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Ma Q, Zhang YH, Guo W, Feng K, Huang T, Cai YD. Machine Learning in Identifying Marker Genes for Congenital Heart Diseases of Different Cardiac Cell Types. Life (Basel) 2024; 14:1032. [PMID: 39202774 PMCID: PMC11355424 DOI: 10.3390/life14081032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/31/2024] [Accepted: 08/14/2024] [Indexed: 09/03/2024] Open
Abstract
Congenital heart disease (CHD) represents a spectrum of inborn heart defects influenced by genetic and environmental factors. This study advances the field by analyzing gene expression profiles in 21,034 cardiac fibroblasts, 73,296 cardiomyocytes, and 35,673 endothelial cells, utilizing single-cell level analysis and machine learning techniques. Six CHD conditions: dilated cardiomyopathy (DCM), donor hearts (used as healthy controls), hypertrophic cardiomyopathy (HCM), heart failure with hypoplastic left heart syndrome (HF_HLHS), Neonatal Hypoplastic Left Heart Syndrome (Neo_HLHS), and Tetralogy of Fallot (TOF), were investigated for each cardiac cell type. Each cell sample was represented by 29,266 gene features. These features were first analyzed by six feature-ranking algorithms, resulting in several feature lists. Then, these lists were fed into incremental feature selection, containing two classification algorithms, to extract essential gene features and classification rules and build efficient classifiers. The identified essential genes can be potential CHD markers in different cardiac cell types. For instance, the LASSO identified key genes specific to various heart cell types in CHD subtypes. FOXO3 was found to be up-regulated in cardiac fibroblasts for both Dilated and hypertrophic cardiomyopathy. In cardiomyocytes, distinct genes such as TMTC1, ART3, ARHGAP24, SHROOM3, and XIST were linked to dilated cardiomyopathy, Neo-Hypoplastic Left Heart Syndrome, hypertrophic cardiomyopathy, HF-Hypoplastic Left Heart Syndrome, and Tetralogy of Fallot, respectively. Endothelial cell analysis further revealed COL25A1, NFIB, and KLF7 as significant genes for dilated cardiomyopathy, hypertrophic cardiomyopathy, and Tetralogy of Fallot. LightGBM, Catboost, MCFS, RF, and XGBoost further delineated key genes for specific CHD subtypes, demonstrating the efficacy of machine learning in identifying CHD-specific genes. Additionally, this study developed quantitative rules for representing the gene expression patterns related to CHDs. This research underscores the potential of machine learning in unraveling the molecular complexities of CHD and establishes a foundation for future mechanism-based studies.
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Affiliation(s)
- Qinglan Ma
- School of Life Sciences, Shanghai University, Shanghai 200444, China;
| | - Yu-Hang Zhang
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
| | - Wei Guo
- Key Laboratory of Stem Cell Biology, Shanghai Jiao Tong University School of Medicine (SJTUSM) & Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200030, China;
| | - Kaiyan Feng
- Department of Computer Science, Guangdong AIB Polytechnic College, Guangzhou 510507, China;
| | - Tao Huang
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yu-Dong Cai
- School of Life Sciences, Shanghai University, Shanghai 200444, China;
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Zhang F, Ding Y, Zhang B, He M, Wang Z, Lu C, Kang Y. Analysis of Methylome, Transcriptome, and Lipid Metabolites to Understand the Molecular Abnormalities in Polycystic Ovary Syndrome. Diabetes Metab Syndr Obes 2023; 16:2745-2763. [PMID: 37720421 PMCID: PMC10503565 DOI: 10.2147/dmso.s421947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/30/2023] [Indexed: 09/19/2023] Open
Abstract
Purpose This study aimed to identify differentially methylated genes (DMGs) and differentially expressed genes (DEGs) to investigate new biomarkers for the diagnosis and treatment of polycystic ovary syndrome (PCOS). Methods To explore the potential biomarkers of PCOS diagnosis and treatment, we performed methyl-binding domain sequencing (MBD-seq) and RNA sequencing (RNA-seq) on ovarian granulosa cells (GCs) from PCOS patients and healthy controls. MBD-seq was also performed on the ovarian tissue of constructed prenatally androgenized (PNA) mice. Differential methylation and expression analysis were implemented to identify DMGs and DEGs, respectively. The identified gene was further verified by real-time quantitative PCR (RT-qPCR) and methylation-specific PCR (MSP) in clinical samples. Furthermore, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was carried out on PCOS patients and healthy controls to identify differential lipid metabolites. Results Compared to the control group, 13,526 DMGs related to the promoter region and 2429 DEGs were found. The function analysis of DMGs and DEGs showed that they were mainly enriched in glycerophospholipid, ovarian steroidogenesis, and other lipid metabolic pathways. Moreover, 5753 genes in DMGs related to the promoter region were screened in the constructed PNA mice. Integrating the DMGs data from PCOS patients and PNA mice, we identified the following 8 genes: CDC42EP4, ERMN, EZR, PIK3R1, ARHGEF18, NECTIN2, TSC2, and TACSTD2. RT-qPCR and MSP verification results showed that the methylation and expression of TACSTD2 were consistent with sequencing data. Additionally, 15 differential lipid metabolites were shown in the serum of PCOS patients. The differential lipids were involved in glycerophospholipid and glycerolipid metabolism. Conclusion Using integration of methylome and lipid metabolites profiling we identified 8 potential epigenetic markers and 15 potential lipid metabolite markers for PCOS. Our results suggest that aberrant DNA methylation and lipid metabolite disorders may provide novel insights into the diagnosis and etiology of PCOS.
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Affiliation(s)
- Fei Zhang
- School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
| | - Yicen Ding
- School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
| | - Bohan Zhang
- School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
| | - Mengju He
- School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
| | - Zhijiang Wang
- Department of Pharmaceutical Engineering, Zhejiang Pharmaceutical University, Ningbo, People’s Republic of China
| | - Chunbo Lu
- Department of Obstetrics and Gynecology, Qiuai Central Health Center, Ningbo, People’s Republic of China
| | - Yani Kang
- School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China
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Patel V, Cui W, Cobben JM. SHORT syndrome with microcephaly and developmental delay. Am J Med Genet A 2023; 191:850-854. [PMID: 36515361 DOI: 10.1002/ajmg.a.63078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/15/2022] [Accepted: 12/01/2022] [Indexed: 12/15/2022]
Abstract
We report a boy with typical clinical features of SHORT syndrome alongside a significant microcephaly and severe developmental delay associated with a de novo single nucleotide missense DNA variant resulting in a single amino acid change in codon 486 of the PIK3R1 gene (PIK3R1 c.1456G>A (p.Ala486Thr)). Our report strikingly coincides with another recently published case from Brazil, describing a 23-year-old woman with the same de novo PIK3R1 DNA variant, who also exhibits SHORT syndrome with severe secondary microcephaly and intellectual disability. On review of the literature, we have identified further cases of PIK3R1-related SHORT Syndrome with a similar phenotype. We note all these cases (including ours) have variants located in the -inter SH2 domain (iSH2); we speculate that pathogenic iSH2 located PIK3R1 variants are associated with a different and otherwise unreported clinical picture of SHORT syndrome that presents with microcephaly and/or significant developmental delay/intellectual disability. The pathogenic mechanism of why these variants apparently lead to a different clinical picture of SHORT syndrome remains unknown.
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Affiliation(s)
- Viraj Patel
- North West Thames Regional Genetics Service, NHS, Northwick Park & St Mark's Hospitals, London, Harrow, UK
| | - Wei Cui
- Faculty of Medicine, Department of Metabolism, Digestions and Reproduction, Imperial College London, London, UK
| | - Jan M Cobben
- North West Thames Regional Genetics Service, NHS, Northwick Park & St Mark's Hospitals, London, Harrow, UK.,Faculty of Medicine, Department of Metabolism, Digestions and Reproduction, Imperial College London, London, UK
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Shvalb NF. SHORT Syndrome: an Update on Pathogenesis and Clinical Spectrum. Curr Diab Rep 2022; 22:571-577. [PMID: 36401775 DOI: 10.1007/s11892-022-01495-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/10/2022] [Indexed: 11/21/2022]
Abstract
PURPOSE OF REVIEW This review describes the unique pathogenesis of SHORT syndrome, a rare genetic form of insulin resistance syndrome, and recent advances in understanding the underlying mechanisms. SHORT syndrome results from dysfunction of PI3K, but the mechanisms behind the clinical manifestations are not entirely understood. Elucidating these mechanisms may contribute to the understanding of the roles of insulin signaling and PI3K signaling in humans. There are paucity of data on treatment and outcomes. RECENT FINDINGS The clinical spectrum of the disorder appears wider than previously understood, and overlaps with other clinical syndromes. PI3K malfunction is associated with insulin resistance, decreased lipogenesis, increased energy expenditure, and possible IGF1 resistance. SHORT syndrome may be underdiagnosed, and should be considered in individuals with growth failure, craniofacial dysmorphism, and lipodystrophy. Much is still unknown about the optimal management and long-term outcomes.
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Affiliation(s)
- Naama Fisch Shvalb
- National Center for Childhood Diabetes, The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, 14 Kaplan St, 49202-35, Petah Tikva, Israel.
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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Wei YL, Wen B, Gao JZ, Chen ZZ. Brain transcriptome analysis reveals genes involved in parental care behaviour in discus fish (Symphysodon haraldi). Gen Comp Endocrinol 2021; 309:113793. [PMID: 33887271 DOI: 10.1016/j.ygcen.2021.113793] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 10/21/2022]
Abstract
Parental care is common in mammals and allows offspring to obtain milk, a substance rich in a range of nutritional and non-nutritional factors crucial to the survival of newborns. The discus fish Symphysodon spp., an Amazonian cichlid, shows an unusual behaviour: Free-swimming fry bite on their parents' skin mucus for growth and development during the first month after hatching. This is similar to the breastfeeding behaviour of mammals, but little is known about the regulatory mechanism by which discus secrete 'milk' and the related genes involved in parental care. Here, transcriptome sequencing was performed by using the brain tissues of female discus fish in parental and non-parental care. The results showed that a total of 86 differentially expressed genes (71 up-regulated genes and 15 down-regulated genes) were obtained by comparing parental with non-parental discus fish, including up-regulated LAPTM, FOXB, SOX1S, OTX2 and NR1F2, and down-regulated EDNRB, PRKCD, H1-5 and HBE. Through functional enrichment analysis, a total of 20 pathways were identified, e.g., estrogen signaling pathway, inflammatory mediator regulation of TRP channels, vascular smooth muscle contraction, GnRH signaling pathway, neurotrophin signaling pathway, NOD-like receptor signaling pathway, Jak-STAT signaling pathway, Fc gamma R-mediated phagocytosis, serotonergic synapse, autophagy-animal and cytokine-cytokine receptor interaction. These pathways and related genes might play important roles in the regulation of discus 'milk' secretion.
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Affiliation(s)
- Yu-Ling Wei
- National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture and Rural Affairs, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
| | - Bin Wen
- National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture and Rural Affairs, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China.
| | - Jian-Zhong Gao
- National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture and Rural Affairs, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
| | - Zai-Zhong Chen
- National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Freshwater Aquatic Genetic Resources, Ministry of Agriculture and Rural Affairs, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Shanghai Engineering Research Center of Aquaculture, Shanghai Ocean University, Shanghai 201306, China.
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