Supplementary Materials for

stm.sciencemag.org/cgi/content/full/12/554/eaax9276/DC1

Supplementary Materials for

Clinical trial in a dish using iPSCs shows lovastatin improves endothelial dysfunction and cellular cross-talk in LMNA cardiomyopathy

Nazish Sayed*, Chun Liu, Mohamed Ameen, Farhan Himmati, Joe Z. Zhang, Saereh Khanamiri, Jan-Renier Moonen, Alexa Wnorowski, Linling Cheng, June-Wha Rhee, Sadhana Gaddam, Kevin C. Wang, Karim Sallam,

Jack H. Boyd, Y. Joseph Woo, Marlene Rabinovitch, Joseph C. Wu*

*Corresponding author. Email: [email protected] (J.C.W.); [email protected] (N.S.) Published 29 July 2020, Sci. Transl. Med. 12, eaax9276 (2020)

DOI: 10.1126/scitranslmed.aax9276

The PDF file includes:

Methods

Fig. S1. Characterization of LMNA mutation family.

Fig. S2. Generation of iPSCs and differentiation of iPSC-ECs.

Fig. S3. Characterization of iPSC-ECs from healthy control and LMNA patients.

Fig. S4. Characterization of iPSC-ECs from additional healthy control and LMNA patients.

Fig. S5. Characterization of primary ECs isolated from LMNA patients.

Fig. S6. Generation and characterization of genome-edited iPSCs.

Fig. S7. Transcriptional characterization of iPSC-ECs.

Fig. S8. Characterization of iPSC-ECs under shear stress.

Fig. S9. Screening of small molecules that increase KLF2 expression in LMNA iPSC-ECs.

Fig. S10. Lovastatin improves EC function in LMNA iPSC-ECs.

Fig. S11. Lovastatin improves EC function in cardiolaminopathy patients.

Fig. S12. Lovastatin improves LMNA iPSC-CM phenotype when cocultured with LMNA iPSC- ECs.

Fig. S13. Lovastatin up-regulates genes responsible for cardiac mechanics in LMNA iPSC-CMs when cocultured with LMNA iPSC-ECs.

Fig. S14. Characterization of LMNA iPSC-CMs in inverse cocultures.

Fig. S15. Summary figure of modeling endothelial dysfunction in LMNA-related DCM using patient-specific iPSC-ECs.

Table S1. Demographic and clinical characteristics of healthy control and LMNA patients at baseline.

References (61–63)

Other Supplementary Material for this manuscript includes the following:

(available at stm.sciencemag.org/cgi/content/full/12/554/eaax9276/DC1) Data file S1 (Microsoft Excel format). Individual subject-level data.

METHODS

EndoPAT measurements. EndoPAT measurements were conducted in a quiet room with the patients in a comfortable position, as per manufacturer’s instructions. Pneumatic probes were placed on the patients’ index fingers with a blood pressure cuff on one arm. With both arms resting on the comfortable arm supports, sub-diastolic pressure was inflated to the probes to avoid the veno-arteriolar vasoconstriction reflex. After 25 min of rest, a 5 min baseline reading was recorded. The blood pressure cuff was inflated to 60 mmHg above the systolic blood pressure. Occlusion was confirmed by visual confirmation of completely attenuated PAT signals from the arm with blood pressure cuff. After 5 min of occlusion recording, the blood pressure cuff was rapidly deflated, and an additional 5 min reading was recorded during the reactive hyperemia phase. The non-occluded arm served as an internal control to correct systemic changes in vascular tone. The measurements of reactive hyperemia index (RHI) were both operator and interpreter independent and the RHI was calculated from the raw pulse wave amplitudes (PWAs) using the computerized algorithm of the manufacturer using predetermined time periods. Specifically, the RHI is the ratio of the post-occlusion to pre-occlusion peripheral arterial tone (PAT) amplitude of the occluded arm, divided by the post-to-pre-occlusion ratio of the control arm. The EndoPAT applies the following formula to calculate the RHI:

PWA Ho

/

/

PWA Ho: hyperemic PWA of the occluded arm (measured 60-120 sec after cuff deflation).

PWA Bo: baseline PWA of the occluded arm.

PWA Hc: PWA of the control arm (measured 90 and 150 sec post-occlusion of the control arm).

PWA Bc: baseline PWA of the control arm.

Real-time RT-PCR. Total RNA was extracted using RNeasy plus mini Kit (Qiagen) according to the manufacturer’s instructions. cDNA was generated using qScript cDNA SuperMix

(Quantabio). Quantitative real-time RT-PCR was conducted on StepOne Real-Time PCR system (Life Technologies) using TaqMan Universal PCR Master Mix (Life Technologies). All samples were normalized against GAPDH as relative expression measurement. Real-time qPCR probes used in this study were ordered from Life Technologies. For each experiment, at least three replicates were performed.

Flow cytometry. Cells were dissociated with TrypLE and fixed using 4% PFA. Cells were resuspended in 2% FBS in PBS and stained with PE-conjugated antibody against CD31 (1:400, BD Biosciences) for 30 min on ice. Stained cells were assessed by a FACSAria II cell sorter (BD Biosciences), and data were analyzed using the Flowjo 8.7 software (TreeStar).

iPSC-EC functional measurement.

Tube formation: Cultured iPSC-ECs were dissociated using TyrpLE for 5 min. iPSC-EC

pellets were resuspended in EGM2 medium supplemented with 50 ng/ml VEGF, and then seeded into 24-well plates (10⁴ cells/well) coated with 300 μl Matrigel Basement Membrane Matrix GFR (BD Biosciences). Following 16-24 hr incubation, tube branches were imaged and counted.

Nitric oxide (NO) production: The NO production capacity of iPSC-ECs was assessed by

measuring the concentration of NO in culture supernatants using a NO detection kit (Molecular Probe). Nitrate was converted into nitrite, and the total amount of nitrite was determined by colorimetric Griess reaction. The absorbance at 540 nm was detected by microplate reader.

Acetylcholine (10 μM) or Ca²⁺ ionophore A23187 (1 μM) was added according to the experimental design.

Ac-LDL uptake: The ability of iPSC-ECs to uptake Ac-LDL was evaluated by incubating

iPSC-ECs (4x10⁴ cells/well) with fluorescently-labeled LDL in 96-well white clear-bottom cell culture plates for 24 hr. Fluorescence (Ex/Em = 540/575 nm) was measured, and LDL uptake was quantitatively calculated with fluorescently labeled LDL standard curve according to the manufacturer’s instructions (Biovision). To determine the non-specific fluorescently labeled LDL binding, a wash-off step was performed where fluorescently-labeled LDL was incubated with cells for 2 min, followed by repeated washing with assay buffer and measured for fluorescence.

Ox-LDL uptake: The ability of iPSC-ECs to uptake ox-LDL was evaluated by incubating

iPSC-ECs (4x10⁴ cells/well) with oxLDL-DyLight 488 (fluorescently conjugated ox-LDL, Cayman Chemical Inc) in a 24-well plate overnight. After incubation, cells were washed and stained with Hoechst Staining Solution for 15 min and visualized under a fluorescent microscope.

Isolation of vessel and blood ECs. Protocols for isolation and use of patients’ vessel and blood ECs were approved by Stanford University Human Subjects Research Institution Review Board.

Vessel endothelial cell (VEC) isolation: Left anterior descending (LAD) arteries from

LMNA Pt. 2 (n=1) and unrelated healthy control (n=1) were carefully dissected and cut into small pieces (1-3 mm³). Dissected tissues were incubated in freshly prepared 1 μg/ml Liberase solution (R&D) for 30 min. The incubation was repeated for another 30 min with fresh Liberase solution. To neutralize the incubation, the EGM2 medium supplemented with 5% FBS was added to the digested tissues. ECs were collected by a centrifuge and purified by MACS sorting using CD144-conjugated magnetic microbeads.

Blood endothelial cell (BEC) isolation: Buffy coat was collected from the patients’ blood by

centrifugation and washed with PBS as previously described (61). Cellular pellets were carefully resuspended in the BOEC medium (18% FBS in EGM2 medium) and seeded on Collagen type I- coated 48-well plates with approximately 1.5x10⁵ cells per well. The medium was changed three times per week and blood ECs were ready for passage after around 4 weeks of culturing following seeding.

Genotyping and genome-editing. Genomic DNA was extracted from patient iPSCs using the DNeasy Blood & Tissue Kit (Qiagen) (62). Genotyping at the LMNA mutation target site was performed by PCR amplification using Primer STAR GXL DNA polymerase (Clonetech) with primers designed to amplify around 500 bp fragment surrounding LMNA mutation loci. PCR products were purified with the QIAquick Purification Kit (Qiagen) and sequenced to confirm the presence of mutation by Sanger. Patient iPSCs were genome-edited via transfection of TALEN pairs and targeting vectors by nucleofection and selected by puromycin as previously described (17).

RNA and ATAC sequencing.

RNA-seq: RNA was extracted using a Qiagen RNeasy kit. 100 ng RNA was used to generate

index-tagged paired-end cDNA libraries. Briefly, mRNAs were purified using Dyna Oligo(dT) beads (Life technologies) and fragmentated to 200-300 bp fragments as described previously (63). Illumina sequencing adapters were ligated to cDNA fragments through PCR. Library quality was assessed using the Agilent high Sensitivity DNA Kit and Agilent 2100 Bioanalyzer.

Sequencing was performed on Illumina Hiseq platform. Paired-end fastq sequencing reads were

mapped to human reference genome (hg38) using STAR (2.5.4b), and quantified raw counts and RPKM values using Homer (analyzeRepeats.pl). Differential gene expression was performed using DEseq2 and genes with p<0.05 as well as an absolute value of log2 fold-change >1 were considered as differentially expressed. Heatmaps were plotted using the RPKM values of the differential gene list and Gene ontology analysis was performed using R package (clusterProfiler).

ATAC-seq: ATAC-seq pair-end reads were mapped to human genome hg38 using Bowtie

(1.2.2) with parameters -S -m 1. Reads were sorted and duplicate and mitochondrial reads were removed using samtools (1.8). Peaks were called using MACS2 (2.1.1) with p-value of 0.01. A window from -2.5k upstream to +2.5k downstream of transcription start sites (TSS) was taken and divided into 50 bp bins, the signal distribution over the TSS regions was calculated and plotted using deeptools (3.1.3) as previously described (17).

Western blot analysis. Cells were lysed with RIPA buffer supplemented with a protease inhibitor and phosphatase inhibitor cocktail (Sigma). Lysates were centrifuged at 4 °C at 16,000 rpm for 15 min. Supernatants were collected and quantified using DC protein Assay (Bio-Rad).

25 µg of protein lysates loaded on NuPAGE Bis-Tris Gels (Life Technologies) and transferred on nitrocellulose membranes using Trans-Blot Turbo Transfer System (Bio-Rad). Membranes were incubated with Anti-KLF2 antibodies (1:200, Abcam) overnight at 4 °C. HRP-conjugated secondary antibodies were incubated for 1 hr and detected by Chemi Doc XRS system (Bio- Rad). HRP-conjugated GAPDH antibodies (Life Technologies) were used as a loading control for band intensity quantification and normalization.

ChIP-qPCR. ChIP assays were conducted using SimpleChIP Enzymatic Chromatin IP Kit (Cell Signaling Technology, Danvers, MA) according to the manufacturer’s protocol. Chromatins were crosslinked using formaldehyde and sheared. A small portion of sheared chromatin was stored as input. Chromatins were incubated overnight (4 °C) and immunoprecipitated with Dynabead-conjugated H3K4me3 and H3K27me3 antibodies (CST). Non-specific mouse IgG (CST) was used as a negative control. Immunoprecipitated DNA was analyzed by qPCR. qPCR was performed using iQ SYBR Green Supermix (Bio-Rad) with designed primers targeting KLF2 promoter

Forward 5’  3’: GGGGTTGTCTTTGTTTTGTTTTAG.

Reverse 5’  3’: TTGGGAGTAATGTCATTCTTCTCTC.

Drug screening. Small molecules were selected as described above and dissolved in DMSO to generate a KLF2 activator library (at the concentration of 10 mM). Cells were treated with small molecule library at 0.1, 1, and 10 μM for 48 hr. KLF2 mRNA expression changes were used as readout to identify potential KLF2 activators. In brief, cells were collected after screening and qRT-PCR analysis of KLF2 were performed.

Unidirectional laminar flow studies. Unidirectional laminar shear stress experiments of iPSC- ECs were conducted using Ibidi fludic units (Ibidi) according to the manufacturer’s instructions.

Cells were plated on collagen pre-coated Ibidi µ-Slide I0.4 Luer (Ibidi) at the concentration of 1x10⁵ cells per slide. With overnight culture, cells proliferated to a confluent monolayer and were placed in fresh EGM2 medium. Two µ-slides with cultured cells were attached in series to each fluidic unit, while the EGM2 medium flowing across slides was driven by coupled air

pump. Ibidi software generated flow rates equating to pre-set shear stress (10-15 dynes/cm²) for 48 hr under laminar flow. Several fluidic units were used in parallel for healthy control and LMNA patient iPSC-ECs. For drug treatments, vehicle or lovastatin was prepared in the EGM2 medium in fluidic unit reservoirs with the medium flowing across attached cells. At the end of the shear stress run, cell culture supernatant and cells were collected from Ibidi µ-slides for designed experiments.

Isometric tension recordings. Left anterior descending (LAD) coronary arteries from heart transplant patients (LMNA Pt. 2 and healthy control heart; n=1 each) were carefully dissected and then transferred to a dish with ice-cold Krebs Solution (in mmol/L: 133 NaCl, 4.6 KCl, 2.5 CaCl2, 16.3 NaHCO3, 1.75 Na2HPO4, 0.6 MgSO4, 10 glucose). Each vessel was cut into small rings and these LAD rings were threaded on 40 μm tungsten wires. The vessels were mounted in an isometric wire myograph chamber (Danish Myo Technology) and subjected to a normalization protocol. A concentration-dependent contraction curve was created by accumulative application of the prostaglandin agonist U46619. Subsequently, concentration- dependent relaxation curves of acetylcholine were conducted on LAD arteries collected from a healthy heart of a rejected donor (42 yo female) or LMNA Pt. 2 with or without incubation with lovastatin. Effects of nicardipine and pinacidil were also measured on the same vessel when terminating each experiment. DMSO was used as a time-matched control in all experiments and all measurements were normalized to the DMSO to exclude the time-dependent loss of tone.

Fig. S1. Characterization of LMNA mutation family. (A) Genotyping of patients shows presence of a heterozygous insertion of a guanine at K117fs in LMNA patients. (B-G) Representative images of raw EndoPAT data showing reactive hyperemia index (RHI) from LMNA patients. (B) healthy control 2; (C) Pt. 1; (D) Pt. 3; (E) Pt. 6; (F) Pt. 7; and (G) Pt. 8. (H) Representative images of raw EndoPAT data showing RHI from a non-LMNA patient with hypertension (HTN). Readings of RHI above 1.67 are considered normal endothelial function.

Fig. S2. Generation of iPSCs and differentiation of iPSC-ECs. (A) Representative images of patient-specific iPSCs shows positive staining for pluripotent markers, Oct4 and Nanog. Scale bar: 100 μm. (B) Representative images of differentiated iPSC-ECs from healthy control (HC1, HC2) and LMNA patients (Pt. 1-7) showing typical “cobblestone” monolayer. Scale bar: 50 μm.

Fig. S3. Characterization of iPSC-ECs from healthy control and LMNA patients. (A) Quantitative PCR data show gene expression of all three arterial (NRP1, EFNB2, and NOTCH1), venous (EPHB4, NR2F2, and NOTCH4), and lymphatic markers (PROX1, PDPN) in healthy control and LMNA iPSC-ECs. Data represented as relative fold-change to respective individual’s iPSCs. (B) Immunoblot shows LMNA expression in healthy control and LMNA iPSC-ECs (upper panel). GAPDH was used as loading control. Data represented from three biological replicates. Bar graph shows quantification of LMNA protein concentration in healthy control and LMNA iPSC-ECs (lower panel). (C) Fluorescence-activated cell sorting (FACS) analysis of healthy control and LMNA iPSC-ECs at day 12 of the differentiation protocol (passage 0; left panel) and cultured iPSC-ECs at passage 1 (right panel) with CD31 antibody. (D) Cell proliferation assays show growth curves over 4 days in healthy control and LMNA iPSC-ECs.

Each data point represents an average of 10 individual measurements of cell count. All data represented as mean ± SEM, n = 3, *P < 0.05. Statistical analyses were performed using one-way ANOVA corrected with Bonferroni method.

Fig. S4. Characterization of iPSC-ECs from additional healthy control and LMNA patients. (A) Quantitative PCR data show expression of endothelial markers CD31 (left) and eNOS (right) in healthy control and LMNA iPSC-ECs. Data represented as relative fold-change to respective individual’s iPSCs. (B) Representative images of capillary-like networks formed by healthy control and LMNA iPSC-ECs. Right panel shows quantification of the number of tubes.

(C) Quantification of NO production by healthy control and LMNA iPSC-ECs in response to acetylcholine (Ach) or Ca²⁺ ionophore A23187. (D) Quantification of LDL-uptake by healthy control and LMNA iPSC-ECs. (E) Representative immunofluorescent images of iPSC-ECs showing uptake of oxidized-LDL (ox-LDL) in healthy control and LMNA iPSC-ECs. DAPI- stained nuclei are shown in blue and ox-LDL is shown in green. (F) Assessment of EC function in LMNA iPSC-ECs. Quantification of the number of capillary-like networks (top panel) and NO production in response to Ach (bottom panel) between LMNA iPSC-ECs. All data represented as mean ± SEM, n = 3, *P < 0.05. Statistical analyses were performed using one-way ANOVA corrected with Bonferroni method. Scale bar: 50 μm.

Fig. S5. Characterization of primary ECs isolated from LMNA patients. (A) Representative images of ECs isolated from LMNA Pt. 2 blood vessels (VECs, left) and LMNA Pt. 3 blood endothelial cells (BECs, right) show the typical “cobblestone” monolayer. (B) Quantitative PCR data show expression of CD31 (left) and eNOS (right) in Pt. 2 VECs, Pt. 3 BECs, and healthy control ECs (commercially obtained human cardiac microvascular endothelial cells from Lonza).

(C) Representative images of capillary-like networks formed by healthy control ECs, Pt. 2 VECs, and Pt. 3 BECs. Right panel shows quantification of the number of tubes. (D) Quantification of NO production by healthy control ECs, Pt. 2 VECs, and Pt. 3 BECs in response to acetylcholine (Ach) or Ca²⁺ ionophore A23187. (E) Quantification of LDL-uptake by healthy control ECs, Pt. 2 VECs, and Pt. 3 BECs. (F) Representative images of differentiated iPSC-ECs from another family carrying a different LMNA mutation (p.Arg133Gln; c.398G>A) show typical “cobblestone” monolayer. (G) Quantitative PCR data show expression of CD31 (left) and eNOS (right) in healthy control and LMNA (Arg133Gln) iPSC-ECs. Data represented as relative fold-change to respective individual’s iPSCs. (H) Representative images of capillary-like networks formed by healthy control and LMNA (Arg133Gln) iPSC-ECs. Right panel shows quantification of the number of tubes formed. (I) Quantification of NO production by healthy control and LMNA (Arg133Gln) iPSC-ECs in response to acetylcholine (Ach) or Ca²⁺ ionophore A23187. All data represented as mean ± SEM, n = 3, *P < 0.05. Statistical analyses were performed using Student’s t-test or one-way ANOVA corrected with Bonferroni method. Scale bar: 50 μM.

Fig. S6. Generation and characterization of genome-edited iPSCs. (A) Schematic workflow of the experimental design. iPSCs from LMNA patient were gene-edited to correct the mutation (“LMNA-WT”). Similarly, iPSCs from healthy control patient were gene-edited to insert the LMNA mutation (“Control-MT”). Both LMNA-WT (corrected) and Control-MT (mutated) were differentiated to iPSC-ECs for further characterization. (B) Morphology of iPSC-ECs from both parental lines; LMNA and healthy control and genome-edited lines; LMNA-WT (corrected) and Control-MT (mutated) show typical “cobblestone” appearance. (C-F) Whole exome sequencing (WES) of genome-edited iPSCs. (C) Integrative genomics viewer (IGV) file shows the absence and presence of variant in LMNA gene in LMNA-WT and Control-MT genome-edited iPSC lines, respectively. (D) WES indel analysis of the top 20 targets in iPSC-ECs and iPSC-CMs shows absence of any indel. (E-F) IGV file shows the absence of any variant in KLF2 gene in both LMNA-WT and Control-MT genome-edited iPSC lines. Scale bar: 100 μm.

Fig. S7. Transcriptional characterization of iPSC-ECs. (A) Hierarchical clustering of RNA- seq data of iPSC-ECs differentiated from both parental lines (LMNA and healthy control) and genome-edited isogenic lines (LMNA-WT (corrected) and Control-MT (mutated)). (B) Direct comparison of RNA expression between healthy control and LMNA iPSC-ECs reveals 2925 upregulated genes and 3841 downregulated genes. (C) Normalized ATAC-seq signal across transcription start sites (TSS) in LMNA iPSC-ECs compared to LMNA-WT iPSC-ECs shown as averaged plots. (D) Representative immunofluorescent images of GFP expression show transfection efficiency of scramble- and KLF2-shRNA in iPSC-ECs differentiated from both parental lines (LMNA and healthy control) and genome-edited isogenic lines (LMNA-WT and Control-MT). (E) Quantitative PCR data show expression of KLF2 in iPSC-ECs following transfection with scramble or KLF2-shRNA. (F) Quantitative PCR data show expression of endothelial markers CD31 (left) and eNOS (right) in scramble and KLF2-KD in both healthy control and LMNA-WT iPSC-ECs. Data represented as relative fold-change to their respective undifferentiated iPSCs. All data represented as mean ± SEM, n = 3, *P < 0.05. Statistical analyses were performed using one-way ANOVA corrected with the Bonferroni method. Scale bar: 50 μm.

Fig. S8. Characterization of iPSC-ECs under shear stress. (A-B) Schematic illustrating the hypothesis behind the experimental workflow. (A) Healthy ECs regulate vascular tone by transmitting mechanical force generated by blood flow via upregulating KLF2. (B) On the contrary, LMNA ECs fail to upregulate KLF2 even in the presence of laminar flow, thereby inducing vasoconstriction. (C) Representative images of scramble and KLF2-KD in both LMNA and Control-MT (mutated) iPSC-ECs when subjected to shear stress. Blue arrows represent the direction of the flow. (D) Representative images of capillary-like networks formed by LMNA and Control-MT iPSC-ECs when KLF2 is knocked down in comparison to scramble controls.

Bottom panel shows quantification of the number of tubes. (E) Quantification of NO production by LMNA and Control-MT iPSC-ECs following shear stress when KLF2 is knocked down in comparison to scramble controls. All data represented as mean ± SEM, n = 3, *P < 0.05.

Statistical analyses were performed using one-way ANOVA corrected with the Bonferroni method. Scale bar: 50 μm.

Fig. S9. Screening of small molecules that increase KLF2 expression in LMNA iPSC-ECs.

(A) Schematic workflow of the experimental design. LMNA and Control-MT (mutated) iPSC- ECs were screened for KLF2 agonists followed by treatment with lovastatin for 24 hr and then characterized for their phenotype and function both in vitro and in vivo. (B) List of small molecules that are known to regulate KLF2. (C) Quantitative PCR data show expression of KLF2 in LMNA and Control-MT iPSC-ECs when treated with an increasing concentration of lovastatin, mevastatin, and simvastatin.

Fig. S10. Lovastatin improves EC function in LMNA iPSC-ECs. (A) Representative images of healthy control and LMNA-WT (corrected) iPSC-ECs when subjected to shear stress in the presence of lovastatin. Arrows represents the direction of the flow. (B) Quantitative PCR data show expression of KLF2 (left) and eNOS (right) in healthy control and LMNA-WT iPSC-ECs following lovastatin treatment. (C) Representative images of capillary-like networks formed by healthy control and LMNA-WT iPSC-ECs after lovastatin treatment. Right panel shows quantification of the number of tubes. (D) Quantification of NO production by healthy control and LMNA-WT iPSC-ECs after shear stress in the presence of lovastatin. (E) Representative images of capillary-like networks formed by healthy control and LMNA iPSC-ECs in response to lovastatin and atorvastatin treatment. Right panel shows quantification of the number of tubes.

All data represented as mean ± SEM, n = 3, *P < 0.05. Statistical analyses were performed using one-way ANOVA corrected with the Bonferroni method. Scale bar: 50 μm.

Fig. S11. Lovastatin improves EC function in cardiolaminopathy patients. (A) Quantitative PCR data show expression of KLF2 (left panel) and eNOS (right panel) in LMNA Pt. 2 VECs (isolated from coronary arteries) after 6 months of lovastatin treatment. (B) Quantitative PCR data show expression of KLF2 (left panel) and eNOS (right panel) in LMNA Pt. 3 BECs (isolated from PBMCs) after 6 months of lovastatin treatment. (C-D) Bar graph showing isometric measurements of contraction in LMNA Pt. 2 left anterior descending (LAD) coronary when exposed to (C) 60 mM KCl or 3 mM U46619 and (D) 1 μM nicardipine or 10 μM pinacidil. (E) Traces of concentration-dependent relaxation in pre-contracted LAD to 0.1, 0.3, 1, 3, and 10 μΜ acetylcholine with or without 1 μM lovastatin in healthy control donor heart (left) and LMNA Pt.

2 (right). All responses were compared with DMSO. All data represented as mean ± SEM, n = 3,

**P < 0.01; ***P < 0.001; ****P < 0.0001. Statistical analyses were performed using Student’s t-test or one-way ANOVA corrected with Bonferroni method. Significance of effects of lovastatin treatment in LMNA patient LADs was determined by 2-way ANOVA, followed by a Bonferroni post-test. n = 3, (three separate segments from LMNA Pt. 2 and from healthy control heart).

Fig. S12. Lovastatin improves LMNA iPSC-CM phenotype when cocultured with LMNA iPSC-ECs. (A) Pulsed tissue Doppler of the lateral and medial mitral annulus of LMNA Pt. 2.

(B) Representative immunofluorescent images of iPSC-CMs and iPSC-ECs co-culture stained for TNNT2 (CM marker) and CD31 (EC marker). (C-D) Quantification of the contractile properties of iPSC-CMs using video microscopy-based motion vector analysis. (C) Bar graph shows spontaneous beating rate in all conditions of co-culture experiments and (D) contraction velocity in LMNA iPSC-CMs when co-cultured with LMNA iPSC-ECs and 1 μM lovastatin. (E- F) Calcium imaging of iPSC-CMs in co-cultures. (E) Representative Ca²⁺ traces and (F) quantification of Ca²⁺ imaging parameters in LMNA iPSC-CMs when co-cultured with LMNA iPSC-ECs and treated with 1 μM lovastatin. (G-H) Bar graphs show quantification of Ca²⁺

imaging parameters as (G) time constant and (H) systolic Ca²⁺ amplitude in LMNA iPSC-CMs when co-cultured with LMNA iPSC-ECs and treated with 1 μM lovastatin. All data represented as mean ± SEM, n = 3, *P < 0.05; **P < 0.01; ****P < 0.0001. Statistical analyses were performed using one-way ANOVA corrected with Bonferroni method or one-way multivariate analysis of variance (MANOVA).

Fig. S13. Lovastatin up-regulates genes responsible for cardiac mechanics in LMNA iPSC- CMs when cocultured with LMNA iPSC-ECs. (A) Schematic of co-culture experiments for RNA sequencing. (B-C) Gene expression profile of co-cultured iPSC-ECs. (B) Direct comparison of RNA expression in co-cultured iPSC-ECs when treated with 1 μM lovastatin reveal a differential pattern of gene expression (387 upregulated genes and 230 downregulated genes). (C) Expression of KLF2 and eNOS in co-cultured LMNA iPSC-ECs when treated with 1 μM lovastatin. (D-E) Gene expression profile of co-cultured iPSC-CMs. (D) Direct comparison of RNA expression in co-cultured iPSC-CMs when treated with 1 μM lovastatin reveal a differential pattern of gene expression (419 upregulated genes and 574 downregulated genes).

(E) Expression of MYH6/7, ACTC1, TNNI3 (genes responsible for cardiac contractility) and CASQ2 and PLN (genes involved in calcium-handling) in co-cultured LMNA iPSC-CMs when treated with 1 μM lovastatin. (F) Bar graphs of RPKM values for MYH6 (cardiac marker) in iPSC-ECs sorted from co-cultures (upper panel) and eNOS (EC marker) in iPSC-CMs sorted from co-cultures (lower panel).

Fig. S14. Characterization of LMNA iPSC-CMs in inverse cocultures. (A-B) Schematic of inverse co-culture experiments for phenotypic characterization. (A) Co-culture of healthy control iPSC-ECs with LMNA iPSC-CMs. (B) Co-culture of LMNA iPSC-ECs with healthy control iPSC-CMs. (C-E) Quantification of contractile kinetics of iPSC-CMs in inverse co-cultures. (C) Bar graph shows spontaneous beating rate in control iPSC-CMs when co-cultured with LMNA iPSC-ECs in the presence or absence of 1 μM lovastatin and LMNA iPSC-CMs when co- cultured with healthy control iPSC-ECs in the presence or absence of 1 μM lovastatin. Bar graphs show (D) relaxation velocity and (E) contraction velocity in control iPSC-CMs when co- cultured with LMNA iPSC-ECs in the presence or absence of 1 μM lovastatin, and LMNA iPSC- CMs when co-cultured with healthy control iPSC-ECs in the presence or absence of 1 μM lovastatin. All data represented as mean ± SEM, n = 3, *P < 0.05; **P < 0.01; ***P < 0.001.

Statistical analyses were performed using one-way multivariate analysis of variance (MANOVA).

Fig. S15. Summary figure of modeling endothelial dysfunction in LMNA-related DCM using patient-specific iPSC-ECs. A large family cohort of patients carrying a mutation in LMNA exhibiting clinical features of autosomal-dominant cardiac disease. Measurement of their reactive hyperemia index (RHI) using EndoPAT revealed the presence of endothelial dysfunction in all LMNA carriers. In vitro disease modeling of these patients using iPSCs-ECs showed endothelial dysfunction that was recapitulated using genome-edited isogenic iPSC-ECs.

RNA-seq analysis of LMNA iPSC-ECs revealed downregulation of KLF2, a transcription factor that is important for regulating downstream signaling pathways in ECs, thereby maintaining vascular reactivity. Drug screening for KLF2 agonist identified three statins, including lovastatin, that improved EC function in LMNA iPSC-ECs. In addition to improving iPSC-EC function, lovastatin also improved iPSC-CM function in LMNA patients when co-cultured together by upregulating the KLF2-eNOS-NO pathway. Importantly, when given as an oral regimen, lovastatin improved the RHI in two of our recruited cardiolaminopathy patients by as early as 6 months after treatment and lasting up to 18 months. Taken together, we have uncovered mechanistic insights into the pathological processes of LMNA-related vascular dysfunction.

Table S1. Demographic and clinical characteristics of healthy control and LMNA patients at baseline.

- Absent; + Present (mild); ++ Present (moderate); * Prescribed