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Zhang J, He J, Liao Y, Xia X, Yang F. Genetic association between gut microbiome and blood pressure and blood cell count as mediator: A two-step Mendelian randomization analysis. Gene 2024; 925:148573. [PMID: 38762013 DOI: 10.1016/j.gene.2024.148573] [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: 01/25/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Previous studies have established a genetic link between gut microbiota and hypertension, but whether blood cell count plays a mediating role in this remains unknown. This study aims to explore genetic associations and causal factors involving the gut microbiome, peripheral blood cell count, and blood pressure. METHODS We utilized summary statistics derived from genome-wide association studies to conduct a two-sample mediation Mendelian randomization analysis (https://gwas.mrcieu.ac.uk/). We applied inverse variance weighted (IVW) estimation method as the primary method, along with MR Egger, Weighted median, Simple mode and Weighted mode as complementary methods. To ensure the robustness of the results, several sensitivity analyses were conducted. RESULTS Genetic variants significantly associated with the microbiome, blood pressure, or peripheral blood cell counts were selected as instrumental variables. Fourteen microbial taxa were found to have suggestive associations with diastolic blood pressure (DBP), while fifteen microbial taxa showed suggestive associations with systolic blood pressure (SBP). Meanwhile, red blood cell count, lymphocyte count, and platelet count were identified to mediate the influence of the gut microbiome on blood pressure. Specifically, red cell count was identified to mediate the effects of the phylum Cyanobacteria on DBP (mediated proportion: 8.262 %). Lymphocyte count was found mediate the effects of the genus Subdoligranulum (mediated proportion: 2.642 %) and genus Collinsella (mediated proportion: 2.749 %) on SBP. Additionally, platelet count was found to mediate the relationship between the genus Eubacterium ventriosum group and SBP, explaining 3.421 % of the mediated proportion. CONCLUSIONS Our findings highlighted that gut microbiota may have causal influence on the blood pressure by modulating blood cell counts, which sheds new light on the pathogenesis and potential clinical interventions through the intricate axis of gut microbiome, blood cell counts, and blood pressure.
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Affiliation(s)
- Jiyu Zhang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Junyi He
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China.
| | - Yuhan Liao
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Xinyi Xia
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Fen Yang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China.
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2
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Foyzun T, Whiting M, Velasco KK, Jacobsen JC, Connor M, Grimsey NL. Single nucleotide polymorphisms in the cannabinoid CB 2 receptor: Molecular pharmacology and disease associations. Br J Pharmacol 2024; 181:2391-2412. [PMID: 38802979 DOI: 10.1111/bph.16383] [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: 11/30/2023] [Revised: 02/26/2024] [Accepted: 03/09/2024] [Indexed: 05/29/2024] Open
Abstract
Preclinical evidence implicating cannabinoid receptor 2 (CB2) in various diseases has led researchers to question whether CB2 genetics influence aetiology or progression. Associations between conditions and genetic loci are often studied via single nucleotide polymorphism (SNP) prevalence in case versus control populations. In the CNR2 coding exon, ~36 SNPs have high overall population prevalence (minor allele frequencies [MAF] ~37%), including non-synonymous SNP (ns-SNP) rs2501432 encoding CB2 63Q/R. Interspersed are ~27 lower frequency SNPs, four being ns-SNPs. CNR2 introns also harbour numerous SNPs. This review summarises CB2 ns-SNP molecular pharmacology and evaluates evidence from ~70 studies investigating CB2 genetic variants with proposed linkage to disease. Although CNR2 genetic variation has been associated with a wide variety of conditions, including osteoporosis, immune-related disorders, and mental illnesses, further work is required to robustly validate CNR2 disease links and clarify specific mechanisms linking CNR2 genetic variation to disease pathophysiology and potential drug responses.
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Affiliation(s)
- Tahira Foyzun
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Maddie Whiting
- Department of Pharmacology and Clinical Pharmacology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Department of Medicine, School of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Kate K Velasco
- Department of Pharmacology and Clinical Pharmacology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Department of Medicine, School of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Jessie C Jacobsen
- School of Biological Sciences, Faculty of Science, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Mark Connor
- Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Natasha L Grimsey
- Department of Pharmacology and Clinical Pharmacology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, New Zealand
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3
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Zheng S, Tsao PS, Pan C. Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation. Nat Commun 2024; 15:5652. [PMID: 38969659 DOI: 10.1038/s41467-024-49921-7] [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: 12/05/2023] [Accepted: 06/25/2024] [Indexed: 07/07/2024] Open
Abstract
Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.
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Affiliation(s)
- Shufen Zheng
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Guangzhou, China
- Center for Evolutionary Biology, Intelligent Medicine Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Philip S Tsao
- Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.
- Stanford Cardiovascular Institute, Stanford University, California, USA.
- VA Palo Alto Health Care System, Palo Alto, California, USA.
| | - Cuiping Pan
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Guangzhou, China.
- Center for Evolutionary Biology, Intelligent Medicine Institute, School of Life Sciences, Fudan University, Shanghai, China.
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4
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Monistrol-Mula A, Diaz-Torres S, Felez-Nobrega M, Haro JM, Medland SE, Mitchell BL. Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19. Mol Psychiatry 2024:10.1038/s41380-024-02643-0. [PMID: 38956374 DOI: 10.1038/s41380-024-02643-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 07/04/2024]
Abstract
Current literature suggests that people with psychiatric disorders have a higher risk of COVID-19 infection and a worse prognosis of the disease. We aimed to study the genetic contribution to these associations across seven psychiatric disorders as well as a general psychopathology factor (P-factor) and determine whether these are unique or shared across psychiatric disorders using statistical genetic techniques. Using the largest available genome-wide association studies (GWAS), we found a significant genetic overlap between depression, ADHD, PTSD, and the P-factor with both COVID-19 infection and hospitalization, and between anxiety and COVID-19 hospitalization. We used pairwise GWAS to examine this overlap on a fine-grained scale and identified specific regions of the genome shared between several psychiatric disorders, the P-factor, and COVID-19. Gene-based analysis in these genomic regions suggested possible links with immune-related pathways such as thyroid homeostasis, inflammation, and stress response. Finally, we show preliminary evidence for causal associations between depression, ADHD, PTSD, and the P-factor, and higher COVID-19 infection and hospitalization using Mendelian Randomization and Latent Causal Variable methods. Our results support the hypothesis that the relationship between psychiatric disorders and COVID-19 risk is likely due to shared alterations in immune-related pathways and is not a result of environmental factors alone, shedding light on potentially viable therapeutic targets.
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Affiliation(s)
- Anna Monistrol-Mula
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
- Department of Medicine, University of Barcelona, Barcelona, Spain.
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
| | - Santiago Diaz-Torres
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mireia Felez-Nobrega
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Josep Maria Haro
- Group of Epidemiology of Psychiatric disorders and Ageing, Sant Joan de Déu Research Institute, Sant Boi de Llobregat, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Sarah E Medland
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, University of Queensland, Brisbane, QLD, Australia
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5
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Murphy MB, Yang Z, Subati T, Farber-Eger E, Kim K, Blackwell DJ, Fleming MR, Stark JM, Van Amburg JC, Woodall KK, Van Beusecum JP, Agrawal V, Smart CD, Pitzer A, Atkinson JB, Fogo AB, Bastarache JA, Kirabo A, Wells QS, Madhur MS, Barnett JV, Murray KT. LNK/SH2B3 loss of function increases susceptibility to murine and human atrial fibrillation. Cardiovasc Res 2024; 120:899-913. [PMID: 38377486 PMCID: PMC11218690 DOI: 10.1093/cvr/cvae036] [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: 04/28/2023] [Revised: 08/31/2023] [Accepted: 10/07/2023] [Indexed: 02/22/2024] Open
Abstract
AIMS The lymphocyte adaptor protein (LNK) is a negative regulator of cytokine and growth factor signalling. The rs3184504 variant in SH2B3 reduces LNK function and is linked to cardiovascular, inflammatory, and haematologic disorders, including stroke. In mice, deletion of Lnk causes inflammation and oxidative stress. We hypothesized that Lnk-/- mice are susceptible to atrial fibrillation (AF) and that rs3184504 is associated with AF and AF-related stroke in humans. During inflammation, reactive lipid dicarbonyls are the major components of oxidative injury, and we further hypothesized that these mediators are critical drivers of the AF substrate in Lnk-/- mice. METHODS AND RESULTS Lnk-/- or wild-type (WT) mice were treated with vehicle or 2-hydroxybenzylamine (2-HOBA), a dicarbonyl scavenger, for 3 months. Compared with WT, Lnk-/- mice displayed increased AF duration that was prevented by 2-HOBA. In the Lnk-/- atria, action potentials were prolonged with reduced transient outward K+ current, increased late Na+ current, and reduced peak Na+ current, pro-arrhythmic effects that were inhibited by 2-HOBA. Mitochondrial dysfunction, especially for Complex I, was evident in Lnk-/- atria, while scavenging lipid dicarbonyls prevented this abnormality. Tumour necrosis factor-α (TNF-α) and interleukin-1 beta (IL-1β) were elevated in Lnk-/- plasma and atrial tissue, respectively, both of which caused electrical and bioenergetic remodelling in vitro. Inhibition of soluble TNF-α prevented electrical remodelling and AF susceptibility, while IL-1β inhibition improved mitochondrial respiration but had no effect on AF susceptibility. In a large database of genotyped patients, rs3184504 was associated with AF, as well as AF-related stroke. CONCLUSION These findings identify a novel role for LNK in the pathophysiology of AF in both experimental mice and humans. Moreover, reactive lipid dicarbonyls are critical to the inflammatory AF substrate in Lnk-/- mice and mediate the pro-arrhythmic effects of pro-inflammatory cytokines, primarily through electrical remodelling.
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MESH Headings
- Animals
- Atrial Fibrillation/metabolism
- Atrial Fibrillation/physiopathology
- Atrial Fibrillation/genetics
- Mice, Knockout
- Humans
- Disease Models, Animal
- Action Potentials/drug effects
- Adaptor Proteins, Signal Transducing/genetics
- Adaptor Proteins, Signal Transducing/metabolism
- Mice, Inbred C57BL
- Male
- Myocytes, Cardiac/metabolism
- Myocytes, Cardiac/drug effects
- Myocytes, Cardiac/pathology
- Interleukin-1beta/metabolism
- Interleukin-1beta/genetics
- Oxidative Stress/drug effects
- Mitochondria, Heart/metabolism
- Mitochondria, Heart/pathology
- Mitochondria, Heart/drug effects
- Genetic Predisposition to Disease
- Benzylamines/pharmacology
- Heart Rate/drug effects
- Tumor Necrosis Factor-alpha/metabolism
- Tumor Necrosis Factor-alpha/genetics
- Inflammation Mediators/metabolism
- Signal Transduction
- Female
- Intracellular Signaling Peptides and Proteins/genetics
- Intracellular Signaling Peptides and Proteins/metabolism
- Phenotype
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Affiliation(s)
- Matthew B Murphy
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Zhenjiang Yang
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Tuerdi Subati
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Eric Farber-Eger
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Kyungsoo Kim
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Daniel J Blackwell
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Matthew R Fleming
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Joshua M Stark
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Joseph C Van Amburg
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Kaylen K Woodall
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Justin P Van Beusecum
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Vineet Agrawal
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Charles D Smart
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Ashley Pitzer
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - James B Atkinson
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, 1161 21 Avenue South, Nashville, TN 37232, USA
| | - Agnes B Fogo
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, 1161 21 Avenue South, Nashville, TN 37232, USA
| | - Julie A Bastarache
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
| | - Annet Kirabo
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Quinn S Wells
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, USA
| | - Meena S Madhur
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Joey V Barnett
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
| | - Katherine T Murray
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, 559 PRB, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University School of Medicine, 2220 Pierce Avenue, Nashville, TN 37232, USA
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6
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Tuo S, Jiang J. A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search. Interdiscip Sci 2024:10.1007/s12539-024-00621-2. [PMID: 38954231 DOI: 10.1007/s12539-024-00621-2] [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: 08/06/2023] [Revised: 02/06/2024] [Accepted: 02/17/2024] [Indexed: 07/04/2024]
Abstract
To elucidate the genetic basis of complex diseases, it is crucial to discover the single-nucleotide polymorphisms (SNPs) contributing to disease susceptibility. This is particularly challenging for high-order SNP epistatic interactions (HEIs), which exhibit small individual effects but potentially large joint effects. These interactions are difficult to detect due to the vast search space, encompassing billions of possible combinations, and the computational complexity of evaluating them. This study proposes a novel explicit-encoding-based multitasking harmony search algorithm (MTHS-EE-DHEI) specifically designed to address this challenge. The algorithm operates in three stages. First, a harmony search algorithm is employed, utilizing four lightweight evaluation functions, such as Bayesian network and entropy, to efficiently explore potential SNP combinations related to disease status. Second, a G-test statistical method is applied to filter out insignificant SNP combinations. Finally, two machine learning-based methods, multifactor dimensionality reduction (MDR) as well as random forest (RF), are employed to validate the classification performance of the remaining significant SNP combinations. This research aims to demonstrate the effectiveness of MTHS-EE-DHEI in identifying HEIs compared to existing methods, potentially providing valuable insights into the genetic architecture of complex diseases. The performance of MTHS-EE-DHEI was evaluated on twenty simulated disease datasets and three real-world datasets encompassing age-related macular degeneration (AMD), rheumatoid arthritis (RA), and breast cancer (BC). The results demonstrably indicate that MTHS-EE-DHEI outperforms four state-of-the-art algorithms in terms of both detection power and computational efficiency. The source code is available at https://github.com/shouhengtuo/MTHS-EE-DHEI.git .
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Affiliation(s)
- Shouheng Tuo
- School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, 710121, China.
- Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi'an, 710121, China.
- Xi'an Key Laboratory of Big Data and Intelligent Computing, Xi'an, 710121, China.
| | - Jiewei Jiang
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, 710121, China
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7
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Sun Z, Pan L, Tian A, Chen P. Critically-ill COVID-19 susceptibility gene CCR3 shows natural selection in sub-Saharan Africans. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 121:105594. [PMID: 38636619 DOI: 10.1016/j.meegid.2024.105594] [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: 01/15/2024] [Revised: 03/28/2024] [Accepted: 04/15/2024] [Indexed: 04/20/2024]
Abstract
The prevalence of COVID-19 critical illness varies across ethnicities, with recent studies suggesting that genetic factors may contribute to this variation. The aim of this study was to investigate natural selection signals of genes associated with critically-ill COVID-19 in sub-Saharan Africans. Severe COVID-19 SNPs were obtained from the HGI website. Selection signals were assessed in 661 sub-Sahara Africans from 1000 Genomes Project using integrated haplotype score (iHS), cross-population extended haplotype homozygosity (XP-EHH), and fixation index (Fst). Allele frequency trajectory analysis of ancient DNA samples were used to validate the existing of selection in sub-Sahara Africans. We also used Mendelian randomization to decipher the correlation between natural selection and critically-ill COVID-19. We identified that CCR3 exhibited significant natural selection signals in sub-Sahara Africans. Within the CCR3 gene, rs17217831-A showed both high iHS (Standardized iHS = 2) and high XP-EHH (Standardized XP-EHH = 2.5) in sub-Sahara Africans. Allele frequency trajectory of CCR3 rs17217831-A revealed natural selection occurring in the recent 1,500 years. Natural selection resulted in increased CCR3 expression in sub-Sahara Africans. Mendelian Randomization provided evidence that increased blood CCR3 expression and eosinophil counts lowered the risk of critically ill COVID-19. Our findings suggest that sub-Saharan Africans are resistant to critically ill COVID-19 due to natural selection and identify CCR3 as a potential novel therapeutic target.
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Affiliation(s)
- Zewen Sun
- Department of Genetics, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China
| | - Lin Pan
- Department of Genetics, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China; The First Hospital of Jilin University, Changchun, Jilin 130021, China
| | - Aowen Tian
- Department of Pathology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China; Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Peng Chen
- Department of Genetics, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China; Department of Pathology, College of Basic Medical Sciences, Jilin University, Changchun, Jilin, China; Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, Jilin, China.
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8
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Liu A, Genovese G, Zhao Y, Pirinen M, Zekavat SM, Kentistou KA, Yang Z, Yu K, Vlasschaert C, Liu X, Brown DW, Hudjashov G, Gorman BR, Dennis J, Zhou W, Momozawa Y, Pyarajan S, Tuzov V, Pajuste FD, Aavikko M, Sipilä TP, Ghazal A, Huang WY, Freedman ND, Song L, Gardner EJ, Sankaran VG, Palotie A, Ollila HM, Tukiainen T, Chanock SJ, Mägi R, Natarajan P, Daly MJ, Bick A, McCarroll SA, Terao C, Loh PR, Ganna A, Perry JRB, Machiela MJ. Genetic drivers and cellular selection of female mosaic X chromosome loss. Nature 2024; 631:134-141. [PMID: 38867047 DOI: 10.1038/s41586-024-07533-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 05/07/2024] [Indexed: 06/14/2024]
Abstract
Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.
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Affiliation(s)
- Aoxing Liu
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
| | - Yajie Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Seyedeh M Zekavat
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Katherine A Kentistou
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Zhiyu Yang
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Derek W Brown
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
- Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, Rockville, MD, USA
| | - Georgi Hudjashov
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Bryan R Gorman
- Center for Data and Computational Sciences (C-DACS), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Weiyin Zhou
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Valdislav Tuzov
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fanny-Dhelia Pajuste
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Mervi Aavikko
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Timo P Sipilä
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Awaisa Ghazal
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Lei Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Eugene J Gardner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Vijay G Sankaran
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hanna M Ollila
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pradeep Natarajan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alexander Bick
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Po-Ru Loh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Andrea Ganna
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - John R B Perry
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
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9
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Xiong J, Xu Y, Wang N, Wang S, Zhang Y, Lu S, Zhang X, Liang X, Liu C, Jiang Q, Xu J, Qian Q, Zhou P, Yin L, Liu F, Chen S, Yin S, Liu J. Obstructive Sleep Apnea Syndrome Exacerbates NASH Progression via Selective Autophagy-Mediated Eepd1 Degradation. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2405955. [PMID: 38924647 DOI: 10.1002/advs.202405955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Indexed: 06/28/2024]
Abstract
Obstructive sleep apnea syndrome (OSAS), characterized by chronic intermittent hypoxia (CIH), is an independent risk factor for aggravating non-alcoholic steatohepatitis (NASH). The prevailing mouse model employed in CIH research is inadequate for the comprehensive exploration of the impact of CIH on NASH development due to reduced food intake observed in CIH-exposed mice, which deviates from human responses. To address this issue, a pair-feeding investigation with CIH-exposed and normoxia-exposed mice is conducted. It is revealed that CIH exposure aggravates DNA damage, leading to hepatic fibrosis and inflammation. The analysis of genome-wide association study (GWAS) data also discloses the association between Eepd1, a DNA repair enzyme, and OSAS. Furthermore, it is revealed that CIH triggered selective autophagy, leading to the autophagic degradation of Eepd1, thereby exacerbating DNA damage in hepatocytes. Notably, Eepd1 liver-specific knockout mice exhibit aggravated hepatic DNA damage and further progression of NASH. To identify a therapeutic approach for CIH-induced NASH, a drug screening is conducted and it is found that Retigabine dihydrochloride suppresses CIH-mediated Eepd1 degradation, leading to alleviated DNA damage in hepatocytes. These findings imply that targeting CIH-mediated Eepd1 degradation can be an adjunctive approach in the treatment of NASH exacerbated by OSAS.
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Affiliation(s)
- Jie Xiong
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Ying Xu
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Ning Wang
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Shengming Wang
- Department of Otolaryngology Head and Neck Surgery & Shanghai, Key Laboratory of Sleep Disordered Breathing & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Yao Zhang
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Sijia Lu
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Xiaoman Zhang
- Department of Otolaryngology Head and Neck Surgery & Shanghai, Key Laboratory of Sleep Disordered Breathing & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | | | - Chuchu Liu
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Quanxin Jiang
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Junting Xu
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Qiqi Qian
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Peihui Zhou
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Limin Yin
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Feng Liu
- Department of Otolaryngology Head and Neck Surgery & Shanghai, Key Laboratory of Sleep Disordered Breathing & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Suzhen Chen
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Shankai Yin
- Department of Otolaryngology Head and Neck Surgery & Shanghai, Key Laboratory of Sleep Disordered Breathing & Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Junli Liu
- Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
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10
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Singh M, Dolan CV, Lapato DM, Hottenga JJ, Pool R, Verhulst B, Boomsma DI, Breeze CE, de Geus EJC, Hemani G, Min JL, Peterson RE, Maes HHM, van Dongen J, Neale MC. Twin-based Mendelian Randomization Analyses Highlight Smoking's Effects on Blood DNA Methylation, with Putative Reverse Causation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.19.24309184. [PMID: 38946972 PMCID: PMC11213072 DOI: 10.1101/2024.06.19.24309184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Epigenome-wide association studies (EWAS) aim to identify differentially methylated loci associated with complex traits and disorders. EWAS of cigarette smoking shows some of the most widespread DNA methylation (DNAm) associations in blood. However, traditional EWAS cannot differentiate between causation and confounding, leading to ambiguity in etiological interpretations. Here, we apply an integrated approach combining Mendelian Randomization and twin-based Direction-of-Causation analyses (MR-DoC) to examine causality underlying smoking-associated blood DNAm changes in the Netherlands Twin Register (N=2577). Evidence across models suggests that current smoking's causal effects on DNAm likely drive many of the previous EWAS findings, implicating functional pathways relevant to several adverse health outcomes of smoking, including hemopoiesis, cell- and neuro-development, and immune regulation. Additionally, we find evidence of potential reverse causal influences at some DNAm sites, with 17 of these sites enriched for gene regulatory functional elements in the brain. The top three sites with evidence of DNAm's effects on smoking annotate to genes involved in G protein-coupled receptor signaling (GNG7, RGS3) and innate immune response (SLC15A4), elucidating potential biological risk factors for smoking. This study highlights the utility of integrating genotypic and DNAm measures in twin cohorts to clarify the causal relationships between health behaviors and blood DNAm.
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Affiliation(s)
- Madhurbain Singh
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
| | - Conor V. Dolan
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Dana M. Lapato
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University, College Station, TX, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Current address: Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
| | - Charles E. Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department Health and Human Services, Bethesda, MD, USA
- UCL Cancer Institute, University College London, London, UK
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Josine L. Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Roseann E. Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Hermine H. M. Maes
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- These authors jointly supervised this work
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Biological Psychology, Vrije Universiteit (VU) Amsterdam, Amsterdam, The Netherlands
- These authors jointly supervised this work
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11
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Seufert AL, Struthers H, Caplan L, Napier RJ. CARD9 in the pathogenesis of axial spondyloarthritis. Best Pract Res Clin Rheumatol 2024:101964. [PMID: 38897880 DOI: 10.1016/j.berh.2024.101964] [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: 06/04/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/21/2024]
Abstract
Axial spondyloarthritis (axSpA) has been long classified as an autoimmune disease caused by a breakdown in the ability of the immune system to delineate self from foreign, resulting in self-reactive T cells. The strong genetic association of HLA-B27 supports this role for T cells. More recently, genetic and clinical studies indicate a prominent role of the environment in triggering axSpA, including an important role for microbes and the innate immune response. As an example, mutations in genes associated with innate immunity, including the anti-fungal signaling molecule Caspase recruitment domain-containing protein 9 (CARD9), have been linked to axSpA susceptibility. Thus, current thought classifies axSpA as a "mixed pattern condition" caused by both autoimmune and autoinflammatory mechanisms. The goal of this review is to convey.
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Affiliation(s)
- A L Seufert
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA.
| | - H Struthers
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA.
| | - L Caplan
- Rocky Mountain Regional VA Medical Center, Aurora, CO, 80045, USA.
| | - R J Napier
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA; Division of Arthritis and Rheumatic Diseases, Oregon Health & Science University, USA; VA Portland Health Care System, Portland, OR, 97239, USA.
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12
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Zou Y, Carbonetto P, Xie D, Wang G, Stephens M. Fast and flexible joint fine-mapping of multiple traits via the Sum of Single Effects model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.04.14.536893. [PMID: 37425935 PMCID: PMC10327118 DOI: 10.1101/2023.04.14.536893] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
We introduce mvSuSiE, a multi-trait fine-mapping method for identifying putative causal variants from genetic association data (individual-level or summary data). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal SNPs. Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multi-trait methods, and uniformly improves on single-trait fine-mapping (SuSiE) in each trait separately. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing the traits and modeling heterogeneous effect sharing patterns, we discovered a much larger number of causal SNPs (>3,000) compared with single-trait fine-mapping, and with narrower credible sets. mvSuSiE also more comprehensively characterized the ways in which the genetic variants affect one or more blood cell traits; 68% of causal SNPs showed significant effects in more than one blood cell type.
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Affiliation(s)
- Yuxin Zou
- Department of Statistics, University of Chicago, Chicago, IL, USA
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - Peter Carbonetto
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Dongyue Xie
- Department of Statistics, University of Chicago, Chicago, IL, USA
| | - Gao Wang
- Gertrude. H. Sergievsky Center, Department of Neurology, Columbia University, New York, NY, USA
| | - Matthew Stephens
- Department of Statistics, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
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13
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Stefanucci L, Moslemi C, Tomé AR, Virtue S, Bidault G, Gleadall NS, Watson LPE, Kwa JE, Burden F, Farrow S, Chen J, Võsa U, Burling K, Walker L, Ord J, Barker P, Warner J, Frary A, Renhstrom K, Ashford SE, Piper J, Biggs G, Erber WN, Hoffman GJ, Schoenmakers N, Erikstrup C, Rieneck K, Dziegiel MH, Ullum H, Azzu V, Vacca M, Aparicio HJ, Hui Q, Cho K, Sun YV, Wilson PW, Bayraktar OA, Vidal-Puig A, Ostrowski SR, Astle WJ, Olsson ML, Storry JR, Pedersen OB, Ouwehand WH, Chatterjee K, Vuckovic D, Frontini M. SMIM1 absence is associated with reduced energy expenditure and excess weight. MED 2024:S2666-6340(24)00219-8. [PMID: 38906141 DOI: 10.1016/j.medj.2024.05.015] [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: 08/07/2023] [Revised: 12/06/2023] [Accepted: 05/29/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments. METHODS We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan. FINDINGS We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure. CONCLUSION This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them. FUNDING This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant.
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Affiliation(s)
- Luca Stefanucci
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Camous Moslemi
- Department of Clinical Immunology, Zealand University Hospital (Roskilde University), Køge, Denmark
| | - Ana R Tomé
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Samuel Virtue
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Guillaume Bidault
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, MDU MRC, Addenbrooke's Hospital, Cambridge, UK
| | - Nicholas S Gleadall
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Laura P E Watson
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Jing E Kwa
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Frances Burden
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Samantha Farrow
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Ji Chen
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Faculty of Health and Life Sciences RILD Building, Barrack Road, Exeter, UK
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Keith Burling
- NIHR Cambridge Biomedical Research Centre Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lindsay Walker
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - John Ord
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Peter Barker
- NIHR Cambridge Biomedical Research Centre Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - James Warner
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Amy Frary
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Karola Renhstrom
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Sofie E Ashford
- NIHR National BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Jo Piper
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Gail Biggs
- NIHR Cambridge Clinical Research Facility, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Wendy N Erber
- Discipline of Pathology and Laboratory Science, School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
| | - Gary J Hoffman
- Discipline of Pathology and Laboratory Medicine, Medical School, The University of Western Australia, Perth, WA, Australia
| | - Nadia Schoenmakers
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus University, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Klaus Rieneck
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Morten H Dziegiel
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | | | - Vian Azzu
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK; Department of Gastroenterology, Norfolk & Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Michele Vacca
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK; Interdisciplinary Department of Medicine, Università degli Studi di Bari "Aldo Moro", Bari, Italy; Roger Williams Institute of Hepatology, London, UK
| | | | - Qin Hui
- Atlanta VA Medical Center, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA; Emory University Schools of Medicine and Public Health, Atlanta, GA, USA
| | - Omer A Bayraktar
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Antonio Vidal-Puig
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, MDU MRC, Addenbrooke's Hospital, Cambridge, UK; Centro de Innvestigacion Principe Felipe, Valencia, Spain
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - William J Astle
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; MRC Biostatistics Unit, East Forvie Building, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Martin L Olsson
- Clinical Immunology and Transfusion Medicine, Office for Medical Services, Region Skåne, Lund, Sweden; Department of Laboratory Medicine, Division of Hematology and Transfusion Medicine, Lund University, Lund, Sweden
| | - Jill R Storry
- Clinical Immunology and Transfusion Medicine, Office for Medical Services, Region Skåne, Lund, Sweden; Department of Laboratory Medicine, Division of Hematology and Transfusion Medicine, Lund University, Lund, Sweden
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital (Roskilde University), Køge, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Willem H Ouwehand
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; Department of Haematology, Cambridge University Hospitals NHS Trust, CB2 0QQ Cambridge, UK; Department of Haematology, University College London Hospitals NHS Trust, NW1 2BU London, UK
| | - Krishna Chatterjee
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Dragana Vuckovic
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK; British Heart Foundation, Cambridge Centre for Research Excellence, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Faculty of Health and Life Sciences RILD Building, Barrack Road, Exeter, UK.
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14
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Rodriguez-Algarra F, Evans DM, Rakyan VK. Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank. CELL GENOMICS 2024; 4:100562. [PMID: 38749448 DOI: 10.1016/j.xgen.2024.100562] [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: 08/09/2023] [Revised: 11/19/2023] [Accepted: 04/21/2024] [Indexed: 06/15/2024]
Abstract
The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.
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Affiliation(s)
| | - David M Evans
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia; Frazer Institute, The University of Queensland, Brisbane, QLD 4102, Australia; MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Vardhman K Rakyan
- The Blizard Institute, School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK.
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15
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Gelernter J, Levey DF, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Gaziano JM, Eliott D, Stein MB. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. CELL GENOMICS 2024; 4:100582. [PMID: 38870908 DOI: 10.1016/j.xgen.2024.100582] [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: 09/05/2023] [Revised: 02/20/2024] [Accepted: 05/10/2024] [Indexed: 06/15/2024]
Abstract
Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.
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Affiliation(s)
- Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA; Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, USA.
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Priya Gupta
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dean Eliott
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Murray B Stein
- University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
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16
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Jiang C, Lin J, Xie B, Peng M, Dai Z, Mai S, Chen Q. Causal association between circulating blood cell traits and pulmonary embolism: a mendelian randomization study. Thromb J 2024; 22:49. [PMID: 38863024 PMCID: PMC11167760 DOI: 10.1186/s12959-024-00618-3] [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: 03/20/2024] [Accepted: 05/31/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Pulmonary embolism (PE) is a life-threatening thromboembolic disease for which there is limited evidence for effective prevention and treatment. Our goal was to determine whether genetically predicted circulating blood cell traits could influence the incidence of PE. METHODS Using single variable Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) analyses, we identified genetic associations between circulating blood cell counts and lymphocyte subsets and PE. GWAS blood cell characterization summary statistics were compiled from the Blood Cell Consortium. The lymphocyte subpopulation counts were extracted from summary GWAS statistics for samples from 3757 individuals that had been analyzed by flow cytometry. GWAS data related to PE were obtained from the FinnGen study. RESULTS According to the SVMR and reverse MR, increased levels of circulating white blood cells (odds ratio [OR]: 0.88, 95% confidence interval [CI]: 0.81-0.95, p = 0.0079), lymphocytes (OR: 0.90, 95% CI: 0.84-0.97, p = 0.0115), and neutrophils (OR: 0.88, 95% CI: 0.81-0.96, p = 0.0108) were causally associated with PE susceptibility. MVMR analysis revealed that lower circulating lymphocyte counts (OR: 0.84, 95% CI: 0.75-0.94, p = 0.0139) were an independent predictor of PE. According to further MR results, this association may be primarily related to HLA-DR+ natural killer (NK) cells. CONCLUSIONS Among European populations, there is a causal association between genetically predicted low circulating lymphocyte counts, particularly low HLA-DR+ NK cells, and an increased risk of PE. This finding supports observational studies that link peripheral blood cells to PE and provides recommendations for predicting and preventing this condition.
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Affiliation(s)
- Chen Jiang
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Jianing Lin
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Bin Xie
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Meijuan Peng
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Ziyu Dai
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Suyin Mai
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Qiong Chen
- Department of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
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17
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Yao Y, Zhou Z, Wang X, Liu Z, Zhai Y, Chi X, Du J, Luo L, Zhao Z, Wang X, Xue C, Rao S. SpRY-mediated screens facilitate functional dissection of non-coding sequences at single-base resolution. CELL GENOMICS 2024:100583. [PMID: 38889719 DOI: 10.1016/j.xgen.2024.100583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/28/2024] [Accepted: 05/16/2024] [Indexed: 06/20/2024]
Abstract
CRISPR mutagenesis screens conducted with SpCas9 and other nucleases have identified certain cis-regulatory elements and genetic variants but at a limited resolution due to the absence of protospacer adjacent motif (PAM) sequences. Here, leveraging the broad targeting scope of the near-PAMless SpRY variant, we have demonstrated that saturated SpRY mutagenesis and base editing screens can faithfully identify functional regulatory elements and essential genetic variants for target gene expression at single-base resolution. We further extended this methodology to investigate a genome-wide association study (GWAS) locus at 10q22.1 associated with a red blood cell trait, where we identified potential enhancers regulating HK1 gene expression, despite not all of these enhancers exhibiting typical chromatin signatures. More importantly, our saturated base editing screens pinpoint multiple causal variants within this locus that would otherwise be missed by Bayesian statistical fine-mapping. Our approach is generally applicable to functional interrogation of all non-coding genomic elements while complementing other high-coverage CRISPR screens.
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Affiliation(s)
- Yao Yao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
| | - Zhiwei Zhou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Xiaoling Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Zhirui Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yixin Zhai
- Department of Oncology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Xiaolin Chi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Jingyi Du
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Liheng Luo
- Center for Bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine & Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Zhigang Zhao
- Department of Medical Oncology, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin 300192, China
| | - Xiaoyue Wang
- Center for Bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine & Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Chaoyou Xue
- Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.
| | - Shuquan Rao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
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18
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Reeve MP, Vehviläinen M, Luo S, Ritari J, Karjalainen J, Gracia-Tabuenca J, Mehtonen J, Padmanabhuni SS, Kolosov N, Artomov M, Siirtola H, Olilla HM, Graham D, Partanen J, Xavier RJ, Daly MJ, Ripatti S, Salo T, Siponen M. Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer. Am J Hum Genet 2024; 111:1047-1060. [PMID: 38776927 PMCID: PMC11179409 DOI: 10.1016/j.ajhg.2024.04.020] [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: 02/29/2024] [Revised: 04/23/2024] [Accepted: 04/25/2024] [Indexed: 05/25/2024] Open
Abstract
Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.
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Affiliation(s)
- Mary Pat Reeve
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Mari Vehviläinen
- Department of Oral and Maxillofacial Diseases, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Shuang Luo
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Jarmo Ritari
- Finnish Red Cross Blood Service, Helsinki, Finland
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Javier Gracia-Tabuenca
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Juha Mehtonen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Shanmukha Sampath Padmanabhuni
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Nikita Kolosov
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA; Ohio State University College of Medicine, Columbus, OH, USA
| | - Mykyta Artomov
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA; Ohio State University College of Medicine, Columbus, OH, USA
| | - Harri Siirtola
- TAUCHI Research Center, Tampere University, Tampere, Finland
| | - Hanna M Olilla
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel Graham
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Ramnik J Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytical and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Tuula Salo
- Research Unit of Population Health, Department of Oral Pathology, University of Oulu and Oulu University Hospital, Oulu, Finland; Medical Research Center, Oulu University Hospital, Oulu, Finland; Department of Oral and Maxillofacial Diseases, and Translational Immunology Program (TRIMM), University of Helsinki, Helsinki, Finland
| | - Maria Siponen
- Institute of Dentistry, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; Odontology Education Unit, and Oral and Maxillofacial Diseases Clinic, Kuopio University Hospital, Kuopio, Finland
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19
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Zhu JH, Xu BJ, Pang XY, Lian J, Gu K, Ji SJ, Lu HB. Genetic Evidence for a Causal Relationship Between Innate Leukocytes and the Risk of Digestive System Cancers in East Asians and Europeans. World J Oncol 2024; 15:482-491. [PMID: 38751703 PMCID: PMC11092417 DOI: 10.14740/wjon1860] [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: 02/29/2024] [Accepted: 04/06/2024] [Indexed: 05/18/2024] Open
Abstract
Background Peripheral traditional immune cell disorder plays an important role in cancer onset and development. The causal relationships between leukocytes prior to cancer and the risk of digestive system cancer remain unknown. This study assesses the causal correlations between leukocytes and digestive system cancer risk in East Asians and Europeans. Methods Summary-level data on leukocyte-related genetic variation were extracted from Biobank Japan (107,964 participants) and a recent large-scale meta-analysis (563,946 participants). Summary-level data for the cancers were obtained from Biobank Japan (212,978 individuals) and the FinnGen consortium (178,802 participants). Univariable and multivariable Mendelian randomization (MR) analyses were performed on East Asians and Europeans separately. Results Univariable MR analysis demonstrated the significant association between circulating eosinophil counts and risk of colorectal cancer (CRC) in East Asians (odds ratio (OR) = 0.80, 95% confidence interval (CI): 0.69 - 0.92, P = 0.002) and a suggestive relationship in the European population (OR = 0.86, 95% CI: 0.77 - 0.97, P = 0.013). An inverse suggestive association was observed between levels of basophils and the risk of gastric cancer (GC) in East Asians (OR = 0.83, 95% CI: 0.72 - 0.97, P = 0.019). The multivariable MR analysis showed the independent causal effect of eosinophil count on CRC risk in East Asians (OR = 0.72, 95% CI: 0.57 - 0.92, P = 0.009) and Europeans (OR = 0.80, 95% CI: 0.70 - 0.92, P = 0.002). Circulating basophils served as the negative causal factor in GC risk in East Asians (OR = 0.80, 95% CI: 0.67 - 0.94, P = 0.007). Conclusions Our MR analyses revealed a genetic causal relationship between reduced blood eosinophils and an increased CRC risk in both Europeans and East Asians. Furthermore, our results suggested a causal association between decreased basophils and an elevated GC risk specifically in East Asians.
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Affiliation(s)
- Jia Hao Zhu
- Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150000, China
- These authors contributed equally to the study
| | - Ben Jie Xu
- Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150000, China
- These authors contributed equally to the study
| | - Xiang Yi Pang
- Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150000, China
- These authors contributed equally to the study
| | - Jie Lian
- Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150000, China
| | - Ke Gu
- Department of Radiotherapy and Oncology, The Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214000, China
| | - Sheng Jun Ji
- Department of Radiotherapy and Oncology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou, Jiangsu 215000, China
| | - Hai Bo Lu
- Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150000, China
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20
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Bellavance J, Wang L, Gagliano Taliun SA. Eight quick tips for including chromosome X in genome-wide association studies. PLoS Comput Biol 2024; 20:e1012160. [PMID: 38843110 PMCID: PMC11156303 DOI: 10.1371/journal.pcbi.1012160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024] Open
Affiliation(s)
- Justin Bellavance
- Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Linda Wang
- Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Sarah A. Gagliano Taliun
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Neurosciences, Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
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21
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Noordam R, Ao L, Stroo JF, Willems van Dijk K, van Heemst D. No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses. Eur J Clin Invest 2024; 54:e14189. [PMID: 38429948 DOI: 10.1111/eci.14189] [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: 11/04/2023] [Revised: 02/12/2024] [Accepted: 02/22/2024] [Indexed: 03/03/2024]
Abstract
BACKGROUND Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. METHODS Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/μL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. RESULTS Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. CONCLUSION Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.
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Affiliation(s)
- Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Linjun Ao
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jasmijn F Stroo
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Leiden Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
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Jiang Z, Sullivan PF, Li T, Zhao B, Wang X, Luo T, Huang S, Guan PY, Chen J, Yang Y, Stein JL, Li Y, Liu D, Sun L, Zhu H. The pivotal role of the X-chromosome in the genetic architecture of the human brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294848. [PMID: 37693466 PMCID: PMC10491353 DOI: 10.1101/2023.08.30.23294848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Genes on the X-chromosome are extensively expressed in the human brain. However, little is known for the X-chromosome's impact on the brain anatomy, microstructure, and functional network. We examined 1,045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X-chromosome interactions, while proposing an atlas outlining dosage compensation (DC) for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we discovered unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X-chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.
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Shi XY, Zhang QK, Li J, Zhu CY, Jin L, Fan S. Mendelian randomization analysis reveals causal relationships between circulating cell traits and renal disorders. Front Med (Lausanne) 2024; 11:1360868. [PMID: 38828235 PMCID: PMC11140107 DOI: 10.3389/fmed.2024.1360868] [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: 12/24/2023] [Accepted: 04/30/2024] [Indexed: 06/05/2024] Open
Abstract
Purpose The aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders. Methods We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05. Results Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined. Conclusion Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.
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Affiliation(s)
- Xing-yu Shi
- Department of Nephrology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Qian-kun Zhang
- Department of Nephrology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Jie Li
- Department of Nephrology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Chao-yong Zhu
- Department of Nephrology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Lie Jin
- Department of Nephrology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Shipei Fan
- Department of Ophthalmology, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
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Kunkel D, Sørensen P, Shankar V, Morgante F. Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592745. [PMID: 38766136 PMCID: PMC11100663 DOI: 10.1101/2024.05.06.592745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Polygenic prediction of complex trait phenotypes has become important in human genetics, especially in the context of precision medicine. Recently, Morgante et al. introduced mr.mash, a flexible and computationally efficient method that models multiple phenotypes jointly and leverages sharing of effects across such phenotypes to improve prediction accuracy. However, a drawback of mr.mash is that it requires individual-level data, which are often not publicly available. In this work, we introduce mr.mash-rss, an extension of the mr.mash model that requires only summary statistics from Genome-Wide Association Studies (GWAS) and linkage disequilibrium (LD) estimates from a reference panel. By using summary data, we achieve the twin goal of increasing the applicability of the mr.mash model to data sets that are not publicly available and making it scalable to biobank-size data. Through simulations, we show that mr.mash-rss is competitive with, and often outperforms, current state-of-the-art methods for single- and multi-phenotype polygenic prediction in a variety of scenarios that differ in the pattern of effect sharing across phenotypes, the number of phenotypes, the number of causal variants, and the genomic heritability. We also present a real data analysis of 16 blood cell phenotypes in UK Biobank, showing that mr.mash-rss achieves higher prediction accuracy than competing methods for the majority of traits, especially when the data has smaller sample size.
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Affiliation(s)
- Deborah Kunkel
- School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC, United States of America
| | - Peter Sørensen
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Vijay Shankar
- Center for Human Genetics, Clemson University, Greenwood, SC, United States of America
| | - Fabio Morgante
- Center for Human Genetics, Clemson University, Greenwood, SC, United States of America
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, United States of America
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25
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Hernandez RA, Hearn JI, Bhoopalan V, Hamzeh AR, Kwong K, Diamand K, Davies A, Li FJ, Padmanabhan H, Milne R, Ballard F, Spensberger D, Gardiner EE, Miraghazadeh B, Enders A, Cook MC. L-plastin associated syndrome of immune deficiency and hematologic cytopenia. J Allergy Clin Immunol 2024:S0091-6749(24)00458-5. [PMID: 38710235 DOI: 10.1016/j.jaci.2024.05.001] [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: 11/01/2023] [Revised: 04/01/2024] [Accepted: 05/01/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND LCP1 encodes L-plastin, an actin-bundling protein primarily expressed in hematopoietic cells. In mouse and fish models, LCP1 deficiency has been shown to result in hematologic and immune defects. OBJECTIVE This study aimed to determine the nature of a human inborn error of immunity resulting from a novel genetic variant of LCP1. METHODS We performed genetic, protein, and cellular analysis of PBMCs from a kindred with apparent autosomal dominant immune deficiency. We identified a candidate causal mutation in LCP1, which we evaluated by engineering the orthologous mutation in mice and Jurkat cells. RESULTS A splice-site variant in LCP1 segregated with lymphopenia, neutropenia, and thrombocytopenia. The splicing defect resulted in at least 2 aberrant transcripts, producing an in-frame deletion of 24 nucleotides, and a frameshift deletion of exon 8. Cellular analysis of the kindred revealed a proportionate reduction of T and B cells and a mild expansion of transitional B cells. Similarly, mice carrying the orthologous genetic variant exhibited the same in-frame aberrant transcript, reduced expression Lcp1 and gene dose-dependent leukopenia, mild thrombocytopenia, and lymphopenia, with a significant reduction of T-cell populations. Functional analysis revealed that LCP1c740-1G>A confers a defect in platelet development and function with aberrant spreading on collagen. Immunologic analysis revealed defective actin organization in T cells, reduced migration of PBMCs from patients, splenocytes from mutant mice, and a mutant Jurkat cell line in response to CXCL12; impaired germinal center B-cell expansion after immunization; and reduced cytokinesis during T cell proliferation. CONCLUSIONS We describe a unique human hematopoietic defect affecting neutrophils, lymphocytes, and platelets arising from partial LCP1 deficiency.
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Affiliation(s)
- Raquel A Hernandez
- Division of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - James I Hearn
- Division of Genome Sciences and Cancer, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Vijay Bhoopalan
- Division of Genome Sciences and Cancer, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | | | - Kristy Kwong
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Koula Diamand
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Ainsley Davies
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Fei-Ju Li
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Harish Padmanabhan
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Rachel Milne
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Fiona Ballard
- Division of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Dominik Spensberger
- Australian Phenomics Facility and John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Elizabeth E Gardiner
- Division of Genome Sciences and Cancer, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Bahar Miraghazadeh
- Division of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Anselm Enders
- Division of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, Australia
| | - Matthew C Cook
- Division of Immunology and Infectious Diseases, John Curtin School of Medical Research, Australian National University, Canberra, Australia; Canberra Clinical Genomics, Canberra, Australia; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge, United Kingdom.
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26
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Guo Y, Liu Q, Zheng Z, Qing M, Yao T, Wang B, Zhou M, Wang D, Ke Q, Ma J, Shan Z, Chen W. Genetic association of inflammatory marker GlycA with lung function and respiratory diseases. Nat Commun 2024; 15:3751. [PMID: 38704398 PMCID: PMC11069551 DOI: 10.1038/s41467-024-47845-w] [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: 05/03/2023] [Accepted: 04/12/2024] [Indexed: 05/06/2024] Open
Abstract
Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = -0.14), FVC (rg = -0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.
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Affiliation(s)
- Yanjun Guo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- Department of Epidemiology, Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA.
| | - Quanhong Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Zhilin Zheng
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Mengxia Qing
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Tianci Yao
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Min Zhou
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Dongming Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Qinmei Ke
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jixuan Ma
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Zhilei Shan
- Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Weihong Chen
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
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Qu D, Schürmann P, Rothämel T, Fleßner J, Rehberg D, Dörk T, Klintschar M. Revisiting the association of sudden infant death syndrome (SIDS) with polymorphisms of NHE3 and IL13. Int J Legal Med 2024; 138:743-749. [PMID: 38091065 PMCID: PMC11003888 DOI: 10.1007/s00414-023-03139-2] [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: 10/04/2023] [Accepted: 11/20/2023] [Indexed: 04/11/2024]
Abstract
OBJECTIVES Disturbances of the central nervous system and immune system are thought to play a role in sudden infant death syndrome (SIDS). Dysregulated expression of sodium (Na+)/hydrogen (H+) exchanger 3 (NHE3) in the brainstem and of interleukin 13 (IL13) in the lungs has been observed in SIDS. An association of single-nucleotide polymorphisms (SNPs) in NHE3 and IL13 with SIDS has been proposed, but controversial results were reported. Therefore, there is a need to revisit the association of SNPs in NHE3 and IL13 with SIDS. METHODS Genotyping of rs71597645 (G1131A) and rs2247114 (C2405T) in NHE3 and rs20541 (+ 4464A/G) in IL13 was performed in 201 SIDS cases and 338 controls. A meta-analysis was performed after merging our data with previously published data (all from European populations). RESULTS Polymorphisms rs2247114 (NHE3) and rs20541 (IL13) were significantly associated with SIDS overall and in multiple subgroups, but no association was found for rs71597645 (NHE3). After combining our data with previously published data, a fixed-effect meta-analysis showed that rs2247114 in NHE3 retained a significant association with SIDS under a recessive model (OR 2.78, 95%CI 1.53 to 5.06; p = 0.0008). CONCLUSION Our findings suggest an association of NHE3 variant rs2247114 (C2405T), though not rs71597645 (NHE3), with SIDS. A potential role of rs20541 (IL13) still has to be elucidated. Especially NHE3 seems to be an interesting topic for future SIDS research.
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Affiliation(s)
- Dong Qu
- Institute of Legal Medicine, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Peter Schürmann
- Gynaecology Research Unit, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Thomas Rothämel
- Institute of Legal Medicine, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Jessica Fleßner
- Institute of Legal Medicine, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Daniela Rehberg
- Institute of Legal Medicine, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Michael Klintschar
- Institute of Legal Medicine, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
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28
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Leung PBM, Liu Z, Zhong Y, Tubbs JD, Di Forti M, Murray RM, So HC, Sham PC, Lui SSY. Bidirectional two-sample Mendelian randomization study of differential white blood cell counts and schizophrenia. Brain Behav Immun 2024; 118:22-30. [PMID: 38355025 DOI: 10.1016/j.bbi.2024.02.015] [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: 07/24/2023] [Revised: 01/15/2024] [Accepted: 02/08/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Schizophrenia and white blood cell counts (WBC) are both complex and polygenic traits. Previous evidence suggests that increased WBC are associated with higher all-cause mortality, and other studies have found elevated WBC in first-episode psychosis and chronic schizophrenia. However, these observational findings may be confounded by antipsychotic exposures and their effects on WBC. Mendelian randomization (MR) is a useful method for examining the directions of genetically-predicted relationships between schizophrenia and WBC. METHODS We performed a two-sample MR using summary statistics from genome-wide association studies (GWAS) conducted by the Psychiatric Genomics Consortium Schizophrenia Workgroup (N = 130,644) and the Blood Cell Consortium (N = 563,946). The MR methods included inverse variance weighted (IVW), MR Egger, weighted median, MR-PRESSO, contamination mixture, and a novel approach called mixture model reciprocal causal inference (MRCI). False discovery rate was employed to correct for multiple testing. RESULTS Multiple MR methods supported bidirectional genetically-predicted relationships between lymphocyte count and schizophrenia: IVW (b = 0.026; FDR p-value = 0.008), MR Egger (b = 0.026; FDR p-value = 0.008), weighted median (b = 0.013; FDR p-value = 0.049), and MR-PRESSO (b = 0.014; FDR p-value = 0.010) in the forward direction, and IVW (OR = 1.100; FDR p-value = 0.021), MR Egger (OR = 1.231; FDR p-value < 0.001), weighted median (OR = 1.136; FDR p-value = 0.006) and MRCI (OR = 1.260; FDR p-value = 0.026) in the reverse direction. MR Egger (OR = 1.171; FDR p-value < 0.001) and MRCI (OR = 1.154; FDR p-value = 0.026) both suggested genetically-predicted eosinophil count is associated with schizophrenia, but MR Egger (b = 0.060; FDR p-value = 0.010) and contamination mixture (b = -0.013; FDR p-value = 0.045) gave ambiguous results on whether genetically predicted liability to schizophrenia would be associated with eosinophil count. MR Egger (b = 0.044; FDR p-value = 0.010) and MR-PRESSO (b = 0.009; FDR p-value = 0.045) supported genetically predicted liability to schizophrenia is associated with elevated monocyte count, and the opposite direction was also indicated by MR Egger (OR = 1.231; FDR p-value = 0.045). Lastly, unidirectional genetic liability from schizophrenia to neutrophil count were proposed by MR-PRESSO (b = 0.011; FDR p-value = 0.028) and contamination mixture (b = 0.011; FDR p-value = 0.045) method. CONCLUSION This MR study utilised multiple MR methods to obtain results suggesting bidirectional genetic genetically-predicted relationships for elevated lymphocyte counts and schizophrenia risk. In addition, moderate evidence also showed bidirectional genetically-predicted relationships between schizophrenia and monocyte counts, and unidirectional effect from genetic liability for eosinophil count to schizophrenia and from genetic liability for schizophrenia to neutrophil count. The influence of schizophrenia to eosinophil count is less certain. Our findings support the role of WBC in schizophrenia and concur with the hypothesis of neuroinflammation in schizophrenia.
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Affiliation(s)
- Perry B M Leung
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Zipeng Liu
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Guangzhou Women and Children's Medical Center, Guangdong Provincial Clinical Research Centre for Child Health, Guangzhou, China
| | - Yuanxin Zhong
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Justin D Tubbs
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marta Di Forti
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region; Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Pak C Sham
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region.
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
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29
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Schmit SL, Tsai YY, Bonner JD, Sanz-Pamplona R, Joshi AD, Ugai T, Lindsey SS, Melas M, McDonnell KJ, Idos GE, Walker CP, Qu C, Kast WM, Da Silva DM, Glickman JN, Chan AT, Giannakis M, Nowak JA, Rennert HS, Robins HS, Ogino S, Greenson JK, Moreno V, Rennert G, Gruber SB. Germline genetic regulation of the colorectal tumor immune microenvironment. BMC Genomics 2024; 25:409. [PMID: 38664626 PMCID: PMC11046907 DOI: 10.1186/s12864-024-10295-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
OBJECTIVE To evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC). METHODS Germline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication. RESULTS We identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10- 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa. CONCLUSIONS Our study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.
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Affiliation(s)
- Stephanie L Schmit
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA.
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, Cleveland, OH, USA.
| | - Ya-Yu Tsai
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Joseph D Bonner
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Rebeca Sanz-Pamplona
- Catalan Institute of Oncology (ICO), Hospitalet de Llobregat, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Barcelona, Spain
| | - Amit D Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Tomotaka Ugai
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Sidney S Lindsey
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Marilena Melas
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Kevin J McDonnell
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Gregory E Idos
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Christopher P Walker
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Chenxu Qu
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - W Martin Kast
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Diane M Da Silva
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | | | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Marios Giannakis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jonathan A Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Hedy S Rennert
- B. Rappaport Faculty of Medicine, Technion and the Association for Promotion of Research in Precision Medicine (APRPM), Haifa, Israel
| | | | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Tokyo Medical and Dental University (Institute of Science Tokyo), Tokyo, Japan
| | - Joel K Greenson
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Victor Moreno
- Catalan Institute of Oncology (ICO), Hospitalet de Llobregat, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - Gad Rennert
- B. Rappaport Faculty of Medicine, Technion and the Association for Promotion of Research in Precision Medicine (APRPM), Haifa, Israel
| | - Stephen B Gruber
- Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA.
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Liu CG, Li DY, Gao X, Ma T, Zhang K, Liu DY. Examining the causal relationship between circulating immune cells and the susceptibility to osteomyelitis: A Mendelian randomization study. Int Immunopharmacol 2024; 131:111815. [PMID: 38492335 DOI: 10.1016/j.intimp.2024.111815] [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: 01/14/2024] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND Osteomyelitis is considered as a deleterious inflammatory condition affecting the bone, primarily attributed to pathogenic infection. However, the underlying factors predisposing individuals to osteomyelitis remain incompletely elucidated. The immune system plays a multifaceted role in the progression of this condition, yet previous observational studies and randomized controlled trials investigating the association between circulating immune cell counts and osteomyelitis have been constrained. In order to address this knowledge gap, we conducted a Mendelian randomization (MR) analysis to evaluate the impact of diverse immune cell counts on the risk of developing osteomyelitis. METHODS In our study, we utilized single nucleotide polymorphisms (SNPs) that have been strongly linked to circulating immune cells or specific lymphocyte subtypes, as identified in large-scale genome-wide association studies (GWAS). These SNPs served as instrumental variables (IVs) for our MR analysis. We employed a more relaxed clumping threshold to conduct MR analysis on several related lymphocyte subtypes. To estimate causal effects, we utilized the Wald ratio, as well as the random-effects inverse variance weighted (IVW) and weighted median (WM) methods. To enhance the credibility of our results, we performed F-statistic calculations and a series of sensitivity analyses. RESULTS Our findings revealed a significant correlation between the absolute count of circulating lymphocytes and the risk of osteomyelitis [odds ratio(OR) 1.20;95 % confidence interval (CI), 1.08-1.32;P = 0.0005]. Furthermore, we identified a causal relationship between the absolute count of CD8+ T cells and susceptibility to osteomyelitis (OR 1.16; 95 % CI, 1.04-1.30; P = 0.0098). Importantly, these findings remained robust across a wide range of sensitivity analyses. CONCLUSION Through our MR analysis, we have provided evidence supporting a causal relationship between genetic predisposition to higher circulating immune cell counts and an increased risk of osteomyelitis. Specifically, our findings highlight the association between elevated CD8+ T cell counts and a heightened susceptibility to osteomyelitis. These results offer valuable insights for the future exploration of immunotherapy approaches in the management of osteomyelitis.
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Affiliation(s)
- Chun-Gui Liu
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Dong-Yang Li
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Xi Gao
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Teng Ma
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Kun Zhang
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - De-Yin Liu
- Severe & Poly-trauma Division, Orthopedic Trauma Department, Hong-Hui Hospital, Xi'an Jiaotong University, Xi'an, China.
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31
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Xiang R, Liu Y, Ben-Eghan C, Ritchie S, Lambert SA, Xu Y, Takeuchi F, Inouye M. Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.15.24305830. [PMID: 38699308 PMCID: PMC11065006 DOI: 10.1101/2024.04.15.24305830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Blood cell phenotypes are routinely tested in healthcare to inform clinical decisions. Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. Here, we mapped variance quantitative trait loci (vQTL), i.e. genetic loci associated with trait variance, for 29 blood cell phenotypes from the UK Biobank (N~408,111). We discovered 176 independent blood cell vQTLs, of which 147 were not found by additive QTL mapping. vQTLs displayed on average 1.8-fold stronger negative selection than additive QTL, highlighting that selection acts to reduce extreme blood cell phenotypes. Variance polygenic scores (vPGSs) were constructed to stratify individuals in the INTERVAL cohort (N~40,466), where genetically less variable individuals (low vPGS) had increased conventional PGS accuracy (by ~19%) than genetically more variable individuals. Genetic prediction of blood cell traits improved by ~10% on average combining PGS with vPGS. Using Mendelian randomisation and vPGS association analyses, we found that alcohol consumption significantly increased blood cell trait variances highlighting the utility of blood cell vQTLs and vPGSs to provide novel insight into phenotype aetiology as well as improve prediction.
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Affiliation(s)
- Ruidong Xiang
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
- Baker Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, VIC, 3086, Australia
- Baker Department of Cardiometabolic Health, The University of Melbourne, VIC, 3010, Australia
| | - Yang Liu
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Chief Ben-Eghan
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Scott Ritchie
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Samuel A. Lambert
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Yu Xu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Fumihiko Takeuchi
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
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Yang Z, Hu L, Zhen J, Gu Y, Liu Y, Huang S, Wei Y, Zheng H, Guo X, Chen GB, Yang Y, Xiong L, Wei F, Liu S. Genetic basis of pregnancy-associated decreased platelet counts and gestational thrombocytopenia. Blood 2024; 143:1528-1538. [PMID: 38064665 PMCID: PMC11033587 DOI: 10.1182/blood.2023021925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 12/01/2023] [Accepted: 12/01/2023] [Indexed: 02/29/2024] Open
Abstract
ABSTRACT Platelet count reduction occurs throughout pregnancy, with 5% to 12% of pregnant women being diagnosed with gestational thrombocytopenia (GT), characterized by a more marked decrease in platelet count during pregnancy. However, the underlying biological mechanism behind these phenomena remains unclear. Here, we used sequencing data from noninvasive prenatal testing of 100 186 Chinese pregnant individuals and conducted, to our knowledge, the hitherto largest-scale genome-wide association studies on platelet counts during 5 periods of pregnancy (the first, second, and third trimesters, delivery, and the postpartum period) as well as 2 GT statuses (GT platelet count < 150 × 109/L and severe GT platelet count < 100 × 109/L). Our analysis revealed 138 genome-wide significant loci, explaining 10.4% to 12.1% of the observed variation. Interestingly, we identified previously unknown changes in genetic effects on platelet counts during pregnancy for variants present in PEAR1 and CBL, with PEAR1 variants specifically associated with a faster decline in platelet counts. Furthermore, we found that variants present in PEAR1 and TUBB1 increased susceptibility to GT and severe GT. Our study provides insight into the genetic basis of platelet counts and GT in pregnancy, highlighting the critical role of PEAR1 in decreasing platelet counts during pregnancy and the occurrence of GT. Those with pregnancies carrying specific variants associated with declining platelet counts may experience a more pronounced decrease, thereby elevating the risk of GT. These findings lay the groundwork for further investigation into the biological mechanisms and causal implications of GT.
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Affiliation(s)
- Zijing Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
| | - Liang Hu
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
| | - Jianxin Zhen
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
| | - Yuqin Gu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yanhong Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Shang Huang
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
- Shenzhen Children's Hospital of China Medical University, Shenzhen, Guangdong, China
| | - Yuandan Wei
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
| | - Hao Zheng
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xinxin Guo
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Guo-Bo Chen
- Department of Genetic and Genomic Medicine, Center for Productive Medicine, Clinical Research Institute, Zhejiang Provincial People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China
- Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yan Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Likuan Xiong
- Central Laboratory, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Birth Defects Research, Shenzhen, Guangdong, China
| | - Fengxiang Wei
- The Genetics Laboratory, Longgang District Maternity and Child Healthcare Hospital of Shenzhen City, Shenzhen, Guangdong, China
- Longgang Maternity and Child Institute of Shantou University Medical College, Shenzhen, Guangdong, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
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Ou Y, Zhan Y, Shao X, Xu P, Ji L, Zhuang X, Chen H, Cheng Y. Lipoprotein lipids and apolipoproteins in primary immune thrombocytopenia: Results from a clinical characteristics and causal relationship verification, potential drug target identification by Mendelian randomization analyses. Br J Haematol 2024; 204:1483-1494. [PMID: 38031970 DOI: 10.1111/bjh.19229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 11/01/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023]
Abstract
Primary immune thrombocytopenia (ITP) is an acquired autoimmune disease. Cellular and systemic lipid metabolism plays a significant role in the regulation of immune cell activities. However, the role of lipoprotein lipids and apolipoproteins in ITP remains elusive. The automatic biochemistry analyser was used to measure the levels of serum total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-I (apoA-I), apoB, apoE and lipoprotein a [LP(a)]. Genetic variants strongly associated with circulating lipoprotein lipids and apolipoproteins (LDL-C, apoB, TG, HDL-C and apoA-I) were extracted to perform Mendelian randomization (MR) analyses. Finally, drug-target MR and passive ITP mice model was used to investigate the potential druggable targets of ITP. Levels of HDL-C, apoA-I, decreased and LP(a) increased in ITP patients compared with healthy controls. Low HDL-C was causally associated with ITP susceptibility. Through drug-target MR and animal modelling, ABCA1 was identified as a potential target to design drugs for ITP. Our study found that lipid metabolism is related to ITP. The causative association between HDL-C and the risk of ITP was also established. The study provided new evidence of the aetiology of ITP. ABCA1 might be a potential drug target for ITP.
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Affiliation(s)
- Yang Ou
- Center for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Yanxia Zhan
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xia Shao
- Center for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Pengcheng Xu
- Center for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, China
| | - Lili Ji
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xibing Zhuang
- Center for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Chen
- Department of Thoracic Surgery, Zhongshan-Xuhui Hospital, Fudan University, Shanghai, China
| | - Yunfeng Cheng
- Center for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital Qingpu Branch, Fudan University, Shanghai, China
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34
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Zhang XX, Yu XY, Xu SJ, Shi XQ, Chen Y, Shi Q, Sun C. rs2736098, a synonymous polymorphism, is associated with carcinogenesis and cell count in multiple tissue types by regulating TERT expression. Heliyon 2024; 10:e27802. [PMID: 38496869 PMCID: PMC10944260 DOI: 10.1016/j.heliyon.2024.e27802] [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: 12/18/2023] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/19/2024] Open
Abstract
rs2736098 is a synonymous polymorphism in TERT (telomerase reverse transcriptase), an enzyme involved in tumor onset of multiple tissues, and should play no roles in carcinogenesis. However, a search in cancer somatic mutation database indicated that the mutation frequency at rs2736098 is much higher than the average one for TERT. Moreover, there are significant H3K4me1 and H3K27Ac signals, two universal histone modifications for active enhancers, surrounding rs2736098. Therefore, we hypothesized that rs2736098 might be within an enhancer region, regulate TERT expression and influence cancer risk. Through luciferase assay, it was verified that the enhancer activity of rs2736098C allele is significantly higher than that of T in multiple tissues. Transfection of plasmids containing TERT coding region with two different alleles indicated that rs2736098C allele can induce a significantly higher TERT expression than T. By chromatin immunoprecipitation, it was observed that the fragment spanning rs2736098 can interact with USF1 (upstream transcription factor 1). The two alleles of rs2736098 present evidently different binding affinity with nuclear proteins. Database and literature search indicated that rs2736098 is significantly associated with carcinogenesis in multiple tissues and count of multiple cell types. All these facts indicated that rs2736098 is also an oncogenic polymorphism and plays important role in cell proliferation.
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Affiliation(s)
- Xin-Xin Zhang
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Xin-Yi Yu
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Shuang-Jia Xu
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Xiao-Qian Shi
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Ying Chen
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
| | - Qiang Shi
- College of Biology Pharmacy and Food Engineering, Shangluo University, Shangluo, Shaanxi, 726000, PR China
| | - Chang Sun
- College of Life Sciences, Shaanxi Normal University, Xi'an, Shaanxi, 710119, PR China
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35
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Chang Z, Wang S, Liu K, Lin R, Liu C, Zhang J, Wei D, Nie Y, Chen Y, He J, Li H, Cheng ZJ, Sun B. Peripheral blood indicators and COVID-19: an observational and bidirectional Mendelian randomization study. BMC Med Genomics 2024; 17:81. [PMID: 38549094 PMCID: PMC10979573 DOI: 10.1186/s12920-024-01844-4] [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: 05/05/2023] [Accepted: 03/01/2024] [Indexed: 04/01/2024] Open
Abstract
Blood is critical for health, supporting key functions like immunity and oxygen transport. While studies have found links between common blood clinical indicators and COVID-19, they cannot provide causal inference due to residual confounding and reverse causality. To identify indicators affecting COVID-19, we analyzed clinical data (n = 2,293, aged 18-65 years) from Guangzhou Medical University's first affiliated hospital (2022-present), identifying 34 significant indicators differentiating COVID-19 patients from healthy controls. Utilizing bidirectional Mendelian randomization analyses, integrating data from over 2.46 million participants from various large-scale studies, we established causal links for six blood indicators with COVID-19 risk, five of which is consistent with our observational findings. Specifically, elevated Troponin I and Platelet Distribution Width levels are linked with increased COVID-19 susceptibility, whereas higher Hematocrit, Hemoglobin, and Neutrophil counts confer a protective effect. Reverse MR analysis confirmed four blood biomarkers influenced by COVID-19, aligning with our observational data for three of them. Notably, COVID-19 exhibited a positive causal relationship with Troponin I (Tnl) and Serum Amyloid Protein A, while a negative association was observed with Plateletcrit. These findings may help identify high-risk individuals and provide further direction on the management of COVID-19.
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Affiliation(s)
- Zhenglin Chang
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
- Guangzhou Laboratory, Guangzhou International Bio Island, XingDaoHuanBei Road, Guangdong Province, Guangzhou, 510005, China
| | - Suilin Wang
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Kemin Liu
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Runpei Lin
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Changlian Liu
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Jiale Zhang
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Daqiang Wei
- Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Yuxi Nie
- Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Yuerong Chen
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Jiawei He
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China
| | - Haiyang Li
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
| | - Zhangkai J Cheng
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
- Guangzhou Laboratory, Guangzhou International Bio Island, XingDaoHuanBei Road, Guangdong Province, Guangzhou, 510005, China.
| | - Baoqing Sun
- Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, Guangdong, China.
- Guangzhou Laboratory, Guangzhou International Bio Island, XingDaoHuanBei Road, Guangdong Province, Guangzhou, 510005, China.
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36
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Yeyeodu S, Hanafi D, Webb K, Laurie NA, Kimbro KS. Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease. Front Endocrinol (Lausanne) 2024; 14:1286979. [PMID: 38577257 PMCID: PMC10991756 DOI: 10.3389/fendo.2023.1286979] [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: 09/01/2023] [Accepted: 12/07/2023] [Indexed: 04/06/2024] Open
Abstract
Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.
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Affiliation(s)
- Susan Yeyeodu
- Julius L Chambers Biomedical/Biotechnology Institute (JLC-BBRI), North Carolina Central University, Durham, NC, United States
- Charles River Discovery Services, Morrisville, NC, United States
| | - Donia Hanafi
- Julius L Chambers Biomedical/Biotechnology Institute (JLC-BBRI), North Carolina Central University, Durham, NC, United States
| | - Kenisha Webb
- Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA, United States
| | - Nikia A. Laurie
- Julius L Chambers Biomedical/Biotechnology Institute (JLC-BBRI), North Carolina Central University, Durham, NC, United States
| | - K. Sean Kimbro
- Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA, United States
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Plender EG, Prodanov T, Hsieh P, Nizamis E, Harvey WT, Sulovari A, Munson KM, Kaufman EJ, O'Neal WK, Valdmanis PN, Marschall T, Bloom JD, Eichler EE. Structural and genetic diversity in the secreted mucins, MUC5AC and MUC5B. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585560. [PMID: 38562829 PMCID: PMC10983947 DOI: 10.1101/2024.03.18.585560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The secreted mucins MUC5AC and MUC5B play critical defensive roles in airway pathogen entrapment and mucociliary clearance by encoding large glycoproteins with variable number tandem repeats (VNTRs). These polymorphic and degenerate protein coding VNTRs make the loci difficult to investigate with short reads. We characterize the structural diversity of MUC5AC and MUC5B by long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that human MUC5B is largely invariant (5761-5762aa); however, seven haplotypes have expanded VNTRs (6291-7019aa). In contrast, 30 allelic variants of MUC5AC encode 16 distinct proteins (5249-6325aa) with cysteine-rich domain and VNTR copy number variation. We grouped MUC5AC alleles into three phylogenetic clades: H1 (46%, ~5654aa), H2 (33%, ~5742aa), and H3 (7%, ~6325aa). The two most common human MUC5AC variants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium (LD) and Tajima's D analyses reveal that East Asians carry exceptionally large MUC5AC LD blocks with an excess of rare variation (p<0.05). To validate this result, we used Locityper for genotyping MUC5AC haplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observed signatures of positive selection in H1 and H2 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Africans and Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium, consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein coding VNTRs for improved disease associations.
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Affiliation(s)
- Elizabeth G Plender
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Timofey Prodanov
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstr. 5, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Moorenstr. 5, 40225 Düsseldorf, Germany
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Evangelos Nizamis
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Eli J Kaufman
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Wanda K O'Neal
- Marsico Lung Institute/UNC CF Research Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, 27599, North Carolina, USA
| | - Paul N Valdmanis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstr. 5, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Moorenstr. 5, 40225 Düsseldorf, Germany
| | - Jesse D Bloom
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Howard Hughes Medical Institute, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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38
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Artaza H, Eriksson D, Lavrichenko K, Aranda-Guillén M, Bratland E, Vaudel M, Knappskog P, Husebye ES, Bensing S, Wolff ASB, Kämpe O, Røyrvik EC, Johansson S. Rare copy number variation in autoimmune Addison's disease. Front Immunol 2024; 15:1374499. [PMID: 38562931 PMCID: PMC10982488 DOI: 10.3389/fimmu.2024.1374499] [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: 01/22/2024] [Accepted: 03/05/2024] [Indexed: 04/04/2024] Open
Abstract
Autoimmune Addison's disease (AAD) is a rare but life-threatening endocrine disorder caused by an autoimmune destruction of the adrenal cortex. A previous genome-wide association study (GWAS) has shown that common variants near immune-related genes, which mostly encode proteins participating in the immune response, affect the risk of developing this condition. However, little is known about the contribution of copy number variations (CNVs) to AAD susceptibility. We used the genome-wide genotyping data from Norwegian and Swedish individuals (1,182 cases and 3,810 controls) to investigate the putative role of CNVs in the AAD aetiology. Although the frequency of rare CNVs was similar between cases and controls, we observed that larger deletions (>1,000 kb) were more common among patients (OR = 4.23, 95% CI 1.85-9.66, p = 0.0002). Despite this, none of the large case-deletions were conclusively pathogenic, and the clinical presentation and an AAD-polygenic risk score were similar between cases with and without the large CNVs. Among deletions exclusive to individuals with AAD, we highlight two ultra-rare deletions in the genes LRBA and BCL2L11, which we speculate might have contributed to the polygenic risk in these carriers. In conclusion, rare CNVs do not appear to be a major cause of AAD but further studies are needed to ascertain the potential contribution of rare deletions to the polygenic load of AAD susceptibility.
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Affiliation(s)
- Haydee Artaza
- Department of Clinical Science, University of Bergen, Bergen, Norway
- K. G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
| | - Daniel Eriksson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Center for Molecular Medicine, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden
| | - Ksenia Lavrichenko
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Maribel Aranda-Guillén
- Center for Molecular Medicine, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden
| | - Eirik Bratland
- K. G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Per Knappskog
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Eystein S. Husebye
- K. G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
- Department of Medicine, Haukeland University Hospital, Bergen, Norway
| | - Sophie Bensing
- Department of Endocrinology, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Anette S. B. Wolff
- Department of Clinical Science, University of Bergen, Bergen, Norway
- K. G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
- Department of Medicine, Haukeland University Hospital, Bergen, Norway
| | - Olle Kämpe
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ellen C. Røyrvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
- K. G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
- Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Bergen, Norway
| | - Stefan Johansson
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
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Li Y, Wang X, Zhang Z, Shi L, Cheng L, Zhang X. Effect of the gut microbiome, plasma metabolome, peripheral cells, and inflammatory cytokines on obesity: a bidirectional two-sample Mendelian randomization study and mediation analysis. Front Immunol 2024; 15:1348347. [PMID: 38558794 PMCID: PMC10981273 DOI: 10.3389/fimmu.2024.1348347] [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: 12/02/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Background Obesity is a metabolic and chronic inflammatory disease involving genetic and environmental factors. This study aimed to investigate the causal relationship among gut microbiota abundance, plasma metabolomics, peripheral cell (blood and immune cell) counts, inflammatory cytokines, and obesity. Methods Summary statistics of 191 gut microbiota traits (N = 18,340), 1,400 plasma metabolite traits (N = 8,299), 128 peripheral cell counts (blood cells, N = 408,112; immune cells, N = 3,757), 41 inflammatory cytokine traits (N = 8,293), and 6 obesity traits were obtained from publicly available genome-wide association studies. Two-sample Mendelian randomization (MR) analysis was applied to infer the causal links using inverse variance-weighted, maximum likelihood, MR-Egger, weighted median, weighted mode, and Wald ratio methods. Several sensitivity analyses were also utilized to ensure reliable MR results. Finally, we used mediation analysis to identify the pathway from gut microbiota to obesity mediated by plasma metabolites, peripheral cells, and inflammatory cytokines. Results MR revealed a causal effect of 44 gut microbiota taxa, 281 plasma metabolites, 27 peripheral cells, and 8 inflammatory cytokines on obesity. Among them, five shared causal gut microbiota taxa belonged to the phylum Actinobacteria, order Bifidobacteriales, family Bifidobacteriaceae, genus Lachnospiraceae UCG008, and species Eubacterium nodatum group. Furthermore, we screened 42 shared causal metabolites, 7 shared causal peripheral cells, and 1 shared causal inflammatory cytokine. Based on known causal metabolites, we observed that the metabolic pathways of D-arginine, D-ornithine, linoleic acid, and glycerophospholipid metabolism were closely related to obesity. Finally, mediation analysis revealed 20 mediation relationships, including the causal pathway from gut microbiota to obesity, mediated by 17 metabolites, 2 peripheral cells, and 1 inflammatory cytokine. Sensitivity analysis represented no heterogeneity or pleiotropy in this study. Conclusion Our findings support a causal relationship among gut microbiota, plasma metabolites, peripheral cells, inflammatory cytokines, and obesity. These biomarkers provide new insights into the mechanisms underlying obesity and contribute to its prevention, diagnosis, and treatment.
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Affiliation(s)
- Ying Li
- Human Molecular Genetics Group, National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
- Department of Child and Adolescent Health, School of Public Health, Harbin Medical University, Harbin, China
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
| | - Xin Wang
- Human Molecular Genetics Group, National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Zitong Zhang
- Human Molecular Genetics Group, National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
- Department of Medical Genetics, College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Lei Shi
- Human Molecular Genetics Group, National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
- Department of Medical Genetics, College of Basic Medical Sciences, Harbin Medical University, Harbin, China
| | - Liang Cheng
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xue Zhang
- Human Molecular Genetics Group, National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
- Department of Child and Adolescent Health, School of Public Health, Harbin Medical University, Harbin, China
- National Health Commission (NHC) Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, China
- Department of Medical Genetics, College of Basic Medical Sciences, Harbin Medical University, Harbin, China
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40
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Ling S, Dai Y, Weng R, Li Y, Wu W, Zhou Z, Zhong Z, Zheng Y. Epidemiologic and genetic associations of female reproductive disorders with depression or dysthymia: a Mendelian randomization study. Sci Rep 2024; 14:5984. [PMID: 38472314 DOI: 10.1038/s41598-024-55993-8] [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: 09/01/2023] [Accepted: 02/29/2024] [Indexed: 03/14/2024] Open
Abstract
Observational studies have previously reported an association between depression and certain female reproductive disorders. However, the causal relationships between depression and different types of female reproductive disorders remain unclear in terms of direction and magnitude. We conducted a comprehensive investigation using a two-sample bi-directional Mendelian randomization analysis, incorporating publicly available GWAS summary statistics. Our aim was to establish a causal relationship between genetically predicted depression and the risk of various female reproductive pathological conditions, such as ovarian dysfunction, polycystic ovary syndrome(PCOS), ovarian cysts, abnormal uterine and vaginal bleeding(AUB), endometriosis, leiomyoma of the uterus, female infertility, spontaneous abortion, eclampsia, pregnancy hypertension, gestational diabetes, excessive vomiting in pregnancy, cervical cancer, and uterine/endometrial cancer. We analyzed a substantial sample size, ranging from 111,831 to 210,870 individuals, and employed robust statistical methods, including inverse variance weighted, MR-Egger, weighted median, and MR-PRESSO, to estimate causal effects. Sensitivity analyses, such as Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and funnel plots, were also conducted to ensure the validity of our results. Furthermore, risk factor analyses were performed to investigate potential mediators associated with these observed relationships. Our results demonstrated that genetic predisposition to depression or dysthymia was associated with an increased risk of developing PCOS (OR = 1.43, 95% CI 1.28-1.59; P = 6.66 × 10-11), ovarian cysts (OR = 1.36, 95% CI 1.20-1.55; P = 1.57 × 10-6), AUB (OR = 1.41, 95% CI 1.20-1.66; P = 3.01 × 10-5), and endometriosis (OR = 1.43, 95% CI 1.27-1.70; P = 2.21 × 10-7) after Bonferroni correction, but no evidence for reverse causality. Our study did not find any evidence supporting a causal or reverse causal relationship between depression/dysthymia and other types of female reproductive disorders. In summary, our study provides evidence for a causal relationship between genetically predicted depression and specific types of female reproductive disorders. Our findings emphasize the importance of depression management in the prevention and treatment of female reproductive disorders, notably including PCOS, ovarian cysts, AUB, and endometriosis.
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Affiliation(s)
- Shuyi Ling
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Yuqing Dai
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Ruoxin Weng
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Yuan Li
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Wenbo Wu
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Ziqiong Zhou
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China
| | - Zhisheng Zhong
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China.
| | - Yuehui Zheng
- Reproductive Health Department, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, 518000, Guangdong, China.
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41
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Wong THT, Mo JMY, Zhou M, Zhao JV, Schooling CM, He B, Luo S, Au Yeung SL. A two-sample Mendelian randomization study explores metabolic profiling of different glycemic traits. Commun Biol 2024; 7:293. [PMID: 38459184 PMCID: PMC10923832 DOI: 10.1038/s42003-024-05977-1] [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: 01/02/2023] [Accepted: 02/27/2024] [Indexed: 03/10/2024] Open
Abstract
We assessed the causal relation of four glycemic traits and type 2 diabetes liability with 167 metabolites using Mendelian randomization with various sensitivity analyses and a reverse Mendelian randomization analysis. We extracted instruments for fasting glucose, 2-h glucose, fasting insulin, and glycated hemoglobin from the Meta-Analyses of Glucose and Insulin-related traits Consortium (n = 200,622), and those for type 2 diabetes liability from a meta-analysis of multiple cohorts (148,726 cases, 965,732 controls) in Europeans. Outcome data were from summary statistics of 167 metabolites from the UK Biobank (n = 115,078). Fasting glucose and 2-h glucose were not associated with any metabolite. Higher glycated hemoglobin was associated with higher free cholesterol in small low-density lipoprotein. Type 2 diabetes liability and fasting insulin were inversely associated with apolipoprotein A1, total cholines, lipoprotein subfractions in high-density-lipoprotein and intermediate-density lipoproteins, and positively associated with aromatic amino acids. These findings indicate hyperglycemia-independent patterns and highlight the role of insulin in type 2 diabetes development. Further studies should evaluate these glycemic traits in type 2 diabetes diagnosis and clinical management.
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Affiliation(s)
- Tommy H T Wong
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Jacky M Y Mo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Mingqi Zhou
- Department of Biological Chemistry, School of Medicine, University of California Irvine, Irvine, CA, USA
- Center for Epigenetics and Metabolism, University of California Irvine, Irvine, CA, USA
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Baoting He
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Shan Luo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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42
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Lu HF, Chou CH, Lin YJ, Uchiyama S, Terao C, Wang YW, Yang JS, Liu TY, Wong HSC, Chen SCC, Tsai FJ. The genome-wide association study of serum IgE levels demonstrated a shared genetic background in allergic diseases. Clin Immunol 2024; 260:109897. [PMID: 38199299 DOI: 10.1016/j.clim.2024.109897] [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: 08/10/2023] [Revised: 12/12/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
Immunoglobulin E (IgE) synthessis is highly related to a variety of atopic diseases, and several genome-wide association studies (GWASs) have demonstrated the association between genes and IgE level. In this study, we conducted the largest genome-wide association study of IgE involving a Taiwanese Han population. Eight independent variants exhibited genome-wide significance. Among them, an intronic SNP of CD28, rs1181388, and an intergenic SNP, rs1002957030, on 11q23.2 were identified as novel signals for IgE. Seven of the loci were replicated successfully in a meta-analysis using data on Japanese population. Among all the human leukocyte antigen (HLA) regions, HLA-DQA1*03:02 - HLA-DQB1*03:03 was the most significant haplotype (OR = 1.25, SE = 0.02, FDR = 1.6 × 10-14), corresponding to HLA-DQA1 Asp160 and HLA-DQB1 Leu87 amino acid residues. The genetic correlation showed significance between IgE and allergic diseases including asthma, atopic dermatitis, and pollinosis. IgE PRS was significantly correlated with total IgE levels. Furthermore, the top decile IgE polygenic risk score (PRS) group had the highest risk of asthma for the Taiwan Biobank and Biobank Japan cohorts. IgE PRS may be used to aid in predicting the occurrence of allergic reactions before symptoms occur and biomarkers are detectable. Our study provided a more comprehensive understanding of the impact of genomic variants, including complex HLA alleles, on serum IgE levels.
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Affiliation(s)
- Hsing-Fang Lu
- Department of Medical Research, China Medical University Hospital, Taichung 404327, Taiwan; Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chen-Hsing Chou
- PhD Program for Health Science and Industry, College of Health Care, China Medical University, Taichung, Taiwan; Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Ying-Ju Lin
- Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan; School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Shunsuke Uchiyama
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan; The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Yu-Wen Wang
- Department of Medical Research, China Medical University Hospital, Taichung 404327, Taiwan
| | - Jai-Sing Yang
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404327, Taiwan
| | - Ting-Yuan Liu
- Department of Medical Research, China Medical University Hospital, Taichung 404327, Taiwan
| | - Henry Sung-Ching Wong
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Sean Chun-Chang Chen
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Fuu-Jen Tsai
- Department of Medical Research, China Medical University Hospital, Taichung 404327, Taiwan; School of Chinese Medicine, China Medical University, Taichung, Taiwan; Department of Biotechnology and Bioinformatics, Asia University, Taichung, Taiwan.
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Tindula G, Issac B, Mukherjee SK, Ekramullah SM, Arman DM, Islam J, Suchanda HS, Sun L, Rockowitz S, Christiani DC, Warf BC, Mazumdar M. Genome-wide analysis of spina bifida risk variants in a case-control study from Bangladesh. Birth Defects Res 2024; 116:e2331. [PMID: 38526198 PMCID: PMC10963057 DOI: 10.1002/bdr2.2331] [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: 11/01/2023] [Revised: 03/07/2024] [Accepted: 03/09/2024] [Indexed: 03/26/2024]
Abstract
BACKGROUND Human studies of genetic risk factors for neural tube defects, severe birth defects associated with long-term health consequences in surviving children, have predominantly been restricted to a subset of candidate genes in specific biological pathways including folate metabolism. METHODS In this study, we investigated the association of genetic variants spanning the genome with risk of spina bifida (i.e., myelomeningocele and meningocele) in a subset of families enrolled from December 2016 through December 2022 in a case-control study in Bangladesh, a population often underrepresented in genetic studies. Saliva DNA samples were analyzed using the Illumina Global Screening Array. We performed genetic association analyses to compare allele frequencies between 112 case and 121 control children, 272 mothers, and 128 trios. RESULTS In the transmission disequilibrium test analyses with trios only, we identified three novel exonic spina bifida risk loci, including rs140199800 (SULT1C2, p = 1.9 × 10-7), rs45580033 (ASB2, p = 4.2 × 10-10), and rs75426652 (LHPP, p = 7.2 × 10-14), after adjusting for multiple hypothesis testing. Association analyses comparing cases and controls, as well as models that included their mothers, did not identify genome-wide significant variants. CONCLUSIONS This study identified three novel single nucleotide polymorphisms involved in biological pathways not previously associated with neural tube defects. The study warrants replication in larger groups to validate findings and to inform targeted prevention strategies.
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Affiliation(s)
- Gwen Tindula
- Department of Neurology, Boston Children’s Hospital, Boston, MA, 02115, United States
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, United States
| | - Biju Issac
- Research Computing, Information Technology, Boston Children’s Hospital, Boston, MA, 02115, United States
| | - Sudipta Kumer Mukherjee
- Department of Paediatric Neurosurgery, National Institute of Neurosciences and Hospital (NINS), Sher-e-Bangla Nagar, Agargoan, Dhaka-1207, Bangladesh
| | - Sheikh Muhammad Ekramullah
- Department of Paediatric Neurosurgery, National Institute of Neurosciences and Hospital (NINS), Sher-e-Bangla Nagar, Agargoan, Dhaka-1207, Bangladesh
| | - DM Arman
- Department of Paediatric Neurosurgery, National Institute of Neurosciences and Hospital (NINS), Sher-e-Bangla Nagar, Agargoan, Dhaka-1207, Bangladesh
| | - Joynul Islam
- Department of Clinical Neurosurgery, National Institute of Neurosciences and Hospital (NINS), Sher-e-Bangla Nagar, Agargoan, Dhaka-1207, Bangladesh
| | - Hafiza Sultana Suchanda
- Pediatric Neurosurgery Research Committee, National Institute of Neurosciences and Hospital (NINS), Sher-e-Bangla Nagar, Agargoan, Dhaka-1207, Bangladesh
| | - Liang Sun
- Research Computing, Information Technology, Boston Children’s Hospital, Boston, MA, 02115, United States
| | - Shira Rockowitz
- Research Computing, Information Technology, Boston Children’s Hospital, Boston, MA, 02115, United States
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, 02115, United States
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, United States
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, United States
| | - Benjamin C. Warf
- Department of Neurosurgery, Boston Children's Hospital, Boston, MA, 02115, United States
| | - Maitreyi Mazumdar
- Department of Neurology, Boston Children’s Hospital, Boston, MA, 02115, United States
- Department of Neurology, Harvard Medical School, Boston, MA, 02115, United States
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, United States
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44
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Bian R, Xu X, Li Z. Causal effects between circulating immune cells and heart failure: evidence from a bidirectional Mendelian randomization study. BMC Med Genomics 2024; 17:62. [PMID: 38408984 PMCID: PMC10895739 DOI: 10.1186/s12920-024-01827-5] [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] [Received: 12/13/2023] [Accepted: 02/07/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND Heart failure (HF) is a prevalent cardiac condition characterized by high mortality and morbidity rates. Immune cells play a pivotal role as crucial biomarkers in assessing the overall immune status of individuals. However, the causal relationship between circulating immune cells and the pathogenesis of HF remains an area requiring further investigation. OBJECTIVES The aim of this study was to investigate the genetic interactions between circulating immune cells and HF, and to further elucidate the genetic associations between different lymphocyte subsets and HF. METHODS We obtained genetic variants associated with circulating immune cells as instrumental variables (IVs) from the Blood Cell Consortium and publicly available HF summary data. We conducted additional subsets analyses on lymphocyte counts. Our study utilized two-sample and multivariate Mendelian randomization (MVMR) analysis to investigate the causal effect of immune cells on HF. The primary analysis employed inverse variance weighting (IVW) and was complemented by a series of sensitivity analyses. RESULTS The findings of the study showed that the IVW model demonstrated a significant correlation between an elevation in lymphocyte count and a decreased risk of HF (OR = 0.97, 95% CI, 0.94 - 1.00, P = 0.032). However, no such correlation was evident in the MVMR analysis for lymphocytes and HF. Furthermore, the examination of the lymphocyte subsets indicated that an increase in CD39+ CD4+ T-cell counts was notably linked to a reduced risk of HF (OR = 0.96, 95% CI, 0.95 - 0.98, P = 0.0002). The MVMR results confirmed that the association between CD39+ CD4+ T-cell counts and HF remained significant. There was no substantial evidence of reverse causality observed between circulating immune cells and HF. CONCLUSION Our MR research provided evidence for a causal relationship between lymphocyte cell and HF. Subsets analyses revealed a causal relationship between CD39+ CD4+ T lymphocytes and HF. These findings will facilitate a future understanding of the mechanisms underlying HF.
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Affiliation(s)
- Rutao Bian
- Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China
- Guangzhou University of Traditional Chinese Medicine - Zhengzhou Hospital of Traditional Chinese Medicine Joint Laboratory of formulas-syndromes Research, Zhengzhou, China
| | - Xuegong Xu
- Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China.
- Guangzhou University of Traditional Chinese Medicine - Zhengzhou Hospital of Traditional Chinese Medicine Joint Laboratory of formulas-syndromes Research, Zhengzhou, China.
- Henan Key Laboratory of Traditional Chinese Medicine Cardiovascular Disease, Zhengzhou, China.
| | - Zishuang Li
- Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China
- Guangzhou University of Traditional Chinese Medicine - Zhengzhou Hospital of Traditional Chinese Medicine Joint Laboratory of formulas-syndromes Research, Zhengzhou, China
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45
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Natarajan P, Patel AP. Differences in Circulating Progenitor Cells and Risk of Atherosclerotic Cardiovascular Disease in South Asian Individuals. J Am Coll Cardiol 2024; 83:770-771. [PMID: 38355247 DOI: 10.1016/j.jacc.2023.12.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 02/16/2024]
Affiliation(s)
- Pradeep Natarajan
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - Aniruddh P Patel
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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46
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Chen L, Zhu LF, Zhang LY, Chu YH, Dong MH, Pang XW, Yang S, Zhou LQ, Shang K, Xiao J, Wang W, Qin C, Tian DS. Causal association between the peripheral immunity and the risk and disease severity of multiple sclerosis. Front Immunol 2024; 15:1325938. [PMID: 38390334 PMCID: PMC10881847 DOI: 10.3389/fimmu.2024.1325938] [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: 10/22/2023] [Accepted: 01/25/2024] [Indexed: 02/24/2024] Open
Abstract
Background Growing evidence links immunological responses to Multiple sclerosis (MS), but specific immune factors are still unclear. Methods Mendelian randomization (MR) was performed to investigate the association between peripheral hematological traits, MS risk, and its severity. Then, further subgroup analysis of immune counts and circulating cytokines and growth factors were performed. Results MR revealed higher white blood cell count (OR [95%CI] = 1.26 [1.10,1.44], P = 1.12E-03, P adjust = 3.35E-03) and lymphocyte count (OR [95%CI] = 1.31 [1.15,1.50], P = 5.37E-05, P adjust = 3.22E-04) increased the risk of MS. In further analysis, higher T cell absolute count (OR [95%CI] = 2.04 [1.36,3.08], P = 6.37E-04, P adjust = 2.19E-02) and CD4+ T cell absolute count (OR [95%CI] = 2.11 [1.37,3.24], P = 6.37E-04, P adjust = 2.19E-02), could increase MS risk. While increasing CD25++CD4+ T cell absolute count (OR [95%CI] = 0.75 [0.66,0.86], P = 2.12E-05, P adjust = 1.72E-03), CD25++CD4+ T cell in T cell (OR [95%CI] = 0.79[0.70,0.89], P = 8.54E-05, P adjust = 5.29E-03), CD25++CD4+ T cell in CD4+ T cell (OR [95%CI] = 0.80[0.72,0.89], P = 1.85E-05, P adjust = 1.72E-03), and CD25++CD8+ T cell in T cell (OR [95%CI] = 0.68[0.57,0.81], P = 2.22E-05, P adjust = 1.72E-03), were proved to be causally defensive for MS. For the disease severity, the suggestive association between some traits related to CD4+ T cell, Tregs and MS severity were demonstrated. Moreover, elevated levels of IL-2Ra had a detrimental effect on the risk of MS (OR [95%CI] = 1.22 [1.12,1.32], P = 3.20E-06, P adjust = 1.34E-04). Conclusions This study demonstrated a genetically predicted causal relationship between elevated peripheral immune cell counts and MS. Subgroup analysis revealed a specific contribution of peripheral immune cells, holding potential for further investigations into the underlying mechanisms of MS and its severity.
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Affiliation(s)
- Lian Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Li-Fang Zhu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Lu-Yang Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Yun-Hui Chu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Ming-Hao Dong
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Xiao-Wei Pang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng Yang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Luo-Qi Zhou
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Shang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Xiao
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Wang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Chuan Qin
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
| | - Dai-Shi Tian
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Neural Injury and Functional Reconstruction, Huazhong University of Science and Technology, Wuhan, China
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47
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Sun Q, Rowland BT, Chen J, Mikhaylova AV, Avery C, Peters U, Lundin J, Matise T, Buyske S, Tao R, Mathias RA, Reiner AP, Auer PL, Cox NJ, Kooperberg C, Thornton TA, Raffield LM, Li Y. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nat Commun 2024; 15:1016. [PMID: 38310129 PMCID: PMC10838303 DOI: 10.1038/s41467-024-45135-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: 10/07/2022] [Accepted: 01/16/2024] [Indexed: 02/05/2024] Open
Abstract
Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
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Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bryce T Rowland
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Anna V Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Ulrike Peters
- 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
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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48
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Pardo-Cea MA, Farré X, Esteve A, Palade J, Espín R, Mateo F, Alsop E, Alorda M, Blay N, Baiges A, Shabbir A, Comellas F, Gómez A, Arnan M, Teulé A, Salinas M, Berrocal L, Brunet J, Rofes P, Lázaro C, Conesa M, Rojas JJ, Velten L, Fendler W, Smyczynska U, Chowdhury D, Zeng Y, He HH, Li R, Van Keuren-Jensen K, de Cid R, Pujana MA. Biological basis of extensive pleiotropy between blood traits and cancer risk. Genome Med 2024; 16:21. [PMID: 38308367 PMCID: PMC10837955 DOI: 10.1186/s13073-024-01294-8] [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: 08/11/2023] [Accepted: 01/22/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. METHODS Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. RESULTS The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. CONCLUSIONS This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.
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Affiliation(s)
- Miguel Angel Pardo-Cea
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Xavier Farré
- Genomes for Life - GCAT Lab Group, Institut Germans Trias i Pujol (IGTP), Badalona, 08916, Barcelona, Catalonia, Spain
| | - Anna Esteve
- Badalona Applied Research Group in Oncology (B-ARGO), Catalan Institute of Oncology, Institut Germans Trias i Pujol (IGTP), Badalona, 08916, Barcelona, Catalonia, Spain
| | - Joanna Palade
- Cancer and Cell Biology, Translational Genomics Research Institute (TGen), Arizona, Phoenix, AZ, 85004, USA
| | - Roderic Espín
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Francesca Mateo
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Eric Alsop
- Cancer and Cell Biology, Translational Genomics Research Institute (TGen), Arizona, Phoenix, AZ, 85004, USA
| | - Marc Alorda
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Natalia Blay
- Genomes for Life - GCAT Lab Group, Institut Germans Trias i Pujol (IGTP), Badalona, 08916, Barcelona, Catalonia, Spain
| | - Alexandra Baiges
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Arzoo Shabbir
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Francesc Comellas
- Department of Mathematics, Technical University of Catalonia, Castelldefels, 08860, Barcelona, Catalonia, Spain
| | - Antonio Gómez
- Department of Biosciences, Faculty of Sciences and Technology (FCT), University of Vic - Central University of Catalonia (UVic-UCC), Vic, 08500, Barcelona, Catalonia, Spain
| | - Montserrat Arnan
- Department of Hematology, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Alex Teulé
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Monica Salinas
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Laura Berrocal
- OncoGir, Catalan Institute of Oncology, Girona Biomedical Research Institute (IDIBGI), 17190, Salt, Catalonia, Spain
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
- OncoGir, Catalan Institute of Oncology, Girona Biomedical Research Institute (IDIBGI), 17190, Salt, Catalonia, Spain
- Biomedical Research Network Centre in Cancer (CIBERONC), Instituto de Salud Carlos III, 28222, Madrid, Spain
| | - Paula Rofes
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
- Biomedical Research Network Centre in Cancer (CIBERONC), Instituto de Salud Carlos III, 28222, Madrid, Spain
| | - Conxi Lázaro
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
- Biomedical Research Network Centre in Cancer (CIBERONC), Instituto de Salud Carlos III, 28222, Madrid, Spain
| | - Miquel Conesa
- Department of Pathology and Experimental Therapies, University of Barcelona (UB), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Juan Jose Rojas
- Department of Pathology and Experimental Therapies, University of Barcelona (UB), Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain
| | - Lars Velten
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), 08003, Barcelona, Spain
- University Pompeu Fabra (UPF), 08002, Barcelona, Spain
| | - Wojciech Fendler
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, 92-215, Lodz, Poland
| | - Urszula Smyczynska
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, 92-215, Lodz, Poland
| | - Dipanjan Chowdhury
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
- Center for BRCA and Related Genes, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Yong Zeng
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5G 2C4, Canada
| | - Housheng Hansen He
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5G 2C4, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada
| | - Rong Li
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20052, USA
| | - Kendall Van Keuren-Jensen
- Cancer and Cell Biology, Translational Genomics Research Institute (TGen), Arizona, Phoenix, AZ, 85004, USA.
| | - Rafael de Cid
- Genomes for Life - GCAT Lab Group, Institut Germans Trias i Pujol (IGTP), Badalona, 08916, Barcelona, Catalonia, Spain.
| | - Miquel Angel Pujana
- ProCURE, Catalan Institute of Oncology, Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet del Llobregat, 08908, Barcelona, Catalonia, Spain.
- Biomedical Research Network Centre in Respiratory Diseases (CIBERES), Instituto de Salud Carlos III, 28222, Madrid, Spain.
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49
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Guo J, Walter K, Quiros PM, Gu M, Baxter EJ, Danesh J, Di Angelantonio E, Roberts D, Guglielmelli P, Harrison CN, Godfrey AL, Green AR, Vassiliou GS, Vuckovic D, Nangalia J, Soranzo N. Inherited polygenic effects on common hematological traits influence clonal selection on JAK2 V617F and the development of myeloproliferative neoplasms. Nat Genet 2024; 56:273-280. [PMID: 38233595 PMCID: PMC10864174 DOI: 10.1038/s41588-023-01638-x] [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: 12/22/2022] [Accepted: 12/01/2023] [Indexed: 01/19/2024]
Abstract
Myeloproliferative neoplasms (MPNs) are chronic cancers characterized by overproduction of mature blood cells. Their causative somatic mutations, for example, JAK2V617F, are common in the population, yet only a minority of carriers develop MPN. Here we show that the inherited polygenic loci that underlie common hematological traits influence JAK2V617F clonal expansion. We identify polygenic risk scores (PGSs) for monocyte count and plateletcrit as new risk factors for JAK2V617F positivity. PGSs for several hematological traits influenced the risk of different MPN subtypes, with low PGSs for two platelet traits also showing protective effects in JAK2V617F carriers, making them two to three times less likely to have essential thrombocythemia than carriers with high PGSs. We observed that extreme hematological PGSs may contribute to an MPN diagnosis in the absence of somatic driver mutations. Our study showcases how polygenic backgrounds underlying common hematological traits influence both clonal selection on somatic mutations and the subsequent phenotype of cancer.
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Affiliation(s)
- Jing Guo
- Wellcome Sanger Institute, Hinxton, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | | | - Pedro M Quiros
- Wellcome Sanger Institute, Hinxton, UK
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Muxin Gu
- Wellcome Sanger Institute, Hinxton, UK
| | - E Joanna Baxter
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - John Danesh
- Wellcome Sanger Institute, Hinxton, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Emanuele Di Angelantonio
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Fondazione Human Technopole, Milan, Italy
| | - David Roberts
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- NHS Blood and Transplant-Oxford Centre, John Radcliffe Hospital and Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Paola Guglielmelli
- Department of Experimental and Clinical Medicine, Center for Research and Innovation of Myeloproliferative Neoplasms (CRIMM), AOU Careggi, University of Florence, Florence, Italy
| | - Claire N Harrison
- Department of Haematology, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | | | - Anthony R Green
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - George S Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Dragana Vuckovic
- Wellcome Sanger Institute, Hinxton, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Jyoti Nangalia
- Wellcome Sanger Institute, Hinxton, UK.
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
- Cambridge University Hospitals NHS Trust, Cambridge, UK.
- Department of Haematology, University of Cambridge, Cambridge, UK.
| | - Nicole Soranzo
- Wellcome Sanger Institute, Hinxton, UK.
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
- Fondazione Human Technopole, Milan, Italy.
- Department of Haematology, University of Cambridge, Cambridge, UK.
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Li H, Li X. Genetic relationships between high blood eosinophil count, asthma susceptibility, and asthma severity. J Asthma 2024; 61:119-131. [PMID: 37560908 DOI: 10.1080/02770903.2023.2247490] [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: 06/19/2023] [Revised: 07/30/2023] [Accepted: 08/09/2023] [Indexed: 08/11/2023]
Abstract
OBJECTIVE Genetic relationships between blood eosinophil count (BEC), asthma susceptibility, and severity are unclear. We sought to identify the genetic difference between type 2 (T2) and nontype 2 (non-T2) asthma (defined by BEC) and investigate genetic relationships between high BEC, asthma susceptibility, and severity. METHODS Genome-wide association studies (GWASs) were performed for T2 (n = 9,064; BEC ≥ 300 cells/μL) versus non-T2 asthma (n = 14,379; BEC < 150 cells/μL) and asthma susceptibility (37,227 asthmatics vs. 124,132 nonasthma controls) in the UK Biobank and asthma severity (moderate-to-severe asthma [n = 2,153] vs. mild asthma [n = 5165]) in the All of Us Research Program (AoURP). Genetic causality between BEC, asthma susceptibility, and severity were dissected using Mendelian randomization (MR). RESULTS High BEC was associated with asthma and decreased pulmonary function. GWASs revealed four sets of genetic variants (p < 5 × 10-8): genes associated with only BEC or asthma and genes associated with high BEC and asthma in the same or opposite direction. The C allele of rs653178 in ATXN2 was associated with high BEC, risk for autoimmune diseases, and protection for asthma. Genetic variants associated with BEC or asthma were not associated with asthma severity. MR indicated high BEC and asthma were in bidirectional causal relationship (p < .001); however, they were not causal for asthma severity. CONCLUSIONS Genetic variants associated with asthma or BEC and asthma severity are distinctive. High BEC is a risk factor for asthma; however, it is neither necessary nor sufficient for asthma susceptibility and severity.
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Affiliation(s)
- Huashi Li
- Statistics Consulting Lab, BIO5 Institute, University of Arizona, Tucson, AZ, USA
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Xingnan Li
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
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