Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death

Yu Kakimoto; Xueting Guan; Atsushi Ueda; Yayoi Kimura; Tomoko Akiyama; Masayuki Tanaka; Haruka Ikeda; Kazuho Maeda; Shotaro Isozaki

doi:10.1371/journal.pone.0339886

. 2025 Dec 30;20(12):e0339886. doi: 10.1371/journal.pone.0339886

Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death

Yu Kakimoto ^1,^*, Xueting Guan ¹, Atsushi Ueda ¹, Yayoi Kimura ², Tomoko Akiyama ², Masayuki Tanaka ³, Haruka Ikeda ¹, Kazuho Maeda ⁴, Shotaro Isozaki ¹

Editor: Aldrin V Gomes⁵

PMCID: PMC12753045 PMID: 41468454

Abstract

Background

Recent studies have shown that decreased longitudinal strain in speckle-tracking echography can predict sudden cardiac death (SCD) in patients with cardiac hypertrophy (CH). Histologically, the heart wall consists of the inner longitudinal, middle circular, and outer longitudinal layers. Thus, layer-specific proteomic changes may contribute to SCD risk.

Methods

The three layers in human cardiac tissues were obtained during autopsies of SCD, compensated CH, and control cases (18 cases aged > 40 years, 54 samples in total). SCD cases consisted of patients with ischemic or hypertensive heart failure, whereas CH and control cases were accidental deaths. After histological analysis, cardiomyocytes were collected separately from the three layers of the left ventricular wall using laser microdissection. The extracted proteins were analyzed using liquid chromatography–tandem mass spectrometry, followed by label-free quantification.

Results and discussion

Histologically, cardiomyocytes were enlarged in all layers of SCD and CH cases without significant progression of myocardial fibrosis. The proteomic profiles of SCD and CH cases were distinguishable from those of control cases, especially in the inner layer. The levels of mitochondrial and calcium-handling proteins were significantly decreased in SCD hearts. Arrhythmogenic changes, including decreased PKP2 and RYR2 levels, developed in a stepwise manner from control through CH to SCD, most prominently in the inner layer. Immunohistochemical analysis showed reduced levels of PKP2 in intercalated disks and RYR2 in sarcomeres. Because proteomic alterations precede the progression of myocardial fibrosis, their detection may enhance the accuracy of postmortem diagnosis of SCD in middle-aged and older asymptomatic individuals with CH.

1. Introduction

Sudden cardiac death (SCD) accounts for millions of deaths worldwide every year [1,2] and exerts substantial psychological and economic effects on society [3,4]. To date, many clinical trials have been performed for the risk stratification of SCD in patients with cardiomyopathies, those with inherited arrhythmias, and the general population [5,6]. However, SCD prevention remains challenging because SCD may occur in apparently healthy individuals, and the pathologies underlying SCD are heterogeneous.

Recently, imaging techniques have been further developed, and speckle-tracking echocardiography has advanced the quantification of regional left ventricular function by discerning the multidirectional components of ventricular deformation [7]. High-resolution imaging can detect mortality risk from an early phase as reduced longitudinal strain predicts SCD in patients with hypertrophic cardiomyopathy [8], as well as cardiovascular mortality in hypertensive patients [9] and even the general population [10,11]. Regional differences in the three-dimensional contractility of the heart can reflect the spatial heterogeneity of myocardial pathologies. However, the anisotropic proteomic changes of the human heart remain unknown.

Anatomically, the ventricular wall comprises a three-dimensional mesh of longitudinal and circular cardiomyocytes [12]. The structure of the myocardial layers—inner longitudinal layer (In), middle circular layer (Mid), and outer longitudinal layer (Out)—is most distinct at the mid-level of the left ventricle. The coordinated function of these anisotropic layers is crucial for maintaining stable systemic circulation, and layer-specific proteomic alterations can underlie the physiological adaptation and pathological degeneration of the heart. We recently performed layer-specific proteomic profiling of normal human hearts, and demonstrated the anisotropic levels of actin-filament-binding proteins. CTNNA3, highly expressed in the inner layer, can stabilize the endocardial conduction system, and MYH1, highly expressed in the outer layer, can support cardiac contractile endurance [13].

In the current study, we focused on layer-specific proteomic alterations in cases of SCD and cardiac hypertrophy (CH). In middle-aged and older adults, CH is often associated with obesity and hypertension and is an established risk factor for SCD [14,15]. Sudden death cases are often examined at forensic autopsy, including SCD cases with lethal CH, and accidental death cases with CH not contributing to the cause of death, termed compensated CH. However, the postmortem differentiation between lethal and compensated CH is sometimes difficult due to the lack of specific histological findings, and arrhythmia-induced deaths, which account for more than 50% of SCD cases, are often determined by exclusion [16]. Thus, molecular markers for lethal arrhythmogenesis are not only necessary to determine the probability of SCD in patients but also to accurately diagnose the cause of death postmortem.

In this study, we hypothesized that layer-specific proteomic alterations occur in SCDs of middle-aged and older adults with CH. We performed high-throughput mass spectrometry (MS) on cardiomyocytes collected separately from three myocardial layers. Spatial proteomic analysis revealed various proteomic changes that occurred mainly in the inner layer and proceeded from CH to SCD, preceding the progression of myocardial fibrosis.

Materials and methods

Study population

Forensic cases in which the deceased were discovered within 24 h after their death were selected for this study. All patients were over 40 years of age and were divided into three groups: SCD, CH, and control (Fig 1A). SCD was defined as death within 1 h of symptom onset or unwitnessed death with the individual exhibiting normal health within 24 h before death [1]. SCD cases in this study died from either ischemic or hypertensive heart failure, whereas CH and control cases were accidental deaths. Causes of death were comprehensively determined based on clinical history, macroscopic autopsy findings, microscopic pathological examination, blood biochemistry, and toxicology screening. Ischemic heart failure was diagnosed based on the presence of coronary atherosclerosis with > 80% luminal stenosis. Hypertensive heart failure was diagnosed based on a clinical history of hypertension and cardiomegaly, defined as a heart weight/body height ratio of > 2.4 g/cm [15]. Accidental death was defined as death due to fatal trauma in the absence of significant disease or intoxication. CH cases were considered as compensated hypertrophy in the absence of a clinical history of heart failure or cardiac pathology other than cardiomegaly. Patients with hypertrophic cardiomyopathy were excluded. Control individuals were enrolled in a previous proteomic study [13]; all samples including those from controls were simultaneously analyzed in this study. Written informed consent for the academic use of the tissue was obtained from the relatives of all decedents included in the study, and the study was approved by the institutional ethics committee (approval number: 21R177). The recruitment period was from May 2, 2014, to December 31, 2024. This study was conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its subsequent amendments.

Fig 1 — Data are presented as the mean ± standard deviation. * p < 0.05, ** p < 0.01 compared with control as determined via the Steel-Dwass test. (B) Laser microdissection of the three myocardial layers. Cardiomyocytes were separately collected from each layer. FFPE, formalin-fixed paraffin-embedded; FFPE stored time, interval from paraffin embedding to protein extraction.

Histological analysis

The body of the deceased was stored at 4°C until cardiac tissue sampling during the autopsy. The heart was transversely sectioned at the mid-level between the base and apex, and preserved in 10% formalin for approximately 48 h. Formalin-fixed paraffin-embedded (FFPE) tissues were used for subsequent analyses. The three myocardial layers were demarcated on transverse sections of the left ventricular free wall under microscopy. Specifically, cross-sectioned myocardial bundles were identified as the inner and outer longitudinal layers, and longitudinally-sectioned myocardial bundles were considered the middle circular layer. Diagonally-sliced or partly disarrayed myocardial bundles were excluded from analysis. Microscopic measurements were performed on 4-μm sections of the left ventricular free wall. The minor diameter of the cardiomyocytes at the nuclear point was measured at 200 × magnification using hematoxylin and eosin staining, and the values were averaged from 10 viewing fields per case. As we assessed 10 cardiomyocytes per field, a total of 100 cardiomyocytes were analyzed per myocardial layer in each case. Myocardial fibrosis was assessed at 100 × magnification using picrosirius red staining, excluding the endocardium, epicardium, and chordae tendineae. The fibrosis rate was quantified using ImageJ software (https://imagej.net/), and the percentage of the total image was averaged over 20 viewing fields per case [17]. Multiple groups were compared using the Steel–Dwass test in Excel Statistics 2015 (SSRI, Tokyo, Japan), and a p-value < 0.05 was considered significant.

Laser microdissection

The 5-μm FFPE sections of the left ventricular free wall were mounted on PET-membrane frame slides (Micro Dissect GmbH, Herborn, Germany). After staining with toluidine blue, the slides were air-dried. Cardiomyocytes covering an area of 10 mm² were dissected from each myocardial layer of the specimens using laser microdissection (LMD 6500; Leica Microsystems, Wetzlar, Germany; Fig 1B). Tissues with large capillaries, fibrosis, or lipid accumulation were excluded.

Sample preparation for proteomic analysis

Microdissected samples were washed with 150 µL of 100 mM ammonium bicarbonate containing 30% acetonitrile and then dissolved in 50 µL of the same solution. The samples were then heated at 95°C for 90 min, cooled on ice, and centrifuged at 5,000 × g for 1 min. Subsequently, samples were enzymatically digested with 5 µL of 0.2 µg/µL Trypsin Gold Mass Spectrometry Grade (Promega, Madison, WI, USA) at 37°C for 16 h. After centrifugation at 15,000 × g for 3 min, the peptides in the collected supernatants were quantified using a DC Protein Assay Kit II (Bio-Rad, Hercules, CA, USA). In total, 5 µg of peptide samples were dried using a SpeedVac Vacuum Concentrator (Thermo Fisher Scientific, Waltham, MA, USA) and dissolved in 100 µL of 2% acetonitrile containing 0.1% trifluoroacetic acid. Samples were manually cleaned up using GL-Tip SDB (GL Science Inc., Tokyo, Japan), according to the manufacturer’s instructions, but the solution volume was changed from 20 µL to 100 µL. Samples were eluted with 100 µL of 30% and 60% acetonitrile containing 0.1% trifluoroacetic acid, respectively. The eluted peptides were dried using a Speed Vac concentrator.

Proteomic analysis using data dependent acquisition-MS analysis

Proteome profiles were individually determined by proteomic analysis using liquid chromatography–tandem MS and label-free quantitation. The desalted peptides were resuspended in 2:98 [v/v] acetonitrile/water and 0.1% formic acid. Then, 0.5 µg of each sample was injected individually and analyzed once using a Q Exactive mass spectrometer (Thermo Fisher Scientific) equipped with an UltiMate 3000 LC system (Thermo Fisher Scientific). The mass spectrometer was operated using Xcalibur software. Peptides were loaded on a trap column (100 μm × 20 mm, C18, 5 μm, 100 A, Thermo Fisher Scientific) and subsequently separated on a Nano HPLC capillary column (75 μm × 180 mm, C18, 3 μm; Nikkyo Technos Co., Ltd., Tokyo, Japan) with a linear gradient of 2–33% buffer B (95:5 [v/v] acetonitrile/water, 0.1% formic acid) in buffer A (2:98 [v/v] acetonitrile/water, 0.1% formic acid) for 120 min at a flow rate of 300 nL/min. Full-scan MS spectra were measured from 300 to 1,500 m/z, and each of the 20 most abundant ions was subsequently subjected to HCD product ion scans. Tandem MS scanning conditions were as follows: spray voltage, 2.0 kV; capillary temperature, 250°C; and normalized collision energy, 27%.

Label-free quantitation was conducted using Progenesis QI for proteomics (version 4.2; Nonlinear Dynamics). The samples were categorized into three groups—In, Mid, and Out—and subsequently statistically analyzed. For protein and peptide identification, peak lists were generated using Progenesis QI for proteomics and then searched against human protein sequences in the UniProtKB/Swiss-Prot database (Jan 2020) using Mascot software (v2.7, Matrix Science, London, UK). The search parameters were set as follows: trypsin digestion with two permitted missed cleavages; peptide mass tolerance of ± 5 ppm; fragment mass tolerance of ± 0.05 Da; and common variable modifications including methionine oxidation, cysteine carbamidomethylation, protein N-terminal acetylation, and N-terminal carbamylation. A 1% overall false discovery rate was applied as the threshold to export the results from the database search using the Mascot software. Additionally, peptides with a peptide ion score ≥ 30 were utilized for quantitation. Only peptides uniquely assigned to a single protein were included in quantitative analysis. Those shared with other protein hits were excluded. Significance was determined using a p-value < 0.05 in analyses of variance of the normalized values among groups.

Bioinformatic analysis

Principal component analysis was performed using SIMCA software (Infocom, Tokyo, Japan). Gene Ontology (GO) enrichment analysis was performed using R (4.4.2) and R Studio (2024.09.0 + 375). Prior to GO enrichment analysis, the accession IDs of significantly different proteins were extracted. Using AnnotationDbi (1.68.0), these IDs were converted to Entriz IDs and gene symbols from the org.Hs.e.g.,db database (3.20.0). Converted probes were subjected to GO enrichment analyses with a focus on the “Molecular Function” category using the package clusterProfiler (4.14.0) [18]. The Benjamini–Hochberg method was applied to adjust the p-value, with a significance cutoff of 0.05. The threshold of the q-value was set to 0.05 to further minimize the false discovery rate. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the same parameters. Dot and box plots were created using the package ggplot2 in the framework tidyverse (2.0.0) [19]. To illustrate the connections between genes and pathways, a network plot was created using the packages igraph (2.1.1) and ggraph (2.2.1). The Kruskal–Wallis test was used to assess statistical significance in the three groups, followed by pairwise comparisons using the Steel–Dwass test (R v.4.4.2). The Friedman test was used for inter-layer comparisons within each group, followed by pairwise comparisons using the Wilcoxon signed-rank test. p < 0.05 was deemed to indicate statistical significance.

PKP2 sequencing

DNA was extracted from cardiac tissue samples using a QIA Amp DNA Investigator Kit (Qiagen, Hilden, Germany). Oligonucleotide primers (S1 Table) were designed for the amplification and sequencing of PKP2 exons. PCR amplification was performed using Tks Gflex DNA Polymerase (Takara Bio Inc., Kusatsu, Japan) with 10 ng of DNA as the template. The PCR products were purified using ExoSAP-IT Express (Thermo Fisher Scientific). The directly sequenced products were analyzed using a Genetic Analyzer 3500 (Thermo Fisher Scientific). For all SCD cases, the coding region of PKP2 was determined, and no mutations affecting PKP2 level were found.

Immunohistochemical analysis

The 4-μm sections of the left ventricular free wall were used for immunohistochemistry. Because intercalated disks (IDs), where PKP2 localizes, and T-tubules, where RYR2 localizes, are clearly visible in longitudinal sections of cardiomyocytes, we used vertical sections in addition to transverse sections of the ventricular wall. A vertical section block was available for four SCD cases, three CH cases, and three control cases. Antigen retrieval was conducted by heating the samples in Target Retrieval Solution (pH 9.0; Dako, Santa Clara, CA, USA), at 95°C for 20 min. Specimens were immunostained with an anti-PKP2 antibody (1:800; ab223757, Abcam, Cambridge, UK) for 60 min at room temperature and an anti-RYR2 antibody (1:200, 19765–1-AP, Proteintech, Rosemont, IL, USA). Subsequently, samples were incubated with a secondary antibody (Histofine MAX-PO-MULTI; Nichirei Biosciences, Tokyo, Japan) at room temperature for 30 min. DAB and hematoxylin were used for color development.

Results

Myocardial hypertrophy without significant fibrosis in SCD and CH cases

Body mass index and serum brain natriuretic peptide (BNP) levels were not clinically different among all cases, whereas heart weight and cardiomyocyte diameter were significantly increased in the SCD and CH groups (Fig 1A and 2A). The heart weight/body height ratio was > 2.4 g/cm in all SCD and CH cases. Slight myocardial fibrosis was observed in the inner and middle layers of cases with SCD and CH; however, myocardial fibrosis was not significantly different among the three study groups (Fig 2B). No significant inflammatory infiltrate was observed in any samples.

Fig 2 — Cardiomyocyte diameters are increased in SCD and CH cases compared with controls, whereas myocardial fibrosis does not differ significantly among the groups. Representative images of the three layers stained with hematoxylin and eosin (A; scale bar: 50 µm) or picrosirius red (B; scale bar: 100 µm) dye. *p < 0.05, **p < 0.01 (Steel–Dwass test). Abbreviations: CH, cardiac hypertrophy; Ctrl, control; SCD, sudden cardiac death.

Pronounced proteomic alterations in the inner layer of SCD cases

In total, 54 samples (three cardiac layers of 18 enrolled cases) were collected and analyzed. The proteomic profiles of SCD and CH cases were distinguishable from those of the control cases in all layers; however, the characteristic changes of SCD cases were most prominent in the inner layer (Fig 3A, S2 Table). In all layers of SCD cases, the numbers of proteins with decreased levels were larger than those of proteins with increased levels. Of the 1,250 proteins identified in the inner layer, 26 were significantly increased in SCD cases, and 111 were significantly decreased compared with control cases. Of the 1,217 proteins identified in the middle layer, 13 were significantly increased and 90 were significantly decreased. Of the 1,255 proteins identified in the outer layer, 13 were significantly increased and 87 were significantly decreased. Proteins with the greatest changes in the three groups are shown in Fig 3B.

Fig 3 — **(A)** Principal component analysis based on 1,250 proteins for the inner longitudinal layer (In), 1,217 proteins for the middle circular layer (Mid), and 1,255 proteins for the outer longitudinal layer (Out). Numbers represent the individual cases. The proteomic profiles of SCD and CH cases were distinguishable from those of the control cases in all layers. **(B)** Major proteins with the greatest fold changes between SCD and control cases. Proteins identified with at least two unique peptides with p values < 0.05 as determined by the Steel–Dwass test were selected. The top 10 proteins with decreased abundance in each layer of SCD cases are listed. In contrast, only 9, 3, and 7 proteins met the criteria for increased abundance in SCD cases in the respective layers. The fold change indicates the ratio of the relative abundance of SCD to Ctrl for proteins with increased levels, and that of Ctrl to SCD for proteins with decreased levels. Abbreviations: CH, cardiac hypertrophy; Ctrl, control; SCD, sudden cardiac death; PC, principal component.

In contrast, the differences between SCD and CH cases were minimal. Only 17 (10 increased and 7 decreased), 12 (9 increased and 3 decreased), and 13 (5 increased and 8 decreased) proteins were differentially detected in the inner, middle, and outer layers, respectively (S2 Table). The inter-layer comparisons in each group were separately presented in S3-S5 Table, and the list of differentially expressed proteins were summarized in S6 Table. Note that the original data for inter-layer comparisons in the control cases was previously published [13]; in the present study, we reanalyzed these data using multiple nonparametric methods.

Many GO terms related to molecular function were associated with decreased proteins in SCD cases compared with control cases (S7 Table). In contrast, no GO terms were associated with increased proteins in either the inner or middle layers in SCD cases, and only five terms were identified for increased proteins in the outer layer. The major GO terms related to molecular function are summarized in Fig 4A. Cadherin-binding proteins, transmembrane transporter proteins, and mitochondrial proteins with oxidoreductase or electron transfer activities were significantly decreased in all layers of SCD cases, most prominently in the inner layer. Nucleosomal proteins were significantly increased in the outer layer of SCD cases.

Fig 4 — **(A)** Dot plots summarizing major GO terms and related molecular functions. Only GO terms that remained significantly overrepresented after adjusting for multiple tests are shown. No GO terms were associated with proteins of increased abundance in either the inner or middle layers in SCD cases. The circle size indicates the number of proteins linked to each GO term. The circle color indicates gene ratio, which indicates the proportion of input genes associated with a specific GO term (number of genes in the term/ total number of input genes). **(B)** Corresponding KEGG pathway analysis for each layer. No significantly enriched pathways were identified for proteins with increased abundance in either the inner or middle layers. **(C)** Gene concept network focusing on cardiovascular diseases, based on proteins with decreased abundance in the inner layer of SCD cases. Abbreviations: GO, gene ontology; SCD, sudden cardiac death.

The decreased proteins in SCD cases compared with control cases, especially in the inner layer, were strongly related to various types of cardiomyopathies, including diabetic, dilated, and arrhythmogenic right ventricular cardiomyopathies (Fig 4B, 4C, S8 Table). In contrast, no gene concept was identified for proteins with increased abundance in either the inner or middle layers in SCD cases, and only seven concepts were identified for increased proteins in the outer layer. However, histological findings of autopsies did not suggest the presence of these cardiomyopathies (Fig 2A). Moreover, critical mutations were not detected in the PKP2-coding region, whereas PKP2 levels were transmurally decreased in SCD cases. No GO terms or KEGG pathways were significantly associated with the proteins differentially detected between SCD and CH cases across all layers.

Decreased Ca² ⁺ -handling and energy-producing proteins from CH to SCD cases

Levels of cardiomyopathy-related proteins, cadherin-binding proteins, including PKP2, and Ca²⁺-handling proteins such as RYR2, SERCA2a, and NCX gradually decreased from control through CH to SCD groups (Fig 5). In the inner and middle layers, the levels of energy-producing proteins involved in glycolysis and mitochondrial oxidative phosphorylation were lower in the SCD group than in the CH group.

Fig 5 — Stepwise alterations in cardiomyocyte protein levels are evident from the control through CH to SCD groups, especially in the inner layer. *p < 0.05, **p < 0.01 as determined by the Steel-Dwass test. Abbreviations: CH, cardiac hypertrophy; ID, intercalated disk; SCD, sudden cardiac death.

In control hearts, PKP2 was tightly localized at IDs between cardiomyocytes (Fig 6). However, ID detachment was observed in SCD and CH hearts, and the density of PKP2 levels was generally lower in SCD hearts. RYR2 was widely expressed in the myocardial cytoplasm and was highly expressed in IDs of control hearts. In contrast, reduction in RYR2 levels at IDs and in the cytoplasm was observed in SCD and CH hearts. In particular, SCD hearts exhibited a striated decolorization pattern. These microscopic changes were most prominent in the inner myocardial layer.

Abbreviations: CH, cardiac hypertrophy; ID, intercalated disk; SCD, sudden cardiac death

Discussion

In this study, we showed the spatial proteomic changes in human SCD hearts. We focused on the three myocardial layers—inner longitudinal, middle circular, and outer longitudinal. Laser microdissection enabled layer-specific proteomic profiling of archived human hearts which demonstrated that levels of cardiomyopathy-related and energy-producing proteins were decreased, most significantly in the inner layer of SCD hearts (Fig. 7).

Fig 7 — Many proteins that contribute to calcium handling and energy production are decreased. Red stars indicate proteins with significantly decreased levels in the inner and other layers of SCD hearts. Purple stars indicate proteins with significantly decreased levels only in the inner layer of SCD hearts. Abbreviation: SCD, sudden cardiac death.

Downregulation of PKP2 and RYR2

The level of PKP2, a desmosomal protein that maintains intercellular mechanical connections and electrical coupling [20], was transmurally decreased, most prominently in the inner layer of SCD hearts. These immunohistochemical results imply that intercellular adhesion is weakened in SCD hearts.

PKP2 is essential for the normal development of the myocardial junction, as mice with germline PKP2 knockout (KO) present with cytoskeletal disarray and rupture of the cardiac wall, leading to embryonic death [21]. Clinically, mutations in PKP2 are frequently observed in patients with congenital arrhythmias, such as arrhythmogenic cardiomyopathy, Brugada syndrome, and idiopathic ventricular fibrillation [22]. However, none of the enrolled individuals had a family history of arrhythmia, and critical mutations in PKP2-coding regions were not detected. Therefore, decreased PKP2 levels in SCD hearts were most likely induced by acquired pathology, including epigenetic alterations, rather than congenital changes.

Moreover, the downregulation of RYR2, a sarcoplasmic reticulum (SR) transmembrane protein, was observed mainly in the inner layer of SCD hearts. As RYR2 is dense and close to the T-tubule at the Z band, RYR2 attenuation with a striated pattern in SCD hearts may reflect the disturbance of T-tubule structures at the sarcomere. RYR2 releases large amounts of Ca²⁺ from the SR in response to mildly elevated intracellular Ca²⁺ levels induced by L-type Ca²⁺ channel (Ca_v1.2) activation during an action potential. The substantial increase in Ca²⁺ concentration (Ca²⁺-induced Ca²⁺ release) caused by RYR2 leads to cardiomyocyte contraction, and thus RYR2 plays a central role in the excitation-contraction coupling of cardiomyocytes. Interestingly, the conditional KO (cKO) of PKP2 in mice reduces the level of RYR2 and enhances its Ca²⁺ sensitivity [23]. Defective RYR2 gating and the associated aberrant Ca²⁺ release from the SR during diastole trigger arrhythmia initiation in PKP2 cKO mice [24,25].

The constitutive KO of RYR2 in mice results in embryonic death with SR vacuolation [26], and RYR2 cKO mice show tachycardic arrhythmia, resulting in SCD [27]. However, cKO rabbits with 50% loss of the RYR2 protein do not develop an overt phenotype in the whole heart with normal levels of other Ca²⁺-handling proteins, although remodeling of RYR2 clusters and significant desynchronization of Ca²⁺ transients have been observed at the myocyte level [28]. These animal experiments demonstrate species specificity in Ca²⁺ homeostasis mechanisms, and the importance of experimental validation in the human heart to evaluate the pathogenicity of altered protein levels. Moreover, different results at the levels of the entire heart and the cardiomyocytes indicate the necessity of comprehensive expression profiling of Ca²⁺-handling proteins using human tissue samples to reveal the changes underlying pathological cardiac excitation-contraction coupling.

Downregulation of SERCA2a and NCX

Proteomic profiling of human SCD hearts also revealed the downregulation of Ca²⁺-handling proteins, such as SERCA2a and NCX. SERCA2a is a transmembrane protein that transports Ca²⁺ back into the SR, whereas NCX is a cell membrane-bound protein that excretes Ca²⁺ from the cell. These proteins have a diastolic effect on the human heart; approximately 76% and 24% of Ca²⁺ are removed by SERCA2a and NCX, respectively [29]. Cardiac SERCA2a abundance correlates with PKP2 abundance [30], and a mild decrease in SERCA2a has been observed in PKP2-mutant cardiomyocytes [31]. The downregulation of SERCA2a induces ventricular arrhythmia during ischemia-reperfusion [32] and oxidative stress [33]. Therefore, the decreased SERCA2a levels observed in this study may be related to PKP2 downregulation and an increased risk of ventricular arrhythmia. Moreover, decreased NCX activity has been reported to promote proarrhythmic delayed afterdepolarization and RYR2 gating failure in PKP2 cKO mice [25]. As NCX is concentrated in the T-tubular membrane, its blockade increases Ca²⁺ levels in the dyadic cleft (T-tubule–SR junction) and triggers Ca²⁺ sparks [34]. Therefore, decreased NCX levels in SCD hearts may also contribute to intracellular Ca²⁺ overload and increase the risk of ventricular arrhythmia.

Downregulation of energy-producing proteins

In this study, the levels of various energy-producing proteins were transmurally decreased in SCD hearts. A reduction of energy-producing proteins including glycolysis-related proteins, such as ALDOA and TPI1 [35], and mitochondrial proteins, such as oxidative phosphorylation complexes [36], has also been reported in the arterial tissue of patients with atrial fibrillation. These proteins were most substantially decreased in the inner layer of SCD hearts.

Mitochondrial dysfunction with the downregulation of electron transport activity facilitates the production of reactive oxygen species (ROS) and induces ventricular arrhythmias during ischemia-reperfusion injury [37]. Mitochondrial ROS production promotes Ca²⁺ leakage from the SR through RYR2 [38] and triggers a transient increase in Ca²⁺ sparks [39]. In contrast, increased oxidative stress inhibits SERCA2a-dependent Ca²⁺ transport into the SR and enhances intracellular Ca²⁺ overload [40]. Moreover, ROS promote reverse-mode NCX transport, whereby Na⁺ efflux and Ca²⁺ influx in ischemia-reperfusion contribute to Ca²⁺ overload [41]. Thus, mitochondrial dysfunction increases the risk of arrhythmia through enhanced ROS generation and reduced ATP production, necessary for the maintenance of ion channels and transporters [42].

Impact of endocardial ischemia

Based on physiological hemodynamics of the heart, chronic ischemia promotes myocardial fibrosis from the inner to the outer layer, with the progression of coronary atherosclerosis or cardiac hypertrophy. A pathological study focusing on the three myocardial layers in relation to cardiac strain reported that subendocardial fibrosis was weakly correlated with a decrease in the longitudinal strain of the hypertensive rat heart [43]. In contrast, our study revealed an inner-layer-dominant proteomic alteration without significant myocardial fibrosis, indicating that proteomic changes precede myocardial fibrosis in chronic mild ischemia.

Regarding the effects of ischemia on the expression of individual proteins, it has been reported that cardiac PKP2 levels are decreased in models of ischemia-reperfusion injury [44] and myocardial infarction [45]. SERCA2a suppression is a hallmark of ischemic heart disease [46,47] and cardiac hypertrophy [48]. Moreover, mitochondrial oxidative phosphorylation of proteins is reduced in rats with ischemic heart failure [49] and in a model of hypertensive heart failure [50]. Thus, the proteomic changes observed mainly in the inner layer were at least partly caused by endocardial ischemia.

Overall, the detected levels of each protein were moderately changed in SCD hearts, generally less than two-fold compared with the levels in control hearts. However, the combination of moderate changes in several Ca²⁺-handling proteins with mitochondrial dysfunction increases the risk of arrhythmia, and inner longitudinal layer dominance contributes to the decreased longitudinal strain often observed in high-risk patients with SCD.

Implications for forensic and clinical practice

Currently, cardiac injury markers used in clinical settings, such as cardiac troponin T and CK-MB in blood, are known to increase nonspecifically after death, making them unreliable for postmortem diagnosis. Furthermore, serum samples are often unavailable in postmortem investigations, and histological examination remains the cornerstone for determining the cause of death.

In this study, histological analysis revealed no significant myocardial fibrosis, and proteomic analysis did not detect significant alterations in known cardiac injury markers in SCD hearts. This may be explained by the fact that the SCD cases in this study did not suffer chronic heart failure and experienced fatal arrhythmia leading to cardiac arrest within an extremely short period, without histological evidence of myocardial necrosis. In contrast, the proteomic alterations identified in the inner myocardial layer in this study, which may lead to arrhythmic death, could precede myocardial fibrosis. These alterations can be detected by routine laboratory methods such as immunohistochemistry and may serve as histological indicators suggesting arrhythmogenic susceptibility. Although SCD remains a diagnosis of exclusion after ruling out other causes, detection of these protein changes may improve the diagnostic accuracy of SCD.

From a clinical perspective, measurement of the identified protein markers in the blood may offer a novel approach for early risk stratification of SCD before onset. Although circulating protein levels were not examined in the present study, the proteomic alterations identified in the inner myocardial layer could influence their circulating concentrations. Notably, serum BNP levels—known to correlate with SCD risk in patients with chronic heart failure—were not elevated in the SCD group of this study. These findings suggest that the identified protein candidates may serve as even earlier, subclinical indicators of susceptibility to SCD, preceding conventional biomarkers such as BNP.

Study limitations

During sample collection, we selected fresh tissue specimens at autopsy, within 24 hours of death. However, some degree of postmortem degradation is unavoidable when using human autopsy tissues, and this may have affected proteomic profiling. In addition, microscopical tissue sampling required considerable time, resulting in a relatively small sample size in this study. Moreover, clinical history—including comorbidities, daily medication use, and data at the time of death—was not always obtained after death. Therefore, while the findings are clinically valuable, they should be regarded as observational and hypothesis-generating rather than definitive.

In this study, high-throughput MS was used to quantify thousands of proteins; however, the protein levels do not directly reflect protein activity in vivo. For example, decreased RYR2 levels result in increased Ca²⁺ release through RYR2 [23]. Therefore, the decreased protein levels detected in the current study do not necessarily indicate decreased activity of this protein. As we used FFPE-archived tissues, we could not directly evaluate the activity of each protein in this study. Fresh samples enable the evaluation of protein activity; however, layer-specific cardiomyocyte sampling without fixation is difficult. Thus, protein activity assays for myocardial layers are a future topic of SCD research.

Moreover, protein modifications, including phosphorylation, glycosylation, ubiquitination, and oxidation, which are important regulators of protein activity, have not been examined. For example, phosphorylation and oxidation increase the open probability of RYR2 and promote Ca²⁺ leakage from RYR2, resulting in enhanced arrhythmic susceptibility [51]. Future comprehensive studies on protein modifications will deepen our understanding of post-translational alterations in SCD in middle-aged and older individuals.

Conclusion

This is the first report on the layer-specific proteomic profiling of human SCD hearts. Arrhythmogenic changes, including reduced levels of PKP2, RYR2, SERCA2a, NCX, and mitochondrial proteins, develop most prominently in the inner layer. As the proteome profile gradually changes from CH to SCD before myocardial fibrosis progresses, the detection of endocardial proteomic alterations may aid in the postmortem diagnosis of SCD in middle-aged and older asymptomatic individuals with CH.

Highlights

Human cardiomyocytes were microdissected separately from the three myocardial layers.
Proteomic alterations were most pronounced in the inner layer in sudden cardiac death (SCD).
SCD hearts exhibited decreased levels of energy-producing and Ca² ⁺ -handling proteins.
Proteomic changes progressed stepwise from control to cardiac hypertrophy and SCD.
These proteomic changes appeared before the development of myocardial fibrosis.

Supporting information

S1 Table. Oligonucleotide sequences for PKP2.

(DOCX)

pone.0339886.s001.docx^{(17KB, docx)}

S2 Table. Inter-group comparisons in all cases.

(XLSX)

pone.0339886.s002.xlsx^{(1.7MB, xlsx)}

S3 Table. Inter-layer comparisons in SCD cases.

(XLSX)

pone.0339886.s003.xlsx^{(676.4KB, xlsx)}

S4 Table. Inter-layer comparisons in CH cases.

(XLSX)

pone.0339886.s004.xlsx^{(493.8KB, xlsx)}

S5 Table. Inter-layer comparisons in control cases.

Note that the original data for inter-layer comparisons in control cases was previously published [13]; in the present study, we reanalyzed these data using multiple nonparametric methods.

(XLSX)

pone.0339886.s005.xlsx^{(483.2KB, xlsx)}

S6 Table. Differentially expressed protein lists.

(XLSX)

pone.0339886.s006.xlsx^{(532.2KB, xlsx)}

S7 Table. Gene Ontology (GO) analysis of proteins with altered levels in SCD cases.

(XLSX)

pone.0339886.s007.xlsx^{(34.5KB, xlsx)}

S8 Table. Pathway analysis of proteins with altered levels in SCD cases.

(XLSX)

pone.0339886.s008.xlsx^{(30.6KB, xlsx)}

S1 File. SuppData.

(DOCX)

pone.0339886.s009.docx^{(14.9KB, docx)}

Acknowledgments

The authors are grateful to the technical staff at the Forensic Laboratory and Support Center for Medical Research and Education at Tokai University.

Abbreviations

BNP: brain natriuretic peptide
CH: cardiac hypertrophy
KO: conditional knockout
FFPE: formalin-fixed paraffin-embedded
GO: gene ontology
ID: intercalated disk
KO: knockout
MS: mass spectrometry
ROS: reactive oxygen species
SCD: sudden cardiac death
SR: sarcoplasmic reticulum

Data Availability

All relevant data for this study are publicly available from the Dryad repository (https://doi.org/10.5061/dryad.q573n5tx2).

Funding Statement

This work was supported by JSPS KAKEHNHI (grant number: 23H03178) and the MEXT promotion of the Distinctive Joint Research Center Program at the Advanced Medical Research Center, Yokohama City University (grant number: JPMXP0622717006).

References

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PLoS One. doi: 10.1371/journal.pone.0339886.r001

Decision Letter 0

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22 Oct 2025

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Additional Editor Comments:

The reviewers all commented positively on your manuscript. However, several concerns need to be addressed including the need for within-group comparisons of proteomic profiles across three ventricular layers, particularly in the SCD group.

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Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: The paper titled: “Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death” is authored by Yu Kakimoto et al.

Some concerns could be addressed to consolidate the scientific message:

1- Please indicate the scale bar on each picture of Figure 2 and 5.

2- Indicate the dots in the whisker box plot graphs.

3- Figure legends must be consolidated with a scientific title and more descriptive information. Please improve.

4- Bar graph from figure 5 are unreadable. Please separate in different figures and increase the size of graphs.

5- Define all abbreviations at first use.

6- More information about the included patients is required, including sex, comorbidities, medication, weight, etc.

7- Provide a Highlight section with up to 5 bullet points to describe the main findings of the paper.

Reviewer #2: Review Comments to the Author

This study, based on sudden cardiac death (SCD) cases and matched controls, presents meaningful findings. However, the overall presentation and interpretation of the data are insufficient in several key aspects.

Merits:

The research team enrolled SCD cases and controls over a nearly 10-year period and compared proteomic features across the three ventricular layers-an approach that adds spatial resolution and biological insight to the analysis.

Shortcomings and Recommendations:

1. Layer-Specific Comparison Within Groups

I strongly recommend that the authors perform within-group comparisons of proteomic profiles across the three ventricular layers, particularly in the SCD group. This would help clarify whether layer-specific proteomic alterations are associated with the pathophysiology of SCD.

2. Validation of Layer-Specific Protein Expression

It would be informative to simultaneously demonstrate the expression of validated proteins (e.g., PKP2, RyR2) across all three layers within individual samples. This would allow for a direct assessment of inter-layer expression heterogeneity and strengthen the spatial proteomic

3. Protein Degradation analysis

Postmortem autolysis can lead to significant protein degradation, potentially confounding proteomic findings. The authors should carefully evaluate and, if possible, quantify the extent of postmortem protein degradation to ensure that observed differences are primarily disease-related rather than degradation-related.

4. Data Presentation and Statistical Clarity

The result section: each subtitle should represent the main finding of the relative part. For example, line 238, this title meaningless and need to be modified according to the relative contents or findings.

Figure 1: The BNP levels appear markedly different between SCD and control groups. Please clarify why this difference was not statistically significant.

Figure 2: Provide detailed methodology for myocyte diameter measurement. How was measurement consistency ensured across different regions? Also, report the total number of myocytes analyzed per group.

Figure 3B: The fold changes do not appear to correspond directly to the relative abundance values. Please verify whether fold changes should be expressed as inverse values (e.g., 1/9.2 ≈ 0.11). Additionally, comparisons between SCD and CH (control heart?) groups should be included.

Figure 4A-C: Similar to Figure 3B, include direct comparisons between SCD and CH groups to enhance interpretability.

Figure 5B: The immunostaining images lack clarity in distinguishing target signals (e.g., PKP2, RyR2) from background. Consider adjusting color contrast or providing higher-resolution images. Please also specify the sample size for each group and include a comprehensive statistical summary table.

SuppData: I suggested to give a full list of differential expressed proteins (DEPs) among different groups and among different layers. Each data table should have a specific name.

5. Discussion-Forensic Application Potential

The discussion should be expanded to address the potential utility of the identified proteins in forensic practice. A comparative analysis with existing cardiac biomarkers used in postmortem SCD diagnosis would strengthen the translational relevance of the findings.

Reviewer #3: This Reviewer rewards the authors for this elegant study. It is well written, clear and concise, with novel and interesting data on the proteomic changes in the three muscular layers of the human heart in cases of sudden cardiac death and cardiac hypertrophy (w/o HCM).

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Ida Gjervold Lunde

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PLoS One. 2025 Dec 30;20(12):e0339886. doi: 10.1371/journal.pone.0339886.r002

Author response to Decision Letter 1

3 Nov 2025

Journal Requirements:

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Response: We have ensured that JSPS KAKEHNHI (grant number 23H03178) and the MEXT promotion of the Distinctive Joint Research Center Program at the Advanced Medical Research Center, Yokohama City University (grant number JPMXP0622717006) are correct.

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Response: We have added the above statement to the cover letter.

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Response: Thank you for your request. We have deposited the raw data set to Dryad. The stable access information is:DOI: 10.5061/dryad.q573n5tx2.

Reviewer Sharing Link (for private access): http://datadryad.org/share/LINK_NOT_FOR_PUBLICATION/oZ7H4y_TtOndYYe7L2co_qQCkN6W12dxfwaDnjxDv6A.

Response: We have added the captions for supplemental tables at the end of the manuscript.

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5. Review Comments to the Author

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Reviewer #1: The paper titled: “Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death” is authored by Yu Kakimoto et al.

Some concerns could be addressed to consolidate the scientific message:

1- Please indicate the scale bar on each picture of Figure 2 and 5.

Response: Thank you for your scientific review comments. We have revised the manuscript and figures according to your advice. We have added the scale bars.

2- Indicate the dots in the whisker box plot graphs.

Response: Thank you for your helpful suggestion. We have added the data points (dots) to the whisker box plots in the revised Figures 2 and 5.

3- Figure legends must be consolidated with a scientific title and more descriptive information. Please improve.

Response: We have enriched the legends of Fig.2, 3, 5, 6 and 7.

4- Bar graph from figure 5 are unreadable. Please separate in different figures and increase the size of graphs.

Response: Thank you for your feedback regarding the readability of Figure 5. We have separated the original panels 5A and 5B into new Figures 5 and 6. In addition, we have increased the overall graph and font sizes, particularly for the y-axis labels, in the new Figure 5 to improve clarity. The figure numbers have been revised throughout the manuscript accordingly.

5- Define all abbreviations at first use.

Response: We have confirmed that all abbreviations are defined upon their first use.

6- More information about the included patients is required, including sex, comorbidities, medication, weight, etc.

Response: Thank you for your careful review. At the time of forensic autopsy, the clinical history of the deceased is often unknown, and unfortunately, information on medication was unavailable for this study. We have, however, incorporated the available information, including sex, body weight, and comorbidities, into Fig. 1.

7- Provide a Highlight section with up to 5 bullet points to describe the main findings of the paper.

Response: We have added a Highlight section on page 2.

Reviewer #2: Review Comments to the Author

Merits:

Response: Thank you for your scientific review comments. We have revised the manuscript and figures according to your advice.

Shortcomings and Recommendations:

1. Layer-Specific Comparison Within Groups

Response: Thank you for your suggestion. As you recommended, we have performed additional within-group comparisons of proteomic profiles across the three ventricular layers. These results are presented in Supplementary Tables S3 (SCD cases), S4 (CH cases), and S5 (Control cases). This analysis was conducted using the Friedman test, followed by the Wilcoxon signed-rank test for post-hoc comparisons.

2. Validation of Layer-Specific Protein Expression

Response: We agree that demonstrating protein expression across all three layers within individual samples is informative. However, presenting the complete dataset of individual protein profiles in the main text would be excessively lengthy and redundant given the aggregated data already provided. To ensure clarity and maintain focus, we have included these detailed data in Supplementary Table S2.

3. Protein Degradation analysis

Response: We acknowledge that postmortem degradation is an inevitable limitation when using autoptic tissue samples, and we have addressed this in the limitation section. Unfortunately, the small sample volume of the FFPE tissues precludes us from performing additional validation experiments, such as Western blotting.

4. Data Presentation and Statistical Clarity

Response: Thank you for your helpful comments. We have revised all subtitles in the Results section to clearly reflect the main findings of the respective content, and the paragraphs have been rearranged accordingly.

Figure 1: The BNP levels appear markedly different between SCD and control groups. Please clarify why this difference was not statistically significant.

Response: We appreciate your important comments. We apologize for the mispresentation: several values in Fig. 1 incorrectly displayed as standard error (SE). We have corrected this, and Fig. 1 now consistently presents all values as mean ± SD. Due to the notably wide standard deviation (for example, 13.6 ±18.0), a statistically significant difference in BNP levels was not observed between the groups.

Response: As the nucleus is located at the center of each cardiomyocyte, the cardiomyocyte diameter was defined as the minor axis measured at the nuclear level. Because some degree of inconsistency is inevitable in microscopic measurements, we assessed 10 cardiomyocytes per field and averaged the values from 10 randomly selected fields for each case. In total, 100 cardiomyocytes were analyzed per myocardial layer per case. The Methods section has been revised accordingly to include these details.

Figure 3B: The fold changes do not appear to correspond directly to the relative abundance values. Please verify whether fold changes should be expressed as inverse values (e.g., 1/9.2 ≈ 0.11).

Response: The fold change values are calculated to always be greater than 1. Specifically, the fold change represents the ratio of SCD/Ctrl for proteins with increased abundance, and the ratio of Ctrl/SCD for proteins with decreased abundance. We have updated the figure legend to clarify this calculation method.

Additionally, comparisons between SCD and CH (control heart?) groups should be included.

Response: As shown in Table S2, the differences between SCD and CH cases were minimal. Only 17 (10 increased and 7 decreased), 12 (9 increased and 3 decreased), and 13 (5 increased and 8 decreased) proteins were differentially detected in the inner, middle, and outer layers, respectively. We have enriched the result section accordingly.

Figure 4A-C: Similar to Figure 3B, include direct comparisons between SCD and CH groups to enhance interpretability.

Response: We confirm that the number of differentially detected proteins between the SCD and CH groups was small. Consequently, no GO terms or KEGG pathways were significantly associated with the proteins differentially detected between SCD and CH cases across all layers. We have added this clarifying statement to the Results section.

Response: We increased the color contrast by 10% for all figures. We performed immunostaining on four SCD cases, three CH cases, and three control cases, from which a vertical section of the ventricular wall was available. Absolute quantification of these immunostaining images is inherently difficult, and moreover, the small sample size makes reliable statistical analysis infeasible. Consequently, we did not perform statistical tests on the immunostaining results. We have revised the Methods section accordingly.

SuppData: I suggested to give a full list of differential expressed proteins (DEPs) among different groups and among different layers. Each data table should have a specific name.

Response: Thank you for the suggestion. Comprehensive lists of differentially expressed proteins (DEPs) have been compiled in S6 Table, each with specific nomenclature. DEPs among groups were identified using the Kruskal–Wallis test (p < 0.05), and DEPs among layers within each group were identified using the Friedman test (p < 0.05). The table includes complete protein annotations and detailed statistical results, including post hoc p-values obtained from the Steel–Dwass and Wilcoxon signed-rank tests, respectively.

5. Discussion-Forensic Application Potential

Response: We appreciate the reviewer’s

Attachment

Submitted filename: Rebuttal-20251023.docx

pone.0339886.s011.docx^{(29.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0339886.r003

Decision Letter 1

Aldrin Gomes

14 Dec 2025

<p>Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death

PONE-D-25-50384R1

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2. Is the manuscript technically sound, and do the data support the conclusions??>

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The PLOS Data policy

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PLoS One. doi: 10.1371/journal.pone.0339886.r004

Acceptance letter

Aldrin Gomes

PONE-D-25-50384R1

PLOS One

Dear Dr. Kakimoto,

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Oligonucleotide sequences for PKP2.

(DOCX)

pone.0339886.s001.docx^{(17KB, docx)}

S2 Table. Inter-group comparisons in all cases.

(XLSX)

pone.0339886.s002.xlsx^{(1.7MB, xlsx)}

S3 Table. Inter-layer comparisons in SCD cases.

(XLSX)

pone.0339886.s003.xlsx^{(676.4KB, xlsx)}

S4 Table. Inter-layer comparisons in CH cases.

(XLSX)

pone.0339886.s004.xlsx^{(493.8KB, xlsx)}

S5 Table. Inter-layer comparisons in control cases.

Note that the original data for inter-layer comparisons in control cases was previously published [13]; in the present study, we reanalyzed these data using multiple nonparametric methods.

(XLSX)

pone.0339886.s005.xlsx^{(483.2KB, xlsx)}

S6 Table. Differentially expressed protein lists.

(XLSX)

pone.0339886.s006.xlsx^{(532.2KB, xlsx)}

S7 Table. Gene Ontology (GO) analysis of proteins with altered levels in SCD cases.

(XLSX)

pone.0339886.s007.xlsx^{(34.5KB, xlsx)}

S8 Table. Pathway analysis of proteins with altered levels in SCD cases.

(XLSX)

pone.0339886.s008.xlsx^{(30.6KB, xlsx)}

S1 File. SuppData.

(DOCX)

pone.0339886.s009.docx^{(14.9KB, docx)}

Attachment

Submitted filename: Review Comments to the Author.docx

pone.0339886.s010.docx^{(19.7KB, docx)}

Attachment

Submitted filename: Rebuttal-20251023.docx

pone.0339886.s011.docx^{(29.4KB, docx)}

Data Availability Statement

All relevant data for this study are publicly available from the Dryad repository (https://doi.org/10.5061/dryad.q573n5tx2).

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PERMALINK

Layer-specific proteomic analysis of human hearts in patients with sudden cardiac death

Yu Kakimoto

Xueting Guan

Atsushi Ueda

Yayoi Kimura

Tomoko Akiyama

Masayuki Tanaka

Haruka Ikeda

Kazuho Maeda

Shotaro Isozaki

Roles

Abstract

Background

Methods

Results and discussion

1. Introduction

Materials and methods

Study population

Fig 1. Microscopic tissue sampling of three myocardial layers in the human heart. (A) Case characteristics.

Histological analysis

Laser microdissection

Sample preparation for proteomic analysis

Proteomic analysis using data dependent acquisition-MS analysis

Bioinformatic analysis

PKP2 sequencing

Immunohistochemical analysis

Results

Myocardial hypertrophy without significant fibrosis in SCD and CH cases

Fig 2. Histological findings in human cardiac tissue samples.

Pronounced proteomic alterations in the inner layer of SCD cases

Fig 3. Overview of layer-specific proteomic profiling of human heart samples.

Fig 4. Bioinformatic analysis of cardiomyocyte proteins with altered abundance in SCD cases compared to control cases.

Decreased Ca2 ⁺ -handling and energy-producing proteins from CH to SCD cases

Fig 5. Proteomic changes in cardiomyopathy-related and energy-producing proteins.

Fig 6. Representative immunohistochemistry images of the inner myocardial layer.

Discussion

Fig 7. Summary of the proteomic changes mainly in the inner layer of SCD hearts.

Downregulation of PKP2 and RYR2

Downregulation of SERCA2a and NCX

Downregulation of energy-producing proteins

Impact of endocardial ischemia

Implications for forensic and clinical practice

Study limitations

Conclusion

Highlights

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Aldrin Gomes

Roles

Author response to Decision Letter 1

Decision Letter 1

Aldrin Gomes

Roles

Acceptance letter

Aldrin Gomes

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Decreased Ca² ⁺ -handling and energy-producing proteins from CH to SCD cases