differential expression studies. In this study, we used weighted gene coexpression network analysis to identify gene modules significantly associated with atrial fibrillation in a large sample of human left atrial appendage tissues. We further identified highly interconnected genes (ie, hub genes) within these gene modules that may be novel candidates for functional studies. The discovery of the atrial fibrillation-associated gene modules and their corresponding hub genes provide novel insight into the gene network changes that occur with atrial fibrillation, and closer study of these findings can lead to more effective targeted therapies for disease management.

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Heart, Vascular Smooth Muscle, Excitation-Contraction Coupling (E-CC), Cytoskeleton, Cellular Dynamics and Ca2 Signaling

Heart, Vascular Smooth Muscle, Excitation-Contraction Coupling (E-CC), Cytoskeleton, Cellular Dynamics and Ca2 Signaling

Author and Curator: Larry H Bernstein, MD, FCAP

Author and Cardiovascular Three-volume Series, Editor: Justin Pearlman, MD, PhD, FACC, and

Curator: Aviva Lev-Ari, PhD, RN


AP, action potential; ARVD2, arrhythmogenic right ventricular cardiomyopathy type 2; CaMKII, Ca2+/calmodulim-dependent protein kinase II; CICR, Ca2+ induced Ca2+ release;CM, calmodulin; CPVT, catecholaminergic polymorphic ventricular tachycardia;  ECC, excitation–contraction coupling; FKBP12/12.6, FK506 binding protein; HF, heart failure; LCC, L-type Ca2+ channel;  P-1 or P-2, phosphatase inhibitor type-1 or type-2; PKA, protein kinase A; PLB, phosphoplamban; PP1, protein phosphatase 1; PP2A, protein phosphatase 2A; RyR1/2, ryanodine receptor type-1/type-2; SCD, sudden cardiac death; SERCA, sarcoplasmic reticulum Ca2+ ATPase; SL, sarcolemma; SR, sarcoplasmic reticulum.

This is Part V of a series on the cytoskeleton and structural shared thematics in cellular movement and cellular dynamics.

The Series consists of the following articles:

Part I: Identification of Biomarkers that are Related to the Actin Cytoskeleton

Larry H Bernstein, MD, FCAP


Part II: Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

Larry H. Bernstein, MD, FCAP, Stephen Williams, PhD and Aviva Lev-Ari, PhD, RN


Part III: Renal Distal Tubular Ca2+ Exchange Mechanism in Health and Disease

Larry H. Bernstein, MD, FCAP, Stephen J. Williams, PhD
 and Aviva Lev-Ari, PhD, RN


Part IV: The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets


Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN


Part V: Heart, Vascular Smooth Muscle, Excitation-Contraction Coupling (E-CC), Cytoskeleton, Cellular Dynamics and Ca2 Signaling

Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN


Part VI: Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD

Aviva Lev-Ari, PhD, RN


Part VII: Cardiac Contractility & Myocardium Performance: Ventricular Arrhythmias and Non-ischemic Heart Failure – Therapeutic Implications for Cardiomyocyte Ryanopathy (Calcium Release-related Contractile Dysfunction) and Catecholamine Responses

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

In the first part, we discussed common MOTIFs across cell-types that are essential for cell division, embryogenesis, cancer metastasis, osteogenesis, musculoskeletal function, vascular compliance, and cardiac contractility.   This second article concentrates on specific functionalities for cardiac contractility based on Ca++ signaling in excitation-contraction coupling.  The modifications discussed apply specifically to cardiac muscle and not to skeletal muscle.  Considering the observations described might raise additional questions specifically address to the unique requirements of smooth muscle, abundant in the GI tract and responsible for motility in organ function, and in blood vessel compliance or rigidity. Due to the distinctly different aspects of the cardiac contractility and contraction force, and the interactions with potential pharmaceutical targets, there are two separate articles on calcium signaling and cardiac arrhythmias or heart failure (Part 2 and Part 3).  Part 2 focuses on the RYANODINE role in cardiac Ca(2+) signaling and its effect in heart failure.  Part 3 takes up other aspects of heart failure and calcium signaling with respect to phosporylation/dephosphorylation. I add a single review and classification of genetic cardiac disorders of the same cardiac Ca(2+) signaling and the initiation and force of contraction. Keep in mind that the heart is a syncytium, and this makes a huge difference compared with skeletal muscle dynamics. In Part 1 there was some discussion of the importance of Ca2+ signaling on innate immune system, and the immunology will be further expanded in a fourth of the series.


This second article on the cardiomyocyte and the Ca(2+) cycling between the sarcomere and the cytoplasm, takes a little distance from the discussion of the ryanodine that precedes it.  In this discussion we found that there is a critical phosphorylation/dephosphorylation balance that exists between Ca(+) ion displacement and it occurs at a specific amino acid residue on the CaMKIId, specific for myocardium, and there is a 4-fold increase in contraction and calcium release associated with this CAM kinase (ser 2809) dependent exchange.  These events are discussed in depth, and the research holds promise for therapeutic application. We also learn that Ca(2+) ion channels are critically involved in the generation of arrhythmia as well as dilated and hypertrophic cardiomyopathy.  In the case of arrhythmiagenesis, there are two possible manners by which this occurs.  One trigger is Ca(2+) efflux instability.  The other is based on the finding that when the cellular instability is voltage driven, the steady-state wave­length (separation of nodes in space) depends on electrotonic coupling between cells and the steepness of APD and CV restitution. The last article is an in depth review of the genetic mutations that occur in cardiac diseases.  It is an attempt at classifying them into reasonable groupings. What are the therapeutic implications of this? We see that the molecular mechanism of cardiac function has been substantially elucidated, although there are contradictions in experimental findings that are unexplained.  However, for the first time, it appears that personalized medicine is on a course that will improve health in the population, and the findings will allow specific targets designed for the individual with a treatable impairment in cardiac function that is identifiable early in the course of illness. This article is a continuation to the following articles on tightly related topics: Part I: Identification of Biomarkers that are Related to the Actin Cytoskeleton     Larry H Bernstein, MD, FCAP Part II:  Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility    Larry H. Bernstein, MD, FCAP, Stephen Williams, PhD and Aviva Lev-Ari, PhD, RN Part III: Renal Distal Tubular Ca2+ Exchange Mechanism in Health and Disease    Larry H. Bernstein, MD, FCAP, Stephen J. Williams, PhD
 and  Aviva Lev-Ari, PhD, RN Part  IV:  The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN  http:/ Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets

Part V:  Heart Smooth Muscle and Cardiomyocyte Cells: Excitation-Contraction Coupling & Ryanodine Receptor (RyR) type-1/type-2 in Cytoskeleton Cellular Dynamics and Ca2+ Signaling

Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN Part VI:  Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD Curator: Aviva Lev-Ari, PhD, RN and Advanced Topics in Sepsis and the Cardiovascular System at its End Stage Larry H Bernstein, MD, FCAP

The Role of Protein Kinases and Protein Phosphatases in the Regulation of Cardiac Sarcoplasmic Reticulum Function

EG Kranias, RC Gupta, G Jakab, HW Kim, NAE Steenaart, ST Rapundalo Molecular and Cellular Biochemistry 06/1988; 82(1):37-44. · 2.06 Impact Factor Canine cardiac sarcoplasmic reticulum is phosphorylated by

  • adenosine 3,5-monophosphate (cAMP)-dependent and
  • calcium calmodulin-dependent protein kinases on
  • a proteolipid, called phospholamban.

Both types of phosphorylation are associated with

  •  an increase in the initial rates of Ca(2+) transport by SR vesicles
  • which reflects an increased turnover of elementary steps of the calcium ATPase reaction sequence.

The stimulatory effects of the protein kinases on the calcium pump may be reversed by an endogenous protein phosphatase, which

  • can dephosphorylate both the CAMP-dependent and the calcium calmodulin-dependent sites on phospholamban.

Thus, the calcium pump in cardiac sarcoplasmic reticulum appears to be under reversible regulation mediated by protein kinases and protein phosphatases. calcium release calmodulin + ER Ca(2+) and contraction

Regulation of the Cardiac Ryanodine Receptor Channel by Luminal Ca2+ involves Luminal Ca2+ Sensing Sites

I Györke, S Györke.   Biophysical Journal 01/1999; 75(6):2801-10. · 3.65 Impact factor  http:// The mechanism of activation of the cardiac calcium release channel/ryanodine receptor (RyR) by luminal Ca(2+) was investigated in native canine cardiac RyRs incorporated into lipid bilayers in the presence of 0.01 microM to 2 mM Ca(2+) (free) and 3 mM ATP (total) on the cytosolic (cis) side and 20 microM to 20 mM Ca(2+) on the luminal (trans) side of the channel and with Cs+ as the charge carrier. Under conditions of low [trans Ca(2+)] (20 microM), increasing [cis Ca(2+)] from 0.1 to 10 microM caused a gradual increase in channel open probability (Po). Elevating [cis Ca(2+)] [cytosolic] above 100 microM resulted in a gradual decrease in Po. Elevating trans [Ca(2+)] [luminal] enhanced channel activity (EC50 approximately 2.5 mM at 1 microM cis Ca2+) primarily by increasing the frequency of channel openings. The dependency of Po on trans [Ca2+] [luminal] was similar at negative and positive holding potentials and was not influenced by high cytosolic concentrations of the fast Ca(2+) chelator, 1,2-bis(2-aminophenoxy)ethane-N,N,N, N-tetraacetic acid. Elevated luminal Ca(2+)

  1. enhanced the sensitivity of the channel to activating cytosolic Ca(2+), and it
  2. essentially reversed the inhibition of the channel by high cytosolic Ca(2+).

Potentiation of Po by increased luminal Ca(2+) occurred irrespective of whether the electrochemical gradient for Ca(2+) supported a cytosolic-to-luminal or a luminal-to-cytosolic flow of Ca(2+) through the channel. These results rule out the possibility that under our experimental conditions, luminal Ca(2+) acts by interacting with the cytosolic activation site of the channel and suggest that the effects of luminal Ca2+ are mediated by distinct Ca(2+)-sensitive site(s) at the luminal face of the channel or associated protein. F1.large  calcium movement and RyR2 receptor

Protein phosphatases Decrease Sarcoplasmic Reticulum Calcium Content by Stimulating Calcium Release in Cardiac Myocytes

D Terentyev, S Viatchenko-Karpinski, I Gyorke, R Terentyeva and S Gyorke Texas Tech University Health Sciences Center, Lubbock, TX J Physiol 2003; 552(1), pp. 109–118. Phosphorylation/dephosphorylation of Ca2+ transport proteins by cellular kinases and phosphatases plays an important role in regulation of cardiac excitation–contraction coupling; furthermore,

  • abnormal protein kinase and phosphatase activities have been implicated in heart failure.

However, the precise mechanisms of action of these enzymes on intracellular Ca2+ handling in normal and diseased hearts remains poorly understood. We have investigated

  •   the effects of protein phosphatases PP1 and PP2A on spontaneous Ca(2+) sparks and SR Ca(2+) load in myocytes permeabilized with saponin.

Exposure of myocytes to PP1 or PP2A caused a dramatic increase in frequency of Ca(2+) sparks followed by a nearly complete disappearance of events, which were accompanied by depletion of the SR Ca(2+) stores, as determined by application of caffeine. These changes in

  •  Ca(2+) release and
  • SR Ca(2+) load

could be prevented by the inhibitors of PP1 and PP2A phosphatase activities okadaic acid and calyculin A. At the single channel level, PP1 increased the open probability of RyRs incorporated into lipid bilayers. PP1-medited RyR dephosphorylation in our permeabilized myocytes preparations was confirmed biochemically by quantitative immunoblotting using a phosphospecific anti-RyR antibody. Our results suggest that

  •  increased intracellular phosphatase activity stimulates
  • RyR mediated SR Ca(2+) release
    • leading to depleted SR Ca(2+) stores in cardiac myocytes.

In heart muscle cells, the process of excitation–contraction (EC) coupling is mediated by

  •  Ca(2+) influx through sarcolemmal L-type Ca(2+) channels
  • activating Ca(2+) release channels (ryanodine receptors, RyRs) in the sarcoplasmic reticulum (SR).

Once activated, the RyR channels allow Ca(2+) to be released from the SR into the cytosol to induce contraction. This mechanism is known as Ca(2+)-induced calcium release (CICR) (Fabiato, 1985; Bers, 2002).  During relaxation, most of the Ca(2+) is resequestered into the SR by the Ca(2+)-ATPase. The amount of Ca(2+) released and the force of contraction depend on

  •  the magnitude of the Ca(2+) trigger signal,
  • the functional state of the RyRs and
  • the amount of Ca(2+) stored in the SR.

F1.large  calcium movement and RyR2 receptor Ca(2+) and contraction calcium release calmodulin + ER Reversible phosphorylation of proteins composing the EC coupling machinery plays an important role in regulation of cardiac contractility (Bers, 2002). Thus, during stimulation of the b-adrenergic pathway, phosphorylation of several target proteins, including

  • the L-type Ca(2+) channels,
  • RyRs and
  • phospholamban,

by protein kinase A (PKA) leads to an overall increase in SR Ca2+ release and contractile force in heart cells (Callewaert et al. 1988, Spurgeon et al. 1990; Hussain & Orchard, 1997; Zhou et al. 1999; Song et al. 2001; Viatchenko-Karpinski & Gyorke, 2001). PKA-dependent phosphorylation of the L-type Ca(2+) channels increases the Ca2+ current (ICa), increasing both

  • the Ca2+ trigger for SR Ca2+ release and
  • the SR Ca(2+) content

(Callewaert et al. 1988; Hussain & Orchard, 1997; Del Principe et al. 2001). Phosphorylation of phospholamban (PLB) relieves the tonic inhibition dephosphorylated PLB exerts on the SR Ca(2+)-ATPase (SERCA) resulting in enhanced SR Ca(2+) accumulation and enlarged Ca(2+) release (Kranias et al. 1985; Simmermann & Jones, 1998). With regard to the RyR, despite clear demonstration of phosphorylation of the channel in biochemical studies (Takasago et al. 1989; Yoshida et al. 1992), the consequences of this reaction to channel function have not been clearly defined. RyR phosphorylation by PKA and Ca(2+)–calmodulin dependent protein kinase (CaMKII) has been reported to increase RyR activity in lipid bilayers (Hain et al. 1995; Marx et al. 2000; Uehara et al. 2002). Moreover, it has been reported that in heart failure (HF), hyperphosphorylation of RyR causes

  •  the release of FK-506 binding protein (FKBP12.6) from the RyR,
    • rendering the channel excessively leaky for Ca(2+) (Marx et al. 2000).

However, other studies have reported no functional effects (Li et al. 2002) or even found phosphorylation to reduce RyR channel steady-state open probability (Valdivia et al. 1995; Lokuta et al. 1995).  The action of protein kinases is opposed by dephosphorylating phosphatases. Three types of protein phosphatases (PPs), referred to as PP1, PP2A and PP2B (calcineurin), have been shown to influence cardiac performance (Neumann et al. 1993; Rusnak & Mertz, 2000). Overall, according to most studies phosphatases appear to downregulate SR Ca(2+) release and contractile performance (Neumann et al. 1993; duBell et al. 1996, 2002; Carr et al. 2002; Santana et al. 2002). Furthermore, PP1 and PP2A activities appear to be increased in heart failure (Neumann, 2002; Carr et al. 2002). However, again the precise mode of action of these enzymes on intracellular Ca(2+) handling in normal and diseased hearts remains poorly understood.  In the present study, we have investigated the effects of protein phosphatases PP1 and PP2A on local Ca(2+) release events, Ca(2+) sparks, in cardiac cells. Our results show that

  •  phosphatases activate RyR mediated SR Ca(2+) release
    • leading to depletion of SR Ca(2+) stores.

These results provide novel insights into the mechanisms and potential role of protein phosphorylation/dephosphorylation in regulation of Ca(2+) signaling in normal and diseased hearts. F2.large   RyR and calcium


Effects of PP1 and PP2A on Ca2+ sparks and SR Ca(2+) content.

[1]  PP1 caused an early transient potentiation of Ca2+ spark frequency followed by a delayed inhibition of event occurrence. [2]  PP1 produced similar biphasic effects on the magnitude and spatio-temporal characteristics of Ca(2+) sparks Specifically, during the potentiatory phase (1 min after addition of the enzyme), PP1 significantly increased

  • the amplitude,
  • rise-time,
  • duration and
  • width of Ca(2+) sparks;

during the inhibitory phase (5 min after addition of the enzyme),

  •  all these parameters were significantly suppressed by PP1.

The SR Ca(2+) content decreased by 35 % or 69 % following the exposure of myocytes to either 0.5 or 2Uml_1 PP1, respectively (Fig. 1C). Qualitatively similar results were obtained with phosphatase PP2A. Similar to the effects of PP1, PP2A (5Uml_1) produced a transient increase in Ca(2+) spark frequency (~4-fold) followed by a depression of event occurrence and decreased SR Ca(2+) content (by 82 % and 65 %, respectively). Also similar to the action of PP1, PP2A increased

  •  the amplitude and
  • spatio-temporal spread (i.e. rise-time, duration and width) of Ca(2+) sparks at 1 min
  • and suppressed the same parameters at 5 min of exposure to the enzyme (Table 1).

Together, these results suggest that phosphatases enhance spark-mediated SR Ca2+ release, leading to decreased SR Ca(2+) content. Preventive effects of calyculin A and okadaic acid Preventive effects of ryanodine

PP1-mediated RyR dephosphorylation

F3.large  cardiomyocyte SR F3.large  cardiomyocyte SR F2.large   RyR and calcium coupled receptors coupled receptors The cardiac RyR is phosphorylated at Ser-2809 (in the rabbit sequence) by both PKA and CAMKII (Witcher et al. 1991; Marx et al. 2000). Although additional phosphorylation sites may exist on the RyR (Rodriguez et al. 2003), but Ser-2809 is believed to be the only site that is phosphorylated by PKA, and RyR hyperphosphorylation at this site has been reported in heart failure (Marx et al. 2000).  To test whether indeed phosphatases dephosphorylated the RyR in our permeabilized myocyte experiments we performed quantitative immunoblotting using an antibody that specifically recognizes the phosphorylated form of the RyR at Ser-2809 (Rodriguez et al. 2003). Myocytes exhibited a significant level of phosphorylation under baseline conditions. Maximal phosphorylation was 201 % of control. When exposed to 2Uml_1 PP1, RyR phosphorylation was 58 % of the control basal condition. Exposing to a higher PP1 concentration (10Uml_1) further reduced RyR phosphorylation to 22% of control. Thus, consistent with the results of our functional measurements,

  •  PP1 decreased RyR phosphorylation in cardiac myocytes.

Figure 1. Effects of PP1 on properties of Ca(2+) sparks and SR Ca(2+) content in rat permeabilized myocytes    see . A, spontaneous Ca(2+) spark images recorded under reference conditions, and 1 or 5 min after exposure of the cell to 2Uml_1 PP1. Traces below the images are Ca(2+) transients induced by application of 10 mM caffeine immediately following the acquisition of sparks before (3 min) and after (5 min) application of PP1 in the same cell. The Ca(2+) transients were elicited by a whole bath application of 10 mM caffeine. B, averaged spark frequency at early (1 min) and late (5 min) times following the addition of either 0.5 or 2Uml_1 of PP1 to the bathing solution. C, averaged SR Ca(2+) content for 0.5 or 2Uml_1 of PP1 measured before and 5 min after exposure to the enzyme. Data are presented as means ± S.E.M. of 6 experiments in different cells. Figure 2. Effects of PP2A on properties of Ca2+ sparks and SR Ca2+ content in rat permeabilized myocytes   see . A, spontaneous Ca(2+) spark images recorded under reference conditions, and 1 or 5 min after exposure of the cell to 5Uml_1 PP2A. Traces below the images are Ca(2+) transients induced by application of 10 mM caffeine immediately following the acquisition of sparks before (3 min) and after (5 min) application of PP2A in the same cell. B and C, averaged spark frequency (B) and SR Ca(2+) content (C) for the same conditions as in A. Data are presented as means ± S.E.M. of 6 experiments in different cells.


In the present study, we have investigated the impact of physiologically relevant exogenous protein phosphatases PP1 and PP2A on RyR-mediated SR Ca(2+) release (measured as Ca(2+) sparks) in permeabilized heart cells. Our principal finding is that

  • phosphatases stimulated RyR channels lead to depleted SR Ca(2+) stores.

These results have important ramifications for understanding the mechanisms and role of protein phosphorylation/dephosphorylation in

  •  modulation of Ca(2+) handling in normal and diseased heart.

Modulation of SR Ca2+ release by protein phosphorylation/dephophorylation

Since protein dephosphorylation clearly resulted in increased functional activity of the Ca(+)release channel, our results imply that a reverse, phosphorylation reaction should reduce RyR activity. If indeed such effects take place, why do they not manifest in inhibition of Ca(+)sparks? One possibility is that enhanced Ca(+) uptake by SERCA

  •  masks or overcomes the effects phosphorylation may have on RyRs.

In addition, the potential inhibitory influence of protein phosphorylation on RyR activity in myocytes could be countered by feedback mechanisms  involving changes in luminal Ca(2+)(Trafford et al. 2002; Gyorke et al. 2002). In particular, reduced open probability of RyRs would be expected to lead to

  •  increased Ca2+ accumulation in the SR;
  • and increased intra-SR [Ca(2+)], in turn would
  • increase activity of RyRs at their luminal Ca(2+) regulatory sites

as demonstrated for the RyR channel inhibitor tetracaine (Gyorke et al. 1997; Overend et al. 1997). Thus

  • potentiation of SERCA
  • combined with the intrinsic capacity of the release mechanism to self-regulate

could explain at least in part why PKA-mediated protein phoshorylation results in maintained potentiation of Ca(2+) sparks despite a potential initial decrease in RyR activity.

Role of altered RyR Phosphorylation in Heart Failure

Marx et al. (2000) have proposed that  enhanced levels of circulating catecholamines lead to increased phosphorylation of RyR in heart failure.  Based on biochemical observations as well as on studying properties of single RyRs incorporated into artificial lipid bilayers, these investigators have hypothesized that

  •  hyperphosphorylation of RyRs contributes to pathogenesis of heart failure
    • by making the channel excessively leaky due to dissociation of FKBP12.6 from the channel.

We show that the mode of modulation of RyRs by phosphatases does not support this hypothesis as

  • dephosphorylation caused activation instead of

Interestingly, our results provide the basis for a different possibility in which

  •  dephophosphorylation of RyR rather than its phosphorylation causes depletion of SR Ca(2+) stores by stimulating RyRs in failing hearts.

It has been reported that PP1 and PP2 activities are increased in heart failure (Huang et al. 1999; Neumann et al. 1997; Neuman, 2002). Furthermore,  overexpression of PP1 or ablation of the endogenous PP1 inhibitor, l-1, results in

  • depressed contractile performance and heart failure (Carr et al. 2002).

Our finding that PP1 causes depletion of SR Ca(2+) stores by activating RyRs could account for, or contribute to, these results.


1 DelPrincipe F, Egger M, Pignier C & Niggli E (2001). Enhanced E-C coupling efficiency after beta-stimulation of cardiac myocytes. Biophys J 80, 64a. 2 Gyorke I & Gyorke S (1998). Regulation of the cardiac ryanodine receptor channel by luminal Ca2+ involves luminal Ca2+ sensing sites. Biophys J 75, 2801–2810. 3 Gyorke S, Gyorke I, Lukyanenko V, Terentyev D, Viatchenko-Karpinski S & Wiesner TF (2002). Regulation of sarcoplasmic reticulum calcium release by luminal calcium in cardiac muscle. Front Biosci 7, d1454–d1463. 4 Gyorke I, Lukyanenko V & Gyorke S (1997). Dual effects of tetracaine on spontaneous calcium release in rat ventricular myocytes. J Physiol 500, 297–309. 5 MacDougall LK, Jones LR & Cohen P (1991). Identification of the major protein phosphatases in mammalian cardiac muscle which dephosphorylate phospholamban. Eur J Biochem 196, 725–734. 6 Marx SO, Reiken S, Hisamatsu Y, Jayaraman T, Burkhoff D, Rosemblit N & Marks AR (2000). PKA phosphorylation dissociates FKBP12.6 from the calcium release channel (ryanodine receptor): defective regulation in failing hearts. Cell 101, 365–376. 7 Rodriguez P, Bhogal MS & Colyer J (2003). Stoichiometric phosphorylation of cardiac ryanodine receptor on serine-2809 by calmodulin-dependent kinase II and protein kinase A. J Biol Chem (in press).

The δC Isoform of CaMKII Is Activated in Cardiac Hypertrophy and Induces Dilated Cardiomyopathy and Heart Failure

T Zhang, LS Maier, ND Dalton, S Miyamoto, J Ross, DM Bers, JH Brown.  University of California, San Diego, La Jolla, Calif; and Loyola University, Chicago, Ill. Circ Res. 2003;92:912-919. Recent studies have demonstrated that transgenic (TG) expression of either Ca(2+)/calmodulin-dependent protein kinase IV (CaMKIV) or CaMKIIδB, both of which localize to the nucleus, induces cardiac hypertrophy. However,

  •  CaMKIV is not present in heart, and
  • cardiomyocytes express not only the nuclear CaMKIIδB
    • but also a cytoplasmic isoform, CaMKII δC.

In the present study, we demonstrate that

  1.  expression of the δC isoform of CaMKII is selectively increased and
  2. its phosphorylation elevated as early as 2 days and continuously for up to 7 days after pressure overload.

To determine whether enhanced activity of this cytoplasmic δC isoform of CaMKII can lead to phosphorylation of Ca(2+) regulatory proteins and induce hypertrophy, we generated TG mice that expressed the δC isoform of CaMKII.  Immunocytochemical staining demonstrated that the expressed transgene is confined to the cytoplasm of cardiomyocytes isolated from these mice. These mice develop a dilated cardiomyopathy with up to a 65% decrease in fractional shortening and die prematurely. Isolated myocytes are enlarged and exhibit reduced contractility and altered Ca2(2+) handling. Phosphorylation of the ryanodine receptor (RyR) at a CaMKII site is increased even before development of heart failure, and

  • CaMKII is found associated with the RyR  from the CaMKII TG mice.
  • Phosphorylation of phospholamban is increased specifically at the CaMKII but not at the PKA phosphorylation site.

These findings are the first to demonstrate that CaMKIIδC can mediate phosphorylation of Ca(2+) regulatory proteins in vivo and provide evidence for the involvement of CaMKIIδC activation in the pathogenesis of dilated cardiomyopathy and heart failure.  Multifunctional Ca(2+)/calmodulin-dependent protein kinases (CaM kinases or CaMKs) are transducers of Ca2+ signals that phosphorylate a wide range of substrates and thereby affect Ca(2+)-mediated cellular responses.1 The family includes CaMKI and CaMKIV, monomeric enzymes activated by CaM kinase kinase,2,3 and CaMKII, a multimer of 6 to 12 subunits activated by autophosphorylation.1 The CaMKII subunits α, β, γ, and δ show different tissue distributions,1 with

  • the δ isoform predominating in the heart.4–7
  • Splice variants of the δ isoform, characterized by the presence of a second variable domain,4,7 include δB, which contains a nuclear localization signal (NLS), and
  • δC, which does not. CaMKII composed of δB subunits localizes to the nucleus, whereas CaMKIIδC localizes to the cytoplasm.4,8,9

CaMKII has been implicated in several key aspects of acute cellular Ca(2+) regulation related to cardiac excitation-contraction (E-C) coupling. CaMKII

  • phosphorylates sarcoplasmic reticulum (SR) proteins including the ryanodine receptors (RyR2) and
  • phospholamban (PLB).10–14

Phosphorylation of RyR has been suggested to alter the channel open probability,14,15 whereas phosphorylation of PLB has been suggested to regulate SR Ca(2+) uptake.14 It is also likely that CaMKII phosphorylates the L-type Ca(2+) channel complex or an associated regulatory protein and thus

  1. mediates Ca(2+) current (ICa) facilitation.16-18 and
  2. the development of early after-depolarizations and arrhythmias.19

Thus, CaMKII has significant effects on E-C coupling and cellular Ca(2 +) regulation. Nothing is known about the CaMKII isoforms regulating these responses.  Contractile dysfunction develops with hypertrophy, characterizes heart failure, and is associated with changes in cardiomyocyte (Ca2+) homeostasis.20  CaMKII expression and activity are altered in the myocardium of rat models of hypertensive cardiac hypertrophy21,22 and heart failure,23 and

  • in cardiac tissue from patients with dilated cardiomyopathy.24,25

Several transgenic mouse models have confirmed a role for CaMK in the development of cardiac hypertrophy, as originally suggested by studies in isolated neonatal rat ventricular myocytes.9,26–28 Hypertrophy develops in transgenic mice that overexpress CaMKIV,27 but this isoform is not detectable in the heart,4,29 and CaMKIV knockout mice still develop hypertrophy after transverse aortic constriction (TAC).29  Transgenic mice overexpressing calmodulin developed severe cardiac hypertrophy,30 later shown to be associated with an increase in activated CaMKII31; the isoform of CaMKII involved in hypertrophy could not be determined from these studies. We recently reported that transgenic mice that overexpress CaMKIIδB, which is highly concentrated in cardiomyocyte nuclei, develop hypertrophy and dilated cardiomyopathy.32 To determine whether

  • in vivo expression of the cytoplasmic CaMKIIδC can phosphorylate cytoplasmic Ca(2+) regulatory proteins and
  • induce hypertrophy or heart failure,

we generated transgenic (TG) mice that expressed the δC isoform of CaMKII under the control of the cardiac specific α-myosin heavy chain (MHC) promoter. Our findings implicate CaMKIIδC in the pathogenesis of dilated cardiomyopathy and heart failure and suggest that

  • this occurs at least in part via alterations in Ca(2+) handling proteins.33

Ca(2+) and contraction RyR yuan_image3  Ca++ exchange yuan_image3  Ca++ exchange


 Expression and Activation of CaMKIIδC Isoform After TAC

To determine whether CaMKII was regulated in pressure overload–induced hypertrophy, CaMKIIδ expression and phosphorylation were examined by Western blot analysis using left ventricular samples obtained at various times after TAC.  A selective increase (1.6-fold) in the lower band of CaMKIIδwas observed as early as 1 day and continuously for 4 days (2.3-fold) and 7 days (2-fold) after TAC (Figure 1A).  To confirm that CaMKIIδC was increased and determine whether this occurred at the transcriptional level, we performed semiquantitative RT-PCR using primers specific for the CaMKIIδC isoform. These experiments revealed that

  • mRNA levels for CaMKIIδC were increased 1 to 7 days after TAC (Figure 1B).

In addition to examining CaMKII expression, the activation state of CaMKII was monitored by its autophosphorylation, which confers Ca2-independent activity.

Figure 1. Expression and activation of CaMKII δC isoform after TAC.

see A, Western blot analysis of total CaMKII in left ventricular (LV) homogenates obtained at indicated times after TAC. Cardiomyocytes transfected with CaMKIIδB and δC (right) served as positive controls and molecular markers. Top band (58 kDa) represents CaMKIIδB plus δ9, and the bottom band (56 kDa) corresponds to CaMKIIδC. *P0.05 vs control. B, Semiquantitative RT-PCR using primers specific for CaMKIIδC isoform (24 cycles) and GAPDH (19 cycles) using total RNA isolated from the same LV samples. C, Western blot analysis of phospho-CaMKII in LV homogenates obtained at various times after TAC. Three bands seen for each sample represent CaMKIIγ subunit (uppermost), CaMKIIδB plus δ9 (58 kDa), and CaMKIIδC (56 kDa). Quantitation is based on the sum of all of the bands. *P0.05 vs control.

 Figure 2. Expression and activation of CaMKII in CaMKIIδC transgenic mice.

see A, Transgene copy number based on Southern blots using genomic DNA isolated from mouse tails (digested with EcoRI). Probe (a 32P-labeled 1.7-kb EcoRI-SalI -MHC fragment) was hybridized to a 2.3-kb endogenous fragment (En) and a 3.9-kb transgenic fragment (TG). Transgene copy number was determined from the ratio of the 3.9-kb/2.3-kb multiplied by 2. B, Immunocytochemical staining of ventricular myocytes isolated from WT and CaMKIIδTG mice. Myocytes were cultured on laminin-coated slides overnight. Transgene was detected by indirect immunofluorescence staining using rabbit anti-HA antibody (1:100 dilution) followed by FITC-conjugated goat antirabbit IgG antibody (1:100 dilution). CaMKIIδB localization to the nucleus in CaMKIIδB TG mice (see Reference 32) is shown here for comparative purpose. C, Quantitation of the fold increase in CaMKIIδprotein expression in TGL and TGM lines. Different amounts of ventricular protein (numbers) from WT control, TG () and their littermates () were immunoblotted with an anti-CaMKIIδ antibody. Standard curve from the WT control was used to calculate fold increases in protein expression in TGL and TGM lines. D, Phosphorylated CaMKII in ventricular homogenates was measured by Western blot analysis (n5 for each group). **P0.01 vs WT.

 Generation and Identification of CaMKIIδC Transgenic Mice

TG mice expressing HA-tagged rat wild-type CaMKIIδC under the control of the cardiac-specific α-MHC promoter were generated as described in Materials and Methods. By Southern blot analysis, 3 independent TG founder lines carrying 3, 5, and 15 copies of the transgene were identified. They were designated as TGL (low copy number), TGM (medium copy number), and TGH (high copy number), The founder mice from the TGH line died at 5 weeks of age with marked cardiac enlargement.  The other two lines showed germline transmission of the transgene. The transgene was expressed only in the heart. Although CaMKII protein levels in TGL and TGM hearts were increased 12- and 17-fold over wild-type (WT) controls (Figure 2C), the amount of activated CaMKII was only increased 1.7- and 3-fold in TGL and TGM hearts (Figure 2D). The relatively small increase in CaMKII activity in the TG lines probably reflects the fact that the enzyme is not constitutively activated and that the availability of Ca2/CaM, necessary for activation of the overexpressed CaMKII, is limited. Importantly,

  • the extent of increase in active CaMKII in the TG lines was similar to that elicited by TAC.

 Cardiac Overexpression of CaMKIIδC Induces Cardiac Hypertrophy and Dilated Cardiomyopathy

There was significant enlargement of hearts from CaMKIIδC TGM mice by 8 to 10 weeks [see  (Figure 3A) and from TGL mice by 12 to 16 weeks. Histological analysis showed ventricular dilation (Figure 3B), cardiomyocyte enlargement (Figure 3C), and mild fibrosis (Figure 3D) in CaMKIIδC TG mice. Quantitative analysis of cardiomyocyte cell volume from 12-week-old TGM mice gave values of 54.7 + 0.1 pL for TGM (n = 96) versus 28.6 + 0.1 pL for WT littermates (n=94; P0.001). Ventricular dilation and cardiac dysfunction developed over time in proportion to the extent of transgene expression. Left ventricular end diastolic diameter (LVEDD) was increased by 35% to 45%, left ventricular posterior wall thickness (LVPW) decreased by 26% to 29% and fractional shortening decreased by 50% to 60% at 8 weeks for TGM and at 16 weeks for TGL. None of these parameters were significantly altered at 4 weeks in TGM or up to 11 weeks in TGL mice, indicating that heart failure had not yet developed.  Contractile function was significantly decreased. Figure 6. Dilated cardiomyopathy and dysfunction in CaMKIIδC TG mice at both whole heart and single cell levels.  [see Fig 6:] C, Decreased contractile function in ventricular myocytes isolated from 12-week old TGM and WT controls presented as percent change of resting cell length (RCL) stimulated at 0.5 Hz. Representative trace and mean values are shown. *P0.05 vs WT. Figure 7. Phosphorylation of PLB in CaMKIIδC TG mice.  [see Fig 7:] Thr17 and Ser16 phosphorylated PLB was measured by Western blots using specific anti-phospho antibodies. Ventricular homogenates were from 12- to 14-week-old WT and TGM mice (A) or 4 to 5-week-old WT and TGM mice (B). Data were normalized to total PLB examined by Western blots (data not shown here). n = 6 to 8 mice per group; *P0.05 vs WT.

 Cardiac Overexpression of CaMKIIδC Results in Changes in the Phosphorylation of Ca2 Handling Proteins

To assess the possible involvement of phosphorylation of Ca2cycling proteins in the phenotypic changes observed in the CaMKIIC TG mice, we first compared PLB phosphorylation state in homogenates from 12- to 14-week-old TGM and WT littermates. Western blots using antibodies specific for phosphorylated PLB showed a 2.3-fold increase in phosphorylation of Thr17 (the CaMKII site) in hearts from TGM versus WT (Figure 7A). Phosphorylation of PLB at the CaMKII site was also increased 2-fold in 4- to 5-week-old TGM mice (Figure 7B). Significantly, phosphorylation of the PKA site (Ser16) was unchanged in either the older or the younger TGM mice (Figures 7A and 7B). (see  To demonstrate that the RyR2 phosphorylation changes observed in the CaMKII transgenic mice are not secondary to development of heart failure, we performed biochemical studies examining RyR2 phosphorylation in 4- to 5-week-old TGM mice. At this age, most mice showed no signs of hypertrophy or heart failure (see Figure 6B) and there was no significant increase in myocyte size (21.3 + 1.3 versus 27.7 + 4.6 pL; P0.14). Also, twitch Ca2 transient amplitude was not yet significantly depressed, and mean δ [Ca2+]i (1 Hz) was only 20% lower (192 + 36 versus 156 + 13 nmol/L; P0.47) versus 50% lower in TGM at 13 weeks.33  The in vivo phosphorylation of RyR2, determined by back phosphorylation, was significantly (2.10.3-fold; P0.05) increased in these 4- to 5-week-old TGM animals (Figure 8C), an increase equivalent to that seen in 12- to 14-week-old mice. We also performed the RyR2 back-phosphorylation assay using purified CaMKII rather than PKA. RyR2 phosphorylation at the CaMKII site was also significantly increased (2.2 + 0.3-fold; P0.05) in 4- to 5-week-old TGM mice (Figure 8C).  ( The association of CaMKII with the RyR2 is consistent with a physical interaction between this protein kinase and its substrate. The catalytic subunit of PKA and the phosphatases PP1 and PP2A were also present in the RyR2 immunoprecipitates, but not different in WT versus TG mouse hearts (Figure 8D). These data provide further evidence that

  • the increase in RyR2 phosphorylation, which precedes development of failure in the 4- to 5-week-old CaMKIIδC TG hearts, can be attributed to the increased activity of CaMKII.


  1. CaMKII is involved in the dynamic modulation of cellular
  2. Ca2 regulation and has been implicated in the development of cardiac hypertrophy and heart failure.14
  3. Published data from CaMK-expressing TG mice demonstrate that forced expression of CaMK can induce cardiac hypertrophy and lead to heart failure.27,32

However, the CaMK genes expressed in these mice are neither the endogenous isoforms of the enzyme nor the isoforms likely to regulate cytoplasmic Ca(2+) handling, because they localize to the nucleus.

  1.  the cytoplasmic cardiac isoform of CaMKII is upregulated at the expression level and is in the active state (based on autophosphorylation) after pressure overload induced by TAC.
  2.  two cytoplasmic CaMKII substrates (PLB and RyR) are phosphorylated in vivo when CaMKII is overexpressed and its activity increased to an extent seen under pathophysiological conditions.
  3. CaMKIIδ is found to associate physically with the RyR in the heart.
  4.  heart failure can result from activation of the cytoplasmic form of CaMKII and this may be due to altered Ca(2+) handling.

 Differential Regulation of CaMKIIδ Isoforms in Cardiac Hypertrophy

  1.  The isoform of CaMKII that predominates in the heart is the δ isoform.4–7 Neither the α nor the β isoforms are expressed and there is only a low level of expression of the γ isoforms.39
  2. Both δB and δC splice variants of CaMKIIδ are present in the adult mammalian myocardium36,40 and expressed in distinct cellular compartments.4,8,9

We suggest that the CaMKIIδ isoforms are differentially regulated in pressure-overload–induced hypertrophy, because the expression of CaMKIIδC is selectively increased as early as 1 day after TAC. Studies using RT-PCR confirm that

  • CaMKIIδC is regulated at the transcriptional level in response to TAC. In addition,
  • activation of both CaMKIIδB and CaMKIIδC, as indexed by autophosphorylation, increases as early as 2 days after TAC.
  • Activation of CaMKIIδB by TAC is relevant to our previous work indicating its role in hypertrophy.9,32
  • The increased expression, as well as activation of the CaMKIIδC isoform, suggests that it could also play a critical role in both the acute and longer responses to pressure overload.

In conclusion, we demonstrate here that CaMKIIδC can phosphorylate RyR2 and PLB when expressed in vivo at levels leading to 2- to 3-fold increases in its activity. Similar increases in CaMKII activity occur with TAC or in heart failure. Data presented in this study and in the accompanying article33 suggest that altered phosphorylation of Ca(2+) cycling proteins is a major component of the observed decrease in contractile function in CaMKIIδC TG mice. The occurrence of increased CaMKII activity after TAC, and of RyR and PLB phosphorylation in the CaMKIIδC TG mice suggest that

  • CaMKIIδC plays an important role in the pathogenesis of dilated cardiomyopathy and heart failure.

These results have major implications for considering CaMKII and its isoforms in exploring new treatment strategies for heart failure.

Cardiac Electrophysiological Dynamics From the Cellular Level to the Organ Level

Daisuke Sato and Colleen E. Clancy Department of Pharmacology, University of California – Davis, Davis, CA. Biomedical Engineering and Computational Biology 2013:5: 69–75 Abstract: Cardiac alternans describes contraction of the ventricles in a strong-weak-strong-weak sequence at a constant pacing fre­quency. Clinically, alternans manifests as alternation of the T-wave on the ECG and predisposes individuals to arrhythmia and sudden cardiac death. In this review, we focus on the fundamental dynamical mechanisms of alternans and show how alternans at the cellular level underlies alternans in the tissue and on the ECG. A clear picture of dynamical mechanisms underlying alternans is important to allow development of effective anti-arrhythmic strategies. The cardiac action potential is the single cellular level electrical signal that triggers contraction of the heart.1 Under normal conditions, the originating activation signal comes from a small bundle of tissue in the right atrium called the sinoatrial node (SAN). The action potentials generated by the SAN initiate an excitatory wave that, in healthy tissue, propagates smoothly through a well-defined path and causes excitation and contraction in the ventricles. In disease states, the normal excitation pathway is disrupted and a variety of abnormal rhythms can occur, including cardiac alternans, a well-known precursor to sudden cardiac death. Cardiac alternans was initially documented in 1872 by a German physician, Ludwig Traube.2 He observed contraction of the ventricles in a strong-weak-strong-weak sequence even though the pacing frequency was constant. Clinically, alternans mani­fests as alternation of the T-wave on the ECG, typi­cally in the microvolt range. It is well established that individuals with microvolt T-wave alternans are at much higher risk for arrhythmia and sudden cardiac death. A clear picture of physio­logical mechanisms underlying alternans is important to allow development of effective anti-arrhythmic drugs. It is also important to understand dynamical mechanisms because while the cardiac action poten­tial is composed of multiple currents, each of which confers specific properties, revelation of dynamical mechanisms provides a unified fundamental view of the emergent phenomena that holds independently of specific current interactions. The ventricular myocyte is an excitable cell pro­viding the cellular level electrical activity that under­lies cardiac contraction. Under resting conditions, the membrane potential is about -80 mV. When the cell is stimulated, sodium (Na) channels open and the membrane potential goes above 0 mV. Then, a few ms later, the inward current L-type calcium (Ca) current activates and maintains depolarization of the mem­brane potential. During this action potential plateau, several types of outward current potassium (K) chan­nels also activate. Depending on the balance between inward and outward currents, the action potential duration (APD) is determined.The diastolic interval (DI) that follows cellular repolarization describes the duration the cell resides in the resting state until the next excitation. During the DI, channels recover with kinetics determined by intrinsic time constants. APD restitution defines the relationship between the APD and the previous DI (Fig. 1 top panel). In most cases1, the APD becomes longer as the previous DI becomes longer due to recovery of the L-type Ca channel (Fig. 1, bottom panel), and thus the APD restitution curve has a positive slope. Figure 1. (Top): APD and DI. (Bottom): The physiological mechanism of APD alternans involves recovery from inactivation of ICaL.  [see]

 Action Potential Duration Restitution

In 1968 Nolasco and Dahlen showed graphically that APD alternans occurs when the slope of the APD res­titution curve exceeds unity. Why is the steepness of the slope important? As shown graphically in Figure 2, APD alternans amplitude is multiplied by the slope of the APD restitution curve in each cycle. When the slope is larger than one, then the alternans amplitude will be amplified until the average slope reaches 1 or the cell shows a 2:1 stimulus to response ratio.  The one-dimensional mapping between APD and DI fails to explain quasi-periodic oscillation of the APD. Figure 2. APD restitution and dynamical mechanism of APD alternans.   [see]

Calcium Driven Alternans

A strong-weak-strong-weak oscillation in contrac­tion implies that the Ca transient (CaT) is alternating. Until 1999 it was assumed that if the APD is alternat­ing then the CaT alternates because the CaT follows APD changes. However, Chudin et al showed that CaT can alternate even when APD is kept constant during pacing with a periodic AP clamp waveform.14 This implies that the intracellular Ca cycling has intrinsic nonlinear dynamics. A critical component in this process is the sarcoplasmic reticulum (SR), a subcellular organelle that stores Ca inside the cell. When Ca enters a cell through the L-type Ca channel (or reverse mode Na-Ca exchanger (NCX) ryanodine receptors open and large Ca releases occur from the SR (Ca induced Ca release). The amount of Ca release steeply depends on SR Ca load. This steep relation between Ca release and SR Ca load is the key to induce CaT alternans.  A one-dimensional map between Ca release and SR calcium load can be constructed to describe the relationship21 similar to the map used in APD restitution.

 Subcellular Alternans

A number of experimental and computational stud­ies have been undertaken to identify molecular mechanisms of CaT alternans by identifying the specific components in the calcium cycling process critical to formation of CaT alternans. These compo­nents include SR Ca leak and load, Ca spark frequency and amplitude, and rate of SR refilling. For example, experiments have shown that alternation in diastolic SR Ca is not required for CaT alternans.24 In addition, stochastic openings of ryanodine receptors (RyR) lead to Ca sparks that occur randomly, not in an alternating sequence that would be expected to underlie Ca altern-ans. So, how do local random sparks and constant dia­stolic SR calcium load lead to global CaT alternans? Mathematical models with detailed representations of subcellular Ca cycling have been developed in order to elucidate the underlying mechanisms. Model­ing studies have shown that even when SR Ca load is not changing, RyRs, which are analogous to ICaL in APD alternans, recover gradually from refractoriness. As RyR availability increases (for example during a long diastolic interval) a single Ca spark from a RyR will be larger in amplitude and recruit neighboring Ca release units to generate more sparks. The large resultant CaT causes depletion of the SR and when complete recovery of RyRs does not occur prior to the arrival of the next stimulus, the subsequent CaT will be small. This process results in an alternans of CaT amplitude from beat-to-beat.

 Coupling Between the Membrane Potential and Subcellular Calcium Dynamics

Importantly, the membrane voltage and intracellu­lar Ca cycling are coupled via Ca sensitive channels such as the L-type Ca channel and the sodium-calcium exchanger (NCX). The membrane voltage dynamics and the intracellular Ca dynamics are bi-directionally coupled. One direction is from voltage to Ca. As the DI becomes longer, the CaT usually becomes larger since the recovery time for the L-type Ca channel in increased and the SR Ca release becomes larger. The other direction is from Ca to voltage. Here we consider two major currents, NCX and ICaL. As the CaT becomes larger, forward mode NCX becomes larger and pro­longs APD. On the other hand, as the CaT becomes larger, ICaL becomes smaller due to Ca-induced inacti­vation, and thus, larger CaT shortens the APD. There­fore, depending on which current dominates, larger CaT can prolong or shorten APD. If a larger CaT pro­longs (shortens) the APD, then the coupling is positive (negative). The coupled dynamics of the membrane voltage and the intracellular Ca cycling can be cate­gorized by the instability of membrane voltage (steep APD restitution), instability of the intracellular Ca cycling (steep relation between Ca release versus SR Ca load), and the coupling (positive or negative). If the coupling is positive, alternans is electromechani­cally concordant (long-short-long-short APD cor­responds to large-small-large-small CaT sequence) regardless of the underlying instability mechanism. On the other hand, if the coupling is negative, alternans is electromechanically concordant in a voltage-driven regime. However, if alternans is Ca driven, alternans becomes electromechanically discordant (long-short-long-short APD corresponds to small-large-small-large CaT sequence). It is also possible to induce quasi- periodic oscillation of APD and CaT when volt­age and Ca instabilities contribute equally.

 Alternans in Higher Dimensions

Tissue level alternans in APD and CaT also occur and here we describe how the dynamical mechanism of alternans at the single cell level determines the phenomena in tissue. Spatially discordant alternans (SDA) where APDs in different regions of tissue alternate out-of-phase, is more arrhythmogenic since it causes large gradients of refractoriness and wave-break, which can initiate ventricular tachycardia and ventricular fibrillation. How is SDA induced? As the APD is a function of the previous DI, con­duction velocity (CV) is also function of the previ­ous DI (CV restitution) since the action potential propagation speed depends on the availability of the sodium channel. As the DI becomes shorter, sodium channels have less time to recover. Therefore, in general, as the DI becomes shorter, the CV becomes slower. When tissue is paced rapidly, action poten­tials propagate slowly near the stimulus, and thenac-celerate downstream as the DI becomes longer. This causes heterogeneity in APD (APD is shorter near the stimulus). During the following tissue excitation, APD becomes longer and the CV becomes faster at the pacing site then gradually APD becomes shorter and the CV becomes slower. The interaction between steep APD restitution and steep CV restitution creates SDA. This mechanism applies only when the cel­lular instability is voltage driven. When the cellular instability is Ca driven, the mechanism of SDA formation is different. If the volt­age-Ca coupling is negative, SDA can form without steep APD and CV restitution. The mechanism can be understood as follows. First, when cells are uncou­pled, alternans of APD and Ca are electromechanically discordant. If two cells are alternating in opposite phases, once these cells are coupled by voltage, due to electrotonic coupling, the membrane voltage of both cells is synchronized and thus APD becomes the same. This synchronization of APD amplifies the difference of CaT between two cells (Fig. 5 in). In other words it desynchronizes CaT. This instability mechanism is also found in subcellular SDA. In the case where the instability is Ca driven and the coupling is positive, there are several interest­ing distinctive phenomena that can occur. First, the profile of SDA of Ca contains a much steeper gra­dient at the node (point in space where no alternans occurs–cells downstream of the node are alternating out of phase with those upstream of the node) com­pared to the case of voltage driven SDA. Thus, the cellular mechanism of instability can be identified by evaluating the steepness of the alternans amplitude gradient in space around the node. When the cellular instability is voltage driven, the steady-state wave­length (separation of nodes in space) depends on electrotonic coupling between cells and the steepness of APD and CV restitution, regardless of the initial conditions. However, if the cellular instability is Ca driven, the location of nodes depends on the pacing history, which includes pacing cycle length and other parameters affected by pacing frequency. In this case, once the node is formed, the location of the node may be fixed, especially when Ca instability is strong. Such an explanation may apply to recent experimen­tal results. Summary In this review, we described how the origin of alternans at the cellular level (voltage driven, Ca drive, coupling between voltage and Ca) affects the formation of spatially discordant alternans at the tissue level. Cardiac alternans is a multi-scale emergent phenomenon. Channel properties determine the instability mechanism at the cellular level. Alternans mechanisms at cellular level determine SDA patterns at the tissue level. In order to understand alternans and develop anti-arrhythmic drug and therapy, multi-scale modeling of the heart is useful, which is increasingly enabled by emerging technologies such as general-purpose computing on graphics processing units (GPGPU) and cloud computing.

English: Diagram of contraction of smooth musc...

English: Diagram of contraction of smooth muscle fiber (Photo credit: Wikipedia)

Schematic representation of Calcium Cycling in Contractile and Proliferating VSMCs receptors voltage gated Ca(2) channel Marks-Wehrens Model and multiphosphorylation  site model ncpcardio0419-f4   calcium leak

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