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Zhang Z, Wang J, Teng M, Yan X, Liu Q. The role of serum interleukins in Cancer: A Multi-center Mendelian Randomization study. Int Immunopharmacol 2024; 137:112520. [PMID: 38901247 DOI: 10.1016/j.intimp.2024.112520] [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: 02/22/2024] [Revised: 06/02/2024] [Accepted: 06/16/2024] [Indexed: 06/22/2024]
Abstract
The occurrence of cancer is often accompanied by immune evasion and tumor-promoting inflammation, with interleukins (IL) playing a pivotal role in the immune-inflammatory mechanism. However, the precise contribution of serum interleukins in cancer remains elusive. We obtained GWAS summary data for 35 interleukins from eight independent large-scale serum proteome studies of European ancestry populations and for 23 common cancers from the FinnGen Consortium. We then conducted a multicenter Mendelian Randomization (MR) study to explore the relationship between systemic inflammatory status and cancers. 24 causal associations between interleukins and cancers were supported by multicenter data, 18 of which were reported for the first time. Our results indicated that IL-1α (Hodgkin lymphoma), IL-5 (bladder cancer), IL-7 (prostate cancer), IL-11 (bone malignant tumor), IL-16 (lung cancer), IL-17A (pancreatic cancer), IL-20 (bladder cancer), IL-22 (lymphocytic leukemia), IL-34 (breast cancer), IL-36β (prostate cancer), and IL-36γ (liver cancer) were risk factors for related cancers. Conversely, IL-9 (malignant neoplasms of the corpus uteri), IL-17C (liver cancer), and IL-31 (colorectal cancer, bladder cancer, pancreatic cancer, and cutaneous melanoma) exhibited protective effects against related cancers. Notably, the dual effects of serum interleukins were also observed. IL-18 acted as a risk factor for prostate cancer, however, was a protective factor against laryngeal cancer. Similarly, IL-19 promoted the development of lung cancer and myeloid leukemia, while conferring protection against Breast, cervical, and thyroid cancers. Our study confirmed the genetic association between multiple serum interleukins and cancers. Immune and anti-inflammatory strategies targeting these associations provide opportunities for prevention and treatment.
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Affiliation(s)
- Zheng Zhang
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, China
| | - Jiachen Wang
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, China
| | - Menghao Teng
- Department of Orthopedics, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, China
| | - Xinyang Yan
- Department of Neurosurgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, China
| | - Qingguang Liu
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, China.
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2
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Zhou S, Tao B, Guo Y, Gu J, Li H, Zou C, Tang S, Jiang S, Fu D, Li J. Integrating plasma protein-centric multi-omics to identify potential therapeutic targets for pancreatic cancer. J Transl Med 2024; 22:557. [PMID: 38858729 PMCID: PMC11165868 DOI: 10.1186/s12967-024-05363-9] [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: 03/22/2024] [Accepted: 05/29/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Deciphering the role of plasma proteins in pancreatic cancer (PC) susceptibility can aid in identifying novel targets for diagnosis and treatment. METHODS We examined the relationship between genetically determined levels of plasma proteins and PC through a systemic proteome-wide Mendelian randomization (MR) analysis utilizing cis-pQTLs from multiple centers. Rigorous sensitivity analyses, colocalization, reverse MR, replications with varying instrumental variable selections and additional datasets, as well as subsequent meta-analysis, were utilized to confirm the robustness of significant findings. The causative effect of corresponding protein-coding genes' expression and their expression pattern in single-cell types were then investigated. Enrichment analysis, between-protein interaction and causation, knock-out mice models, and mediation analysis with established PC risk factors were applied to indicate the pathogenetic pathways. These candidate targets were ultimately prioritized upon druggability and potential side effects predicted by a phenome-wide MR. RESULTS Twenty-one PC-related circulating proteins were identified in the exploratory phase with no evidence for horizontal pleiotropy or reverse causation. Of these, 11 were confirmed in a meta-analysis integrating external validations. The causality at a transcription level was repeated for neutrophil elastase, hydroxyacylglutathione hydrolase, lipase member N, protein disulfide-isomerase A5, xyloside xylosyltransferase 1. The carbohydrate sulfotransferase 11 and histo-blood group ABO system transferase exhibited high-support genetic colocalization evidence and were found to affect PC carcinogenesis partially through modulating body mass index and type 2 diabetes, respectively. Approved drugs have been established for eight candidate targets, which could potentially be repurposed for PC therapies. The phenome-wide investigation revealed 12 proteins associated with 51 non-PC traits, and interference on protein disulfide-isomerase A5 and cystatin-D would increase the risk of other malignancies. CONCLUSIONS By employing comprehensive methodologies, this study demonstrated a genetic predisposition linking 21 circulating proteins to PC risk. Our findings shed new light on the PC etiology and highlighted potential targets as priorities for future efforts in early diagnosis and therapeutic strategies of PC.
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Affiliation(s)
- Siyu Zhou
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Baian Tao
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yujie Guo
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Jichun Gu
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Hengchao Li
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Caifeng Zou
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Sichong Tang
- School of Medicine, Fudan University, Shanghai, 200240, China
| | - Shuheng Jiang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Deliang Fu
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China.
| | - Ji Li
- Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China.
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He Q, Wang W, Xiong Y, Tao C, Ma L, You C. Potential Biomarkers in Cerebrospinal Fluid and Plasma for Dementia. J Alzheimers Dis 2024:JAD240260. [PMID: 38875042 DOI: 10.3233/jad-240260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
Background The identification of biomarkers for different dementias in plasma and cerebrospinal fluid (CSF) has made substantial progress. However, they are observational studies, and there remains a lack of research on dementias with low incidence rates. Objective We performed a comprehensive Mendelian randomization to identify potential biomarkers for different dementia type. Methods The summary-level datasets encompassed 734 plasma and 154 cerebrospinal fluid proteins sourced from recently published genome-wide association studies (GWAS). Summary statistics for different dementias, including any dementia (refering to any type of dementia symptoms, 218,792 samples), Alzheimer's disease (AD, 63,926 samples), vascular dementia (212,389 samples), frontotemporal dementia (3,024 samples), dementia with Lewy bodies (DLB, 6,618 samples), and dementia in Parkinson's disease (216,895 samples), were collected from large GWAS. The primary method is inverse variance weighting, with additional sensitivity analyses conducted to ensure the robustness of the findings. Results The molecules released into CSF, namely APOE2 for any dementia, APOE2 and Siglec-3 for AD, APOE2 for vascular dementia, and APOE2 for DLB, might be potential biomarkers. CD33 for AD and SNCA for DLB in plasma could be promising biomarkers. Conclusions This is the first study to integrate plasma and CSF proteins to identify potential biomarkers for different dementias.
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Affiliation(s)
- Qiang He
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenjing Wang
- Department of Pharmacy, Institute of Metabolic Diseases and Pharmacotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Yang Xiong
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Chuanyuan Tao
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lu Ma
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao You
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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4
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Wang H, Liu D, Meng X, Sun W, Li C, Lu H, Zheng D, Wu L, Sun S, Wang Y. Bidirectional Two-Sample Mendelian Randomization Study of Immunoglobulin G N-Glycosylation and Senescence-Associated Secretory Phenotype. Int J Mol Sci 2024; 25:6337. [PMID: 38928043 PMCID: PMC11203829 DOI: 10.3390/ijms25126337] [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: 05/22/2024] [Revised: 06/01/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
Observational studies revealed changes in Immunoglobulin G (IgG) N-glycosylation during the aging process. However, it lacks causal insights and remains unclear in which direction causal relationships exist. The two-sample bidirectional Mendelian randomization (MR) design was adopted to explore causal associations between IgG N-glycans and the senescence-associated secretory phenotype (SASP). Inverse variance weighted (IVW) and Wald ratio methods were used as the main analyses, supplemented by sensitivity analyses. Forward MR analyses revealed causal associations between the glycan peak (GP) and SASP, including GP6 (odds ratio [OR] = 0.428, 95% confidence interval [CI] = 0.189-0.969) and GP17 (OR = 0.709, 95%CI = 0.504-0.995) with growth/differentiation factor 15 (GDF15), GP19 with an advanced glycosylation end-product-specific receptor (RAGE) (OR = 2.142, 95% CI = 1.384-3.316), and GP15 with matrix metalloproteinase 2 (MMP2) (OR = 1.136, 95% CI =1.008-1.282). The reverse MR indicated that genetic liability to RAGE was associated with increased levels of GP17 (OR = 1.125, 95% CI = 1.003-1.261) and GP24 (OR = 1.222, 95% CI = 1.046-1.428), while pulmonary and activation-regulated chemokines (PARC) exhibited causal associations with GP10 (OR = 1.269, 95% CI = 1.048-1.537) and GP15 (OR = 1.297, 95% CI = 1.072-1.570). The findings provided suggested evidence on the bidirectional causality between IgG N-glycans and SASP, which might reveal potential regulatory mechanisms.
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Affiliation(s)
- Haotian Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Di Liu
- Centre for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Xiaoni Meng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Wenxin Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Cancan Li
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Huimin Lu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Deqiang Zheng
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Lijuan Wu
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Shengzhi Sun
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
| | - Youxin Wang
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
- Centre for Precision Medicine, Edith Cowan University, Perth 6027, Australia
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5
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Cao H, Liu B, Gong K, Wu H, Wang Y, Zhang H, Shi C, Wang P, Du H, Zhou H, Wang S. Association between cathepsins and benign prostate diseases: a bidirectional two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1348310. [PMID: 38904040 PMCID: PMC11188316 DOI: 10.3389/fendo.2024.1348310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 05/20/2024] [Indexed: 06/22/2024] Open
Abstract
Objectives The relationship between cathepsins and prostate cancer (PCa) has been reported. However, there is a lack of research on cathepsins and benign prostate diseases (BPDs). This study investigated the potential genetic link between cathepsins and BPDs through the utilization of Mendelian randomization (MR) analysis to determine if a causal relationship exists. Methods Publicly accessible summary statistics on BPDs were obtained from FinnGen Biobank. The data comprised 149,363 individuals, with 30,066 cases and 119,297 controls for BPH, and 123,057 individuals, with 3,760 cases and 119,297 controls for prostatitis. The IEU OpenGWAS provided the Genome-wide association data on ten cathepsins. To evaluate the causal relationship between BPDs and cathepsins, five distinct MR analyses were employed, with the primary method being the inverse variance weighted (IVW) approach. Additionally, sensitivity analyses were conducted to examine the horizontal pleiotropy and heterogeneity of the findings. Results The examination of IVW MR findings showed that cathepsin O had a beneficial effect on BPH (IVW OR=0.94, 95% CI 0.89-0.98, P=0.0055), while cathepsin X posed a threat to prostatitis (IVW OR=1.08, 95% CI 1.00-1.16, P=0.047). Through reverse MR analysis, it was revealed that prostatitis had an adverse impact on cathepsin V (IVW OR=0.89, 95% CI 0.80-0.99, P=0.035), while no favorable association was observed between BPH and cathepsins. The results obtained from MR-Egger, weighted median, simple mode, and weighted mode methods were consistent with the findings of the IVW approach. Based on sensitivity analyses, heterogeneity, and horizontal pleiotropy are unlikely to distort the results. Conclusion This study offers the initial evidence of a genetic causal link between cathepsins and BPDs. Our findings revealed that cathepsin O was beneficial in preventing BPH, whereas cathepsin X posed a potential threat to prostatitis. Additionally, prostatitis negatively affected cathepsin V level. These three cathepsins could be targets of diagnosis and treatment for BPDs, which need further research.
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Affiliation(s)
- Hongliang Cao
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Bin Liu
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Kejian Gong
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Hao Wu
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Yishu Wang
- Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, China
| | - Haiyang Zhang
- Department of Prosthodontics, Hospital of Stomatology, Jilin University, Changchun, China
| | - Chengdong Shi
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Pengyu Wang
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Hao Du
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Honglan Zhou
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
| | - Song Wang
- Department of Urology II, The First Hospital of Jilin University, Changchun, China
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Ma J, Fu L, Lu Z, Sun Y. Evaluating the Causal Effects of Circulating Proteome on the Risk of Sepsis and Related Outcomes. ACS OMEGA 2024; 9:23864-23872. [PMID: 38854583 PMCID: PMC11154893 DOI: 10.1021/acsomega.4c01934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 05/09/2024] [Accepted: 05/17/2024] [Indexed: 06/11/2024]
Abstract
The current investigation deployed Mendelian randomization (MR) to elucidate the causal relationship between circulating proteins and sepsis. A rigorous two-sample MR analysis evaluated the effect of plasma proteins on the sepsis susceptibility. To affirm the integrity of MR findings, a suite of supplementary analyses, including Bayesian colocalization, Steiger filtering, the assessment of protein-altering polymorphisms, and the correlation between expression quantitative trait loci and protein quantitative trait loci (pQTLs), was employed. The study further integrated the examination of protein-protein interactions and pathway enrichment, along with the identification of pharmacologically actionable targets, to advance our comprehension and outline potential sepsis therapies. Subsequent analyses leveraging cis-pQTLs within MR studies unveiled noteworthy relationships: 94 specific proteins exhibited significant links with sepsis-related 28 day mortality, while 96 distinct proteins correlated with survival outcomes in sepsis. Furthermore, incorporating both cis- and trans-pQTLs in MR investigations revealed more comprehensive findings, associating 201 unique proteins with sepsis-related 28 day mortality and 199 distinct proteins with survival outcomes in sepsis. Markedly, colocalization analyses confirmed that eight of these proteins exhibited prominent evidence for colocalization, emphasizing their potential criticality in sepsis pathophysiology. Further in silico analyses were conducted to delineate putative regulatory networks and to highlight prospective drug targets among these proteins. Employing the MR methodology has shed light on plasma proteins implicated in the etiopathogenesis of sepsis. This novel approach unveiled numerous biomarkers and targets, providing a scientific rationale for the development of new therapeutic strategies and prophylactic measures against sepsis.
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Affiliation(s)
- Jiawei Ma
- The
First Department of Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
- Department
of Critical Care Medicine, Wuxi No. 2 People’s
Hospital, Wuxi 214002, China
- Department
of Critical Care Medicine, Aheqi County
People’s Hospital, Xinjiang 843599, China
| | - Lu Fu
- The
First Department of Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Zhonghua Lu
- The
First Department of Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Yun Sun
- The
First Department of Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
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Chen G, Lin T, Wu M, Cai G, Wu C, Ding Q, Xu J, Chen H, Li W, Xu G, Lan Y. Causal Association of Cytokines and Growth Factors with Stroke and Its Subtypes: a Mendelian Randomization Study. Mol Neurobiol 2024; 61:3212-3222. [PMID: 37979035 DOI: 10.1007/s12035-023-03752-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/28/2023] [Indexed: 11/19/2023]
Abstract
Cytokines and growth factors contribute to nerve growth and angiogenesis and are associated with the development of vascular disease. This Mendelian randomization (MR) study was designed to examine the causal relationship between factors associated with stem cell paracrine mechanisms and with stroke and its subtypes. We used pooled statistics on cytokine levels from three studies (INTERIAL, Olink Proseek CVD array, and KORA) encompassing 7795 participants in Europe. Data for stroke and its subtypes were pooled from these European populations (40,585 cases and 406,111 controls) in a multiprogenitor genome-wide association study (GWAS). MR was performed using established analytical methods, including inverse variance weighting (IVW), weighted median (WM), and MR-Egger. Genetically determined high IGF-1 levels were found to associate negatively with risk of stroke, ischemic stroke (large-artery atherosclerosis), and ischemic stroke (cardiogenic embolism). Meanwhile, high IL-13 levels had a positive causal relationship with ischemic stroke (large-artery atherosclerosis). An additional 27 cytokines were found to have a causal association with stroke or its subtypes. However, these results should be interpreted with caution given that the power efficacy was <80%. This MR study supports the concept of a causal relationship of 29 cytokines with stroke or its subtypes. Our genetic analysis provides new insights into stroke prevention and treatment by demonstrating an association of stem cell paracrine-related cytokines with stroke risk.
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Affiliation(s)
- Gengbin Chen
- Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
- Postgraduate Research Institute, Guangzhou Sport University, Guangzhou, China
| | - Tuo Lin
- Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Manfeng Wu
- Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Guiyuan Cai
- Department of Rehabilitation Medicine, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Cheng Wu
- Department of Rehabilitation Medicine, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China
- Department of Rehabilitation Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No. 106 Zhongshan Road II, Guangzhou, 510080, China
| | - Qian Ding
- Department of Rehabilitation Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No. 106 Zhongshan Road II, Guangzhou, 510080, China
| | - Jiayue Xu
- Department of Rehabilitation Medicine, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Hongying Chen
- Department of Rehabilitation Medicine, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Wanqi Li
- Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Guangqing Xu
- Department of Rehabilitation Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No. 106 Zhongshan Road II, Guangzhou, 510080, China.
| | - Yue Lan
- Department of Rehabilitation Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
- Guangzhou Key Laboratory of Aging Frailty and Neurorehabilitation, Guangzhou, China.
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8
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Li J, Ma X, Yin C. Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases. Sci Rep 2024; 14:11814. [PMID: 38782984 PMCID: PMC11116402 DOI: 10.1038/s41598-024-62742-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 05/21/2024] [Indexed: 05/25/2024] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.
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Affiliation(s)
- Junhang Li
- Department of Ultrasonography, Dali Prefecture Third People's Hospital, Dali Prefecture, Yunnan Province, China
| | - Xiang Ma
- Chongqing Medical University, Chongqing, China
| | - Cuihua Yin
- Department of Ultrasonography, Dali Prefecture Third People's Hospital, Dali Prefecture, Yunnan Province, China.
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9
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Yuan W, Xu W, Xu X, Qu B, Zhao F. Exploration of potential novel drug targets for diabetic retinopathy by plasma proteome screening. Sci Rep 2024; 14:11726. [PMID: 38778174 PMCID: PMC11111739 DOI: 10.1038/s41598-024-62069-0] [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: 01/11/2024] [Accepted: 05/13/2024] [Indexed: 05/25/2024] Open
Abstract
The aim of this study is to identify novel potential drug targets for diabetic retinopathy (DR). A bidirectional two-sample Mendelian randomization (MR) analysis was performed using protein quantitative trait loci (pQTL) of 734 plasma proteins as the exposures and clinically diagnosed DR as the outcome. Genetic instruments for 734 plasma proteins were obtained from recently published genome-wide association studies (GWAS), and external plasma proteome data was retrieved from the Icelandic Decoding Genetics Study and UK Biobank Pharma Proteomics Project. Summary-level data of GWAS for DR were obtained from the Finngen Consortium, comprising 14,584 cases and 202,082 population controls. Steiger filtering, Bayesian co-localization, and phenotype scanning were used to further verify the causal relationships calculated by MR. Three significant (p < 6.81 × 10-5) plasma protein-DR pairs were identified during the primary MR analysis, including CFH (OR = 0.8; 95% CI 0.75-0.86; p = 1.29 × 10-9), B3GNT8 (OR = 1.09; 95% CI 1.05-1.12; p = 5.9 × 10-6) and CFHR4 (OR = 1.11; 95% CI 1.06-1.16; p = 1.95 × 10-6). None of the three proteins showed reverse causation. According to Bayesian colocalization analysis, CFH (coloc.abf-PPH4 = 0.534) and B3GNT8 (coloc.abf-PPH4 = 0.638) in plasma shared the same variant with DR. All three identified proteins were validated in external replication cohorts. Our research shows a cause-and-effect connection between genetically determined levels of CFH, B3GNT8 and CFHR4 plasma proteins and DR. The discovery implies that these proteins hold potential as drug target in the process of developing drugs to treat DR.
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Affiliation(s)
- Weichen Yuan
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, No. 102, Nanqi Road, Heping District, Shenyang, Liaoning, China
- Key Lens Research Laboratory of Liaoning Province, Shenyang, China
| | - Wei Xu
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, No. 102, Nanqi Road, Heping District, Shenyang, Liaoning, China
- Key Lens Research Laboratory of Liaoning Province, Shenyang, China
| | - Xin Xu
- Department of Biochemistry and Molecular Biology, China Medical University, Shenyang, China
| | - Bo Qu
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, No. 102, Nanqi Road, Heping District, Shenyang, Liaoning, China.
- Key Lens Research Laboratory of Liaoning Province, Shenyang, China.
| | - Fangkun Zhao
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, No. 102, Nanqi Road, Heping District, Shenyang, Liaoning, China.
- Key Lens Research Laboratory of Liaoning Province, Shenyang, China.
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10
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Cao Z, Li Q, Li Y, Wu J. Identification of plasma protein markers of allergic disease risk: a mendelian randomization approach to proteomic analysis. BMC Genomics 2024; 25:503. [PMID: 38773393 PMCID: PMC11110418 DOI: 10.1186/s12864-024-10412-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND While numerous allergy-related biomarkers and targeted treatment strategies have been developed and employed, there are still signifcant limitations and challenges in the early diagnosis and targeted treatment for allegic diseases. Our study aims to identify circulating proteins causally associated with allergic disease-related traits through Mendelian randomization (MR)-based analytical framework. METHODS Large-scale cis-MR was employed to estimate the effects of thousands of plasma proteins on five main allergic diseases. Additional analyses including MR Steiger analyzing and Bayesian colocalisation, were performed to test the robustness of the associations; These findings were further validated utilizing meta-analytical methods in the replication analysis. Both proteome- and transcriptome-wide association studies approach was applied, and then, a protein-protein interaction was conducted to examine the interplay between the identified proteins and the targets of existing medications. RESULTS Eleven plasma proteins were identified with links to atopic asthma (AA), atopic dermatitis (AD), and allergic rhinitis (AR). Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. MR analysis and extra validation revealed STAT6 and TNFRSF6B to be Tier 1 and IL1RL2 and IL6R to be Tier 2 proteins with the potential for AA treatment. Two Tier 1 proteins, CRAT and TNFRSF6B, and five Tier 2 proteins, ERBB3, IL6R, MMP12, ICAM1, and IL1RL2, were linked to AD, and three Tier 2 proteins, MANF, STAT6, and TNFSF8, to AR. CONCLUSION Eleven Tier 1 and 2 protein targets that are promising drug target candidates were identified for AA, AD, and AR, which influence the development of allergic diseases and expose new diagnostic and therapeutic targets.
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Affiliation(s)
- Ziqin Cao
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410000, China
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China
| | - Qiangxiang Li
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China
| | - Yajia Li
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China.
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
| | - Jianhuang Wu
- Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410000, China.
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China.
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Zhang Y, Liu W, Lai J, Zeng H. Genetic associations in ankylosing spondylitis: circulating proteins as drug targets and biomarkers. Front Immunol 2024; 15:1394438. [PMID: 38835753 PMCID: PMC11148386 DOI: 10.3389/fimmu.2024.1394438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/29/2024] [Indexed: 06/06/2024] Open
Abstract
Background Ankylosing spondylitis (AS) is a complex condition with a significant genetic component. This study explored circulating proteins as potential genetic drug targets or biomarkers to prevent AS, addressing the need for innovative and safe treatments. Methods We analyzed extensive data from protein quantitative trait loci (pQTLs) with up to 1,949 instrumental variables (IVs) and selected the top single-nucleotide polymorphism (SNP) associated with AS risk. Utilizing a two-sample Mendelian randomization (MR) approach, we assessed the causal relationships between identified proteins and AS risk. Colocalization analysis, functional enrichment, and construction of protein-protein interaction networks further supported these findings. We utilized phenome-wide MR (phenMR) analysis for broader validation and repurposing of drugs targeting these proteins. The Drug-Gene Interaction database (DGIdb) was employed to corroborate drug associations with potential therapeutic targets. Additionally, molecular docking (MD) techniques were applied to evaluate the interaction between target protein and four potential AS drugs identified from the DGIdb. Results Our analysis identified 1,654 plasma proteins linked to AS, with 868 up-regulated and 786 down-regulated. 18 proteins (AGER, AIF1, ATF6B, C4A, CFB, CLIC1, COL11A2, ERAP1, HLA-DQA2, HSPA1L, IL23R, LILRB3, MAPK14, MICA, MICB, MPIG6B, TNXB, and VARS1) that show promise as therapeutic targets for AS or biomarkers, especially MAPK14, supported by evidence of colocalization. PhenMR analysis linked these proteins to AS and other diseases, while DGIdb analysis identified potential drugs related to MAPK14. MD analysis indicated strong binding affinities between MAPK14 and four potential AS drugs, suggesting effective target-drug interactions. Conclusion This study underscores the utility of MR analysis in AS research for identifying biomarkers and therapeutic drug targets. The involvement of Th17 cell differentiation-related proteins in AS pathogenesis is particularly notable. Clinical validation and further investigation are essential for future applications.
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Affiliation(s)
- Ye Zhang
- Traditional Chinese Medicine Department of Immunology, Women & Children Health Institute Futian Shenzhen, Shenzhen, China
| | - Wei Liu
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Junda Lai
- Department of Human Life Sciences, Beijing Sport University, Beijing, China
| | - Huiqiong Zeng
- Traditional Chinese Medicine Department of Immunology, Women & Children Health Institute Futian Shenzhen, Shenzhen, China
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Chen K, Tian T, Gao P, Fang X, Jiang W, Li Z, Tang K, Ouyang P, Li L. Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome. BMJ Open Diabetes Res Care 2024; 12:e003966. [PMID: 38719509 PMCID: PMC11085809 DOI: 10.1136/bmjdrc-2023-003966] [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] [Received: 12/08/2023] [Accepted: 03/31/2024] [Indexed: 05/12/2024] Open
Abstract
INTRODUCTION This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms. RESEARCH DESIGN AND METHODS We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network. RESULTS Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes. CONCLUSIONS Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.
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Affiliation(s)
- Kun Chen
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Tian Tian
- Department of Endocrine and Metabolic Diseases, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Peng Gao
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Xiaoxiang Fang
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Wang Jiang
- Department of Gastroenterology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Zongchao Li
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Kexing Tang
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Pan Ouyang
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Liangjun Li
- Department of Orthopaedics, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
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Wang Y, Shi X, Yin Y, Yang F, Zhang Y, He X, Wen D, Li BX, Ma K. Association Between Neuroinflammation and Parkinson's Disease: A Comprehensive Mendelian Randomization Study. Mol Neurobiol 2024:10.1007/s12035-024-04197-2. [PMID: 38709392 DOI: 10.1007/s12035-024-04197-2] [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: 02/13/2024] [Accepted: 04/22/2024] [Indexed: 05/07/2024]
Abstract
The objective of the study is to determine the causal relationship and potential mechanisms between Parkinson's disease (PD) and neuroinflammatory and neurotoxic mediators. We conducted two-sample Mendelian randomization (2SMR) study and multivariable Mendelian randomization (MVMR) analysis to investigate the causality between PD and neuroinflammatory and neurotoxic mediators. The mediation analysis with MR was also conducted to determine the potential mediating effect of neuroinflammatory and neurotoxic mediators between asthma and PD. Genetically predicted levels of nine neuroinflammation were associated with changes in PD risk. The associations of PD with CCL24, galectin-3 levels, haptoglobin, and Holo-Transcobalamin-2 remained significant in multivariable analyses. The mediation analysis with MR revealed that asthma affects PD through CCL24 and galectin-3. The results showed neuroinflammation could affect the pathogenesis of PD. In the combined analysis of these nine variables, CCL24, galectin-3 levels, HP, and Holo-Transcobalamin-2 alone were found to be significant. Asthma plays an intermediary role through CCL24 and galectin-3 levels.
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Affiliation(s)
- YiNi Wang
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - XinYu Shi
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - YaPing Yin
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Fei Yang
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - YiNan Zhang
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Xin He
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Da Wen
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Bai-Xiang Li
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China.
| | - Kun Ma
- Department of Hygienic Toxicology, School of Public Health, Harbin Medical University, 157 Baojian Road, NanGang District, Harbin, 150081, Heilongjiang Province, People's Republic of China.
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Dong J, Jiang W, Zhang W, Hu R, Huang Z, Guo T, Du T, Jiang X. Genetic association of circulating interleukins and risk of colorectal cancer: A bidirectional Mendelian randomization study. ENVIRONMENTAL TOXICOLOGY 2024; 39:2706-2716. [PMID: 38240193 DOI: 10.1002/tox.24147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 12/31/2023] [Accepted: 01/06/2024] [Indexed: 04/17/2024]
Abstract
BACKGROUND Previous studies have reported that inflammation, especially interleukin family members, plays an important role in the development of colorectal cancer (CRC). However, because of various confounders and the lack of clinical randomized controlled trial, the causal relationship between genetically predicted level of interleukin family and CRC risk has not been fully explained. OBJECTIVE Bi-directional Mendelian randomization (MR) was conducted to investigate the causal association between interleukin family members and CRC. METHODS Several genetic variables were extracted as instrumental variables (IVs) from summary data of genome-wide association studies (GWAS) for interleukin and CRC. IVs of interleukin family were obtained from recently published GWAS studies and the summary data of CRC was from FinnGen Biobank. After a series of quality control measures and strict screening, six models were used to evaluate the causal relationship. Pleiotropy, heterogeneity test, and a variety of sensitivity analysis were also used to estimate the robustness of the model results. RESULTS Genetically predicted higher circulating levels of IL-2 (odds ratio [OR]: 0.76; 95% confidence interval [CI]: 0.63-0.92; p = .0043), IL-17F(OR: 0.78; 95% CI: 0.62-1.00; p = .015), and IL-31 (OR: 0.88; 95% CI: 0.79-0.98; p = .023) were suggestively associated with decreased CRC risk. However, higher level of IL-10 (OR: 1.40; 95% CI: 1.18-1.65; p = .000094) was causally associated with increased risk of CRC. Reverse MR results indicated that the exposure of CRC was suggestively associated with higher levels of IL-36α (OR: 1.23; 95% CI: 1.01-1.49; p = .040) and IL-17RD (OR: 1.22; 95% CI, 1.00-1.48; p = .048) and lower level of IL-13 (OR: 0.78; 95% CI: 0.65-0.95; p = .013). The overall MR results did not provide evidence for causal relationships between other interleukins and CRC (p > .05). CONCLUSION We offer suggestive evidence supporting a potential causal relationship between circulating interleukins and CRC, underscoring the significance of targeting circulating interleukins as a strategy to mitigate the incidence of CRC.
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Affiliation(s)
- Jiaxing Dong
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wanju Jiang
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wenjia Zhang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Renhao Hu
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhiye Huang
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Taohua Guo
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Tao Du
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Xiaohua Jiang
- Department of Gastrointestinal Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
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Wu Y, Cai Y, Chen X, Chen S, Huang X, Lin Z. Proteomic analysis reveals potential therapeutic targets for childhood asthma through Mendelian randomization. Clin Transl Allergy 2024; 14:e12357. [PMID: 38730525 PMCID: PMC11087394 DOI: 10.1002/clt2.12357] [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: 12/11/2023] [Revised: 03/25/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Asthma is the most common chronic disease among children and poses a significant threat to their health. This study aims to assess the relationship between various plasma proteins and childhood asthma, thereby identifying potential therapeutic targets. METHODS Based on publicly available genome-wide association study summary statistics, we employed a two-sample Mendelian randomization (MR) approach to elucidate the causal relationship between plasma proteins and asthma. Mediation analysis was then conducted to evaluate the indirect influence of plasma proteins on childhood asthma mediated through risk factors. Comprehensive analysis was also conducted to explore the association between plasma proteins and various phenotypes using the UK Biobank dataset. RESULTS MR analysis uncovered a causal relationship between 10 plasma proteins and childhood asthma. Elevated levels of seven proteins (TLR4, UBP25, CBR1, Rac GTPase-activating protein 1 [RGAP1], IL-21, MICB, and PDE4D) and decreased levels of three proteins (GSTO1, LIRB4 and PIGF) were associated with an increased risk of childhood asthma. Our findings further validated the connections between reported risk factors (body mass index, mood swings, hay fever or allergic rhinitis, and eczema or dermatitis) and childhood asthma. Mediation analysis revealed the influence of proteins on childhood asthma outcomes through risk factors. Furthermore, the MR analysis identified 73 plasma proteins that exhibited causal associations with at least one risk factor for childhood asthma. Among them, RGAP1 mediates a significant proportion (25.10%) of the risk of childhood asthma through eczema or dermatitis. Finally, a phenotype-wide association study based on these 10 proteins and 1403 diseases provided novel associations between these biomarkers and multiple phenotypes. CONCLUSION Our study comprehensively investigated the causal relationship between plasma proteins and childhood asthma, providing novel insights into potential therapeutic targets.
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Affiliation(s)
- Yi‐Qing Wu
- Department of PediatricsThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
- The Second School of MedicineWenzhou Medical UniversityWenzhouZhejiangChina
- Key Laboratory of Perinatal Medicine of WenzhouWenzhouZhejiangChina
- Key Laboratory of Structural Malformations in Children of Zhejiang ProvinceWenzhouZhejiangChina
| | - Yi‐Xin Cai
- Zhejiang Provincial Clinical Research Center for Pediatric DiseaseThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
| | - Xiao‐Li Chen
- Department of PediatricsThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
- The Second School of MedicineWenzhou Medical UniversityWenzhouZhejiangChina
- Key Laboratory of Perinatal Medicine of WenzhouWenzhouZhejiangChina
- Key Laboratory of Structural Malformations in Children of Zhejiang ProvinceWenzhouZhejiangChina
| | - Shang‐Qin Chen
- Department of PediatricsThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
- The Second School of MedicineWenzhou Medical UniversityWenzhouZhejiangChina
- Key Laboratory of Perinatal Medicine of WenzhouWenzhouZhejiangChina
- Key Laboratory of Structural Malformations in Children of Zhejiang ProvinceWenzhouZhejiangChina
| | - Xiu‐Feng Huang
- Zhejiang Provincial Clinical Research Center for Pediatric DiseaseThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
| | - Zhen‐Lang Lin
- Department of PediatricsThe Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhouZhejiangChina
- The Second School of MedicineWenzhou Medical UniversityWenzhouZhejiangChina
- Key Laboratory of Perinatal Medicine of WenzhouWenzhouZhejiangChina
- Key Laboratory of Structural Malformations in Children of Zhejiang ProvinceWenzhouZhejiangChina
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van der Ark-Vonk EM, Puijk MV, Pasterkamp G, van der Laan SW. The Effects of FABP4 on Cardiovascular Disease in the Aging Population. Curr Atheroscler Rep 2024; 26:163-175. [PMID: 38698167 PMCID: PMC11087245 DOI: 10.1007/s11883-024-01196-5] [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] [Accepted: 03/05/2024] [Indexed: 05/05/2024]
Abstract
PURPOSE OF REVIEW Fatty acid-binding protein 4 (FABP4) plays a role in lipid metabolism and cardiovascular health. In this paper, we cover FABP4 biology, its implications in atherosclerosis from observational studies, genetic factors affecting FABP4 serum levels, and ongoing drug development to target FABP4 and offer insights into future FABP4 research. RECENT FINDINGS FABP4 impacts cells through JAK2/STAT2 and c-kit pathways, increasing inflammatory and adhesion-related proteins. In addition, FABP4 induces angiogenesis and vascular smooth muscle cell proliferation and migration. FABP4 is established as a reliable predictive biomarker for cardiovascular disease in specific at-risk groups. Genetic studies robustly link PPARG and FABP4 variants to FABP4 serum levels. Considering the potential effects on atherosclerotic lesion development, drug discovery programs have been initiated in search for potent inhibitors of FABP4. Elevated FABP4 levels indicate an increased cardiovascular risk and is causally related to acceleration of atherosclerotic disease, However, clinical trials for FABP4 inhibition are lacking, possibly due to concerns about available compounds' side effects. Further research on FABP4 genetics and its putative causal role in cardiovascular disease is needed, particularly in aging subgroups.
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Affiliation(s)
- Ellen M van der Ark-Vonk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Mike V Puijk
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratory, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands.
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Wang C, Wang X, Zhang S, Xu P, Cheng L. Causal relationships between interleukins, interferons and COVID-19 risk: a Mendelian randomization study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:2387-2396. [PMID: 37660260 DOI: 10.1080/09603123.2023.2252461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 08/23/2023] [Indexed: 09/04/2023]
Abstract
Observational studies have shown close associations between COVID-19 risk and cytokines, especially interleukins (ILs) and interferons (IFNs). However, the causal relationships between ILs, IFNs and COVID-19 were still unclear. To resolve the problem, we conducted a Mendelian randomization analysis between COVID-19 and 47 cytokines, including 35 ILs and 12 IFNs. First, three methods were applied to estimate causal effects by using single nucleotide polymorphisms as instrumental variables (IVs). Subsequently, the MR-Egger method was used to estimate the horizontal pleiotropy of IVs. Finally, sensitivity analyses were applied to assess the robustness of results. As a result, one IFN (IFN-W1) and five ILs (IL-5, IL-6, IL-13, IL-16 and IL-37) were identified to significantly decrease the COVID-19 risk. In contrast, one IFN (IFNG) and five ILs (IL-3, IL-8, IL-27, IL-31 and IL-36β) were found to be significantly associated with an increased risk of COVID-19. In summary, the findings of this study provide insights into potential therapeutic interventions for COVID-19.
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Affiliation(s)
- Chao Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xin Wang
- College of Basic Medicine, Harbin Medical University, Harbin, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Peigang Xu
- Chongqing Research Institute of Harbin Institute of Technology, Harbin, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
- NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang, China
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Yang N, Shi L, Xu P, Ren F, Lv S, Li C, Qi X. Identification of potential drug targets for insomnia by Mendelian randomization analysis based on plasma proteomics. Front Neurol 2024; 15:1380321. [PMID: 38725646 PMCID: PMC11079244 DOI: 10.3389/fneur.2024.1380321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/12/2024] [Indexed: 05/12/2024] Open
Abstract
Introduction Insomnia, a common clinical disorder, significantly impacts the physical and mental well-being of patients. Currently, available hypnotic medications are unsatisfactory due to adverse reactions and dependency, necessitating the identification of new drug targets for the treatment of insomnia. Methods In this study, we utilized 734 plasma proteins as genetic instruments obtained from genome-wide association studies to conduct a Mendelian randomization analysis, with insomnia as the outcome variable, to identify potential drug targets for insomnia. Additionally, we validated our results externally using other datasets. Sensitivity analyses entailed reverse Mendelian randomization analysis, Bayesian co-localization analysis, and phenotype scanning. Furthermore, we constructed a protein-protein interaction network to elucidate potential correlations between the identified proteins and existing targets. Results Mendelian randomization analysis indicated that elevated levels of TGFBI (OR = 1.01; 95% CI, 1.01-1.02) and PAM ((OR = 1.01; 95% CI, 1.01-1.02) in plasma are associated with an increased risk of insomnia, with external validation supporting these findings. Moreover, there was no evidence of reverse causality for these two proteins. Co-localization analysis confirmed that PAM (coloc.abf-PPH4 = 0.823) shared the same variant with insomnia, further substantiating its potential role as a therapeutic target. There are interactive relationships between the potential proteins and existing targets of insomnia. Conclusion Overall, our findings suggested that elevated plasma levels of TGFBI and PAM are connected with an increased risk of insomnia and might be promising therapeutic targets, particularly PAM. However, further exploration is necessary to fully understand the underlying mechanisms involved.
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Affiliation(s)
- Ni Yang
- Department of First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Liangyuan Shi
- Qingdao Traditional Chinese Medicine Hospital (Qingdao Hiser Hospital) Qingdao Hiser Hospital Affiliated of Qingdao University, Qingdao, China
| | - Pengfei Xu
- Qingdao Traditional Chinese Medicine Hospital (Qingdao Hiser Hospital) Qingdao Hiser Hospital Affiliated of Qingdao University, Qingdao, China
| | - Fang Ren
- Department of Laboratory, Jimo District Qingdao Hospital of Traditional Chinese Medicine, Qingdao, China
| | - Shimeng Lv
- Department of First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Chunlin Li
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xianghua Qi
- Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
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Su Z, Wan Q. Potential therapeutic targets for membranous nephropathy: proteome-wide Mendelian randomization and colocalization analysis. Front Immunol 2024; 15:1342912. [PMID: 38707900 PMCID: PMC11069303 DOI: 10.3389/fimmu.2024.1342912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/21/2024] [Indexed: 05/07/2024] Open
Abstract
Background The currently available medications for treating membranous nephropathy (MN) still have unsatisfactory efficacy in inhibiting disease recurrence, slowing down its progression, and even halting the development of end-stage renal disease. There is still a need to develop novel drugs targeting MN. Methods We utilized summary statistics of MN from the Kiryluk Lab and obtained plasma protein data from Zheng et al. We performed a Bidirectional Mendelian randomization analysis, HEIDI test, mediation analysis, Bayesian colocalization, phenotype scanning, drug bank analysis, and protein-protein interaction network. Results The Mendelian randomization analysis uncovered 8 distinct proteins associated with MN after multiple false discovery rate corrections. Proteins related to an increased risk of MN in plasma include ABO [(Histo-Blood Group Abo System Transferase) (WR OR = 1.12, 95%CI:1.05-1.19, FDR=0.09, PPH4 = 0.79)], VWF [(Von Willebrand Factor) (WR OR = 1.41, 95%CI:1.16-1.72, FDR=0.02, PPH4 = 0.81)] and CD209 [(Cd209 Antigen) (WR OR = 1.19, 95%CI:1.07-1.31, FDR=0.09, PPH4 = 0.78)], and proteins that have a protective effect on MN: HRG [(Histidine-Rich Glycoprotein) (WR OR = 0.84, 95%CI:0.76-0.93, FDR=0.02, PPH4 = 0.80)], CD27 [(Cd27 Antigen) (WR OR = 0.78, 95%CI:0.68-0.90, FDR=0.02, PPH4 = 0.80)], LRPPRC [(Leucine-Rich Ppr Motif-Containing Protein, Mitochondrial) (WR OR = 0.79, 95%CI:0.69-0.91, FDR=0.09, PPH4 = 0.80)], TIMP4 [(Metalloproteinase Inhibitor 4) (WR OR = 0.67, 95%CI:0.53-0.84, FDR=0.09, PPH4 = 0.79)] and MAP2K4 [(Dual Specificity Mitogen-Activated Protein Kinase Kinase 4) (WR OR = 0.82, 95%CI:0.72-0.92, FDR=0.09, PPH4 = 0.80)]. ABO, HRG, and TIMP4 successfully passed the HEIDI test. None of these proteins exhibited a reverse causal relationship. Bayesian colocalization analysis provided evidence that all of them share variants with MN. We identified type 1 diabetes, trunk fat, and asthma as having intermediate effects in these pathways. Conclusions Our comprehensive analysis indicates a causal effect of ABO, CD27, VWF, HRG, CD209, LRPPRC, MAP2K4, and TIMP4 at the genetically determined circulating levels on the risk of MN. These proteins can potentially be a promising therapeutic target for the treatment of MN.
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Affiliation(s)
| | - Qijun Wan
- Department of Nephrology, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China
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20
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Lin H, Cao B. Circulating VEGF and inflammatory bowel disease: a bidirectional mendelian randomization. Front Genet 2024; 15:1282471. [PMID: 38699232 PMCID: PMC11063361 DOI: 10.3389/fgene.2024.1282471] [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: 12/17/2023] [Accepted: 03/18/2024] [Indexed: 05/05/2024] Open
Abstract
Introduction: Prior observational studies have suggested an association between circulating vascular endothelial growth factor (VEGF) levels and inflammatory bowel disease (IBD). This study sought to demonstrate the directionality of the association between circulating VEGF and particular forms of IBD as well as if there is a causal relationship between them. Methods: We collected summary data from relevant genome-wide association studies (GWASs) to assess the validity of causality, and a two-sample bidirectional Mendelian randomization (MR) study and sensitivity testing were performed to assess the causal relationship between circulating VEGF and IBD risk, including Crohn's disease and ulcerative colitis. Results: Our findings revealed a direct causal link between circulating VEGF and Crohn's disease (b 0.195, se 0.078, p < 0.013). However, neither circulating VEGF nor ulcerative colitis were shown to be causally linked (p > 0.025), nor was there proof of a reverse causal relationship from IBD to VEGF. Discussion: In conclusion, circulating VEGF shows a cause-and-effect relationship with Crohn's disease.
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Affiliation(s)
| | - Bangwei Cao
- Cancer Centre, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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21
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Cao M, Cui B. Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses. Cardiovasc Diabetol 2024; 23:126. [PMID: 38614964 PMCID: PMC11016216 DOI: 10.1186/s12933-024-02222-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 03/31/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach. METHODS We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants. RESULTS Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy. CONCLUSIONS Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.
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Affiliation(s)
- Min Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Bin Cui
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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22
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Mao R, Li J, Xiao W. Identification of prospective aging drug targets via Mendelian randomization analysis. Aging Cell 2024:e14171. [PMID: 38572516 DOI: 10.1111/acel.14171] [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: 10/17/2023] [Revised: 02/26/2024] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Aging represents a multifaceted process culminating in the deterioration of biological functions. Despite the introduction of numerous anti-aging strategies, their therapeutic outcomes have often been less than optimal. Consequently, discovering new targets to mitigate aging effects is of critical importance. We applied Mendelian randomization (MR) to identify potential pharmacological targets against aging, drawing upon summary statistics from both the Decode and FinnGen cohorts, with further validation in an additional cohort. To address potential reverse causality, bidirectional MR analysis with Steiger filtering was utilized. Additionally, Bayesian co-localization and phenotype scanning were implemented to investigate previous associations between genetic variants and traits. Summary-data-based Mendelian randomization (SMR) analysis was conducted to assess the impact of genetic variants on aging via their effects on protein expression. Additionally, mediation analysis was orchestrated to uncover potential intermediaries in these associations. Finally, we probed the systemic implications of drug-target protein expression across diverse indications by MR-PheWas analysis. Utilizing a Bonferroni-corrected threshold, our MR examination identified 10 protein-aging associations. Within this cohort of proteins, MST1, LCT, GMPR2, PSMB4, ECM1, EFEMP1, and ISLR2 appear to exacerbate aging risks, while MAX, B3GNT8, and USP8 may exert protective influences. None of these proteins displayed reverse causality except EFEMP1. Bayesian co-localization inferred shared variants between aging and proteins such as B3GNT8 (rs11670143), ECM1 (rs61819393), and others listed. Mediator analysis pinpointed 1,5-anhydroglucitol as a partial intermediary in the influence LCT exhibits on telomere length. Circulating proteins play a pivotal role in influencing the aging process, making them promising candidates for therapeutic intervention. The implications of these proteins in aging warrant further investigation in future clinical research.
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Affiliation(s)
- Rui Mao
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Wenqin Xiao
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Kalnapenkis A, Jõeloo M, Lepik K, Kukuškina V, Kals M, Alasoo K, Mägi R, Esko T, Võsa U. Genetic determinants of plasma protein levels in the Estonian population. Sci Rep 2024; 14:7694. [PMID: 38565889 PMCID: PMC10987560 DOI: 10.1038/s41598-024-57966-3] [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: 06/22/2023] [Accepted: 03/23/2024] [Indexed: 04/04/2024] Open
Abstract
The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.
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Affiliation(s)
- Anette Kalnapenkis
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
| | - Maarja Jõeloo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Kaido Lepik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Viktorija Kukuškina
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
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24
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Wang H, Pang J, Zhou Y, Qi Q, Tang Y, Gul S, Sheng M, Dan J, Tang W. Identification of potential drug targets for allergic diseases from a genetic perspective: A mendelian randomization study. Clin Transl Allergy 2024; 14:e12350. [PMID: 38573314 PMCID: PMC10994001 DOI: 10.1002/clt2.12350] [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: 01/09/2024] [Revised: 02/26/2024] [Accepted: 03/16/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Allergic diseases typically refer to a heterogeneous group of conditions primarily caused by the activation of mast cells or eosinophils, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma. Asthma, AR, and AD collectively affect approximately one-fifth of the global population, imposing a significant economic burden on society. Despite the availability of drugs to treat allergic diseases, they have been shown to be insufficient in controlling relapses and halting disease progression. Therefore, new drug targets are needed to prevent the onset of allergic diseases. METHOD We employed a Mendelian randomization approach to identify potential drug targets for the treatment of allergic diseases. Leveraging 1798 genetic instruments for 1537 plasma proteins from the latest reported Genome-Wide Association Studies (GWAS), we analyzed the GWAS summary statistics of Ferreira MA et al. (nCase = 180,129, nControl = 180,709) using the Mendelian randomization method. Furthermore, we validated our findings in the GWAS data from the FinnGen and UK Biobank cohorts. Subsequently, we conducted sensitivity tests through reverse causal analysis, Bayesian colocalization analysis, and phenotype scanning. Additionally, we performed protein-protein interaction analysis to determine the interaction between causal proteins. Finally, based on the potential protein targets, we conducted molecular docking to identify potential drugs for the treatment of allergic diseases. RESULTS At Bonferroni significance (p < 3.25 × 10-5), the Mendelian randomization analysis revealed 11 significantly associated protein-allergic disease pairs. Among these, the increased levels of TNFAIP3, ERBB3, TLR1, and IL1RL2 proteins were associated with a reduced risk of allergic diseases, with corresponding odds ratios of 0.82 (0.76-0.88), 0.74 (0.66-0.82), 0.49 (0.45-0.55), and 0.81 (0.75-0.87), respectively. Conversely, increased levels of IL6R, IL1R1, ITPKA, IL1RL1, KYNU, LAYN, and LRP11 proteins were linked to an elevated risk of allergic diseases, with corresponding odds ratios of 1.04 (1.03-1.05), 1.25 (1.18-1.34), 1.48 (1.25-1.75), 1.14 (1.11-1.18), 1.09 (1.05-1.12), 1.96 (1.56-2.47), and 1.05 (1.03-1.07), respectively. Bayesian colocalization analysis suggested that LAYN (coloc.abf-PPH4 = 0.819) and TNFAIP3 (coloc.abf-PPH4 = 0.930) share the same variant associated with allergic diseases. CONCLUSIONS Our study demonstrates a causal association between the expression levels of TNFAIP3 and LAYN and the risk of allergic diseases, suggesting them as potential drug targets for these conditions, warranting further clinical investigation.
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Affiliation(s)
- Hui Wang
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Jianyu Pang
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Yuguan Zhou
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Qi Qi
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Yuheng Tang
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Samina Gul
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Miaomiao Sheng
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Juhua Dan
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
| | - Wenru Tang
- Laboratory of Molecular Genetics of Aging & TumorMedicine SchoolKunming University of Science and TechnologyKunmingYunnanChina
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25
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Li J, Wang F, Li Z, Feng J, Men Y, Han J, Xia J, Zhang C, Han Y, Chen T, Zhao Y, Zhou S, Da Y, Chai G, Hao J. Integrative multi-omics analysis identifies genetically supported druggable targets and immune cell specificity for myasthenia gravis. J Transl Med 2024; 22:302. [PMID: 38521921 PMCID: PMC10960998 DOI: 10.1186/s12967-024-04994-2] [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: 09/28/2023] [Accepted: 02/12/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND Myasthenia gravis (MG) is a chronic autoimmune disorder characterized by fluctuating muscle weakness. Despite the availability of established therapies, the management of MG symptoms remains suboptimal, partially attributed to lack of efficacy or intolerable side-effects. Therefore, new effective drugs are warranted for treatment of MG. METHODS By employing an analytical framework that combines Mendelian randomization (MR) and colocalization analysis, we estimate the causal effects of blood druggable expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) on the susceptibility of MG. We subsequently investigated whether potential genetic effects exhibit cell-type specificity by utilizing genetic colocalization analysis to assess the interplay between immune-cell-specific eQTLs and MG risk. RESULTS We identified significant MR results for four genes (CDC42BPB, CD226, PRSS36, and TNFSF12) using cis-eQTL genetic instruments and three proteins (CTSH, PRSS8, and CPN2) using cis-pQTL genetic instruments. Six of these loci demonstrated evidence of colocalization with MG susceptibility (posterior probability > 0.80). We next undertook genetic colocalization to investigate cell-type-specific effects at these loci. Notably, we identified robust evidence of colocalization, with a posterior probability of 0.854, linking CTSH expression in TH2 cells and MG risk. CONCLUSIONS This study provides crucial insights into the genetic and molecular factors associated with MG susceptibility, singling out CTSH as a potential candidate for in-depth investigation and clinical consideration. It additionally sheds light on the immune-cell regulatory mechanisms related to the disease. However, further research is imperative to validate these targets and evaluate their feasibility for drug development.
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Affiliation(s)
- Jiao Li
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
- Beijing Municipal Geriatric Medical Research Center, Beijing, China
- Key Laboratory for Neurodegenerative Diseases of Ministry of Education, Beijing, China
| | - Fei Wang
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
- Key Laboratory for Neurodegenerative Diseases of Ministry of Education, Beijing, China
| | - Zhen Li
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Jingjing Feng
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Yi Men
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Jinming Han
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Jiangwei Xia
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Chen Zhang
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Yilai Han
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Teng Chen
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Yinan Zhao
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Sirui Zhou
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Yuwei Da
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China
| | - Guoliang Chai
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China.
- Beijing Municipal Geriatric Medical Research Center, Beijing, China.
| | - Junwei Hao
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Capital Medical University, Beijing, 100053, China.
- Beijing Municipal Geriatric Medical Research Center, Beijing, China.
- Key Laboratory for Neurodegenerative Diseases of Ministry of Education, Beijing, China.
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Li J, Zhang Y, You Y, Huang Z, Wu L, Liang C, Weng B, Pan L, Huang Y, Huang Y, Yang M, Lu M, Li R, Yan X, Liu Q, Deng S. Unraveling the mechanisms of NK cell dysfunction in aging and Alzheimer's disease: insights from GWAS and single-cell transcriptomics. Front Immunol 2024; 15:1360687. [PMID: 38464521 PMCID: PMC10920339 DOI: 10.3389/fimmu.2024.1360687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 02/06/2024] [Indexed: 03/12/2024] Open
Abstract
Background Aging is an important factor in the development of Alzheimer's disease (AD). The senescent cells can be recognized and removed by NK cells. However, NK cell function is gradually inactivated with age. Therefore, this study used senescence as an entry point to investigate how NK cells affect AD. Methods The study validated the correlation between cognition and aging through a prospective cohort of the National Health and Nutrition Examination Survey database. A cellular trajectory analysis of the aging population was performed using single-cell nuclear transcriptome sequencing data from patients with AD and different ages. The genome-wide association study (GWAS) cohort of AD patients was used as the outcome event, and the expression quantitative trait locus was used as an instrumental variable. Causal associations between genes and AD were analyzed by bidirectional Mendelian randomization (MR) and co-localization. Finally, clinical cohorts were constructed to validate the expression of key genes. Results A correlation between cognition and aging was demonstrated using 2,171 older adults over 60 years of age. Gene regulation analysis revealed that most of the highly active transcription factors were concentrated in the NK cell subpopulation of AD. NK cell trajectories were constructed for different age populations. MR and co-localization analyses revealed that CHD6 may be one of the factors influencing AD. Conclusion We explored different levels of AD and aging from population cohorts, single-cell data, and GWAS cohorts and found that there may be some correlations of NK cells between aging and AD. It also provides some basis for potential causation.
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Affiliation(s)
- Jinwei Li
- Department of Neurosurgery, Liuzhou Workers Hospital, Liuzhou, China
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yang Zhang
- Department of Vascular Surgery, Fuwai Yunnan Cardiovascular Hospital, Affiliated Cardiovascular Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yanwei You
- Division of Sports Science and Physical Education, Tsinghua University, Beijing, China
| | - Zhiwei Huang
- Department of Neurosurgery, Liuzhou Workers Hospital, Liuzhou, China
| | - Liya Wu
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
| | - Cong Liang
- Department of Pharmacy, Liuzhou Workers Hospital, Liuzhou, China
| | - Baohui Weng
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
| | - Liya Pan
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
| | - Yan Huang
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
| | - Yushen Huang
- Department of Pharmacy, Liuzhou Workers Hospital, Liuzhou, China
| | - Mengqi Yang
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
| | - Mengting Lu
- Department of Dermatology, Liuzhou Workers Hospital, Liuzhou, China
| | - Rui Li
- Department of Medical Imaging, Liuzhou Workers Hospital, Liuzhou, China
| | - Xianlei Yan
- Department of Neurosurgery, Liuzhou Workers Hospital, Liuzhou, China
| | - Quan Liu
- Department of Neurosurgery, Liuzhou Workers Hospital, Liuzhou, China
| | - Shan Deng
- Department of Neurology, Liuzhou Workers Hospital, Liuzhou, China
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Yan C, Bao J, Jin J. Exploring the interplay of gut microbiota, inflammation, and LDL-cholesterol: a multiomics Mendelian randomization analysis of their causal relationship in acute pancreatitis and non-alcoholic fatty liver disease. J Transl Med 2024; 22:179. [PMID: 38374155 PMCID: PMC10875775 DOI: 10.1186/s12967-024-04996-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/12/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Acute pancreatitis and non-alcoholic fatty liver disease are both serious diseases in the digestive system. The pathogenesis of both diseases is extremely complex closely and it related to gut microbiota, inflammation, and blood fat. There is a close relationship between gut microbiota and blood lipids. METHODS In this study, we used three types of exposure: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls), with LDL-C as an intermediary and acute pancreatitis and non-alcoholic fatty liver disease as outcomes. We mainly used MR-IVW, co-localization analysis, and reverse MR analysis methods for analysis. RESULTS 7 gut microbiota, 21 inflammatory cells, and 3 inflammatory proteins can affect LDL-C levels. LDL-C is associated with acute pancreatitis and non-alcoholic fatty liver disease. CONCLUSIONS Three omics were used: 412 gut microbiota, 731 inflammatory cells, and 91 inflammatory proteins (pqtls). It explains the causal relationship between multiomics, LDL- cholesterol, acute pancreatitis, and non-alcoholic fatty liver disease.
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Affiliation(s)
- Congzhi Yan
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, 325000, China
- Wenzhou Medical University, Zhejiang, China
| | - Jingxia Bao
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, 325000, China
- Wenzhou Medical University, Zhejiang, China
| | - Jinji Jin
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, 325000, China.
- Wenzhou Medical University, Zhejiang, China.
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Zou X, Wang L, Wang S, Zhang Y, Ma J, Chen L, Li Y, Yao TX, Zhou H, Wu L, Tang Q, Ma S, Zhang X, Tang R, Yi Y, Liu R, Zeng Y, Zhang L. Promising therapeutic targets for ischemic stroke identified from plasma and cerebrospinal fluid proteomes: a multicenter Mendelian randomization study. Int J Surg 2024; 110:766-776. [PMID: 38016292 PMCID: PMC10871597 DOI: 10.1097/js9.0000000000000922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 11/09/2023] [Indexed: 11/30/2023]
Abstract
BACKGROUND Ischemic stroke (IS) is more common every year, the condition is serious, and have a poor prognosis. New, efficient, and safe therapeutic targets are desperately needed as early treatment especially prevention and reperfusion is the key to lowering the occurrence of poorer prognosis. Generally circulating proteins are attractive therapeutic targets, this study aims to identify potential pharmacological targets among plasma and cerebrospinal fluid (CSF) proteins for the prevention and treatment of IS using a multicenter Mendelian randomization (MR) approach. METHODS First, the genetic instruments of 734 plasma and 151 CSF proteins were assessed for causative connections with IS from MEGASTROKE consortium by MR to identify prospective therapeutic targets. Then, for additional validation, plasma proteins from the deCODE consortium and the Fenland consortium, as well as IS GWAS data from the FinnGen cohort, the ISGC consortium and UK biobank, were employed. A thorough evaluation of the aforementioned possible pharmacological targets was carried out using meta-analysis. The robustness of MR results was then confirmed through sensitivity analysis using several techniques, such as bidirectional MR analysis, Steiger filtering, and Bayesian colocalization. Finally, methods like Protein-Protein Interaction (PPI) Networking were utilized to investigate the relationship between putative drug targets and therapeutic agents. RESULTS The authors discovered three proteins that may function as promising therapeutic targets for IS and meet the Bonferroni correction ( P <0.05/885=5.65×10 -5 ). Prekallikrein (OR=0.41, 95% CI: 0.27-0.63, P =3.61×10 -5 ), a protein found in CSF, has a 10-fold protective impact in IS, while the plasma proteins SWAP70 (OR=0.85, 95% CI: 0.80-0.91, P =1.64×10 -6 ) and MMP-12 (OR=0.92, 95% CI: 0.89-0.95, P =4.49×10 -6 ) of each SD play a protective role in IS. Prekallikrein, MMP-12, SWAP70 was replicated in the FinnGen cohort and ISGC database. MMP-12 (OR=0.93, 95% CI: 0.91-0.94, P <0.001), SWAP70 (OR=0.92, 95% CI: 0.90-0.94, P <0.001), and prekallikrein (OR=0.53, 95% CI: 0.33-0.72, P <0.001) may all be viable targets for IS, according to the combined meta-analysis results. Additionally, no evidence of reverse causality was identified, and Bayesian colocalization revealed MMP-12 (PPH 4 =0.995), SWAP70 (PPH 4 =0.987), and prekallikrein (PPH 4 =0.894) shared the same variant with IS, supporting the robustness of the aforementioned causation. Prekallikrein and MMP-12 were associated with the target protein of the current treatment of IS. Among them, Lanadelumab, a new drug whose target protein is a prekallikrein, may be a promising new drug for the treatment of IS. CONCLUSION The prekallikrein, MMP-12, and SWAP70 are causally associated with the risk of IS. Moreover, MMP-12 and prekallikrein may be treated as promising therapeutic targets for medical intervention of IS.
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Affiliation(s)
- Xuelun Zou
- Department of Neurology, Xiangya Hospital, Central South University
| | - Leiyun Wang
- Department of Pharmacy, Wuhan No.1 Hospital, Wuhan, Hubei, People’s Republic of China
| | - Sai Wang
- Department of Neurology, Xiangya Hospital, Central South University
| | - Yupeng Zhang
- Department of Neurology, Xiangya Hospital, Central South University
| | - Junyi Ma
- Department of Neurology, Xiangya Hospital, Central South University
| | - Lei Chen
- Department of Neurology, Xiangya Hospital, Central South University
| | - Ye Li
- Department of Neurology, Xiangya Hospital, Central South University
| | - Tian-Xing Yao
- Department of Neurology, Xiangya Hospital, Central South University
| | - Huifang Zhou
- Department of Neurology, Xiangya Hospital, Central South University
| | - Lianxu Wu
- Department of Neurology, Xiangya Hospital, Central South University
| | - Qiaoling Tang
- Department of Neurology, Xiangya Hospital, Central South University
| | - Siyuan Ma
- Department of Neurology, Xiangya Hospital, Central South University
| | - Xiangbin Zhang
- Department of Neurology, Xiangya Hospital, Central South University
| | - Rongmei Tang
- Department of Neurology, Xiangya Hospital, Central South University
| | - Yexiang Yi
- Department of Neurology, Xiangya Hospital, Central South University
| | - Ran Liu
- Department of Neurology, Xiangya Hospital, Central South University
| | - Yi Zeng
- Department of Geriatrics, Second Xiangya Hospital
| | - Le Zhang
- Department of Neurology, Xiangya Hospital, Central South University
- Human Brain Disease Biological Resources Platform of Hunan Province, Xiangya Hospital
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital
- Multi-Modal Monitoring Technology for Severe Cerebrovascular Disease of Human Engineering Research Center, Xiangya Hospital
- Brain Health Center of Hunan Province, Xiangya Hospital, Central South University, Changsha, Hunan
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Ishikawa Y, Tanaka N, Asano Y, Kodera M, Shirai Y, Akahoshi M, Hasegawa M, Matsushita T, Saito K, Motegi SI, Yoshifuji H, Yoshizaki A, Kohmoto T, Takagi K, Oka A, Kanda M, Tanaka Y, Ito Y, Nakano K, Kasamatsu H, Utsunomiya A, Sekiguchi A, Niiro H, Jinnin M, Makino K, Makino T, Ihn H, Yamamoto M, Suzuki C, Takahashi H, Nishida E, Morita A, Yamamoto T, Fujimoto M, Kondo Y, Goto D, Sumida T, Ayuzawa N, Yanagida H, Horita T, Atsumi T, Endo H, Shima Y, Kumanogoh A, Hirata J, Otomo N, Suetsugu H, Koike Y, Tomizuka K, Yoshino S, Liu X, Ito S, Hikino K, Suzuki A, Momozawa Y, Ikegawa S, Tanaka Y, Ishikawa O, Takehara K, Torii T, Sato S, Okada Y, Mimori T, Matsuda F, Matsuda K, Amariuta T, Imoto I, Matsuo K, Kuwana M, Kawaguchi Y, Ohmura K, Terao C. GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region. Nat Commun 2024; 15:319. [PMID: 38296975 PMCID: PMC10830486 DOI: 10.1038/s41467-023-44541-z] [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: 03/20/2023] [Accepted: 12/18/2023] [Indexed: 02/02/2024] Open
Abstract
Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.
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Affiliation(s)
- Yuki Ishikawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Nao Tanaka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Rheumatology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshihide Asano
- Department of Dermatology, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Masanari Kodera
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yuichiro Shirai
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Mitsuteru Akahoshi
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
- Department of Rheumatology, Saga University Hospital, Saga, Japan
| | - Minoru Hasegawa
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Takashi Matsushita
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | - Kazuyoshi Saito
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Sei-Ichiro Motegi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hajime Yoshifuji
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ayumi Yoshizaki
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Tomohiro Kohmoto
- Aichi Cancer Center Research Institute, Division of Molecular Genetics, Nagoya, Japan
| | - Kae Takagi
- Tokyo Women's Medical University, Adachi Medical Center, Tokyo, Japan
| | - Akira Oka
- Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Miho Kanda
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yoshihito Tanaka
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yumi Ito
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Kazuhisa Nakano
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Hiroshi Kasamatsu
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akira Utsunomiya
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akiko Sekiguchi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hiroaki Niiro
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Masatoshi Jinnin
- Department of Dermatology, Wakayama Medical University Graduate School of Medicine, Wakayama, Japan
| | - Katsunari Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Takamitsu Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Hironobu Ihn
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Motohisa Yamamoto
- Department of Rheumatology and Allergy, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Chisako Suzuki
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Hiroki Takahashi
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Emi Nishida
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Department of Dermatology, Okazaki City Hospital, Okazaki, Japan
| | - Akimichi Morita
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Toshiyuki Yamamoto
- Department of Dermatology, Fukushima Medical University, School of Medicine, Fukushima, Japan
| | - Manabu Fujimoto
- Department of Dermatology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yuya Kondo
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Daisuke Goto
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Takayuki Sumida
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Naho Ayuzawa
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Hidetoshi Yanagida
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Tetsuya Horita
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Tatsuya Atsumi
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Hirahito Endo
- Omori Medical Center, Toho University, Rheumatic Disease Center, Tokyo, Japan
| | - Yoshihito Shima
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Jun Hirata
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Nao Otomo
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Hiroyuki Suetsugu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Yoshinao Koike
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Kohei Tomizuka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Soichiro Yoshino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Xiaoxi Liu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Shuji Ito
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Keiko Hikino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Pharmacogenomics, Yokohama, Japan
| | - Akari Suzuki
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Autoimmune Diseases, Yokohama, Japan
| | - Yukihide Momozawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Genotyping Development, Yokohama, Japan
| | - Shiro Ikegawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Bone and Joint Diseases, Yokohama, Japan
| | - Yoshiya Tanaka
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Osamu Ishikawa
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuhiko Takehara
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | | | - Shinichi Sato
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Tsuneyo Mimori
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Ijinkai Takeada General Hospital, Kyoto, Japan
| | - Fumihiko Matsuda
- Graduate School of Medicine, Kyoto University, Center for Genomic Medicine, Kyoto, Japan
| | - Koichi Matsuda
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo, Japan
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Tiffany Amariuta
- Center for Data Sciences, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Issei Imoto
- Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Keitaro Matsuo
- Aichi Cancer Center Research Institute, Division of Cancer Epidemiology and Prevention, Nagoya, Japan
| | - Masataka Kuwana
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Yasushi Kawaguchi
- Tokyo Women's Medical University, Division of Rheumatology, Department of Internal Medicine, Tokyo, Japan
| | - Koichiro Ohmura
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Chikashi Terao
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan.
- Shizuoka General Hospital, The Clinical Research Center, Shizuoka, Japan.
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
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30
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Al-Ewaidat OA, Naffaa MM. Stroke risk in rheumatoid arthritis patients: exploring connections and implications for patient care. Clin Exp Med 2024; 24:30. [PMID: 38294723 PMCID: PMC10830780 DOI: 10.1007/s10238-023-01288-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 11/04/2023] [Indexed: 02/01/2024]
Abstract
Rheumatoid arthritis (RA) can independently increase the risk of stroke, affecting both young and adult RA patients. Recent attention has been drawn to the association between stroke and RA, supported by mounting evidence. Given that stroke is a significant and an urgent public health concern, this review aims to highlight the relationship between stroke and RA, covering mechanisms, underlying risk factors, early detection tools, and treatment implications. By uncovering the connection that links RA to stroke, we can pave the way for targeted healthcare practices and the development of preventive strategies for individuals with RA. Therefore, further research is imperative to deepen our understanding of this association and, ideally, guide treatment decisions for individuals at risk of both RA and stroke.
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Affiliation(s)
- Ola A Al-Ewaidat
- Department of Internal Medicine, Ascension Saint Francis Hospital, Evanston, IL, 60202, USA
| | - Moawiah M Naffaa
- Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA.
- Department of Cell Biology, Duke University School of Medicine, Durham, NC, 27710, USA.
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31
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Zilinskas R, Li C, Shen X, Pan W, Yang T. Inferring a directed acyclic graph of phenotypes from GWAS summary statistics. Biometrics 2024; 80:ujad039. [PMID: 38470257 PMCID: PMC10928990 DOI: 10.1093/biomtc/ujad039] [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: 03/01/2023] [Revised: 11/24/2023] [Accepted: 01/04/2024] [Indexed: 03/13/2024]
Abstract
Estimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimer's disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available.
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Affiliation(s)
| | - Chunlin Li
- Department of Statistics, Iowa State University, Ames, IA 50011, United States
| | - Xiaotong Shen
- School of Statistics, University of Minnesota, Minneapolis, MN 55455, United States
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN 55455, United States
| | - Tianzhong Yang
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN 55455, United States
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32
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Iakunchykova O, Leonardsen EH, Wang Y. Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we? Transl Psychiatry 2024; 14:63. [PMID: 38272880 PMCID: PMC10810856 DOI: 10.1038/s41398-024-02778-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 01/06/2024] [Accepted: 01/12/2024] [Indexed: 01/27/2024] Open
Abstract
The question of whether immune dysfunction contributes to risk of psychiatric disorders has long been a subject of interest. To assert this hypothesis a plethora of correlative evidence has been accumulated from the past decades; however, a variety of technical and practical obstacles impeded on a cause-effect interpretation of these data. With the advent of large-scale omics technology and advanced statistical models, particularly Mendelian randomization, new studies testing this old hypothesis are accruing. Here we synthesize these new findings from genomics and genetic causal inference studies on the role of immune dysfunction in major psychiatric disorders and reconcile these new data with pre-omics findings. By reconciling these evidences, we aim to identify key gaps and propose directions for future studies in the field.
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Affiliation(s)
- Olena Iakunchykova
- Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Esten H Leonardsen
- Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Yunpeng Wang
- Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, 0317, Oslo, Norway.
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Wang Y, Yi K, Chen B, Zhang B, Jidong G. Elucidating the susceptibility to breast cancer: an in-depth proteomic and transcriptomic investigation into novel potential plasma protein biomarkers. Front Mol Biosci 2024; 10:1340917. [PMID: 38304232 PMCID: PMC10833003 DOI: 10.3389/fmolb.2023.1340917] [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: 11/19/2023] [Accepted: 12/29/2023] [Indexed: 02/03/2024] Open
Abstract
Objectives: This study aimed to identify plasma proteins that are associated with and causative of breast cancer through Proteome and Transcriptome-wide association studies combining Mendelian Randomization. Methods: Utilizing high-throughput datasets, we designed a two-phase analytical framework aimed at identifying novel plasma proteins that are both associated with and causative of breast cancer. Initially, we conducted Proteome/Transcriptome-wide association studies (P/TWAS) to identify plasma proteins with significant associations. Subsequently, Mendelian Randomization was employed to ascertain the causation. The validity and robustness of our findings were further reinforced through external validation and various sensitivity analyses, including Bayesian colocalization, Steiger filtering, heterogeneity and pleiotropy. Additionally, we performed functional enrichment analysis of the identified proteins to better understand their roles in breast cancer and to assess their potential as druggable targets. Results: We identified 5 plasma proteins demonstrating strong associations and causative links with breast cancer. Specifically, PEX14 (OR = 1.201, p = 0.016) and CTSF (OR = 1.114, p < 0.001) both displayed positive and causal association with breast cancer. In contrast, SNUPN (OR = 0.905, p < 0.001), CSK (OR = 0.962, p = 0.038), and PARK7 (OR = 0.954, p < 0.001) were negatively associated with the disease. For the ER-positive subtype, 3 plasma proteins were identified, with CSK and CTSF exhibiting consistent trends, while GDI2 (OR = 0.920, p < 0.001) was distinct to this subtype. In ER-negative subtype, PEX14 (OR = 1.645, p < 0.001) stood out as the sole protein, even showing a stronger causal effect compared to breast cancer. These associations were robustly supported by colocalization and sensitivity analyses. Conclusion: Integrating multiple data dimensions, our study successfully pinpointed plasma proteins significantly associated with and causative of breast cancer, offering valuable insights for future research and potential new biomarkers and therapeutic targets.
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Affiliation(s)
- Yang Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kexin Yi
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Baoyue Chen
- Department of General Surgery, Beijing Puren Hospital, Beijing, China
| | - Bailin Zhang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gao Jidong
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
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Shi J, Wu X, Qi H, Xu X, Hong S. Application and discoveries of metabolomics and proteomics in the study of female infertility. Front Endocrinol (Lausanne) 2024; 14:1315099. [PMID: 38274228 PMCID: PMC10810415 DOI: 10.3389/fendo.2023.1315099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/21/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction Female infertility is defined as the absence of clinical pregnancy after 12 months of regular unprotected sexual intercourse. Methods This study employed metabolomics and proteomics approaches to investigate the relationship between metabolites and proteins and female infertility. The study used metabolomics and proteomics data from the UK Biobank to identify metabolites and proteins linked to infertility. Results The results showed that GRAM domain-containing protein 1C and metabolites fibrinogen cleavage peptides ADpSGEGDFXAEGGGVR and 3-Hydroxybutyrate had a positive correlation with infertility, whereas proteins such as Interleukin-3 receptor subunit alpha, Thrombospondin type-1 domain-containing protein 1, Intestinal-type alkaline phosphatase, and platelet and endothelial cell adhesion molecule 1 exhibited a negative correlation. These findings provide new clues and targets for infertility diagnosis and treatment. However, further research is required to validate these results and gain a deeper understanding of the specific roles of these metabolites and proteins in infertility pathogenesis. Discussion In conclusion, metabolomics and proteomics techniques have significant application value in the study of infertility, allowing for a better understanding of the biological mechanisms underlying infertility and providing new insights and strategies for its diagnosis and treatment. These research findings provide a crucial biological mechanistic basis for early infertility screening, prevention, and treatment.
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Affiliation(s)
- Junhua Shi
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xingjie Wu
- Department of Obstetrics, Hangzhou Medical College Affiliated Lin’an People’s Hospital, The First People’s Hospital of Hangzhou Lin’an District, Hangzhou, Zhejiang, China
| | - Haiou Qi
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xin Xu
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shihao Hong
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University; Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Hangzhou, China
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Lin S, Wu S, Zhao W, Fang Z, Kang H, Liu X, Pan S, Yu F, Bao Y, Jia P. TargetGene: a comprehensive database of cell-type-specific target genes for genetic variants. Nucleic Acids Res 2024; 52:D1072-D1081. [PMID: 37870478 PMCID: PMC10767789 DOI: 10.1093/nar/gkad901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/24/2023] Open
Abstract
Annotating genetic variants to their target genes is of great importance in unraveling the causal variants and genetic mechanisms that underlie complex diseases. However, disease-associated genetic variants are often located in non-coding regions and manifest context-specific effects, making it challenging to accurately identify the target genes and regulatory mechanisms. Here, we present TargetGene (https://ngdc.cncb.ac.cn/targetgene/), a comprehensive database reporting target genes for human genetic variants from various aspects. Specifically, we collected a comprehensive catalog of multi-omics data at the single-cell and bulk levels and from various human tissues, cell types and developmental stages. To facilitate the identification of Single Nucleotide Polymorphism (SNP)-to-gene connections, we have implemented multiple analytical tools based on chromatin co-accessibility, 3D interaction, enhancer activities and quantitative trait loci, among others. We applied the pipeline to evaluate variants from nearly 1300 Genome-wide association studies (GWAS) and assembled a comprehensive atlas of multiscale regulation of genetic variants. TargetGene is equipped with user-friendly web interfaces that enable intuitive searching, navigation and browsing through the results. Overall, TargetGene provides a unique resource to empower researchers to study the regulatory mechanisms of genetic variants in complex human traits.
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Affiliation(s)
- Shiqi Lin
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Song Wu
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Wei Zhao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Zhanjie Fang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongen Kang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fudong Yu
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China
| | - Yiming Bao
- University of Chinese Academy of Sciences, Beijing 100049, China
- National Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Wu J, Fan Q, He Q, Zhong Q, Zhu X, Cai H, He X, Xu Y, Huang Y, Di X. Potential drug targets for myocardial infarction identified through Mendelian randomization analysis and Genetic colocalization. Medicine (Baltimore) 2023; 102:e36284. [PMID: 38065874 PMCID: PMC10713171 DOI: 10.1097/md.0000000000036284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 11/02/2023] [Indexed: 12/18/2023] Open
Abstract
Myocardial infarction (MI) is a major cause of death and disability worldwide, but current treatments are limited by their invasiveness, side effects, and lack of efficacy. Novel drug targets for MI prevention are urgently needed. In this study, we used Mendelian randomization to identify potential therapeutic targets for MI using plasma protein quantitative trait loci as exposure variables and MI as the outcome variable. We further validated our findings using reverse causation analysis, Bayesian co-localization analysis, and external datasets. We also constructed a protein-protein interaction network to explore the relationships between the identified proteins and known MI targets. Our analysis revealed 2 proteins, LPA and APOA5, as potential drug targets for MI, with causal effects on MI risk confirmed by multiple lines of evidence. LPA and APOA5 are involved in lipid metabolism and interact with target proteins of current MI medications. We also found 4 other proteins, IL1RN, FN1, NT5C, and SEMA3C, that may have potential as drug targets but require further confirmation. Our study demonstrates the utility of Mendelian randomization and protein quantitative trait loci in discovering novel drug targets for complex diseases such as MI. It provides insights into the underlying mechanisms of MI pathology and treatment.
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Affiliation(s)
- Jiayu Wu
- The First School of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qiaoming Fan
- Clifford Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qi He
- The Eighth Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qian Zhong
- The First Affiliated Hospital of Jinzhou Medical University, China
| | - Xianqiong Zhu
- Shenzhen Clinical College, Guangzhou University of Chinese Medicine, China
| | - Huilian Cai
- Clifford Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaolin He
- Clifford Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ying Xu
- The Fourth Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yuxuan Huang
- School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, China
| | - Xingwei Di
- The First Affiliated Hospital of Jinzhou Medical University, China
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Zhang Y, Xie J, Wen S, Cao P, Xiao W, Zhu J, Li S, Wang Z, Cen H, Zhu Z, Ding C, Ruan G. Evaluating the causal effect of circulating proteome on the risk of osteoarthritis-related traits. Ann Rheum Dis 2023; 82:1606-1617. [PMID: 37595989 DOI: 10.1136/ard-2023-224459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 08/02/2023] [Indexed: 08/20/2023]
Abstract
OBJECTIVES This study aims to identify circulating proteins that are causally associated with osteoarthritis (OA)-related traits through Mendelian randomisation (MR)-based analytical framework. METHODS Large-scale two-sample MR was employed to estimate the effects of thousands of plasma proteins on 12 OA-related traits. Additional analyses including Bayesian colocalisation, Steiger filtering analysis, assessment of protein-altering variants and mapping expression quantitative trait loci to protein quantitative trait loci were performed to investigate the reliability of the MR findings; protein-protein interaction, pathway enrichment analysis and evaluation of drug targets were conducted to deepen the understanding and identify potential therapeutic targets of OA. RESULTS Dozens of circulating proteins were identified to have putatively causal effects on OA-related traits, and a majority of these proteins were either drug targets or considered druggable. CONCLUSIONS Through MR analysis, we have identified numerous plasma proteins associated with OA-related traits, shedding light on protein-mediated mechanisms and offering promising therapeutic targets for OA.
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Affiliation(s)
- Yan Zhang
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Jingyu Xie
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Simin Wen
- Clinical Research Centre, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Peihua Cao
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Wende Xiao
- Department of orthopedics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Jianwei Zhu
- Department of orthopedics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Shengfa Li
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhiqiang Wang
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Han Cen
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhaohua Zhu
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Orthopedic Medical Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Changhai Ding
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Clinical Research Centre, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Guangfeng Ruan
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Clinical Research Centre, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
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Zilinskas R, Li C, Shen X, Pan W, Yang T. Inferring a directed acyclic graph of phenotypes from GWAS summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.528092. [PMID: 38045347 PMCID: PMC10690198 DOI: 10.1101/2023.02.10.528092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Estimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimer's disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available at https://github.com/chunlinli/sumdag.
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Affiliation(s)
| | - Chunlin Li
- Department of Statistics, Iowa State University, Ames, Iowa 50011, U.S.A
| | - Xiaotong Shen
- School of Statistics, University of Minnesota, Minneapolis, Minnesota 55455, U.S.A
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota 55455, U.S.A
| | - Tianzhong Yang
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota 55455, U.S.A
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Mälarstig A, Grassmann F, Dahl L, Dimitriou M, McLeod D, Gabrielson M, Smith-Byrne K, Thomas CE, Huang TH, Forsberg SKG, Eriksson P, Ulfstedt M, Johansson M, Sokolov AV, Schiöth HB, Hall P, Schwenk JM, Czene K, Hedman ÅK. Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation. Nat Commun 2023; 14:7680. [PMID: 37996402 PMCID: PMC10667261 DOI: 10.1038/s41467-023-43485-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023] Open
Abstract
Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source for biomarker discovery but so far, few proteins have been identified with breast cancer risk. Here, we measure 2929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project to explore the association between protein levels, clinical characteristics, and gene variants, and to identify proteins with a causal role in breast cancer. We present 812 cis-acting protein quantitative trait loci for 737 proteins which are used as instruments in Mendelian randomisation analyses of breast cancer risk. Of those, we present five proteins (CD160, DNPH1, LAYN, LRRC37A2 and TLR1) that show a potential causal role in breast cancer risk with confirmatory results in independent cohorts. Our study suggests that these proteins should be further explored as biomarkers and potential drug targets in breast cancer.
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Affiliation(s)
- Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
- Pfizer Worldwide Research Development and Medical, Stockholm, Sweden.
| | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Clinical Research and Systems Medicine, Health and Medical University, Potsdam, Germany
| | - Leo Dahl
- Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Marios Dimitriou
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pfizer Worldwide Research Development and Medical, Stockholm, Sweden
| | - Dianna McLeod
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cecilia E Thomas
- Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Tzu-Hsuan Huang
- Cancer Immunology Discovery, Pfizer Inc., San Diego, California, USA
| | | | | | | | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Aleksandr V Sokolov
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Helgi B Schiöth
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, Uppsala, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Jochen M Schwenk
- Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Åsa K Hedman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pfizer Worldwide Research Development and Medical, Stockholm, Sweden
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40
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Constantinescu AE, Bull CJ, Goudswaard LJ, Zheng J, Elsworth B, Timpson NJ, Moore SF, Hers I, Vincent EE. A phenome-wide approach to identify causal risk factors for deep vein thrombosis. BMC Med Genomics 2023; 16:284. [PMID: 37951941 PMCID: PMC10640748 DOI: 10.1186/s12920-023-01710-9] [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: 05/31/2023] [Accepted: 10/20/2023] [Indexed: 11/14/2023] Open
Abstract
Deep vein thrombosis (DVT) is the formation of a blood clot in a deep vein. DVT can lead to a venous thromboembolism (VTE), the combined term for DVT and pulmonary embolism, a leading cause of death and disability worldwide. Despite the prevalence and associated morbidity of DVT, the underlying causes are not well understood. Our aim was to leverage publicly available genetic summary association statistics to identify causal risk factors for DVT. We conducted a Mendelian randomization phenome-wide association study (MR-PheWAS) using genetic summary association statistics for 973 exposures and DVT (6,767 cases and 330,392 controls in UK Biobank). There was evidence for a causal effect of 57 exposures on DVT risk, including previously reported risk factors (e.g. body mass index-BMI and height) and novel risk factors (e.g. hyperthyroidism and varicose veins). As the majority of identified risk factors were adiposity-related, we explored the molecular link with DVT by undertaking a two-sample MR mediation analysis of BMI-associated circulating proteins on DVT risk. Our results indicate that circulating neurogenic locus notch homolog protein 1 (NOTCH1), inhibin beta C chain (INHBC) and plasminogen activator inhibitor 1 (PAI-1) influence DVT risk, with PAI-1 mediating the BMI-DVT relationship. Using a phenome-wide approach, we provide putative causal evidence that hyperthyroidism, varicose veins and BMI enhance the risk of DVT. Furthermore, the circulating protein PAI-1 has a causal role in DVT aetiology and is involved in mediating the BMI-DVT relationship.
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Affiliation(s)
- Andrei-Emil Constantinescu
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Health Data Research UK. Registered Office, 215 Euston Road, London, NW1 2BE, UK
| | - Lucy J Goudswaard
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Benjamin Elsworth
- Our Future Health Ltd. Registered office: 2 New Bailey, 6 Stanley Street, Manchester, M3 5GS, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Samantha F Moore
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
- UKRI Medical Research Council, Swindon, UK
| | - Ingeborg Hers
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- School of Translational Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
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Xue F, He Z, Zhuang DZ, Lin F. The influence of gut microbiota on circulating inflammatory cytokines and host: A Mendelian randomization study with meta-analysis. Life Sci 2023; 332:122105. [PMID: 37739166 DOI: 10.1016/j.lfs.2023.122105] [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: 07/28/2023] [Revised: 09/15/2023] [Accepted: 09/17/2023] [Indexed: 09/24/2023]
Abstract
AIMS The gut microbiota has been found to be altered in different inflammatory disorders, but its involvement in the regulation of inflammatory cytokines remains unclear. Therefore, this study aimed to investigate the impacts of gut microbiota on circulating inflammatory cytokines and their potential roles in host diseases. MAIN METHODS Two-sample Mendelian randomization (MR) analyses were conducted using summary-level data from genome-wide association studies (GWAS) to identify significant causal associations between 196 gut microbiota and 41 inflammatory cytokines. Meta-analysis was applied to test the robustness of the results. Enrichment analyses of identified cytokines were further utilized to infer the effects of gut microbiota on the host. KEY FINDINGS The MR analyses and meta-analyses identified the following significant causal associations: phylum Euryarchaeota on interleukin-2 (IL-2) (βIVW = 0.085, P = 1.5 × 10-2) and interleukin-8 (IL-8) (βIVW = 0.065, P = 4.1 × 10-2), phylum Tenericutes and class Mollicutes on macrophage inflammatory protein 1a (MIP1a) (βIVW = -0.142, P = 7.0 × 10-3), class Bacilli on hepatocyte growth factor (HGF) (βIVW = -0.106, P = 2.5 × 10-2), order Enterobacteriales on monocyte chemoattractant protein-1 (MCP1) (βIVW = 0.182, P = 1.8 × 10-2), and genus Lachnospiraceae NC2004 group on TNF-related apoptosis-inducing ligand (TRAIL) (βIVW = -0.207, P = 6.0 × 10-4). Enrichment analyses suggested that phylum Euryarchaeota and order Enterobacteriales might be risk factors for certain autoimmune diseases and neoplasms, while the phylum Tenericutes may have a protective effect. SIGNIFICANCE This study represents the first evidence confirming the causal effect of specific gut microbial taxa on circulating inflammatory cytokines and sheds light on their potential roles in the development and progression of various host diseases.
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Affiliation(s)
- Fan Xue
- Department of Gastrointestinal Surgery, Affiliated Zhongshan Hospital of Dalian University, Dalian 116001, Liaoning Province, China
| | - Zheng He
- Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
| | - De-Zheng Zhuang
- Department of Gastrointestinal Surgery, Affiliated Zhongshan Hospital of Dalian University, Dalian 116001, Liaoning Province, China
| | - Feng Lin
- Department of Gastrointestinal Surgery, Affiliated Zhongshan Hospital of Dalian University, Dalian 116001, Liaoning Province, China.
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42
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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43
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McBride N, Fernández-Sanlés A, Arab MA, Bond TA, Zheng J, Magnus MC, Corfield EC, Clayton GL, Hwang LD, Beaumont RN, Evans DM, Freathy RM, Gaunt TR, Lawlor DA, Borges MC. Effects of the maternal and fetal proteome on birth weight: a Mendelian randomization analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.20.23297135. [PMID: 37904919 PMCID: PMC10615012 DOI: 10.1101/2023.10.20.23297135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Fetal growth is an indicator of fetal survival, regulated by maternal and fetal factors, but little is known about the underlying molecular mechanisms. We used Mendelian randomization to explore the effects of maternal and fetal genetically-instrumented plasma proteins on birth weight using genome-wide association summary data (n=406,063 with maternal and/or fetal genotype), with independent replication (n=74,932 mothers and n=62,108 offspring), and colocalisation. Higher genetically-predicted maternal levels of PCSK1 increased birthweight (mean-difference: 9g (95% CI: 5g, 13g) per 1 standard deviation protein level). Higher maternal levels of LGALS4 decreased birthweight (-54g (-29g, -80g)), as did VCAM1, RAD51D and GP1BA. In the offspring, higher genetically-predicted fetal levels of LGALS4 (46g (23g, 70g)) increased birthweight, alongside FCGR2B. Higher offspring levels of PCSK1 decreased birth weight (-9g (-16g, 4g), alongside LEPR. Results support maternal and fetal protein effects on birth weight, implicating roles for glucose metabolism, energy homeostasis, endothelial function and adipocyte differentiation.
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44
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Eldjarn GH, Ferkingstad E, Lund SH, Helgason H, Magnusson OT, Gunnarsdottir K, Olafsdottir TA, Halldorsson BV, Olason PI, Zink F, Gudjonsson SA, Sveinbjornsson G, Magnusson MI, Helgason A, Oddsson A, Halldorsson GH, Magnusson MK, Saevarsdottir S, Eiriksdottir T, Masson G, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Thorleifsson G, Ulfarsson MO, Gudbjartsson DF, Thorsteinsdottir U, Sulem P, Stefansson K. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature 2023; 622:348-358. [PMID: 37794188 PMCID: PMC10567571 DOI: 10.1038/s41586-023-06563-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 08/22/2023] [Indexed: 10/06/2023]
Abstract
High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.
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Affiliation(s)
| | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannes Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | - Agnar Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Reykjavik, Iceland
| | | | - Pall Melsted
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Magnus O Ulfarsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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Zhang S, Zhang W, Sun H, Xue R, Lv Q. Therapeutic potential of single-nucleotide polymorphism-mediated interleukin-6 receptor blockade in cancer treatment: A Mendelian randomization study. Heliyon 2023; 9:e20474. [PMID: 37810867 PMCID: PMC10556766 DOI: 10.1016/j.heliyon.2023.e20474] [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: 03/24/2023] [Revised: 09/20/2023] [Accepted: 09/26/2023] [Indexed: 10/10/2023] Open
Abstract
Background Interleukin-6 (IL-6) is a crucial member of the cytokine network and plays a pivotal role in the pathogenesis of various diseases, including cancer. IL-6 receptor (IL-6R) blockade is widely employed as a therapeutic strategy; however, its efficacy in anticancer therapy remains ambiguous. Methods An inverse variance-weighted Mendelian randomization (MR) analysis was conducted to assess the causal effects exerted by IL-6R blockade in remediating cancer. Drug-targeted single-nucleotide polymorphisms (SNPs) were introduced within 300 kb of the IL-6R gene. An instrumental variable comprising 26 SNPs represented IL-6 signaling downregulation and C-reactive protein level reduction. Datasets pertaining to the 33 types of cancer investigated in this study were acquired from the FinnGen genome-wide association study. Results The selected instrumental variable lowered fibrinogen levels, confirming its ability to mimic IL-6R blockade. IL-6R blockade exhibited therapeutic effects on five different cancer types documented in the FinnGen database (N = 334,364, including 76,781 cancer patients): bladder (odds ratios (OR) = 0.563), laryngeal (OR = 0.293), eye (OR = 0.098), gallbladder (OR = 0.059), and myeloid leukemia (OR = 0.442); however, it simultaneously elevated the risk of developing basal cell carcinoma (OR = 1.312) and melanoma (OR = 1.311). Sensitivity analyses did not alter the primary results. Conclusion Therefore, this study aimed to evaluate the potential and efficacy of SNP-based IL-6R blockade in treating cancer.
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Affiliation(s)
- Shuwan Zhang
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
- Key Laboratory of Intelligent and Precision Pathology Diagnosis in Oncology, China Medical University, Shenyang 110004, Liaoning Province, China
| | - Wenchuan Zhang
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Hanxue Sun
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
| | - Rui Xue
- School of Medicine, Chongqing University, Chongqing 400044, China
| | - Qingjie Lv
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning Province, China
- Key Laboratory of Intelligent and Precision Pathology Diagnosis in Oncology, China Medical University, Shenyang 110004, Liaoning Province, China
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Ren F, Jin Q, Liu T, Ren X, Zhan Y. Proteome-wide mendelian randomization study implicates therapeutic targets in common cancers. J Transl Med 2023; 21:646. [PMID: 37735436 PMCID: PMC10512580 DOI: 10.1186/s12967-023-04525-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 09/13/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND The interest in targeted cancer therapies has been growing rapidly. While numerous cancer biomarkers and targeted treatment strategies have been developed and employed, there are still significant limitations and challenges in the early diagnosis and targeted treatment of cancers. Accordingly, there is an urgent need to identify novel targets and develop new targeted drugs. METHODS The study was conducted using combined cis-Mendelian randomization (cis-MR) and colocalization analysis. We analyzed data from 732 plasma proteins to identify potential drug targets associated with eight site-specific cancers. These findings were further validated using the UK Biobank dataset. Then, a protein-protein interaction network was also constructed to examine the interplay between the identified proteins and the targets of existing cancer medications. RESULTS This MR analysis revealed associations between five plasma proteins and prostate cancer, five with breast cancer, and three with lung cancer. Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. Our study indicatied that genetically predicted KDELC2 (OR: 0.89, 95% CI 0.86-0.93) and TNFRSF10B (OR: 0.74, 95% CI 0.65-0.83) are inversely associated with prostate cancer. Furthermore, we observed an inverse association between CPNE1 (OR: 0.96, 95% CI 0.94-0.98) and breast cancer, while PDIA3 (OR: 1.19, 95% CI 1.10-1.30) were found to be associated with the risk of breast cancer. In addition, we also propose that SPINT2 (OR: 1.05, 95% CI 1.03-1.06), GSTP1 (OR: 0.82, 95% CI 0.74-0.90), and CTSS (OR: 0.91, 95% CI 0.88-0.95) may serve as potential therapeutic targets in prostate cancer. Similarly, GDI2 (OR: 0.85, 95% CI 0.80-0.91), ISLR2 (OR: 0.87, 95% CI 0.82-0.93), and CTSF (OR: 1.14, 95% CI 1.08-1.21) could potentially be targets for breast cancer. Additionally, we identified SFTPB (OR: 0.93, 95% CI 0.91-0.95), ICAM5 (OR: 0.95, 95% CI 0.93-0.97), and FLRT3 (OR: 1.10, 95% CI 1.05-1.15) as potential targets for lung cancer. Notably, TNFRSF10B, GSTP1, and PDIA3 were found to interact with the target proteins of current medications used in prostate or breast cancer treatment. CONCLUSIONS This comprehensive analysis has highlighted thirteen plasma proteins with potential roles in three site-specific cancers. Continued research in this area may reveal their therapeutic potential, particularly KDELC2, TNFRSF10B, CPNE1, and PDIA3, paving the way for more effective cancer treatments.
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Affiliation(s)
- Feihong Ren
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Qiubai Jin
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Tongtong Liu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Xuelei Ren
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Yongli Zhan
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
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Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.10.555215. [PMID: 37745480 PMCID: PMC10515765 DOI: 10.1101/2023.09.10.555215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
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Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Erin Buth
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Antwerp, BE
| | | | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Lisa R. Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD, 21287, USA
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA, 90502, USA
| | - Braxton D. Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Joshua P. Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98101, USA
| | - Katherine A. Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Edwin K. Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kari North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rasika A. Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD, 21287, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Arnita F. Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Emelia J. Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, 01702, USA
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98105, USA
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Paul L. Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
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Fang X, Liu D, Zhao J, Li X, He T, Liu B. Using proteomics and metabolomics to identify therapeutic targets for senescence mediated cancer: genetic complementarity method. Front Endocrinol (Lausanne) 2023; 14:1255889. [PMID: 37745724 PMCID: PMC10514473 DOI: 10.3389/fendo.2023.1255889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/18/2023] [Indexed: 09/26/2023] Open
Abstract
Background Senescence have emerged as potential factors of lung cancer risk based on findings from many studies. However, the underlying pathogenesis of lung cancer caused by senescence is not clear. In this study, we try to explain the potential pathogenesis between senescence and lung cancer through proteomics and metabonomics. And try to find new potential therapeutic targets in lung cancer patients through network mendelian randomization (MR). Methods The genome-wide association data of this study was mainly obtained from a meta-analysis and the Transdisciplinary Research in Cancer of the Lung Consortium (TRICL), respectively.And in this study, we mainly used genetic complementarity methods to explore the susceptibility of aging to lung cancer. Additionally, a mediation analysis was performed to explore the potential mediating role of proteomics and metabonomics, using a network MR design. Results GNOVA analysis revealed a shared genetic structure between HannumAge and lung cancer with a significant genetic correlation estimated at 0.141 and 0.135, respectively. MR analysis showed a relationship between HannumAge and lung cancer, regardless of smoking status. Furthermore, genetically predicted HannumAge was consistently associated with the proteins C-type lectin domain family 4 member D (CLEC4D) and Retinoic acid receptor responder protein 1 (RARR-1), indicating their potential role as mediators in the causal pathway. Conclusion HannumAge acceleration may increase the risk of lung cancer, some of which may be mediated by CLEC4D and RARR-1, suggestion that CLEC4D and RARR-1 may serve as potential drug targets for the treatment of lung cancer.
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Affiliation(s)
- Xiaolu Fang
- Department of Clinical Laboratory, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Deyang Liu
- Department of Rehabilitation Medicine, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Jianzhong Zhao
- Department of Clinical Laboratory, Xiangyang No.1 People’s Hospital, Hubei University of Medicine, Xiangyang, China
| | - Xiaojia Li
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
| | - Ting He
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
| | - Baishan Liu
- Department of Respiratory, Jiulongpo District People’s Hospital of Chongqing, Chongqing, China
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Wu Y, Wang Z, Yang Y, Han C, Wang L, Kang K, Zhao A. Exploration of potential novel drug targets and biomarkers for small cell lung cancer by plasma proteome screening. Front Pharmacol 2023; 14:1266782. [PMID: 37745050 PMCID: PMC10511877 DOI: 10.3389/fphar.2023.1266782] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 08/28/2023] [Indexed: 09/26/2023] Open
Abstract
Background: Small cell lung cancer (SCLC) is characterized by extreme invasiveness and lethality. There have been very few developments in its diagnosis and treatment over the past decades. It is urgently needed to explore potential novel biomarkers and drug targets for SCLC. Methods: Two-sample Mendelian Randomization (MR) was performed to investigate causal associations between SCLC and plasma proteins using genome-wide association studies (GWAS) summary statistics of SCLC from Transdisciplinary Research Into Cancer of the Lung Consortium (nCase = 2,791 vs. nControl = 20,580), and was validated in another cohort (nCase = 2,664 vs. nControl = 21,444). 734 plasma proteins and their genetic instruments of cis-acting protein quantitative trait loci (pQTL) were used, whereas external plasma proteome data was retrieved from deCODE database. Bidirectional MR, Steiger filtering and phenotype scanning were applied to further verify the associations. Results: Seven significant (p < 6.81 × 10-5) plasma protein-SCLC pairs were identified by MR analysis, including ACP5 (OR = 0.76, 95% CI: 0.67-0.86), CPB2 (OR = 0.90, 95% CI: 0.86-0.95), GSTM3 (OR = 0.45, 95% CI: 0.33-0.63), SHMT1 (OR = 0.74, 95% CI: 0.64-0.86), CTSB (OR = 0.79, 95% CI: 0.71-0.88), NTNG1 (OR = 0.81, 95% CI: 0.74-0.90) and FAM171B (OR = 1.40, 95% CI: 1.21-1.62). The external validation confirmed that CPB2, GSTM3 and NTNG1 had protective effects against SCLC, while FAM171B increased SCLC risk. However, the reverse causality analysis revealed that SCLC caused significant changes in plasma levels of most of these proteins, including decreases of ACP5, CPB2, GSTM3 and NTNG1, and the increase of FAM171B. Conclusion: This integrative analysis firstly suggested the causal associations between SCLC and plasma proteins, and the identified several proteins may be promising novel drug targets or biomarkers for SCLC.
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Affiliation(s)
- Yijun Wu
- Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Zhile Wang
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yuqi Yang
- West China School of Medicine, Sichuan University, Chengdu, Sichuan, China
| | - Chang Han
- Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Li Wang
- Department of Hematology, West China Hospital, Sichuan University, Chengdu, China
| | - Kai Kang
- Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ailin Zhao
- Department of Hematology, West China Hospital, Sichuan University, Chengdu, China
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50
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Benson MD, Eisman AS, Tahir UA, Katz DH, Deng S, Ngo D, Robbins JM, Hofmann A, Shi X, Zheng S, Keyes M, Yu Z, Gao Y, Farrell L, Shen D, Chen ZZ, Cruz DE, Sims M, Correa A, Tracy RP, Durda P, Taylor KD, Liu Y, Johnson WC, Guo X, Yao J, Chen YDI, Manichaikul AW, Jain D, Yang Q, Bouchard C, Sarzynski MA, Rich SS, Rotter JI, Wang TJ, Wilson JG, Clish CB, Sarkar IN, Natarajan P, Gerszten RE. Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma. Cell Metab 2023; 35:1646-1660.e3. [PMID: 37582364 PMCID: PMC11118091 DOI: 10.1016/j.cmet.2023.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 04/12/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023]
Abstract
Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.
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Affiliation(s)
- Mark D Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Aaron S Eisman
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Center for Biomedical Informatics, Brown University, Providence, RI, USA
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel H Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Debby Ngo
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Alissa Hofmann
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Xu Shi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Shuning Zheng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michelle Keyes
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Zhi Yu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Yan Gao
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Laurie Farrell
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Zsu-Zsu Chen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel E Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mario Sims
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Adolfo Correa
- University of Mississippi Medical Center, Jackson, MS, USA
| | - Russell P Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Peter Durda
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA; Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | | | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Claude Bouchard
- Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Mark A Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, Columbia, SC, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Thomas J Wang
- Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - James G Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Clary B Clish
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Indra Neil Sarkar
- Center for Biomedical Informatics, Brown University, Providence, RI, USA
| | - Pradeep Natarajan
- Broad Institute of Harvard and MIT, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine Harvard Medical School, Boston, MA, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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