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Wei K, Qian F, Li Y, Zeng T, Huang T. Integrating multi-omics data of childhood asthma using a deep association model. FUNDAMENTAL RESEARCH 2024; 4:738-751. [PMID: 39156565 PMCID: PMC11330118 DOI: 10.1016/j.fmre.2024.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 03/06/2024] [Accepted: 03/17/2024] [Indexed: 08/20/2024] Open
Abstract
Childhood asthma is one of the most common respiratory diseases with rising mortality and morbidity. The multi-omics data is providing a new chance to explore collaborative biomarkers and corresponding diagnostic models of childhood asthma. To capture the nonlinear association of multi-omics data and improve interpretability of diagnostic model, we proposed a novel deep association model (DAM) and corresponding efficient analysis framework. First, the Deep Subspace Reconstruction was used to fuse the omics data and diagnostic information, thereby correcting the distribution of the original omics data and reducing the influence of unnecessary data noises. Second, the Joint Deep Semi-Negative Matrix Factorization was applied to identify different latent sample patterns and extract biomarkers from different omics data levels. Third, our newly proposed Deep Orthogonal Canonical Correlation Analysis can rank features in the collaborative module, which are able to construct the diagnostic model considering nonlinear correlation between different omics data levels. Using DAM, we deeply analyzed the transcriptome and methylation data of childhood asthma. The effectiveness of DAM is verified from the perspectives of algorithm performance and biological significance on the independent test dataset, by ablation experiment and comparison with many baseline methods from clinical and biological studies. The DAM-induced diagnostic model can achieve a prediction AUC of 0.912, which is higher than that of many other alternative methods. Meanwhile, relevant pathways and biomarkers of childhood asthma are also recognized to be collectively altered on the gene expression and methylation levels. As an interpretable machine learning approach, DAM simultaneously considers the non-linear associations among samples and those among biological features, which should help explore interpretative biomarker candidates and efficient diagnostic models from multi-omics data analysis for human complex diseases.
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Affiliation(s)
- Kai Wei
- 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
- Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo 315000, China
| | - Fang Qian
- 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
| | - Yixue Li
- 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
- Guangzhou National Laboratory, Guangzhou 510000, China
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou 510000, China
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Tao Zeng
- Guangzhou National Laboratory, Guangzhou 510000, China
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou 510000, 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
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Liu Z, Fan K, Abudukeremu A, Gao M, Tan X, Mao X, Li X, Ma W, Ma X, Li C, Yang Y, Tu K, Chen J, Zhang Y, Guan Y. LIMA1 links the E3 ubiquitin ligase RNF40 to lipid metabolism. Cell Death Discov 2024; 10:298. [PMID: 38909032 PMCID: PMC11193757 DOI: 10.1038/s41420-024-02072-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 06/11/2024] [Accepted: 06/13/2024] [Indexed: 06/24/2024] Open
Abstract
LIMA1 is a LIM domain and Actin binding 1 protein that acts as a skeleton protein to promote cholesterol absorption, which makes it an ideal target for interfering with lipid metabolism. However, the detailed regulation of LIMA1 remains unclear. Here, we identified that ring finger protein 40 (RNF40), an E3 ubiquitin ligase previously known as an epigenetic modifier to increase H2B ubiquitination, mediated the ubiquitination of LIMA1 and thereby promoted its degradation in a proteasome-dependent manner. Fraction studies revealed that the 1-166aa fragment of LIMA1 was indispensable for the interaction with RNF40, and at least two domains of RNF40 might mediate the association of RNF40 with LIMA1. Notably, treatment with simvastatin dramatically decreased the levels of CHO and TG in control cells rather than cells with overexpressed LIMA1. Moreover, RNF40 significantly decreased lipid content, which could be reversed by LIMA1 overexpression. These findings suggest that E3 ubiquitin ligase RNF40 could directly target LIMA1 and promote its protein degradation in cytoplasm, leading to the suppression of lipid accumulation mediated by LIMA1. Collectively, this study unveils that RNF40 is a novel E3 ubiquitin ligase of LIMA1, which underpins its high therapeutic value to combat dysregulation of lipid metabolism.
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Affiliation(s)
- Zhan Liu
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xinjiang Second Medical College, Karamay, Xinjiang, China
| | - Kexin Fan
- The Institute of Molecular and Translational Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Aikedaimu Abudukeremu
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Min Gao
- The Institute of Molecular and Translational Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xinyue Tan
- The Institute of Molecular and Translational Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaojuan Mao
- The Institute of Molecular and Translational Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xinyu Li
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Wenting Ma
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Xusheng Ma
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xinjiang Second Medical College, Karamay, Xinjiang, China
| | - Caolong Li
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xinjiang Second Medical College, Karamay, Xinjiang, China
| | - Yinglai Yang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xinjiang Second Medical College, Karamay, Xinjiang, China
| | - Kangsheng Tu
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jing Chen
- Department of Obstetrics, Xi 'an New Chang 'an Maternity Hospital, Xi'an, Shaanxi, China
| | - Yilei Zhang
- The Institute of Molecular and Translational Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
| | - Yaqun Guan
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China.
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3
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Lindell E, Zhang X. Exploring the Enigma: The Role of the Epithelial Protein Lost in Neoplasm in Normal Physiology and Cancer Pathogenesis. Int J Mol Sci 2024; 25:4970. [PMID: 38732188 PMCID: PMC11084159 DOI: 10.3390/ijms25094970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 04/28/2024] [Accepted: 04/29/2024] [Indexed: 05/13/2024] Open
Abstract
The cytoskeleton plays a pivotal role in maintaining the epithelial phenotype and is vital to several hallmark processes of cancer. Over the past decades, researchers have identified the epithelial protein lost in neoplasm (EPLIN, also known as LIMA1) as a key regulator of cytoskeletal dynamics, cytoskeletal organization, motility, as well as cell growth and metabolism. Dysregulation of EPLIN is implicated in various aspects of cancer progression, such as tumor growth, invasion, metastasis, and therapeutic resistance. Its altered expression levels or activity can disrupt cytoskeletal dynamics, leading to aberrant cell motility and invasiveness characteristic of malignant cells. Moreover, the involvement of EPLIN in cell growth and metabolism underscores its significance in orchestrating key processes essential for cancer cell survival and proliferation. This review provides a comprehensive exploration of the intricate roles of EPLIN across diverse cellular processes in both normal physiology and cancer pathogenesis. Additionally, this review discusses the possibility of EPLIN as a potential target for anticancer therapy in future studies.
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Affiliation(s)
| | - Xiaonan Zhang
- Department of Immunology, Genetics and Pathology, Uppsala University, SE-751 85 Uppsala, Sweden;
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Wang X, Zhang C, Song H, Yuan J, Zhang X, Yuan Y, Zhang L, He J. Characterization of LIMA1 and its emerging roles and potential therapeutic prospects in cancers. Front Oncol 2023; 13:1115943. [PMID: 37274282 PMCID: PMC10235525 DOI: 10.3389/fonc.2023.1115943] [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: 12/04/2022] [Accepted: 05/02/2023] [Indexed: 06/06/2023] Open
Abstract
Actin is the most abundant and highly conserved cytoskeletal protein present in all eukaryotic cells. Remodeling of the actin cytoskeleton is controlled by a variety of actin-binding proteins that are extensively involved in biological processes such as cell motility and maintenance of cell shape. LIM domain and actin-binding protein 1 (LIMA1), as an important actin cytoskeletal regulator, was initially thought to be a tumor suppressor frequently downregulated in epithelial tumors. Importantly, the deficiency of LIMA1 may be responsible for dysregulated cytoskeletal dynamics, altered cell motility and disrupted cell-cell adhesion, which promote tumor proliferation, invasion and migration. As research progresses, the roles of LIMA1 extend from cytoskeletal dynamics and cell motility to cell division, gene regulation, apical extrusion, angiogenesis, cellular metabolism and lipid metabolism. However, the expression of LIMA1 in malignant tumors and its mechanism of action have not yet been elucidated, and many problems and challenges remain to be addressed. Therefore, this review systematically describes the structure and biological functions of LIMA1 and explores its expression and regulatory mechanism in malignant tumors, and further discusses its clinical value and therapeutic prospects.
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Affiliation(s)
- Xiaoxiao Wang
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Chao Zhang
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Huangqin Song
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Junlong Yuan
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Xiaomin Zhang
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Yiran Yuan
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Lei Zhang
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- Hepatic Surgery Center, Institute of Hepato-Pancreato-Biliary Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiefeng He
- Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
- Department of Hepatobiliary Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
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Su MW, Chang CK, Lin CW, Chu HW, Tsai TN, Su WC, Chen YC, Chang TK, Huang CW, Tsai HL, Wu CC, Chou HC, Shiu BH, Wang JY. Genomic and Metabolomic Landscape of Right-Sided and Left-Sided Colorectal Cancer: Potential Preventive Biomarkers. Cells 2022; 11:cells11030527. [PMID: 35159336 PMCID: PMC8834628 DOI: 10.3390/cells11030527] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 01/28/2022] [Accepted: 01/30/2022] [Indexed: 12/27/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common cancer worldwide. The incidence and mortality rates of CRC are significantly higher in Taiwan than in other developed countries. Genes involved in CRC tumorigenesis differ depending on whether the tumor occurs on the left or right side of the colon, and genomic analysis is a keystone in the study and treatment of CRC subtypes. However, few studies have focused on the genetic landscape of Taiwanese patients with CRC. This study comprehensively analyzed the genomes of 141 Taiwanese patients with CRC through whole-exome sequencing. Significant genomic differences related to the site of CRC development were observed. Blood metabolomic profiling and polygenic risk score analysis were performed to identify potential biomarkers for the early identification and prevention of CRC in the Taiwanese population. Our findings provide vital clues for establishing population-specific treatments and health policies for CRC prevention in Taiwan.
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Affiliation(s)
- Ming-Wei Su
- Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan; (M.-W.S.); (C.-K.C.); (C.-W.L.); ho (H.-W.C.)
| | - Chung-Ke Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan; (M.-W.S.); (C.-K.C.); (C.-W.L.); ho (H.-W.C.)
| | - Chien-Wei Lin
- Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan; (M.-W.S.); (C.-K.C.); (C.-W.L.); ho (H.-W.C.)
| | - Hou-Wei Chu
- Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan; (M.-W.S.); (C.-K.C.); (C.-W.L.); ho (H.-W.C.)
| | - Tsen-Ni Tsai
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
| | - Wei-Chih Su
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Yen-Cheng Chen
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Tsung-Kun Chang
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
| | - Ching-Wen Huang
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
- Department of Surgery, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Hsiang-Lin Tsai
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
- Department of Surgery, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Chang-Chieh Wu
- Department of Surgery, Tri-Service General Hospital Keelung Branch, National Defense Medical Center, Keelung 20042, Taiwan;
| | - Huang-Chi Chou
- School of Medicine, Chung Shan Medical University, Taichung 402306, Taiwan; (H.-C.C.); (B.-H.S.)
- Division of Colon and Rectal Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung 402306, Taiwan
| | - Bei-Hao Shiu
- School of Medicine, Chung Shan Medical University, Taichung 402306, Taiwan; (H.-C.C.); (B.-H.S.)
- Division of Colon and Rectal Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung 402306, Taiwan
| | - Jaw-Yuan Wang
- Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan; (T.-N.T.); (W.-C.S.); (Y.-C.C.); (T.-K.C.); (C.-W.H.); (H.-L.T.)
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Department of Surgery, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Center for Cancer Research, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Center for Liquid Biopsy and Cohort Research, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Pingtung Hospital, Ministry of Health and Welfare, Pingtung 900, Taiwan
- Correspondence: & ; Tel.: +886-7-312-2805
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Zimmer A, Korem Y, Rappaport N, Wilmanski T, Baloni P, Jade K, Robinson M, Magis AT, Lovejoy J, Gibbons SM, Hood L, Price ND. The geometry of clinical labs and wellness states from deeply phenotyped humans. Nat Commun 2021; 12:3578. [PMID: 34117230 PMCID: PMC8196202 DOI: 10.1038/s41467-021-23849-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 05/17/2021] [Indexed: 02/05/2023] Open
Abstract
Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. For thousands of people, we have collected longitudinal multi-omics data. To analyze, interpret and visualize this extremely high-dimensional data, we use the Pareto Task Inference (ParTI) method. We find that the clinical labs data fall within a tetrahedron. We then use all other data types to characterize the four archetypes. We find that the tetrahedron comprises three wellness states, defining a wellness triangular plane, and one aberrant health state that captures aspects of commonality in movement away from wellness. We reveal the tradeoffs that shape the data and their hierarchy, and use longitudinal data to observe individual trajectories. We then demonstrate how the movement on the tetrahedron can be used for detecting unexpected trajectories, which might indicate transitions from health to disease and reveal abnormal conditions, even when all individual blood measurements are in the norm.
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Affiliation(s)
- Anat Zimmer
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Yael Korem
- grid.13992.300000 0004 0604 7563Weizmann Institute, Rehovot, Israel
| | - Noa Rappaport
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Tomasz Wilmanski
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Priyanka Baloni
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Kathleen Jade
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Max Robinson
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Andrew T. Magis
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Jennifer Lovejoy
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Sean M. Gibbons
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Leroy Hood
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA ,Providence St Joseph Health, Seattle, WA USA
| | - Nathan D. Price
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
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Masjoudi S, Sedaghati-Khayat B, Givi NJ, Bonab LNH, Azizi F, Daneshpour MS. Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study. Sci Rep 2021; 11:10305. [PMID: 33986338 PMCID: PMC8119714 DOI: 10.1038/s41598-021-89509-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 04/22/2021] [Indexed: 12/21/2022] Open
Abstract
Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role in the pathogenesis of MetS. The present study aimed to assess the association between 18 single nucleotide polymorphisms (SNPs) located at the BUD13, ZPR1, and APOA5 genes with MetS in the Tehran Cardio-metabolic Genetics Study (TCGS). In 5421 MetS affected and non-affected participants, we analyzed the data using two models. The first model (MetS model) examined SNPs' association with MetS. The second model (HTg-MetS Model) examined the association of SNPs with MetS affection participants who had a high plasma triglyceride (TG). The four-gamete rules were used to make SNP sets from correlated nearby SNPs. The kernel machine regression models and single SNP regression evaluated the association between SNP sets and MetS. The kernel machine results showed two sets over three sets of correlated SNPs have a significant joint effect on both models (p < 0.0001). Also, single SNP regression results showed that the odds ratios (ORs) for both models are almost similar; however, the p-values had slightly higher significance levels in the HTg-MetS model. The strongest ORs in the HTg-MetS model belonged to the G allele in rs2266788 (MetS: OR = 1.3, p = 3.6 × 10–7; HTg-MetS: OR = 1.4, p = 2.3 × 10–11) and the T allele in rs651821 (MetS: OR = 1.3, p = 2.8 × 10–7; HTg-MetS: OR = 1.4, p = 3.6 × 10–11). In the present study, the kernel machine regression models could help assess the association between the BUD13, ZPR1, and APOA5 gene variants (11p23.3 region) with lipid-related traits in MetS and MetS affected with high TG.
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Affiliation(s)
- Sajedeh Masjoudi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Niloufar Javanrouh Givi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Leila Najd Hassan Bonab
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran.
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Clark C, Dayon L, Masoodi M, Bowman GL, Popp J. An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer's disease. Alzheimers Res Ther 2021; 13:71. [PMID: 33794997 PMCID: PMC8015070 DOI: 10.1186/s13195-021-00814-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/23/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Multiple pathophysiological processes have been described in Alzheimer's disease (AD). Their inter-individual variations, complex interrelations, and relevance for clinical manifestation and disease progression remain poorly understood. We hypothesize that specific molecular patterns indicating both known and yet unidentified pathway alterations are associated with distinct aspects of AD pathology. METHODS We performed multi-level cerebrospinal fluid (CSF) omics in a well-characterized cohort of older adults with normal cognition, mild cognitive impairment, and mild dementia. Proteomics, metabolomics, lipidomics, one-carbon metabolism, and neuroinflammation related molecules were analyzed at single-omic level with correlation and regression approaches. Multi-omics factor analysis was used to integrate all biological levels. Identified analytes were used to construct best predictive models of the presence of AD pathology and of cognitive decline with multifactorial regression analysis. Pathway enrichment analysis identified pathway alterations in AD. RESULTS Multi-omics integration identified five major dimensions of heterogeneity explaining the variance within the cohort and differentially associated with AD. Further analysis exposed multiple interactions between single 'omics modalities and distinct multi-omics molecular signatures differentially related to amyloid pathology, neuronal injury, and tau hyperphosphorylation. Enrichment pathway analysis revealed overrepresentation of the hemostasis, immune response, and extracellular matrix signaling pathways in association with AD. Finally, combinations of four molecules improved prediction of both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta, clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant protein-1). CONCLUSIONS Applying an integrative multi-omics approach we report novel molecular and pathways alterations associated with AD pathology. These findings are relevant for the development of personalized diagnosis and treatment approaches in AD.
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Affiliation(s)
- Christopher Clark
- Institute for Regenerative Medicine, University of Zürich, Wagistrasse 12, 8952 Schlieren, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015 Lausanne, Switzerland
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015 Lausanne, Switzerland
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Mojgan Masoodi
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015 Lausanne, Switzerland
- Institute of Clinical Chemistry, University Hospital Bern, Bern, Switzerland
| | - Gene L. Bowman
- Nestlé Institute of Health Sciences, Nestlé Research, EPFL Innovation Park, 1015 Lausanne, Switzerland
- Department of Neurology, NIA-Layton Aging and Alzheimer’s Disease Center, Oregon Health & Science University, Portland, USA
| | - Julius Popp
- Old Age Psychiatry, Centre Hospitalier Universitaire Vaudois, Rue du Bugnon 46, 1011 Lausanne, Switzerland
- Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Centre for Gerontopsychiatric Medicine, Minervastrasse 145, P.O. Box 341, 8032 Zürich, Switzerland
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