Subtype Cardiomyopathies Characteristics
In this study, WGCNA was applied to investigate the whole transcription profiling of heart failure patient’s biopsy arise from eight different etiologies (90 cases, 8 case groups sorting, Supporting Table. 1, Fig.1, Supporting Fig.1). It is reasonable to build the co-expression networks with different clinical traits using the Pearson correlation analysis (Fig.2A). The correlation among cardiomyopathy features and eight case groups were separated by performed hierarchical clustering. To discover the correlated modules to cardiomyopathies phenotype, the genes significance of modules was calculated by the linear mixed effects model for testing the association of node to the pathological phenotypes. Next, it was analyzed that the associated significance between identified individual gene modules and different cardiomyopathies, respectively (Fig.2B).
Gene Co-Expression Network Construction and Module Identification
After using a dynamic tree cutting algorithm, the distinct co-expression modules were identified that significantly related to different pathological features (Fig.2B & Fig.3A), and the number of significant related modules and containing genes were varied from different subcases. Twenty-three modules were detected through the dataset (Fig.2B, Table.1), and contained genes varied from 121 to 14938. The correlation significance of module and pathological features were selected by module significance (MS) correlation and statistics p-value. The higher value of module eigengene (ME) correlation, the closer relation of module is correlated to cardiomyopathies (Supporting Fig. 3A-G). Through calculation of the linear mixed-effects model, significant modules were identified for different subtype groups (Fig.3B). In the idiopathic dilated group, six modules were significantly associated with idiopathic dilated status, including turquoise module (t-value = 0.75, p-value = 5e−17), lightcyan module (t-value = 0.54, p-value = 7e−08), tan module (t-value = 0.56, p-value = 2e−08), grey module (t-value = 0.7, p-value = 8e−14), green module (t-value = 0.45, p-value = 1e−05) and the blue module (t-value = 0.72, p-value = 8e−15) (Fig.2B, Fig.3B, Table.1). In ischemic group, six modules were significantly correlated to ischemic (IS) trait, including lightyellow module (t-value = 0.43, p-value = 3e−05), greenyellow module (t-value = 0.41, p-value = 8e−05), lightgreen module (t-value = 0.4, p-value = 1e−04), red module (t-value = 0.35, p-value = 8e−04), green module (t-value = 0.24, p-value = 0.03) and the blue module (t-value = 0.44, p-value = 2e−05) (Fig.2B, Fig.3B, Table.1). In idiopathic cardiomyopathy (IdCM) group, three modules were significantly linked to pathological trait, including Magenta (t-value = 0.43, p-value = 4e−05), Purple (t-value = 0.31, p-value = 0.003) and Brown (t-value = 0.25, p-value = 0.02). In familial cardiomyopathy cases, only Magenta MEs (t-value = 0.22, p-value = 0.04) was significantly correlated to its trait (Fig.2B, Fig.3B). For the Hypertrophic cardiomyopathy (HCM) group, None of ME was identified and ignored in next step analysis (Fig.2B). In the Post. Partum cardiomyopathy (PCM) group, Magenta module (t-value = 0.24, p-value = 0.03) was weakly correlated to trait (Fig.2B, Fig.3B, Table.1). In ischemic cardiomyopathy group, seven modules were significantly correlated to pathological trait, including Black (t-value = 0.56, p-value = 2e−08), Midnightblue (t-value = 0.49, p-value = 2e−06), Darkred (t-value = 0.43, p-value = 3e−05), Cyan (t-value = 0.34, p-value = 0.02), Yellow (t-value = 0.57, p-value = 1e−08), Pink (t-value = 0.29, p-value = 0.007) and Red (t-value = 0.26, p-value = 0.02) (Fig.3B). For Viral cardiomyopathy (VCM), only two modules, Cyan (t-value = 0.35, p-value = 0.001) and Magenta (t-value = 0.23, p-value = 0.03), were significant correlation (Fig.2B, Fig.3B).
Enriched Genes Significant related to different cardiomyopathies
Calculated and compared the module memberships (MM) correlation and Genes Significance (GS) through the whole modules, the most significant modules were identified that correlated to different cardiomyopathies traits (Table.1, Fig.3B). In the idiopathic dilated group, the turquoise (cor = 0.77, p < 1.0e−200, GS=0.4244) was most significant module (Supporting Fig.3A). The lightyellow module was the most significant linked to ischemic (cor = 0.13, p = 3.0e−05, GS=0.2733) (Supporting Fig.3B). The magenta module was the most significant related to idiopathic cardiomyopathy (IdCM) (cor = 0.65, p = 1.5e−114, GS=0.2783) (Supporting Fig.3C). In familial cardiomyopathy, magenta was the highest relevance module (cor = 0.31, p = 1.7e−22, GS=0.1502) (Supporting Fig.3D). In the post. partum cardiomyopathy group, magenta module is the highest relevance to its status (cor = 0.30, p = 4.2e−21, GS=0.1583) (Supporting Fig.3E). In ischemic cardiomyopathy group, yellow module was the highest relevance to ischemic cardiomyopathy (cor = 0.63, p < 1.0e−200, GS=0.3259) (Supporting Fig.3F). In viral cardiomyopathy group, cyan module was the highest relevance to pathological status (cor = 0.39, p = 8.2e−24, GS=0.2245) (Supporting Fig.3G). In addition, the scatter plot of multiple module memberships (MM) was plotted against the Genes Significance (GS) in each significant module, and the point represented each gene contained in a module. It was discovered that the most significantly module associated with different cardiomyopathies feature through the Eigengene dendrogram analysis (Supporting. Fig.4A-G).
Hierarchical Clustering of Eigengene Profiles with cardiomyopathies Traits
Based on the ME’s values, we have calculated and performed the hierarchical clustering to identify relationships between all modules and different cardiomyopathies traits. In the idiopathic dilated group, the turquoise module was tightly clustered with idiopathic dilated in the same cluster (Fig. 4A). In the ischemic group, the greenyellow and lightyellow modules were the closest module clustered with ischemic (Fig.4B). In last step analysis, greenyellow module (t-value = 0.41, p-value = 8e−05, GS = 0.2418) has the secondary higher correlation with ischemic status (Fig.2B, Fig.3B). It suggests that greenyellow module contained genes involve the progress of ischemic. In idiopathic cardiomyopathy group, modules of brown, magenta and purple were clustered with idiopathic cardiomyopathy in a separate branch, and magenta and purple module located in same cluster (Supporting Fig.4C). It suggested that purple and magenta module were the top two significant associated with cardiomyopathy status (Fig.2B, Table. 1). In the familial cardiomyopathy and post. partum cardiomyopathy groups, modules of brown, magenta and purple were tightly clustered with familiar cardiomyopathy, while the magenta module was the most significant associated with disease status (Supporting Fig. 4D-4E). In the hypertrophic cardiomyopathy group, no module was associated with its pathological feature. In the ischemic cardiomyopathy group, although module of black and midnightblue were clustered in closer branch, the yellow module was located in the adjacent branch (Supporting Fig. 4F). Combined with the module-trait relationship correlation and gene significance results, it suggested that module of black, midnightblue and yellow were significant associated with ischemic cardiomyopathy (Fig.2B, Fig. 3B, Table. 1). Although module of brown and blue have higher GS values (Table.1), they were negative and ignored for analysis (Fig. 2B). The yellow module was the most significant correlation to ischemic cardiomyopathy. In the viral cardiomyopathy group, although the modules of magenta, purple and brown clustered with viral cardiomyopathy in a separated branch, and cyan module had the highest GS value associated with pathological feature (t-value = 0.35, p-value = 1e−03, GS = 0.2245) (Fig.2B, Fig. 3B, Supporting Fig.4G). It suggested that magenta module containing genes involve the progress of viral cardiomyopathy.
Function and pathway enrichment analysis
The results of enrichments analysis were summarized as bar chart, including Biological Process, Molecular Function and Cellular Component (Ischemic, Supporting Fig.5A-A; Idiopathic Cardiomyopathy, Supporting Fig.5B-A; Familial Cardiomyopathy, Supporting Fig.5C-A; Post-Partum Cardiomyopathy, Supporting Fig.5D-A; Ischemic Cardiomyopathy, Supporting Fig.5E-A; Viral Cardiomyopathy, Supporting Fig.5F-A). The majority of enriched functions and pathways had some common features. The functions enrichment results showed that these significant genes played key roles in endoplasmic reticulum functions, cell functions (migration, death, growth, division), DNA binding, protein-protein interaction, kinases activity and signal transduction. The Biological Process mainly concentrated on metabolic process, organelle organization, cytoplasmic transport, cell communication, protein targeting to peroxisome and, etc. The genes significance enriched in molecular functions were summarized and listed in table (Supporting Table.4). Molecular functions were linked with transcription coactivator/cofactor activity, RNA binding, ubiquitin protein ligase binding, nucleic acid binding and ligase activity. The cellular component mainly enriched in intracellular organelle part, membrane-bounded organelle, intracellular organelle compartment, cytoplasm, etc. Furthermore, through gene network literature mining and clustering analysis, the significance genes related to these different cardiomyopathies were clustered and labelled according to cellular functions and pathological feature keywords literature corresponding (Ischemic, Supporting Fig.6A; Idiopathic Cardiomyopathy, Supporting Fig.6B; Familial Cardiomyopathy, Supporting Fig.6C; Post-Partum Cardiomyopathy, Supporting Fig.6D; Ischemic Cardiomyopathy, Supporting Fig.6E; Viral Cardiomyopathy, Supporting Fig.6F). The signaling pathways were concentrated on Protein Kinase C pathway and majority of involved genes were labelled as un-reported. Moreover, the genes network and connectivity of significance genes in modules were identified and demonstrated as node-connection map, which correlated to different traits (Ischemic, Supporting Fig.5A-B; Idiopathic Cardiomyopathy, Supporting Fig.5B-B; Familial Cardiomyopathy, Supporting Fig.5C-B; Post-Partum Cardiomyopathy, Supporting Fig.5D-B; Ischemic Cardiomyopathy, Supporting Fig.5E-B; Viral Cardiomyopathy, Supporting Fig.5F-B). The identified key regulatory genes were labelled with purple border, which was reported associated with pathological feature. More interesting, there was no related key regulatory gene identified in the blast of significance genes network and connectivity for Post-Partum cardiomyopathy group.
Identification of hub genes for cardiomyopathies
Through co-expression network (MM-GS) filtered, varied number of hub gene candidates were identified in different cases groups (5 genes in Ischemic group, Fig.4A; 113 genes in Idiopathic Cardiomyopathy group, Fig.4B; 41 genes in Familiar Cardiomyopathy group, Fig.4C; 65 genes in Post-Partum Cardiomyopathy group, Fig.4D; 83 genes in Ischemic Cardiomyopathy group, Fig.4E; 60 genes in Viral Cardiomyopathy group, Fig.4F). Calculated by the PPI network method, the hub gene candidates were summarized as groups (12 genes in Ischemic group, Fig.4A; 120 genes in idiopathic cardiomyopathy group, Fig.4B; 277 genes in Familiar Cardiomyopathy group, Fig.4C; 119 genes in Post-Partum Cardiomyopathy group, Fig.4D; 348 genes in Ischemic Cardiomyopathy group, Fig.4E; 49 genes in Viral Cardiomyopathy group, Fig.4F). These real hub genes were determined by the overlap of PPI network and co-expression network and chosen for further analysis (Table.3). The numbers of real hub genes were listed as Ischemic (1), Idiopathic Cardiomyopathy (19), Familiar Cardiomyopathy (8), Post-Partum Cardiomyopathy (9), Ischemic Cardiomyopathy (15) and Viral Cardiomyopathy (6). In the Idiopathic Dilated group, there was no real hub genes and dismissed for further deep analysis.
Through Venn diagrams analysis, three axes of common hub genes were determined among these cardiomyopathies groups (Fig.4G). The first axis was gene PICALM that shared by Ischemic Cardiomyopathy, Idiopathic Cardiomyopathy and Post. Partum Cardiomyopathy groups (Fig.4G) and PICALM was significantly up-regulated in Idiopathic Cardiomyopathy and Ischemic Cardiomyopathy groups (Table.3). PICALM is key regulator in iron homeostasis, clathrin-mediated endocytosis [11, 12]. Overexpression of PICALM impaired endocytosis of Transferrin (Tf) Receptor (TfR) and Epidermal Growth Factor Receptor (EGFR) and disturbed the iron homeostasis [12, 13]. Up to now, it is still illusive that the exactly role and deregulatory mechanism of PICALM in cardiomyopathies. It is strongly suggesting that PICALM work as potential novel biomarker and therapy target for these subcases of cardiomyopathies. The secondary axis was the genes of PRKACB, MOB1A, CDC40, which shared in Post. Partum Cardiomyopathy and Idiopathic Cardiomyopathy groups. These genes (PRKACB, MOB1A, CDC40) were significantly overexpressed in Idiopathic cardiomyopathy group, and MOB1A was up-regulated in Post. Partum cardiomyopathy group (Table.3).These genes linked with the cAMP (cyclic AMP)-dependent protein kinase A (PKA) mediated the exciting – contraction coupling in cardiomyocytes , and regulated microtubule stability, cell cycle and cell proliferation & migration, and restrained cardiomyocyte proliferation and size via Hippo pathway [15, 16]. PRKACB (protein kinase cAMP-activated catalytic subunit β gene) was linked to congenital heart defect with abnormal over-expression . MOB1A (MOB kinase activator 1A) was required for cytokinesis through regulating microtubule stability. It worked as binding partners as well as co-activators of Ndr family protein kinases and mediated phosphor-recognition in core Hippo pathway that restrains cardiomyocyte proliferation during development to control cardiomyocyte size[15, 16]. Overexpression of MOB1A induces centrosomes fail to split and cell size dysregulation. CDC40 (Cell Division Cycle 40), a splicing factor of cell division cycle 40 homolog, regulates cell cycle and cell proliferation and migration. Overexpression of CDC40 causes abnormally cell proliferation and migration, and linked with carcinogenesis. The third axis contained five genes (CREB1, DBT, NCOA2, NUDT21, PIK3C2A) and was overlapped among three groups of Familial / Idiopathic / Post. Partum Cardiomyopathy (Fig.4G). The CREB1 (cAMP-responsive element-binding protein) had been identified as the transcription factor and mediated cAMP stimulation by multiple extracellular signals, such as growth factors and hormones. The CREB1 was the key regulator in heart and linked with heart disease via cAMP-PKA pathway dysregulation [21, 22]. The DBT (dihydrolipoamide branched chain transacylase E2) is an inner-mitochondrial enzyme complex regulated to degrade the branched-chain amino acids isoleucine, leucine, and valine. The DBT was reported as clinical diagnostics biomarker for patients with dilated cardiomyopathy via caused mitochondria dysfunction . NCOA2 (nuclear receptor coactivator 2) is a transcriptional coactivator that functional aid for nuclear hormone receptors, including steroid, thyroid, retinoid, and vitamin D receptors. NCOA2 promotes muscle cells maintenance and growth, eventually regulates in cardiac cTnT levels[25, 26]. Overexpression of NCOA2 regulated cell proliferation in cardiomyopathy[26, 27]. NUDT21 (nudix hydrolase 21) is a novel of cell fate regulator by alternative polyadenylation chromatin signaling, and suppression of NUDT21 will enhance the cell pluripotent, facilitated trans-differentiation into stem cell. NUDT21 regulates cell proliferation through ERK pathway. Up to now, little knows about the function of NUDT21 in cardiomyocytes. PIK3C2A (phosphatidylinositol-4-phosphate 3-kinase catalytic subunit type 2 alpha) is an enzyme belong to phosphorylate the 3'-OH of inositol ring of phosphatidylinositol (PI) superfamily and regulates multiple signaling pathways. PIK3C2A is mainly expressed in endothelial cells, vascular endothelium, and smooth muscle. Lower expression of PIK3C2A in peripheral blood was used as significant biomarker for acute myocardial infarction patients . More interesting, these hub genes showed different expression pattern. The expression level of DBT, NCOA2, NUDT21 and PIK3C2A were significantly upregulated in Idiopathic cardiomyopathy group, and PIK3C2A was up-regulated in Familiar cardiomyopathy group (Table.3). It hints that these hub genes play different regulatory pattern in the progress of these subtype’s cardiomyopathies. The fourth axis of common hub genes (HNRNPC, UEVLD) were shared by Familiar Cardiomyopathy and Idiopathic Cardiomyopathy groups, and significantly overexpressed in Idiopathic cardiomyopathy group (Table.3). HNRNPC (heterogeneous nuclear ribonucleoprotein C) is RNA binding protein that belong to ubiquitously expressed heterogeneous nuclear ribonucleoproteins subfamily, and mediates pre-mRNAs transport and metabolism between cytoplasm and nucleus [32, 33] and overexpression caused cells multi-nucleation . UEVLD (EV and lactate/malate dehydrogenase domain-containing protein) involves the protein degradation and dysregulated linked with metabolic disease . In this study, the expression level of HNRNPC and UEVLD were significantly up-regulated in Idiopathic cardiomyopathy group (Table.3). Furthermore, through the different significant expression analysis, the significant expressed hub genes were sorted into five different groups (Table.3, p<0.05), including 18 hub genes in Idiopathic Cardiomyopathy group, 1 hub gene in Familiar Cardiomyopathy and Post. Partum Cardiomyopathy groups, 7 genes in Ischemic Cardiomyopathy group and 5 genes in Viral Cardiomyopathy group. Combined these results together, it hints that these significantly expressed Hub genes play dominant role and work as common key regulatory nodes in progress of cardiomyopathies.
Blast through GenClip2, the key functions and pathways of significance genes were enriched and summarized as Biological Process, Molecular Function, Cellular Component and pathway (Supporting Fig.5A-F). The Biological Processes were mainly concentrated in subgroups of cellular macromolecular metabolic process, protein metabolic process, organic substance metabolic process and macromolecule modification. The molecular functions involved in protein binding, heterocyclic compound binding, purine ribonucleotide binding, iron binding and nucleotide binding, etc. The cellular components included membrane-bounded organelle, intracellular organelle part, etc. The pathways concentrated on mitogen-activated protein kinase（MAPK）signaling pathway, protein processing in endoplasmic reticulum, regulation of actin cytoskeleton, etc. These results indicated that dysregulation of cardiac functions were associated with metabolism abnormal and accelerated progress of cardiomyopathies.
Identified Signature genes through Cardiovascular disease BioPortal
The disease signature genes were identified and summarized with the annotation of genetic dysregulation correlated to cardiomyopathies feature (Table. 4). Ten signature genes were identified in the ischemic group and viral cardiomyopathy group. Forty signature genes were shared by the groups of familiar cardiomyopathy, Post-partum cardiomyopathy and Idiopathic cardiomyopathy (Table.4). The 69 signature genes were filtered in the ischemic cardiomyopathy group. All listed disease signature genes were summarized with functional annotation and heart diseases phenotypes (Table.4). The common signature genes among different groups were demonstrated by Venn Diagram (Figure.5A). Four signature genes (MDM4, CFLAR, RPS6KB1, PKD1L2) were shared by Ischemic and Ischemic Cardiomyopathy group (Table.4, Fig.5B &G) [36-39]. Ischemic cardiomyopathy group did share eight disease signature genes (MAPK1, MAPK11, MAPK14, LMNA, RAC1, PECAM1, XIAP, CREB1) with Post. Partum/Familiar/Idiopathic Cardiomyopathy groups, which dysregulated in cardiomyopathies [22, 40], and genes expression level of MAPK1, MAPK11, LMNA, RAC1 were significantly up-regulated in these cardiomyopathies groups (Table.5, Fig.5G). These common disease signature genes would be potential key regulators of the Ischemic Cardiomyopathy progress. Two signature genes (TFAM, RHEB) shared between Viral Cardiomyopathy and Post. Partum / Familiar /Idiopathic Cardiomyopathy groups, which were involving in development of cardiac hypertrophy  and Mitochondrial Cardiomyopathy . It suggests that TFAM and RHEB work as novel biomarker for viral cardiomyopathy.
Validated expression of disease signature genes
The number of significantly changed signature genes were varied from ischemic (1), idiopathic cardiomyopathy (15), familiar cardiomyopathy (9) and post-partum cardiomyopathy (11), Ischemic cardiomyopathy (31) and viral cardiomyopathy (1) (Fig.5D-F, Table.5). In ischemic group, only MDM4 was identified (FC=1.0495, p=0.0037) among 10 genes (Table 5, Fig.5B), which genetic deletion associated with cardiomyopathy . In viral cardiomyopathy group, gene COA5 was significant overexpression (FC=1.087485, p<0.0001) among 10 genes (Table 5, Fig.5C), which was upregulated in Ischemia/Reperfusion Injury caused cardiomyopathy . Seven genes (ADAM10, RAB1A, TFAM, FGF2, ELMOD2, GUF1, ABCC9) were significantly up-regulated and 8 genes (FHL1, CTNNA3, PDLIM5, LMNA, SIRT4, YME1L1, RHEB, GNB1L) down-regulated in idiopathic cardiomyopathy group (Fig.5D, Table.5). Four down-regulated genes (NEBL, FHL1, FHL2, SIRT4) and 5 up-regulated genes (GUF1, ELMOD2, ABCC9, FGF2, YME1L1) were significantly changed in idiopathic cardiomyopathy group, (Fig.5E, Table. 5). In post-partum cardiomyopathy group, 11 genes (ATL3, ADAM10, ELMOD2, FGF2, GUF1, YMEIL1, up-regulated; FHL1, CTNNA3, PTPN11, GNB1L, SIRT4, down-regulated) were significantly changed (Fig.5F, Table.5). In Ischemic cardiomyopathy group, 31 genes are significantly changed expression, including 12 genes (RAC1, FKTN, EDNRB, ZBTB33, TXN, RALGAPA1, PSEN1, LAMP2, UBR5, SCN4B, SMAD1, MYO6) down-regulated and 19 genes up-regulated expression (POLRMT, AVP, GATA4, CACNB2, MAPK1, NOS3, LAMA3, SOD2, LMNA, MAP1LC3A, MAPK14, TCAP, LRP4, BAD, DES, AKAP8, CASP9, HSPB1, SNTA1) (Fig.5G, Table.5).