Methods of inducing dilated cardiomyopathy phenotype in cardiomyocytes and applications thereof

Abstract

The present disclosure provides compositions and methods for inducing a dilated cardiomyopathy (DCM) phenotype in induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The present disclosure also provides methods for identifying a personalized risk stratification paradigm for DCM patients that predicted individual-level risk of mechanical dysfunction and significant arrhythmia using the functional phenotype of patient-specific iPSC-CMs.

Description

PATENT Attorney Docket No.: 079445-079445-014610PC-1494012 Client Reference Nos.: S23-377 METHODS OF INDUCING DILATED CARDIOMYOPATHY PHENOTYPE IN CARDIOMYOCYTES AND APPLICATIONS THEREOF CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No.63 / 570,690, filed March 27, 2024, the disclosure of which is herein incorporated by reference in its entirety for all purposes. STATEMENT AS TO RIGHTS TO INVENTIONS MADE UNDER FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

[0002] This work was supported by the U.S. Department of Veterans Affairs, and the Federal Government has certain rights in this invention. BACKGROUND

[0003] Dilated cardiomyopathy (DCM) is a disorder of cardiac chamber enlargement and reduced contractility mediated by diverse genetic and acquired factors that drive mechanical and electrical dysfunction. The disorder affects at least 1 in 2500 individuals and remains the most common cause of heart transplantation.1,2Identifying subjects at risk for developing DCM poses a significant challenge, driven by the low yield of clinical genetic testing. Even when DCM is diagnosed, risk stratification of disease severity in DCM is equally elusive due to the diversity in clinical phenotypes even in the setting of similar genotypes.3,4Timely identification of patients at risk for DCM and stratifying the risk of arrhythmia in those who carry the diagnosis, can lead to earlier delivery of appropriate therapy, which would translate to improved outcomes.5

[0004] Identifying individuals at risk for developing DCM is usually encountered in the setting of a positive family history of DCM. The majority of patients with DCM do not have identifiable pathogenic variants on clinical genetic testing.3,4This deprives an affected proband’s family members of the opportunity to pursue prospective predictive testing to assess the risk of developing DCM, as can be done for other genetic disorders. As a result, thoseindividuals are subject to lifelong clinical screening to monitor for changes in symptoms or cardiac function.6This approach is resource intensive and places psychological burdens on individuals at risk for DCM.7

[0005] Even if the diagnosis of DCM is made, risk stratifying individual risk of sudden cardiac death (SCD) is even more elusive, as current guidelines fail to capture who stands to benefit from effective prophylactic therapy. SCD is mediated by lethal ventricular arrhythmias and accounts for 35% of deaths in patients with DCM.8Early randomized clinical trials demonstrated internal cardiac defibrillators (ICDs) improved survival from SCD in DCM patients with a left ventricular ejection (LVEF) < 35%.9,10A randomized clinical trial with a more contemporary approach to therapy, showed the current risk stratification standard of LVEF less than 35% was inadequate to identify subjects who stand to derive a cardiovascular mortality benefit from ICD implantation.8Furthermore, the rate of appropriate therapy delivered by ICDs has been reported to be < 25% implying that over 75% of implanted devices were providing no benefit. ICD implantation is associated with significant medical, psychological, and financial burdens arguing against prophylactic ICD implantation in the broader population of DCM patients.11,12Studies have explored the utility of alternative markers to aid in risk stratification, but only cardiac MRI has been shown to offer some incremental utility.13

[0006] Contractile dysfunction, increased loading conditions, and high burden of scar tissue have all been associated with an increased risk of ventricular arrhythmia; but these factors do not capture genetic influences that modulate cardiac electrical function at the cellular or tissue level, which contribute to individual risk of arrhythmia in DCM.14–16Major and minor loci that predict arrhythmic risk have been identified. However, aside from pathogenic LMNA variants, none of this knowledge has translated into individualized risk stratification paradigms or guideline-based decision making.16–18Thus, even in the setting of a known diagnosis of DCM and a known genotype, determining the individual risk of clinically significant arrhythmia is limited. There is an urgent clinical need for individualized risk stratification tools that can guide the effective delivery of prophylactic ICD therapy in DCM patients. SUMMARY

[0007] In one aspect, the present disclosure provides a method of inducing a cellular phenotype of dilated cardiomyopathy (DCM) in a cardiomyocyte. In some embodiments, the method comprises contacting the cardiomyocyte with dobutamine. In some embodiments, themethod comprises contacting the cardiomyocyte with dobutamine and an agent that stabilizes dobutamine. In some embodiments, the agent is ascorbic acid. In some embodiments, the cardiomyocyte is an induced pluripotent stem cell cardiomyocyte (iPSC-CM). In some embodiments, the iPSC-CM is from a subject.

[0008] In another aspect, the present disclosure provides a kit for inducing a cellular phenotype of DCM in a cardiomyocyte, comprising dobutamine.

[0009] In another aspect, the present disclosure provides a method of determining the risk of a subject developing an arrhythmia, comprising characterizing the electrical phenotype of a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity in the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia. In some embodiments, the characterizing is via a multi-electrode array (MEA) recording or an action potential (AP) recording. In some embodiments, the AP recording is a patch-clamp technique. In some embodiments, the arrhythmia is a life-threatening arrhythmia (e.g., a life-threatening ventricular arrhythmia). In some embodiments, detecting EAD, DAD, and / or triggered activity in more than 10% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia.

[0010] In another aspect, the present disclosure provides a method of determining the risk of a subject developing an arrhythmia, comprising detecting one or more abnormal Ca2+movements in a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting one or more abnormal Ca2+movements in more than 20% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia. In some embodiments, the arrhythmia is a life-threatening arrhythmia (e.g., a life-threatening ventricular arrhythmia). In some embodiments, the detecting is via calcium imaging. In some embodiments, the iPSC-CMs have a cellular phenotype of DCM. In some embodiments, the cellular phenotype of DCM is induced by dobutamine. In some embodiments, the cellular phenotype of DCM is induced by dobutamine and an agent that stabilizes dobutamine. In some embodiments, the agent is ascorbic acid.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIGs. 1A and 1B depict experimental design and assessment of contractility in control and DCM iPSC-CMs. (A) Induced pluripotent stem cells (iPSC) from 12 subjects with a history of DCM and age / gender matched 8 healthy controls were obtained from the Stanford Cardiovascular Institute Biobank. All DCM subjects had evidence of contractile dysfunction on cardiac imaging, 7 of the DCM subjects experienced significant ventricular arrhythmia and 5 did not. Induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) were derived from all 20 subjects and assessed with respect to contractility, sarcomere organization, electrical profile (multielectrode array and patch clamp) and Ca2+transients. Results of the cellular phenotype were contrasted with the clinical phenotype in terms of contractile and electrical phenotype to discern the ability of the cellular phenotype to predict the clinical phenotype. (B) Monolayers of iPSC-CMs were plated in 96 well plate format. After recovery cells were treated daily with chemical cocktail or vehicle for 5 days. High resolution videos were obtained at baseline and after 5 days of treatment; results were indexed to the average control contraction velocity for each line (post treatment: control 1.28 + 0.38 and DCM 0.22 + 0.24; p < 0.0001). (All groups compared with One-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, *** p< 0.005, **p<0.005, * p< 0.05, ns nonsignificant).

[0012] FIGs. 2A-2D depict sarcomere organization in control and DCM iPSC-CMs. (A) Sarcomere length distribution as measured by immunofluorescence-stained iPSC-CMs derived from control and DCM subjects before (solid box) and after treatment (striped box) with the chemical stimulation protocol. (B) Representative images of control (WT) sarcomere organization of immunofluorescence-stained iPSC-CMs at baseline (top left panel) and in response to drug treatment (top right panel), and baseline DCM sarcomere organization in immunofluorescence-stained iPSC-CMs at baseline (bottom left panel) and in response to drugtreatment (bottom right panel) (Green: alpha actin, red: troponin, blue: DAPI; scale bar = 8 m).(C) Sarcomere length frequency distribution in aggregate of all control (top) and DCM (bottom) iPSC-CMs before (black) and after (orange) drug treatment (control baseline 1.82 + 0.23 nm and after treatment 1.85 + 0.31, ns; DCM baseline 1.79 + 0.18 nm and after treatment 1.82 + 0.61 nm, p <0.05; n=4,955-7,446 per cohort). (D) Sarcomere organization score computed by automated software in immunofluorescence-stained images of iPSC-CMs derived from control and DCM subjects (control 0.23 + 0.12 and after treatment 0.2 + 0.11, ns; DCM 0.21 + 0.13 and after treatment 0.027 + 0.032, p<0.0001; n=15-25 images per line). For allstatistical comparisons One-way ANOVA was used with Sidak multiple comparisons tests for subgroup comparisons (* p<0.05, *** p< 0.0005, **** p<0.00005, ns p >0.05).

[0013] FIGs.3A-3F depict electrical characterization of DCM iPSC-CMs at the tissue level. (A) Representative signals of Extracellular Field Potential (EFP) signals recorded on CMs derived from one control line (Ctrl) and two dilated cardiomyopathy (DCM) lines with arrhythmic events flagged with a yellow arrow (EADs). (B) Corrected Field potential duration (FPDc) measured on 8 Ctrl iPSC-CM lines (1-8) vs 12 DCM iPSC-CMs (9-20). Each DCM iPSC-CMs set was compared with the average of all the Ctrl lines. (C) Spike amplitude estimation on MEA recordings of Ctrl lines vs DCM derived iPSCs. (D) Beat period variability was expressed in co-variance between each beat (log10) and was evaluated for all Ctrl vs DCM lines. (E) Beat rate was measured for all Ctrl and DCM lines and was expressed in beats per minute. (F) Arrhythmic events frequency estimated in % MEA wells with DCM monolayers showing arrhythmias per well per iPSC line. Comparison between Ctrl lines and DCM lines showing triggered activity (red), EADs (blue) or no events (grey) (Cells with arrhythmia control 0.63 + 1.77, non-arrhythmic DCM 12 + 26.8, arrhythmic DCM 43.4 + 16.6; p <0.0001). (n= 32-97 wells; for all statistical comparisons One-way ANOVA was used with Sidak multiple comparisons tests for subgroup comparisons; * p<0.05, ** p<0.01, *** p< 0.001, **** p<0.0001, ns p >0.05).

[0014] FIGs. 4A-4K depict electrical characterization of DCM iPSC-CMs at the cellular level. (A) Representative recordings of action potential signals using patch clamp in current clamp configuration: control line (1), non-arrhythmic DCM line (10) and one arrhythmic DCM line (11). Arrhythmic events were flagged with a yellow arrow for EADs and red arrow for DADs. (B) Action potential upstroke velocity (dV / dT max) estimation for 3 control lines and 12 DCM lines (n= 6-20). (C) Action Potential Duration (APD) at 90% repolarization interval quantification for the 3 control lines and 12 DCM lines. (D) Arrhythmic event frequency estimated in % cells showing arrhythmias in iPSC-CMs derived from control lines and DCM lines showing DADs (yellow), EADs (blue), triggered Activity (red) or no arrhythmias (grey) (arrhythmic events: control 0; non-arrhythmic DCM 11 + 19.6 events, arrhythmic DCM 44.4 + 16.6 events; p< 0.01). (E) Representative recordings of Ca2+transients using confocal line- scan: control line (3), non-arrhythmic DCM line (10) and one arrhythmic DCM line (11). Cells were loaded with Fluo-4. (F) Ca2+amplitude (F / F0) estimation for 4 control lines and 12 DCM lines. (G) Ca2+Time to Peak for 4 control lines and 12 DCM lines. (H) Ca2+Recapture Decay Tau in 4 control lines and 12 DCM lines. (I) Incidence of abnormal Ca2+movements in iPSC-CMs from 4 control lines and 12 DCM lines (abnormal Ca2+movements: control 1.75 + 3.5, non-arrhythmic DCM 20.2 + 30.2, arrhythmic DCM 42.3 + 19.5; p <0.05). (J) Representative plots of Ca2+sparks in control line, non-arrhythmic DCM line, and arrhythmic DCM line. (K) Ca2+spark rate in iPSC-CMs from 4 control lines and 12 DCM lines. (For patch-clamp recordings n= 6-20, for Ca2+imaging n= 20-65; All comparisons: One Way ANOVA with Sidak multiple comparisons used to compare the mean of individual groups. *p<0.05, **p<0.005, *** p< 0.005, ****p<0,0001).

[0015] FIGs. 5A-5H depict patient-specific iPSC-CMs to inform clinical decision making. (A) Control iPSC-CMs (6): MEA Recording, patch clamp action potentials, late sodium current recordings, and MEA recording following ranolazine treatment. (B) TNNT2 R173W associated DCM iPSC-CMs from subject without arrhythmia (9): MEA recording, patch clamp action potentials, late sodium current recordings, and MEA recording following ranolazine treatment. (C) TNNT2 R173W associated DCM iPSC-CMs from subject with arrhythmia (14): MEA recording (yellow arrows indicate incidence of triggered activity), patch clamp action potentials (red arrows indicating DADs and yellow arrows indicating EADs). Late sodium current recordings, and MEA recording following ranolazine treatment demonstrating resolution of arrhythmia. (D) SCN5A R222Q associated DCM iPSC-CMs from subject without arrhythmia (13): MEA recording, patch clamp action potentials, late sodium current recordings, and MEA recording following ranolazine treatment. (E) SCN5A R814W associated DCM iPSC-CMs from subject with arrhythmia (17): MEA recording (yellow arrows highlight incidence of EADs, patch clamp action potentials (yellow arrow indicates occurrence of EAD), late sodium current (INaL) recordings, and MEA recording following ranolazine treatment showing resolution of arrhythmia. (F) Late sodium current (INaL) recordings in current-clamp configuration from control and DCM iPSC-CMs and graphical representation of the late sodium current density (n=7-10 per line; student’s t-test comparison of mean with mean of control line, ns p> 0.05, * p< 0.05, ** p<0.005). (G) Incidence of arrhythmia on MEA recordings from arrhythmia DCM iPSC-CMs (14 and 17) before and after ranolazine treatment. (n=16 wells per line) (H) Incidence of isolated premature ventricular contractions per hour (PVC count / hr), multiple premature ventricular contractions per hour (PVC runs / hr), and burden of atrial fibrillation (Afib Burden %) extracted from subject 17 clinical data.

[0016] FIG. 6 depicts clinical characteristics of DCM subjects recruited and associated causative variant (if known).

[0017] FIG.7 depicts demographics of control subjects all with no personal or family history of cardiac disease.

[0018] FIG. 8 depicts comparison of drug cocktail versus norepinephrine in inducing contractile dysfunction. iPSC-CMs monolayers were plated in 96 well plate format and then treated with chemical stimulation protocol (Drug), norepinephrine 500 nM (NE), or vehicle (Control) for 5 days. High resolution video recordings were obtained at baseline and following 5 days of treatment and analyzed using software package to compute contraction velocity. (Each data point represents average value for each iPSC-CMs, which is derived from 4-12 biological replicates; n=10-12 for DCM and n=8 for control; All groups compared with One- way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, * p< 0.05, ns nonsignificant).

[0019] FIG. 9 depicts baseline and drug-induced contraction velocity assessment of control and DCM iPSC-CMs. Monolayers of iPSC-CMs were plated in 96 well plate format and after recovery cells were treated with chemical stimulation protocol (drug) or vehicle for 5 days. High resolution videos were obtained at baseline and after 5 days of treatment and results were indexed to the average control contraction velocity. (Data presented as mean with individual values shown; n=16-60 for each iPSC-line; All groups compared with one-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, *** p< 0.005, **p<0.005, * p< 0.05, ns nonsignificant).

[0020] FIG. 10 depicts baseline and drug-induced acceleration assessment of control and DCM iPSC-CMs. Monolayers of iPSC-CMs were plated in 96 well plate format and after recovery cells were treated with chemical stimulation protocol (drug) or vehicle for 5 days. High resolution videos were obtained at baseline and after 5 days of treatment and results were indexed to the average control acceleration velocity. (Data presented as mean with individual shown values n=16-60 for each iPSC-line; All groups compared with one-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, *** p< 0.005, **p<0.005, * p< 0.05, ns nonsignificant).

[0021] FIG. 11 depicts baseline and drug-induced relaxation velocity assessment of control and DCM iPSC-CMs. Monolayers of iPSC-CMs were plated in 96 well plate format and after recovery cells were treated with chemical stimulation protocol (drug) or vehicle for 5 days. High resolution videos were obtained at baseline and after 5 days of treatment and results were indexed to the average control contraction velocity. (Data presented as mean with individualshown values n=16-60 for each iPSC-line; All groups compared with one-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, *** p< 0.005, **p<0.005, * p< 0.05, ns nonsignificant).

[0022] FIG. 12 depicts baseline sarcomere length distribution in control, sarcomere, and non-sarcomere associated DCM. Sarcomere length distribution as measured by immunofluorescence-stained iPSC-CMs derived from control and DCM subjects at baseline. (n=287-345 per condition; One-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups, **** p<0.0005, ns nonsignificant).

[0023] FIG. 13 depicts baseline sarcomere organization score in control and DCM iPSC- CMs. Sarcomere organization score as measured by automated software from immunofluorescence-stained iPSC-CMs images from control and DCM. (n=15-25 per condition; One-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, ns nonsignificant)

[0024] FIG. 14 depicts baseline sarcomere organization score in sarcomere vs non- sarcomere DCM iPSC-CMs. Sarcomere organization score as measured by automated software from immunofluorescence-stained iPSC-CMs images from sarcomere vs non-sarcomere DCM. (n=15-25 per condition; One-way ANOVA with Sidak multiple comparisons used to compare mean of individual groups; **** p<0.0005, ns nonsignificant).

[0025] FIG.15 depicts representative MEA recordings of DCM iPSC-CMs.

[0026] FIG. 16 depicts incidence of arrhythmic susceptibility events in control and DCM iPSC-CMs. Arrhythmic susceptibility was assessed in 12 DCM lines and 8 control lines using MEA technique. Abnormal electric patterns were detected, quantified, and characterized as conduction defects (CD), electrical alternances (Alt) and pauses (Pauses) and were found more prevalent in DCM lines compared to control lines. (n=32-97 wells per iPSC line).

[0027] FIG.17 depicts patch-clamp and voltage-clamp solution composition.

[0028] FIG. 18 depicts action potential characteristics of DCM and representative control iPSC-CMs.

[0029] FIG.19 depicts representative Ca2+transients tracings for DCM iPSC-CMs.DETAILED DESCRIPTION

[0030] Dilated cardiomyopathy (DCM) is a common inherited heart condition that is associated with development of syndrome of heart failure and the need for heart transplantation. The disorder has genetic components, but clinical genetic testing only identifies causative variants in 20-30% of cases. This leaves at risk subjects or borderline cases without the ability to determine their risk of developing disease or a clear diagnosis.

[0031] Cardiomyocytes (also known as cardiac muscle cells), are the contractile myocytes of the cardiac muscle. Cardiomyocytes in the myocardium differentiate into muscular cells which transmit electrical signals (e.g., action potential) through the gap junctions, and coordinate the contractile activity of the muscle. Induced Pluripotent Stem Cell Cardiomyocytes (iPSC-CMs) provide cellular models of human cardiomyocytes that encode the host genetic information. Multiple groups have shown the ability of the cells to model some features of dilated cardiomyopathy for scientific investigation purposes, but no single protocol has shown reliability in being able to unmask DCM features at the cellular level across different causes of DCM. Devising a method to reliably recapitulate the cellular phenotype in the dish would allow for the use of the cellular phenotype as a diagnostic tool that goes beyond knowing the genotype since the cells recapitulate the host’s entire genome.

[0032] There is currently no reliable method to produce this phenotype in iPSC-CMs and using iPSC-CMs cellular phenotype for clinical decision making is not currently part of standard clinical practice. The platform represents an analogous approach to using genetic testing for understanding an individual’s disease risk and diagnosis. DEFINITIONS

[0033] Unless specifically indicated otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this disclosure belongs. In addition, any method or material similar or equivalent to a method or material described herein can be used in the practice of the present disclosure. For purposes of the present disclosure, the following terms are defined.

[0034] The terms “a,” “an,” or “the” as used herein not only include aspects with one member, but also include aspects with more than one member. For instance, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a cell” includes a plurality of such cells and reference to “the agent” includes reference to one or more agents known to those skilled in the art, and so forth.

[0035] In the present application, the term “comprise” generally refers to the meaning of including, inclusive, containing, or encompassing. In some cases, it also means “is / are” and “consist of”.

[0036] “Subject,” “patient,” “individual” and like terms are used interchangeably and refer to, except where indicated, mammals such as humans and non-human primates, as well as rabbits, rats, mice, goats, pigs, dogs, cats, and other mammalian species. The term does not necessarily indicate that the subject has been diagnosed with a particular disease but typically refers to an individual under medical supervision. A patient can be an individual that is seeking treatment, monitoring, adjustment or modification of an existing therapeutic regimen, etc. DESCRIPTION OF THE EMBODIMENTS

[0037] In one aspect, the present disclosure provides a novel method that recapitulates features of DCM in a cardiomyocyte. DCM is phenotypically characterized by dilation of the left ventricular chamber, and it is often accompanied by changes in cellular and tissue organization, including lengthening of individual myocytes and fibrosis-induced stiffening of the myocardial tissue. In some embodiments, the method can induce a cellular phenotype of DCM in the cardiomyocyte. As disclosed herein, inducing a cellular phenotype of DCM refers to triggering or causing cellular and molecular changes in cardiomyocytes and / or cardiac tissue that mimic the characteristic features of DCM. This process can be achieved through genetic, biochemical, mechanical, or pharmacological interventions that replicate the structural, functional, and signaling abnormalities observed in DCM. The cellular phenotype associated with DCM includes, but is not limited to, contractile dysfunction, sarcomere disorganization, calcium handling abnormalities, cellular remodeling, and extracellular matrix alterations.

[0038] In some embodiments, the cellular phenotype of DCM in a cardiomyocyte is induced through contacting the cardiomyocyte with dobutamine. Dobutamine is a 1-adrenergic agonist which stimulates 1-adrenoceptors of heart cells (e.g., cardiomyocytes) and increases contractility and cardiac output of the heart. Dobutamine can be used in the treatment of cardiogenic shock (as a result of inadequate tissue perfusion) and severe heart failure. Dobutamine comprises a chemical structure shown below:.

[0039] In some embodiments, the method further comprises contacting the cardiomyocyte with an agent that stabilizes dobutamine in cell culture. In some embodiments, the agent (or the stabilizer) is ascorbic acid. Ascorbic acid (also known as Vitamin C or ascorbate) is a water-soluble vitamin essential for tissue repair, supporting the immune system, and functioning as an antioxidant. Ascorbic acid comprises a chemical structure shown below:.

[0040] In some instances, the cardiomyocyte is exposed to dobutamine without ascorbic acid. In other instances, the cardiomyocyte is exposed to both dobutamine and ascorbic acid. In some embodiments, ascorbic acid stabilizes dobutamine in cell culture, thereby facilitating the induction of a cellular phenotype associated with DCM in cardiomyocytes.

[0041] In some embodiments, the cardiomyocyte is a primary cardiomyocyte isolated from a subject. In some embodiments, the cardiomyocyte is an induced pluripotent stem cell cardiomyocyte (iPSC-CM). In some embodiments, the iPSC-CMs are derived from a subject. In some embodiments, the method can be used to diagnose dilated cardiomyopathy and / or identify subjects at risk for developing dilated cardiomyopathy. In some embodiments, the method can be used to support the treatment of DCM in subjects. In some embodiments, the method can be used to monitor disease progress of DCM and / or the effectiveness of DCM treatment in subjects.

[0042] In one particular embodiment, the method comprises: 1. plating iPSC-CMs on a 96 well plate at a density of 125-175 K cells / well, 2. after recovering the cells (5-7) days, baseline video recordings are obtained to derive the contraction velocity and / or rate of acceleration of beating iPSC-CMs,3. the cells are treated daily for 5 days with a drug cocktail daily, wherein the drug cocktail comprises 35μM dobutamine and 1mM of ascorbic acid, 4. Following 5 days of treatment, repeat video recordings are obtained to derive the contraction velocity and / or rate of acceleration of beating iPSC-CMs, and 5. DCM iPSC-CMs show a statistically significant reduction in contraction velocity and rate of acceleration, while non-DCM iPSC-CMs do not show a statistically significant drop in either parameter.

[0043] In some embodiments, the method can be used to examine sarcomere disorganization (a feature of DCM). Instead of video recordings, sarcomere length distribution frequency curve is plotted for untreated and after 5 days of treatment with drug cocktail. DCM iPSC-CMs show a broadening of the frequency distribution curve with more outliers, while non-DCM iPSC- CMs maintain a relatively preserved distribution.

[0044] In another aspect, the present disclosure provides a novel method for risk stratification of sudden cardiac death in patients with DCM. Patients with DCM have a risk of dying suddenly from lethal arrhythmias. The field utilizes a risk stratification paradigm that relies on the degree of contraction impairment, which more recent studies show is ineffective in dilated cardiomyopathy patients. While there are some general clinical markers that seem to be associated with increased risk, no clear risk algorithm or score system has been devised to guide the field. The intervention to prevent sudden cardiac death in these patients is called an implantable cardiac defibrillator, which is an invasive device that carries its own risks and thus cannot be used indiscriminately in everyone. Having a personalized tool that can predict the risk of sudden cardiac death can be helpful in risk stratifying patients and provide more targeted approach to delivering early preventive therapy.

[0045] The present disclosure describes a method that utilizes induced pluripotent stem cell- derived cardiomyocytes (iPSC-CMs) from a subject (such as a patient with DCM) to evaluate the subject’s risk of developing arrhythmia. As disclosed herein, iPSC-CMs can recapitulate the biology of the subject’s heart cells largely by encoding all the proteins dictated by a subject’s genome. This allows the iPSC-CMs to act as a simplified version of the “genetic-read out”. The methods disclosed herein can be reliably used to provide predictive information on the risk of developing clinically significant ventricular arrhythmias (sustained VT, VF), which are high risk features for sudden cardiac death. The present disclosure provides superior ability to provide a personalized platform to quantify individual risk of arrhythmia. Currently noclinical risk score or polygenic risk score exists for risk stratification. This present disclosure provides an advantage over the current paradigm.

[0046] In some embodiments, the method comprises differentiating induced-pluripotent stem cells (iPSC-CMs) into cardiomyocytes and utilizing a multi-electrode array, a patch- clamp recording, and / or calcium imaging to profile the cells.

[0047] In some embodiments, the present disclosure provides a method of determining a risk of a subject developing an arrhythmia, comprising characterizing an electrical phenotype of a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject. In some embodiments, the electrical phenotype comprises early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity. As disclosed herein, afterdepolarizations (ADs) are abnormal depolarizations of cardiac myocytes that interrupt phase 2, phase 3, or phase 4 of the cardiac action potential in the electrical conduction system of the heart. Early afterdepolarizations (EADs) occur with abnormal depolarization during phase 2 or phase 3 and are caused by an increase in the frequency of abortive action potentials before normal repolarization is completed. Delayed afterdepolarizations (DADs) begin during phase 4, after repolarization is completed but before another action potential would normally occur via the normal conduction systems of the heart. Triggered activity is caused by ADs. When either EAD or DAD is strong enough to reach a threshold potential for activation of a regenerative inward current, it leads to a new action potential as “triggered activity”.

[0048] In some embodiments, detecting early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity in more than 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25% of iPSC-CMs indicates that the subject is at risk of developing an arrhythmia. In some embodiments, a detection of more than 10% of iPSC-CMs having early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity indicates the subject is at risk of developing an arrhythmia. In some embodiments, the characterizing is via a multi-electrode array (MEA) recording, a patch clamp recording, and / or an action potential (AP) recording.

[0049] In some embodiments, a detection of more than 10% of iPSC-CMs having early afterdepolarization and / or triggered activity on multielectrode array predicts a risk of developing a clinically significant arrhythmia with 100% sensitivity and 92% specificity.

[0050] In some embodiments, a detection of more than 10% of iPSC-CMs having early afterdepolarizations, delayed afterdepolarizations, and / or triggered activity predicts a risk of developing a clinically significant arrhythmia with 100% sensitivity and 92% specificity.

[0051] In some embodiments, the present disclosure provides a method of determining a risk of a subject developing an arrhythmia, comprising detecting one or more abnormal Ca2+movements in a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject. In some embodiments, detecting one or more abnormal Ca2+movements in more than 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, or 40% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia. In some embodiments, detecting one or more abnormal Ca2+movements in more than 20% of the iPSC-CMs determines the subject is at risk of developing an arrhythmia. In some embodiments, the detecting is via calcium imaging.

[0052] In some embodiments, detecting one or more abnormal Ca2+movements in more than 20% of iPSC-CMs predicts a risk of developing a clinically significant arrhythmia with 100% sensitivity and 92% specificity.

[0053] In some embodiments, the iPSC-CMs have a cellular phenotype of DCM. In some embodiments, the cellular phenotype of DCM is induced by dobutamine. In some embodiments, the cellular phenotype of DCM is induced by dobutamine and ascorbic acid.

[0054] In some embodiments, the method comprises differentiating induced-pluripotent stem cells (iPSC-CMs) into cardiomyocytes and utilizing a multi-electrode array, a patch- clamp recording, and / or calcium imaging to profile the cells.

[0055] In some embodiments, the method can be used to determine an individual risk of arrhythmia. In some embodiments, the individual is diagnosed with DCM. In some embodiments, the individual has uncertain significance of DCM. In some embodiments, the individual has genetically idiopathic dilated cardiomyopathy.

[0056] The methods disclosed herein can be used on all individuals with DCM or potentially having DCM to provide prognostic information about their arrhythmia risk. The methods can serve as a complimentary tool to existing clinical data used to decide on patients undergoing an implantable cardiac defibrillator.

[0057] In another aspect, the present disclosure provides a kit for inducing a cellular phenotype of DCM in a cardiomyocyte. Materials and reagents to carry out the variousmethods of the present disclosure can be provided in kits to facilitate execution of the methods. As used herein, the term “kit” includes a combination of articles that facilitates a process, assay, analysis, or manipulation. In particular, kits of the present disclosure find utility in a wide range of applications including, for example, diagnostics, prognostics, therapy, and the like.

[0058] In some embodiments, the kit comprises dobutamine. In some embodiments, the kit comprises dobutamine and ascorbic acid. In some embodiments, the kit further comprises one or more cardiomyocytes. In some embodiments, the one or more cardiomyocytes are induced pluripotent stem cell cardiomyocytes (iPSC-CMs). In some embodiments, the kit comprises materials and / or reagents to isolate cardiomyocytes from a subject. In some embodiments, the kit comprises materials and / or reagents to obtain induced pluripotent stem cells (iPSCs) from a subject. In some embodiments, the kit comprises materials and / or reagents to differentiate iPSCs into cardiomyocytes. In addition, the kits of the present disclosure can include, without limitation, instructions to the kit user, apparatus and reagents for sample collection and / or purification, apparatus and reagents for characterizing the electrical phenotype of iPSC-CMs, apparatus and reagents for detecting Ca2+movements in iPSC-CMs, apparatus and reagents for determining the level(s) of biomarker(s) and / or the activity and / or number of immune cells, sample tubes, holders, trays, racks, dishes, plates, solutions, buffers or other chemical reagents, suitable samples to be used for standardization, normalization, and / or control samples. Examples

[0059] The present disclosure will be described in greater detail by way of specific examples. The following examples are offered for illustrative purposes only, and are not intended to limit the invention in any manner. Those of skill in the art will readily recognize a variety of noncritical parameters which can be changed or modified to yield essentially the same results. Example 1. Patient-Specific Induced Pluripotent Stem-Cell Phenotypes Inform Clinical Decision Making in Dilated Cardiomyopathy

[0060] Dilated cardiomyopathy (DCM) is a disorder of structural remodeling that leads to worsening cardiac function, increased risk of arrhythmias, and sudden cardiac death. Despite impressive advances in preventive and therapeutic strategies, current clinical approaches have significant limitations in determining individual risk of developing DCM and the risk of arrhythmia even in those with known DCM. A cohort of induced pluripotent stem cells from DCM subjects with diverse genetic backgrounds and matched controls was procured and differentiated into cardiomyocytes (iPSC-CMs). Treatment of iPSC-CMs with a novelchemical protocol demonstrated robust contractility changes that distinguished DCM from control iPSC-CMs. Furthermore, detailed electrical and Ca2+transient iPSC-CMs profiles demonstrated 95% accuracy in identifying subjects who developed clinically significant arrhythmias. The ability to recapitulate electrical and mechanical dysfunction included DCM subjects with genetically idiopathic disease and subjects with the same DCM causative variants with variable clinical phenotypes. These findings represent a novel paradigm using iPSC-CMs to individualize the clinical care for DCM patients.

[0061] Here we identified a personalized risk stratification paradigm for DCM patients that predicted individual-level risk of mechanical dysfunction and significant arrhythmia using the functional phenotype of patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). We successfully recapitulated single-cell mechanical dysfunction features using a novel protocol that unmasked the phenotype in DCM, but not in control iPSC-CMs. Then we tested cellular predispositions to arrhythmia at the single-cell and multicellular level. Our approach successfully identified all DCM patients at high risk for ventricular arrhythmias. We explore how this model can lead to a tailored clinical approach to managing DCM patients (FIG.1A). Results: Patient Cohort

[0062] We obtained iPSCs from a cohort of 20 subjects that were differentiated into cardiomyocytes.19Twelve subjects with known DCM and 8 healthy control subjects with no personal history of cardiac disorders. Clinical characteristics of the DCM cohort are detailed in FIG.6. Of the 12 patients with DCM, 7 had a history of significant ventricular arrhythmias defined as ventricular fibrillation or ventricular tachycardia. Ten of the DCM subjects had a known pathogenic or likely pathogenic variant on clinical genetic testing, 1 subject had a variant of uncertain significance, and another subject had no identifiable rare variants on clinical genetic testing despite a familial pattern of cardiomyopathy. DCM subjects without arrhythmia had a similar distribution of systolic function. Five subjects underwent heart transplantation or LVAD implantation consistent with a severe mechanical dysfunction phenotype. The control cohort had no personal history of cardiac disorders and was chosen to match the gender and age range profile of the DCM cohort (FIG.7). Contractile Dysfunction

[0063] We examined contraction velocity using high frame rate video microscopy recordings of differentiated iPSC-CMs to validate the ability of the cells to recapitulate contractile dysfunction features and confirm DCM phenotype for each of the cell lines investigated. We did not observe statistically significant differences in contractility at baseline. Chemical stimulation with norepinephrine failed to demonstrate a consistent phenotype of mechanical dysfunction across the entire cohort (FIG. 8). Instead, we used a novel chemical stimulation protocol, that included dobutamine, to unmask contractile dysfunction in DCM iPSC-CMs. After 5 days of treatment, we observed a reduction in contraction velocity in all DCM iPSC- CMs compared to the untreated group and no change or an increase in contraction velocity in the control iPSC-CMs (FIG. 1B and FIG. 9). We did not identify a correlation between the severity of contractile dysfunction at the clinical and iPSC-CMs levels. Acceleration rates were even more divergent in response to drug treatment between DCM and control iPSC-CMs (FIG. 10). Relaxation velocity was reduced in 9 of the 12 DCM lines compared to none of the control iPSC-CMs in response to drug stimulation (FIG.11). Thus, all DCM iPSC-CMs, including the two lines with genetically uncertain etiologies, recapitulated mechanical dysfunction at the single cell level.

[0064] To further validate the ability of iPSC-CMs to recapitulate single-cell features of DCM, we examined the degree of sarcomere disorganization in control and DCM using immunohistochemical staining. At baseline, sarcomere length distribution was highly conserved within each iPSC-CMs line demonstrating little variance in sarcomere length distribution. There was a small, albeit statistically significant, difference in the average sarcomere length between control and DCM iPSC-CMs, which was largely driven by the non- sarcomere associated DCM iPSC-CMs, but the distribution of length was similar (FIG. 12). We assessed the uniformity of the alignment angle of sarcomeres within iPSC-CMs using a computationally derived quantitative score (sarcomere organization score).20At baseline 2 of the12 DCM lines exhibited significantly reduced sarcomere organization scores compared to control iPSC-CMs (FIG. 13). Sarcomere organization scores from iPSC-CMs from DCM associated with sarcomere variants or non-sarcomere variants did not differ significantly (FIG. 14).

[0065] We used the chemical stimulation performed in contractility assessment to evaluate if this uncovers structural differences between control and DCM iPSC-CMs. In response to drug treatment, we observed a widening in sarcomere length distribution in DCM iPSC-CMs compared to control iPSC-CMs, reflective of significant sarcomere disorganization in DCMiPSC-CMs (FIGs.2A and 2B). The sarcomere disorganization was driven by a change in the distribution of sarcomere lengths from a normal distribution to a broader distribution with more deviation from the median sarcomere length. Conversely, control iPSC-CMs exhibited more preserved (narrower) distribution following drug treatment (FIG.2C). Sarcomere organization scores did not exhibit significant change in control iPSC-CMs, whereas 11 of the 12 DCM iPSC-CMs experienced significant reduction in sarcomere organization scores (FIG.2D). The aggregate of our findings suggests that sarcomere disorganization, driven by dispersed length distribution and worsening alignment of sarcomeres, in response to chemical stimulation can reliably distinguish DCM from control iPSC-CMs. Electrical Dysfunction

[0066] To evaluate the electrical phenotype of DCM iPSC-CMs and their arrhythmogenic potential, we pursued multi-electrode array (MEA) recordings of monolayer DCM iPSC-CMs and control iPSC-CMs (FIG.3A and FIG.15). Extracellular field potentials were recorded on both groups at baseline. Corrected field potential duration (FPD), which represents repolarization duration, was significantly prolonged in all DCM iPSC-CMs compared to control cells (FIG. 3B). Spike amplitude (SA), which reflects the electrical depolarization speed, was considerably variable among DCM iPSC-CMs with 4 lines exhibiting higher SA compared to control and 8 exhibiting SA lower than controls iPSC-CMs (FIG.3C). Beat period variability, which is considered a substrate for triggering arrhythmia, was significantly increased in 5 of the DCM lines compared to control iPSC-CMs (FIG.3D). The baseline beat rate (BR) was higher in 5 of the 12 DCM iPSC-CMs compared to control lines and lower in 4 of the DCM lines (FIG.3E).

[0067] We examined the incidence of arrhythmic events, defined as early afterdepolarizations (EADs) and / or triggered activity, on MEA recordings from DCM and control iPSC-CMs. In the DCM cohort, we observed 8 lines with a high incidence of arrhythmic events (2 lines exhibiting EADs only, 2 lines with triggered activity only, and 4 showed both arrhythmic events) compared to control cell lines (FIG. 3F). The 4 remaining DCM lines exhibited no arrhythmic events despite disturbed electrical parameters. Arrhythmic susceptibility events were broadly observed in all DCM and some control lines but did not correlate with the incidence of clinical arrhythmia (FIG.16). The degree of FPD prolongation or beat period variability did not correlate with the incidence of arrhythmic events in iPSC- CMs nor with clinically significant arrhythmias. Arrhythmic events on MEA recordings(threshold >10%) of patient-specific iPSC-CMs predicted the incidence of clinically significant ventricular arrhythmias with 100% sensitivity and 92% specificity. The predictive ability was preserved in sarcomere and non-sarcomere associated DCM. Single Cell Electrical Phenotype and Intracellular Calcium Handling

[0068] To further investigate the cellular susceptibility and mechanism of arrhythmias observed on MEA, we performed single cell electrophysiology using patch clamp technique in current clamp configuration (FIGs.4A, 17, and 18). Recordings of DCM iPSC-CMs exhibited a wide range of dV / dT max velocities with 9 DCM iPSC-CMs showing significantly lower velocities compared to control iPSC-CMs (FIG. 4B). Consistent with the MEA results, prolonged action potential duration (APD) on action potential (AP) recordings did not systematically foreshadow arrhythmic events (FIG. 4C). Repolarization disturbances such as EADs, delayed afterdepolarizations (DADs) that frequently developed into triggered activity were flagged in 9 DCM lines and none were observed in control lines (FIG. 4D). The DCM lines exhibiting arrhythmias on MEA recordings showed consistent events at the cellular level. Arrhythmic events on AP recordings (>10% threshold) predicted the incidence of clinically significant arrhythmias with 100% sensitivity and 92% specificity.

[0069] DCM has been associated with Ca2+handling abnormalities and is often cited as a driving mechanism for increased arrhythmia incidence. To discern if observed arrhythmic events at the electrical level were driven by Ca2+kinetic defects, we performed Ca2+transient recordings using confocal microscopy and Ca2+sensitive dye on the 12 DCM iPSC-CMs and representative control lines (FIG. 4E and FIG. 19). We observed a reduction in peak Ca2+amplitude in 6 of the 12 DCM iPSC-CMs and 1 DCM iPSC-CM line exhibited a significantly higher transient amplitude (FIG. 4F). In addition, all DCM iPSC-CMs exhibited a prolonged time to peak Ca2+amplitude compared to control iPSC-CMs (FIG.4G). Prolongation in decay tau was observed in 7 of the 12 DCM iPSC-CMs compared to controls (FIG.4H). The reduced peak amplitude, and delay in time to peak Ca2+amplitude is consistent with published reports of reduced and slower Ca2+decay from the SR affecting sarcomere Ca2+interactions in DCM.21,22The results support abnormal Ca2+handling being a feature of DCM at the cellular level, but each DCM line exhibited an individual signature of altered parameters.

[0070] Furthermore, we observed abnormal Ca2+movements during both systolic and diastolic phases of the Ca2+transient in 11 of the 12 DCM iPSC-CMs and 1 out of 4 control iPSC-CMs (FIG. 4I). There was a direct correlation between a high % of cells exhibitingabnormal Ca2+events and the incidence of electrical events on MEA, action potential recordings, and clinical arrhythmias. Lines exhibiting more than 20% of cells with abnormal Ca2+movements, predicted clinically significant arrhythmia with 100% sensitivity and 92% specificity. In the diastolic phase, we observed a global increase in Ca2+sparks frequency in 5 of the 12 DCM iPSC-CMs compared to control cells (FIGs.4J and 4K), with all 5 lines being derived from individuals with clinical arrhythmia. This supports Ca2+dependent and independent mechanisms driving observed arrhythmia in our DCM cohort. Mechanism of Arrhythmia and Predicting Clinical Phenotype

[0071] To further elucidate the ability of iPSC-CMs to delineate mechanisms of DCM and inform individual clinical decision making, we undertook pairwise comparisons of DCM iPSC- CMs. We examined pairs of iPSC-CMs of two DCM subjects from the same family with the same TNNT2 causative variant (R173W) and two unrelated DCM subjects with SCN5A causative variant (R222Q and R814W).19

[0072] We evaluated a pair of DCM affected iPSC-CMs derived from two family members with DCM caused by the same TNNT2 variant; one subject exhibiting arrhythmia (subject 14) while the other did not, despite having severe contractile dysfunction (subject 9). This phenomenon has long been clinically recognized that even within families with identical causative variants for DCM, there is considerable variability to arrhythmic phenotypes appearance. Similar to the clinical phenotypes, both iPSC-CMs lines demonstrated evidence of contractile dysfunction, but only iPSC-CMs from subject 14 demonstrated arrhythmia on MEA and action potential recordings (FIGs. 5A-C). A parameter implicated in DCM-related arrhythmia is an increase in late sodium current (INaL) leading us to examine the current in both DCM lines.23We confirmed a prominent INaLin iPSC-CMs from subject 14, but not subject 9, on voltage clamp recording explaining an important contributory mechanism driving the differential electrical profile observed in both lines (FIGs. 5B, 5C, and 5G). We then proceeded to treat both lines with ranolazine (INaL blocker) which successfully abated the arrhythmia in line 14 with no difference in line 9 suggesting a potential benefit to blocking INaL (FIGs.5C and 5G). Although both subjects are carriers of the same variant and are first-degree relatives, these results mirror the clinical phenotype of increased arrhythmia burden observed in subject 14. Thus, the patient-specific cellular data provides additional insight into arrhythmic propensity that could factor into the decision making for pursuing an ICD for primary prophylaxis against SCD and the potential for therapeutic benefit for INaL blocking.

[0073] Subsequently, we focused on two subjects with causative SCN5A DCM variants. SCN5A variants have historically been associated with increased risk of arrhythmia.24We observed FPD / APD prolongation along with arrhythmic events on MEA and AP recordings in iPSC-CMs from subject 17. iPSC-CMs from subject 13, despite having prolonged FPD / APD, did not exhibit arrhythmia (FIGs. 5D and 5E). Given that the causative variant in both cases affects the voltage gated sodium channel, NaV1.5, which is known to cause repolarization delay through increased INaL; we focused on this current to decipher the mechanism of arrhythmia. We observed an increase in INaLdensity in subject 17 iPSC-CMs compared to subject 13 iPSC- CMs although both were significantly higher than the current recorded in control iPSC-CMs (FIGs.5D-5F). Furthermore, treating iPSC-CMs from subject 17 with ranolazine (INaLblocker) eliminated the observed arrhythmia, suggesting a therapeutic benefit to the treatment with INaL blocker (FIGs. 5E and 5G). These findings were shared with the clinical treatment team for subject 17, who exhibited a high burden of arrhythmia refractory to multiple anti-arrhythmic medications. The clinical treatment team elected to treat the patient with ranolazine, resulting in improvement in her burden of arrhythmia on subsequent device interrogation, mirroring the improvement seen at the iPSC-CMs level (FIG. 5H). In this case, iPSC-CMs provided individual-level insight into the mechanism of disease, beyond a genotype-based approach, that informed clinical decision making and offered a tailored drug option to manage this DCM patient. Discussion:

[0074] In the present study, we determined that DCM iPSC-CMs predict individual level clinical phenotypes with high accuracy. We identified consistent single-cell mechanical dysfunction features that can be used to identify individuals at risk for DCM across a broad range of genotypes and clinical phenotype severity. Furthermore, we observed a 95% accuracy in predicting individual risk of clinically significant ventricular arrhythmias when arrhythmic events were detected on iPSC-CMs electrical recordings. These findings transcended genotype causes of DCM and identified underlying mechanisms that informed novel therapeutic approaches. This supports the utility of iPSC-CMs as adjuncts in informing diagnosis, risk stratification, and personalized treatment in DCM.

[0075] We developed a novel chemical protocol that identifies a consistent phenotype across a genetically heterogenous population of DCM iPSC-CMs with 100% accuracy in discriminating between control and DCM iPSC-CMs. This includes iPSC-CMs from subjectswith non-sarcomere variants and genetically indeterminate etiologies. This can serve as an alternative or adjuvant to genetic testing in informing an individual’s clinical risk for DCM in cases where genetic testing fails to identify a pathogenic or likely pathogenic variant, which is approximately 70% of patients with DCM. Features of mechanical dysfunction have been successfully recapitulated in DCM iPSC-CMs by multiple groups, but the specific phenotypic features and the protocols used to identify these changes have been highly variable.25–32Our chemical cocktail includes dobutamine, a beta-adrenergic receptor agonist, which is known to be a potent inotropic stimulator that increases contractility. In clinical studies dobutamine is associated with long-term worse DCM outcomes, which may explain its ability to unmask contractile dysfunction at the single cell level.33Use of three dimensional constructs and maturation approaches can likely provide superior ability to model DCM and mechanisms of disease, but we prioritized developing an accessible standardized diagnostic approach that can be adopted broadly with good discrimination function to aid in clinical decision making.

[0076] We observed that the arrhythmogenic predisposition in DCM affected patients are predicted at the cellular level in iPSC-CMs. The mechanisms of the arrhythmic events were related to single cell electrical disturbances or intracellular Ca2+handling defects recapitulated at the iPSC-CMs level. MEA offers robust accuracy and high-throughput potential as a screening test for arrhythmic risk. One DCM line showed a false positive phenotype on all electrical evaluations; interestingly the patient had a long-standing high burden of premature ventricular contractions that required multiple ablation procedures – thus the single cell phenotype correlated to an increased clinical propensity to triggered activity, but not in a sustained manner.

[0077] Clinically significant arrhythmias in DCM are at least in part mediated by organ level structural changes and scar formation, but those factors are insufficient to explain the variability in arrhythmia risk observed. Our data supports findings from other groups that genetic factors are independent drivers of clinically significant arrhythmia.34–36With the exception of LMNA variants, there are no genotype-based guidelines or polygenic risk scores to aid arrhythmic risk stratification in DCM.17We demonstrate the ability of patient-specific iPSC-CMs to decipher the arrhythmogenic predispositions at the individual level beyond known genetic predictors. iPSC-CMs were able to discern arrhythmic risk between subjects with causative variants in the same gene and even the same causative variant. To our knowledge this approach represents the first use of patient-specific iPSC-CMs as an individualized clinical risk assessment tool to inform clinical decision making at the cohort level.

[0078] By identifying the underlying mechanism driving observed arrhythmia, iPSC-CMs offer the opportunity to inform targeted therapy in DCM patients. We identified two cases in which a prominent INaL was a driver of arrhythmia independent of genotype. These results guided the clinical decision to use the INaLblocker, ranolazine, which resulted in clinical efficacy in one of the patients. A clinical study with another INaLblocker, eleclazine, failed to show therapeutic benefits in a broader population of patients with reduced LVEF and ventricular arrhythmias.37This is in line with our iPSC-CM findings that the mechanisms of arrhythmia in DCM are diverse and only a subset of patients may derive a benefit from INaLcurrent blockade. Whether this benefit would translate to a long-term favorable outcome is unknown, but iPSC-CMs may provide a mechanism-based tailored approach to initiate anti- arrhythmic drug therapy beyond the current empiric approach used clinically.

[0079] Collectively, we demonstrate that patient-specific iPSC-CMs can provide powerful prognostic information that can be clinically meaningful in the management of DCM patients. So far iPSC-CMs have proven a useful tool for disease modeling in various forms of DCM, but our findings identify clinically relevant cellular-clinical phenotype correlations in DCM. This represents the first effort to use patient-specific iPSC-CMs cellular phenotype as a decision- making tool for individualized clinical care in DCM. The platform is unlikely to replace current clinical tools used to evaluate DCM patients but can provide valuable complementary data to aid in predictive risk stratification of systolic dysfunction and arrhythmia in DCM. Further studies exploring larger cohorts with a wider genetic pool will be important to translate the use of patient-specific cellular phenotypes for clinical decision making in DCM. References: 1. Hershberger, R. E., Hedges, D. J. & Morales, A. Dilated cardiomyopathy: the complexity of a diverse genetic architecture. Nat Rev Cardiol 10, 531–547 (2013). 2. Weintraub, R. G., Semsarian, C. & Macdonald, P. Dilated cardiomyopathy. Lancet 390, 400–414 (2017). 3. Verdonschot, J. A. J. et al. Implications of Genetic Testing in Dilated Cardiomyopathy. Circulation: Genomic and Precision Medicine 13, 476–487 (2020). 4. Dellefave-Castillo, L. M. et al. Assessment of the Diagnostic Yield of Combined Cardiomyopathy and Arrhythmia Genetic Testing. JAMA Cardiology 7, 966–974 (2022).5. Musunuru, K. et al. Genetic Testing for Inherited Cardiovascular Diseases: A Scientific Statement From the American Heart Association. Circulation: Genomic and Precision Medicine 13, e000067 (2020). 6. Hershberger, R. E. et al. Genetic Evaluation of Cardiomyopathy—A Heart Failure Society of America Practice Guideline. Journal of Cardiac Failure 24, 281–302 (2018). 7. Catchpool, M. et al. A cost-effectiveness model of genetic testing and periodical clinical screening for the evaluation of families with dilated cardiomyopathy. Genet Med 21, 2815–2822 (2019). 8. Køber, L. et al. Defibrillator Implantation in Patients with Nonischemic Systolic Heart Failure. N Engl J Med 375, 1221–1230 (2016). 9. Bardy, G. H. et al. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med 352, 225–237 (2005). 10. Kadish, A. et al. Prophylactic Defibrillator Implantation in Patients with Nonischemic Dilated Cardiomyopathy. N Engl J Med 350, 2151–2158 (2004). 11. Sears, S. F. et al. Assessing the Psychosocial Impact of the ICD: A National Survey of Implantable Cardioverter Defibrillator Health Care Providers. Pacing and Clinical Electrophysiology 23, 939–945 (2000). 12. Mark, D. B. et al. Cost-Effectiveness of Defibrillator Therapy or Amiodarone in Chronic Stable Heart Failure. Circulation 114, 135–142 (2006). 13. Halliday, B. P. et al. Association Between Midwall Late Gadolinium Enhancement and Sudden Cardiac Death in Patients With Dilated Cardiomyopathy and Mild and Moderate Left Ventricular Systolic Dysfunction. Circulation 135, 2106–2115 (2017). 14. Iles, L. et al. Myocardial fibrosis predicts appropriate device therapy in patients with implantable cardioverter-defibrillators for primary prevention of sudden cardiac death. J Am Coll Cardiol 57, 821–828 (2011). 15. Wu, K. C. et al. Late gadolinium enhancement by cardiovascular magnetic resonance heralds an adverse prognosis in nonischemic cardiomyopathy. J Am Coll Cardiol 51, 2414– 2421 (2008). 16. Sammani, A. et al. Predicting sustained ventricular arrhythmias in dilated cardiomyopathy: a meta-analysis and systematic review. ESC Heart Fail 7, 1430–1441 (2020). 17. Al-Khatib, S. M. et al. 2017 AHA / ACC / HRS Guideline for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death: Executive Summary: A Report of the American College of Cardiology / American Heart Association TaskForce on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol 72, 1677–1749 (2018). 18. McDonagh, T. A. et al.2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) With the special contribution of the Heart Failure Association (HFA) of the ESC. European Heart Journal 42, 3599–3726 (2021). 19. A, S. et al. Derivation of highly purified cardiomyocytes from human induced pluripotent stem cells using small molecule-modulated differentiation and subsequent glucosestarvation. Journal of visualized experiments : JoVE (2015) doi:10.3791 / 52628.20. Stein, J. M. et al. Software Tool for Automatic Quantification of Sarcomere Length and Organization in Fixed and Live 2D and 3D Muscle Cell Cultures In Vitro. Current Protocols 2, e462 (2022). 21. Vahl, C. F., Bonz, A., Timek, T. & Hagl, S. Intracellular calcium transient of working human myocardium of seven patients transplanted for congestive heart failure. Circ Res 74, 952–958 (1994). 22. Piacentino, V. et al. Cellular basis of abnormal calcium transients of failing human ventricular myocytes. Circ Res 92, 651–658 (2003). 23. Maltsev, V. A., Silverman, N., Sabbah, H. N. & Undrovinas, A. I. Chronic heart failure slows late sodium current in human and canine ventricular myocytes: implications for repolarization variability. Eur J Heart Fail 9, 219–227 (2007). 24. Zaklyazminskaya, E. & Dzemeshkevich, S. The role of mutations in the SCN5A gene in cardiomyopathies. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research 1863, 1799–1805 (2016). 25. Sun, N. et al. Patient-Specific Induced Pluripotent Stem Cell as a Model for Familial Dilated Cardiomyopathy. Sci Transl Med 4, 130ra47 (2012). 26. Hinson, J. T. et al. Titin Mutations in iPS cells Define Sarcomere Insufficiency as a Cause of Dilated Cardiomyopathy. Science 349, 982–986 (2015). 27. Gramlich, M. et al. Antisense-mediated exon skipping: a therapeutic strategy for titin- based dilated cardiomyopathy. EMBO Molecular Medicine 7, 562–576 (2015). 28. Sharma, A., Toepfer, C. N., Schmid, M., Garfinkel, A. C. & Seidman, C. E. Differentiation and Contractile Analysis of GFP-Sarcomere Reporter hiPSC-Cardiomyocytes. Curr Protoc Hum Genet 96, 21.12.1-21.12.12 (2018).29. Dai, Y. et al. Troponin destabilization impairs sarcomere-cytoskeleton interactions in iPSC-derived cardiomyocytes from dilated cardiomyopathy patients. Sci Rep 10, 209 (2020). 30. Pettinato, A. M. et al. Development of a Cardiac Sarcomere Functional Genomics Platform to Enable Scalable Interrogation of Human TNNT2 Variants. Circulation 142, 2262– 2275 (2020). 31. Shah, P. P. et al. Pathogenic LMNA variants disrupt cardiac lamina-chromatin interactions and de-repress alternative fate genes. Cell Stem Cell 28, 938-954.e9 (2021). 32. Huang, G. et al. Titin-truncating variants in hiPSC cardiomyocytes induce pathogenic proteinopathy and sarcomere defects with preserved core contractile machinery. Stem Cell Reports 18, 220–236 (2022). 33. Gorodeski, E. Z. et al. Prognosis on Chronic Dobutamine or Milrinone Infusions for Stage D Heart Failure. Circ: Heart Failure 2, 320–324 (2009). 34. Gigli, M. et al. Genetic Risk of Arrhythmic Phenotypes in Patients With Dilated Cardiomyopathy. Journal of the American College of Cardiology 74, 1480–1490 (2019). 35. Ebert, M. et al. Prevalence and Prognostic Impact of Pathogenic Variants in Patients With Dilated Cardiomyopathy Referred for Ventricular Tachycardia Ablation. JACC: Clinical Electrophysiology 6, 1103–1114 (2020). 36. Levin, M. G. et al. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure. Nat Commun 13, 6914 (2022). 37. Gilead Sciences. A Phase 2, Double-Blind, Randomized, Placebo-Controlled, Dose Ranging, Parallel Group Study to Evaluate the Effect of GS-6615 on Ventricular Arrhythmia in Subjects With Implantable Cardioverter-Defibrillator (ICD) or Cardiac Resynchronization Therapy-Defibrillator (CRT-D). https: / / clinicaltrials.gov / ct2 / show / NCT02104583 (2019). Exemplary Embodiments

[0080] Exemplary embodiments provided in accordance with the presently disclosed subject matter include, but are not limited to, the claims and the following embodiments:

[0081] Embodiment 1. A method of inducing a cellular phenotype of dilated cardiomyopathy (DCM) in a cardiomyocyte, comprising contacting the cardiomyocyte with dobutamine.

[0082] Embodiment 2. The method of embodiment 1, wherein the method comprises contacting the cardiomyocyte with dobutamine and an agent that stabilizes dobutamine.

[0083] Embodiment 3. The method of embodiment 2, wherein the agent is ascorbic acid.

[0084] Embodiment 4. The method of any one of embodiments 1-3, wherein the cardiomyocyte is an induced pluripotent stem cell cardiomyocyte (iPSC-CM).

[0085] Embodiment 5. The method of embodiment 4, wherein the iPSC-CM is from a subject.

[0086] Embodiment 6. A kit for inducing a cellular phenotype of DCM in a cardiomyocyte, comprising dobutamine.

[0087] Embodiment 7. A method of determining a risk of a subject developing an arrhythmia, comprising characterizing an electrical phenotype of a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity in more than 10% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia.

[0088] Embodiment 8. The method of embodiment 7, wherein the characterizing is via a multi-electrode array (MEA) recording or an action potential (AP) recording.

[0089] Embodiment 9. A method of determining the risk of a subject developing an arrhythmia, comprising detecting one or more abnormal Ca2+movements in a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting one or more abnormal Ca2+movements in more than 20% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia.

[0090] Embodiment 10. The method of embodiment 9, wherein the detecting is via calcium imaging.

[0091] Embodiment 11. The method of any one of embodiments 7-10, wherein the iPSC- CMs have a cellular phenotype of DCM.

[0092] Embodiment 12. The method of embodiment 11, wherein the cellular phenotype of DCM is induced by dobutamine.

[0093] Embodiment 13. The method of embodiment 12, wherein the cellular phenotype of DCM is induced by dobutamine and an agent that stabilizes dobutamine.

[0094] Embodiment 14. The method of embodiment 13, wherein the agent is ascorbic acid.

[0095] Although the foregoing disclosure has been described in some detail by way of illustration and example for purposes of clarity of understanding, one of skill in the art will appreciate that certain changes and modifications may be practiced within the scope of the appended claims. In addition, each reference provided herein is incorporated by reference in its entirety to the same extent as if each reference was individually incorporated by reference.

Claims

WHAT IS CLAIMED IS:

1. A method of inducing a cellular phenotype of dilated cardiomyopathy (DCM) in a cardiomyocyte, comprising contacting the cardiomyocyte with dobutamine.

2. The method of claim 1, wherein the method comprises contacting the cardiomyocyte with dobutamine and an agent that stabilizes dobutamine.

3. The method of claim 2, wherein the agent is ascorbic acid.

4. The method of claim 1, wherein the cardiomyocyte is an induced pluripotent stem cell cardiomyocyte (iPSC-CM).

5. The method of claim 4, wherein the iPSC-CM is from a subject.

6. A kit for inducing a cellular phenotype of DCM in a cardiomyocyte, comprising dobutamine.

7. A method of determining a risk of a subject developing an arrhythmia, comprising characterizing an electrical phenotype of a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting early afterdepolarization (EAD), delayed afterdepolarization (DAD), and / or triggered activity in more than 10% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia.

8. The method of claim 7, wherein the characterizing is via a multi- electrode array (MEA) recording or an action potential (AP) recording.

9. A method of determining a risk of a subject developing an arrhythmia, comprising detecting one or more abnormal Ca2+movements in a plurality of induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from the subject, wherein detecting the one or more abnormal Ca2+movements in more than 20% of the iPSC-CMs indicates that the subject is at risk of developing an arrhythmia.

10. The method of claim 9, wherein the detecting is via calcium imaging.

11. The method of claim 7, wherein the iPSC-CMs have a cellular phenotype of DCM.

12. The method of claim 11, wherein the cellular phenotype of DCM is induced by dobutamine.

13. The method of claim 12, wherein the cellular phenotype of DCM is induced by dobutamine and an agent that stabilizes dobutamine.

14. The method of claim 13, wherein the agent is ascorbic acid.

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