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Ren Y, Zhang H. A Mendelian randomization study investigating the causal relationships between inflammation and immunoglobulin A nephropathy. Hum Immunol 2024; 85:110830. [PMID: 38861759 DOI: 10.1016/j.humimm.2024.110830] [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: 10/27/2023] [Revised: 04/27/2024] [Accepted: 06/06/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND Immunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by the production of galactose‑deficient IgA1 (Gd‑IgA1) and the deposition of immune complexes in the kidney. Exploring the landscape of immune dysregulation in IgAN is valuable for pathogenesis and disease treatment. We conducted Mendelian randomization (MR) to assess the causal correlations between inflammation and IgAN. METHODS Based on available genetic datasets, we investigated potential causal links between inflammation and the risk of IgAN using two-sample MR. We used genome-wide association study (GWAS) summary statistics of 5 typical inflammation markers, 41 inflammatory cytokines, and 731 immune cell signatures, accessed from the public GWAS Catalog. The primary method employed for MR analysis was Inverse Variance Weighted (IVW). To confirm consistency across results, four supplementary MR methods were also conducted: MR-Egger, Weighted Median, Weighted Mode, and Simple Mode. To assess pleiotropy, we used the MR-Egger regression intercept test and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test. Cochrane's Q statistic was applied to evaluate heterogeneity. Additionally, the stability of the MR findings was verified through the leave-one-out sensitivity analysis. RESULTS This study revealed that interleukin-7 (IL-7) and stem cell growth factor beta (SCGF-β) were possibly associated with the risk of IgAN according to the IVW approach, with estimated odds ratios (OR) of 1.059 (95 % confidence interval [CI] 1.015 to 1.104, P = 0.008) and 1.043 (95 % CI 1.002 to 1.085, P = 0.037). Five immune traits were identified that might be linked to IgAN risk, each with P-values below 0.01, including natural killer T %T cell (OR = 1.058, 95 % CI: 1.020 to 1.097, P = 0.002), natural killer T %lymphocyte (OR = 1.055, 95 % CI: 1.016 to 1.096, P = 0.006), CD25++ CD8+ T cell %T cell (OR = 1.057, 95 % CI: 1.016 to 1.099, P = 0.006), CD3 on effector memory CD4+ T cell (OR = 1.045, 95 % CI: 1.019 to 1.071, P = 0.001), and CD3 on CD28+ CD45RA+ CD8+ T cell (OR = 1.042, 95 % CI: 1.016 to 1.068, P = 0.001). CD4 on central memory CD4+ T cell might be a protective factor for IgAN (OR = 0.922, 95 % CI: 0.875 to 0.971, P = 0.002). Moreover, IgAN may be implicated in a high risk of elevated granulocyte colony-stimulating factor (G-CSF) (OR = 1.114, 95 % CI 1.002 to 1.239, P = 0.046). CONCLUSION Our study revealed exposures among typical inflammation markers, inflammatory cytokines, and immune cell signatures that may potentially linked to IgAN risk by MR analysis. This insight may advance our understanding of the etiology of IgAN and support the development of targeted therapeutic strategies.
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Affiliation(s)
- Yi Ren
- Institute of Microcirculation, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; International Center of Microvascular Medicine, Chinese Academy of Medical Sciences, Beijing, China; Department of Pathology and Pathophysiology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Honggang Zhang
- Institute of Microcirculation, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; International Center of Microvascular Medicine, Chinese Academy of Medical Sciences, Beijing, China; Department of Pathology and Pathophysiology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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Wu S, Yuan C, Chen Z, Gao Y, Guo X, Chen R, Dai Y, Chen K. Genetically predicted systemic inflammation and the risk of atrial fibrillation: A bidirectional two-sample Mendelian randomization study. IJC HEART & VASCULATURE 2024; 52:101422. [PMID: 38756452 PMCID: PMC11096748 DOI: 10.1016/j.ijcha.2024.101422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/02/2024] [Accepted: 05/03/2024] [Indexed: 05/18/2024]
Abstract
Background Systemic inflammation has been proposed to be associated with the incidence of atrial fibrillation (AF), but whether it is a cause or a consequence of AF remains uncertain. We sought to explore the causal associations between systemic inflammation and AF using bidirectional Mendelian randomization (MR) analysis. Methods Independent genetic variants strongly associated with AF were selected as instrumental variables from the largest genome-wide association study (GWAS) with up to 1,030,836 individuals. Regarding inflammation traits, genetic associations with 41 inflammatory cytokines and 5 inflammatory biomarkers were obtained from their corresponding GWASs databases. Effect estimates were primarily evaluated using the inverse-variance weighted (IVW) method, supplemented by sensitivity analyses using MR-Egger, weighted median, and MR-PRESSO methods. Results In our initial MR analyses, we observed suggestive associations of genetically predicted interleukin-17 (IL-17), interleukin-2 receptor subunit alpha (IL-2rα), and procalcitonin (PCT) with AF. One standard deviation (SD) increase in IL-17, IL-2rα, and PCT caused an increase in AF risk by 6.3 % (OR 1.063, 95 %CI 1.011---1.118, p = 0.018), 4.9 % (OR 1.049, 95 %CI 1.007---1.094, p = 0.023) and 3.4 % (OR 1.034, 95 %CI 1.005---1.064, p = 0.022), respectively. Furthermore, our reverse MR analyses indicated that genetically predicted AF contributed to a suggestive increase in the levels of macrophage inflammatory protein-1β (MIP1β) (β 0.055, 95 %CI 0.006 to 0.103, p = 0.028), while a decrease in the levels of fibrinogen (Fbg) (β -0.091, 95 %CI -0.140 to -0.041, p < 0.001), which remained significant after multiple test correction. Conclusions Our MR study identified several inflammatory biomarkers with suggestive causal associations regarding the upstream and downstream regulation of AF occurrence, offering new insights for therapeutic exploitation of AF. Further research is required to validate the underlying link between systemic inflammation and AF in larger cohorts.
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Affiliation(s)
- Sijin Wu
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chenxi Yuan
- Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, China
| | - Zhongli Chen
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuan Gao
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xiaogang Guo
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ruohan Chen
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yan Dai
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Keping Chen
- Arrhythmia Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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3
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Li J, Ma X, Yin C. Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases. Sci Rep 2024; 14:11814. [PMID: 38782984 PMCID: PMC11116402 DOI: 10.1038/s41598-024-62742-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 05/21/2024] [Indexed: 05/25/2024] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.
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Affiliation(s)
- Junhang Li
- Department of Ultrasonography, Dali Prefecture Third People's Hospital, Dali Prefecture, Yunnan Province, China
| | - Xiang Ma
- Chongqing Medical University, Chongqing, China
| | - Cuihua Yin
- Department of Ultrasonography, Dali Prefecture Third People's Hospital, Dali Prefecture, Yunnan Province, China.
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Yuan D, Wu J, Li S, Zhou X, Zhang R, Zhang Y. Causal relationships between serum albumin, neuroticism and suicidal ideation in depressed patients: A Mendelian randomization study. Heliyon 2024; 10:e30718. [PMID: 38765065 PMCID: PMC11098842 DOI: 10.1016/j.heliyon.2024.e30718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/28/2024] [Accepted: 05/02/2024] [Indexed: 05/21/2024] Open
Abstract
Although serum albumin and neuroticism have revealed a strong association with suicidal ideation in individuals with depression, the causal relationship between them is uncertain. This study analyzed the causal association of serum albumin, neuroticism and suicidal ideation using large-scale GWAS data and Univariable Mendelian Randomization (UVMR) methods. The Multivariable MR (MVMR) analysis was used to explore the causal pathways. UVMR analysis revealed that genetically determined serum albumin is causally associated with neuroticism (β = -0.006 S.D.; 95 % CI: 0.009, -0.002; p = 0.003) and suicidal ideation (β = 0.009 S.D.; 95 % CI: 0.001, 0.016; p = 0.037); and that neuroticism mediates 100 % of the causal association between serum albumin and suicidal ideation in individuals with depression. These findings suggest genetic evidence for the causal effect of serum albumin on suicidal ideation in depressed patients and the significant mediation effect of neuroticism on this causal association. This study proves the protective role of serum albumin for neuroticism and the riskiness of personality traits for suicidal ideation in individuals with depression.
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Affiliation(s)
- Dongling Yuan
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jialing Wu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shansi Li
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xiao Zhou
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ruoyi Zhang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yi Zhang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
- Medical Psychological Institute of Central South University, Central South University, Changsha, China
- National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
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Zhao Y, Pang J, Fang X, Yan Z, Yang H, Deng Q, Ma T, Lv M, Li Y, Tu Z, Zou L. Causal relationships between modifiable risk factors and polycystic ovary syndrome: a comprehensive Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1348368. [PMID: 38779450 PMCID: PMC11109383 DOI: 10.3389/fendo.2024.1348368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 04/15/2024] [Indexed: 05/25/2024] Open
Abstract
Background Polycystic Ovary Syndrome (PCOS) is a heritable condition with an as yet unclear etiology. Various factors, such as genetics, lifestyle, environment, inflammation, insulin resistance, hyperandrogenism, iron metabolism, and gut microbiota, have been proposed as potential contributors to PCOS. Nevertheless, a systematic assessment of modifiable risk factors and their causal effects on PCOS is lacking. This study aims to establish a comprehensive profile of modifiable risk factors for PCOS by utilizing a two-sample Mendelian Randomization (MR) framework. Methods After identifying over 400 modifiable risk factors, we employed a two-sample MR approach, including the Inverse Variance Weighted (IVW) method, Weighted Median method, and MR-Egger, to investigate their causal associations with PCOS. The reliability of our estimates underwent rigorous examination through sensitivity analyses, encompassing Cochran's Q test, MR-Egger intercept analysis, leave-one-out analysis, and funnel plots. Results We discovered that factors such as smoking per day, smoking initiation, body mass index, basal metabolic rate, waist-to-hip ratio, whole body fat mass, trunk fat mass, overall health rating, docosahexaenoic acid (DHA) (22:6n-3) in blood, monounsaturated fatty acids, other polyunsaturated fatty acids apart from 18:2 in blood, omega-3 fatty acids, ratio of bisallylic groups to double bonds, omega-9 and saturated fatty acids, total lipids in medium VLDL, phospholipids in medium VLDL, phospholipids in very large HDL, triglycerides in very large HDL, the genus Oscillibacter, the genus Alistipes, the genus Ruminiclostridium 9, the class Mollicutes, and the phylum Tenericutes, showed a significant effect on heightening genetic susceptibility of PCOS. In contrast, factors including fasting insulin interaction with body mass index, sex hormone-binding globulin, iron, ferritin, SDF1a, college or university degree, years of schooling, household income, the genus Enterorhabdus, the family Bifidobacteriaceae, the order Bifidobacteriales, the class Actinobacteria, and the phylum Actinobacteria were determined to reduce risk of PCOS. Conclusion This study innovatively employs the MR method to assess causal relationships between 400 modifiable risk factors and the susceptibility of PCOS risk. It supports causal links between factors like smoking, BMI, and various blood lipid levels and PCOS. These findings offer novel insights into potential strategies for the management and treatment of PCOS.
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Affiliation(s)
- Yuheng Zhao
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Jinglin Pang
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
- Department of Anorectal Surgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Xingyi Fang
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zhaohua Yan
- Department of Obstetrics and Gynecology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Haili Yang
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Qinghua Deng
- Department of Gynecology, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Tianzhong Ma
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Mengqi Lv
- Department of Pathology, Southwest Hospital of Army Medical University, Chongqing, China
| | - Yingying Li
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
- Department of Obstetrics and Gynecology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Ziying Tu
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
- The First School of Clinical Medicine, Graduate School of Guangdong Medical University, Zhanjiang, China
| | - Lin Zou
- Department of Reproductive Medicine, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
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Gjorgoska M, Rizner TL. The effect of androgens on the risk of endometriosis sub-phenotypes and ovarian neoplasms: A Mendelian randomization study. J Steroid Biochem Mol Biol 2024; 239:106482. [PMID: 38369034 DOI: 10.1016/j.jsbmb.2024.106482] [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: 01/05/2024] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/20/2024]
Abstract
Endometriosis is a complex gynecological pathology with a broad spectrum of symptoms, affecting around 10% of reproductive-aged women. Ovarian cancer (OC) is a heterogeneous disease for which we lack effective diagnostic and therapeutic strategies. The etiology and pathogenesis of both diseases remain ambiguous. Androgens in endometriosis could have a distinct role beyond serving as estrogen sources, whereas in the case of serous OC could be important in the formation of precursor lesions which ultimately lead to tumor formation. Here we performed two-sample Mendelian randomization (MR) analysis to examine the causal relationship between the androgen precursor - dehydroepiandrosterone sulphate (DHEAS), bioactive androgen - testosterone (T), androgen metabolite - androsterone sulphate, steroid hormone binding globulin (SHBG) and albumin and the risk of endometrioses of various sub-phenotypes and ovarian neoplasms across the benign-borderline-malignant spectrum. Stringent quality control procedures were followed to select eligible instrumental variables that were strongly associated with the selected exposures, sensitivity analyses were performed to assess the heterogeneities, horizontal pleiotropy, and stabilities of SNPs in endometriosis and ovarian neoplasms. We discovered an inverse association between genetically predicted levels of all androgens and risk of endometriosis, the same trend was most evident in the ovarian sub-phenotype. Total T levels were also inversely associated with peritoneal sub-phenotype of endometriosis. Likewise, T was causally associated with decreased risk of clear-cell OC, an endometriosis-associated OC subtype, and with malignant serous OC of both low- and high-grade, but with higher risk of their counterpart of low malignant potential. These findings support further investigation of androgen's action at a molecular level in ovary-associated endometriotic lesions, clear cell ovarian tumors and serous precursor lesions.
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Affiliation(s)
- Marija Gjorgoska
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tea Lanisnik Rizner
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
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Venkatesh SS, Wittemans LBL, Palmer DS, Baya NA, Ferreira T, Hill B, Lassen FH, Parker MJ, Reibe S, Elhakeem A, Banasik K, Bruun MT, Erikstrup C, Jensen BA, Juul A, Mikkelsen C, Nielsen HS, Ostrowski SR, Pedersen OB, Rohde PD, Sorensen E, Ullum H, Westergaard D, Haraldsson A, Holm H, Jonsdottir I, Olafsson I, Steingrimsdottir T, Steinthorsdottir V, Thorleifsson G, Figueredo J, Karjalainen MK, Pasanen A, Jacobs BM, Hubers N, Lippincott M, Fraser A, Lawlor DA, Timpson NJ, Nyegaard M, Stefansson K, Magi R, Laivuori H, van Heel DA, Boomsma DI, Balasubramanian R, Seminara SB, Chan YM, Laisk T, Lindgren CM. Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.19.24304530. [PMID: 38562841 PMCID: PMC10984039 DOI: 10.1101/2024.03.19.24304530] [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
Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.
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Affiliation(s)
- Samvida S Venkatesh
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Nikolas A Baya
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Teresa Ferreira
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Barney Hill
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Frederik Heymann Lassen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Melody J Parker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Saskia Reibe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - Bitten A Jensen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | - Anders Juul
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Copenhagen, Denmark
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Christina Mikkelsen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
| | - Henriette S Nielsen
- Department of Obstetrics and Gynecology, The Fertility Clinic, Hvidovre University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole B Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Kge, Denmark
| | - Palle D Rohde
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Erik Sorensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Asgeir Haraldsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Children's Hospital Iceland, Landspitali University Hospital, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Ingileif Jonsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Thora Steingrimsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Obstetrics and Gynecology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Jessica Figueredo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Minna K Karjalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Finland
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Anu Pasanen
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Benjamin M Jacobs
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, United Kingdom
| | - Nikki Hubers
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Margaret Lippincott
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mette Nyegaard
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Kari Stefansson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Reedik Magi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland
- Center for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Finland
| | - David A van Heel
- Blizard Institute, Queen Mary University London, London, E1 2AT, United Kingdom
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Ravikumar Balasubramanian
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Stephanie B Seminara
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yee-Ming Chan
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
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Ren Z, Long J, Deng W, Jing Y, Qiu J, Ren W, Liu D. Causal Relationship Between Sleep Traits and Hypothalamic-Pituitary-Target Gland Axis Function: A Mendelian Randomization Study. Nat Sci Sleep 2024; 16:155-175. [PMID: 38379755 PMCID: PMC10878316 DOI: 10.2147/nss.s442231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 02/04/2024] [Indexed: 02/22/2024] Open
Abstract
Background In recent years, multiple observational studies have confirmed the association between sleep traits and various human physiopathological states. However, the causal relationship between sleep traits and hypothalamic-pituitary-target gland axis (HPTGA) function remains unknown. Methods We obtained summary statistics on sleep traits (insomnia, chronotype, and sleep duration (long and short)) from the UK Biobank database. Data related to the HPTGA functions were obtained from the publicly available database. Subsequently, a two-sample Mendelian randomization (MR) analysis was performed to investigate the causal relationship between different sleep traits and the HPTGA function. Reverse MR analysis was conducted to examine the direction of causality. Results The MR analysis results suggested that chronotype is associated with decreased levels of six hormones in HPTGA. Sleep duration was causally associated with decreased levels of free thyroxine and progesterone. Both long and short sleep durations are detrimental to the secretion of prolactin-releasing peptide, somatostatin, and plasma cortisol, while short sleep duration can promote progesterone secretion. After gender stratification, we found that female reproductive function is more susceptible to the influence of unfavorable sleep traits. Conclusion Our MR analysis indicated a significant causal association between chronotype and suppressed gonadal function in healthy adult humans, with no apparent gender-specific effect. Extreme sleep durations were also found to be detrimental to the maintenance of normal HPTGA secretion function. Compared to males, gonadal function in the female cohort is more susceptible to extreme sleep habits. Subsequent observational studies are urgently needed to confirm the underlying mechanisms.
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Affiliation(s)
- Ziyu Ren
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Jiangchuan Long
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Wenzhen Deng
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Yuanyuan Jing
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Jingwen Qiu
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Wei Ren
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
| | - Dongfang Liu
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
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Xu M, Li J, Xu B, Zheng Q, Sun W. Association of coagulation markers with the severity of white matter hyperintensities in cerebral small vessel disease. Front Neurol 2024; 15:1331733. [PMID: 38390599 PMCID: PMC10883156 DOI: 10.3389/fneur.2024.1331733] [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: 11/06/2023] [Accepted: 01/22/2024] [Indexed: 02/24/2024] Open
Abstract
Background and purpose This study aimed to explore the correlation and causal relationship between fibrinogen, D-dimer, and the severity of cerebral white matter hyperintensity (MMH). Methods A retrospective analysis of 120 patients with cerebral small vessel disease (CSVD) confirmed by head MRI attending the Third Affiliated Hospital of Beijing University of Traditional Chinese Medicine from August 2021 to February 2023 was performed. According to the Fazekas scale score, the patients were divided into 42 cases in the mild group, 44 cases in the moderate group, and 34 cases in the severe group. The levels of fibrinogen and D-dimer were compared among the three groups; the correlations between fibrinogen, D-dimer, and WMH severity were further analyzed; and independent risk factors for WMH severity were explored using the multivariate ordered logistic regression analysis. Furthermore, a two-sample Mendelian randomization (MR) analysis was performed to investigate the genetically predicted effect of fibrinogen and D-dimer on WMH. Results As the severity of WMH increased, the levels of D-dimer and fibrinogen also gradually increased, and the results showed a positive correlational association, with significant differences within the groups (all p < 0.05); the multivariate ordered logistic regression model showed that after adjusting for the relevant covariates, D-dimer (OR = 5.998, 95% CI 2.213-16.252, p < 0.001) and fibrinogen (OR = 9.074, 95% CI 4.054-20.311, p < 0.001) remained independent risk factors for the severity of WMH. In the MR study, the random-effect inverse variance weighted (IVW) model showed that increased levels of genetically predicted D-dimer (OR, 1.01; 95% confidence interval 0.95-1.06; p = 0.81) and fibrinogen (OR, 1.91; 95% confidence interval 0.97-3.78; p = 0.06) were not associated with increased risk of WMH. The authors did not obtain strong evidence of a direct causal relationship between D-dimer, fibrinogen, and WMH. Conclusion In this retrospective-based study, the authors found possible associations between D-dimer, fibrinogen, and WMH, but there was no obvious causal evidence. Further efforts are still needed to investigate the pathophysiology between D-dimer, fibrinogen, and WMH.
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Affiliation(s)
- Mingyuan Xu
- Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Jingjing Li
- Yichang Traditional Chinese Medicine Hospital, Yichang, China
| | - Bu Xu
- Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Qin Zheng
- Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Wenjun Sun
- Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China
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10
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Huang Z, He G, Sun S, Huang Y. Causal relationship of genetically predicted particulate matter 2.5 level with Alzheimer's disease and the mediating effect of dehydroepiandrosterone sulphate. Ann Hum Biol 2024; 51:2337731. [PMID: 38634600 DOI: 10.1080/03014460.2024.2337731] [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: 10/01/2023] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND The causal association between particulate matter 2.5 (PM2.5) and Alzheimer's disease (AD) remains inconclusive, and the mediators of the association have yet to be explored. AIMS We aimed to assess the potential causal relationship between PM2.5 and AD, and to investigate the mediating role of dehydroepiandrosterone sulphate (DHEAS). SUBJECTS AND METHODS We implemented a two-sample Mendelian randomisation (MR) study to examine the genetic predisposition to PM2.5 exposure and its association with AD. The inverse-variance weighted (IVW) method served as the primary analytical tool to estimate the odds ratio (OR) and 95% confidence interval (95% CI). RESULTS There were 6 and 4 genetic variants associated with DHEAS and PM2.5, respectively. Based on the multivariable MR analysis, we found that after adjusting for DHEAS, each standard deviation increase in PM2.5 was associated with the risk of AD (OR: 2.96, 95% CI: 1.33, 6.58, p = 0.00769). The MR Egger intercept test did not detect horizontal pleiotropy for PM2.5 (P-pleiotropy = 0.879) and DHEAS(P-pleiotropy = 0.941). According to the results of the mediation analysis, DHEAS accounted for 18.3% of the association between PM2.5 and AD. CONCLUSION Our findings affirm a significant causal association between PM2.5 exposure and AD, with DHEAS playing a mediating role in this relationship.
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Affiliation(s)
- Zehan Huang
- Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Guodong He
- Research Department of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Shuo Sun
- Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yuqing Huang
- Department of Cardiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
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Hamilton OS, Iob E, Ajnakina O, Kirkbride JB, Steptoe A. Immune-neuroendocrine patterning and response to stress. A latent profile analysis in the English longitudinal study of ageing. Brain Behav Immun 2024; 115:600-608. [PMID: 37967661 DOI: 10.1016/j.bbi.2023.11.012] [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: 07/07/2023] [Revised: 10/10/2023] [Accepted: 11/11/2023] [Indexed: 11/17/2023] Open
Abstract
Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants, with a median age of 65 years, over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36 %, 40 %, and 24 % of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61 % greater risk of belonging to the high-risk profile (RRR: 1.61; 95 %CI = 1.23-2.12, p = 0.001), but not the moderate-risk profile (RRR = 1.10, 95 %CI = 0.89-1.35, p = 0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time.
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Affiliation(s)
- Odessa S Hamilton
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK; Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London, UK; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, UK.
| | - Eleonora Iob
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK; Social, Genetic & Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Memory Lane, London SE5 8AF, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, UK
| | - James B Kirkbride
- Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London, UK
| | - Andrew Steptoe
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
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12
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Zhao M, Lv H, Zhang Y, Zhao H, Qin H. Associations between genetically predicted sex and growth hormones and facial aging in the UK Biobank: a two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2023; 14:1239502. [PMID: 37916150 PMCID: PMC10616234 DOI: 10.3389/fendo.2023.1239502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 09/27/2023] [Indexed: 11/03/2023] Open
Abstract
Background Aging is an inescapable process, but it can be slowed down, particularly facial aging. Sex and growth hormones have been shown to play an important role in the process of facial aging. We investigated this association further, using a two-sample Mendelian randomization study. Methods We analyzed genome-wide association study (GWAS) data from the UK Biobank database comprising facial aging data from 432,999 samples, using two-sample Mendelian randomization. In addition, single-nucleotide polymorphism (SNP) data on sex hormone-binding globulin (SHBG) and sex steroid hormones were obtained from a GWAS in the UK Biobank [SHBG, N = 189,473; total testosterone (TT), N = 230,454; bioavailable testosterone (BT), N = 188,507; and estradiol (E2), N = 2,607)]. The inverse-variance weighted (IVW) method was the major algorithm used in this study, and random-effects models were used in cases of heterogeneity. To avoid errors caused by a single algorithm, we selected MR-Egger, weighted median, and weighted mode as supplementary algorithms. Horizontal pleiotropy was detected based on the intercept in the MR-Egger regression. The leave-one-out method was used for sensitivity analysis. Results SHBG plays a promoting role, whereas sex steroid hormones (TT, BT, and E2) play an inhibitory role in facial aging. Growth hormone (GH) and insulin-like growth factor-1 (IGF-1) levels had no significant effect on facial aging, which is inconsistent with previous findings in vitro. Conclusion Regulating the levels of SHBG, BT, TT, and E2 may be an important means to delay facial aging.
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Affiliation(s)
- Mingjian Zhao
- Graduate School, Dalian Medical University, Dalian, Liaoning, China
| | - Huiyun Lv
- Department of Oncology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yunshu Zhang
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hongliang Zhao
- Department of Burns and Plastic Surgery, Miyun Hospital, Capital Medical University, Beijing, China
| | - Hongzhi Qin
- Graduate School, Dalian Medical University, Dalian, Liaoning, China
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13
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Nordeidet AN, Klevjer M, Wisløff U, Langaas M, Bye A. Exploring shared genetics between maximal oxygen uptake and disease: the HUNT study. Physiol Genomics 2023; 55:440-451. [PMID: 37575066 DOI: 10.1152/physiolgenomics.00026.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 07/25/2023] [Accepted: 08/07/2023] [Indexed: 08/15/2023] Open
Abstract
Low cardiorespiratory fitness, measured as maximal oxygen uptake (V̇o2max), is associated with all-cause mortality and disease-specific morbidity and mortality and is estimated to have a large genetic component (∼60%). However, the underlying mechanisms explaining the associations are not known, and no association study has assessed shared genetics between directly measured V̇o2max and disease. We believe that identifying the mechanisms explaining how low V̇o2max is related to increased disease risk can contribute to prevention and therapy. We used a phenome-wide association study approach to test for shared genetics. A total of 64,479 participants from the Trøndelag Health Study (HUNT) were included. Genetic variants previously linked to V̇o2max were tested for association with diseases related to the cardiovascular system, diabetes, dementia, mental disorders, and cancer as well as clinical measurements and biomarkers from HUNT. In the total population, three single-nucleotide polymorphisms (SNPs) in and near the follicle-stimulating hormone receptor gene (FSHR) were found to be associated (false discovery rate < 0.05) with serum creatinine levels and one intronic SNP in the Rap-associating DIL domain gene (RADIL) with diabetes type 1 with neurological manifestations. In males, four intronic SNPs in the PBX/knotted homeobox 2 gene (PKNOX2) were found to be associated with endocarditis. None of the association tests in the female population reached overall statistical significance; the associations with the lowest P values included other cardiac conduction disorders, subdural hemorrhage, and myocarditis. The results might suggest shared genetics between V̇o2max and disease. However, further effort should be put into investigating the potential shared genetics between inborn V̇o2max and disease in larger cohorts to increase statistical power.NEW & NOTEWORTHY To our knowledge, this is the first genetic association study exploring how genes linked to cardiorespiratory fitness (CRF) relate to disease risk. By investigating shared genetics, we found indications that genetic variants linked to directly measured CRF also affect the level of blood creatinine, risk of diabetes, and endocarditis. Less certain findings showed that genetic variants of high CRF might cause lower body mass index, healthier HDL cholesterol, and lower resting heart rate.
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Affiliation(s)
- Ada N Nordeidet
- Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Marie Klevjer
- Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Cardiology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ulrik Wisløff
- Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Centre for Research on Exercise, Physical Activity and Health, School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Mette Langaas
- Department of Mathematical Sciences, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anja Bye
- Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Cardiology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
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Yan Z, Xu Y, Li K, Liu L. Association between genetically proxied HMGCR inhibition and male reproductive health: A Mendelian randomization study. Medicine (Baltimore) 2023; 102:e34690. [PMID: 37773823 PMCID: PMC10545124 DOI: 10.1097/md.0000000000034690] [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: 07/11/2023] [Accepted: 07/20/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND The causal associations between statin use and male sex hormone levels and related disorders have not been fully understood. In this study, we employed Mendelian randomization for the first time to investigate these associations. METHODS In two-sample Mendelian randomization framework, genetic proxies for hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition were identified as variants in the HMGCR gene that were associated with both levels of gene expression and low density lipoprotein cholesterol (LDL-C). We assessed the causal relationship between HMGCR inhibitor and 5 sex hormone levels/2 male-related diseases. Additionally, we investigated the association between 4 circulating lipid traits and outcomes. The "inverse variance weighting" method was used as the primary approach, and we assessed for potential heterogeneity and pleiotropy. In a secondary analysis, we revalidated the impact of HMGCR on 7 major outcomes using the summary-data-based Mendelian randomization method. RESULTS Our study found a significant causal association between genetic proxies for HMGCR inhibitor and decreased levels of total testosterone (TT) (LDL-C per standard deviation = 38.7mg/dL, effect = -0.20, 95% confidence interval [CI] = -0.25 to -0.15) and bioavailable testosterone (BT) (effect = -0.15, 95% CI = -0.21 to -0.10). Obesity-related factors were found to mediate this association. Furthermore, the inhibitor were found to mediate a reduced risk of prostate cancer (odds ratio = 0.81, 95%CI = 0.7-0.93) by lowering bioavailable testosterone levels, without increasing the risk of erectile dysfunction (P = .17). On the other hand, there was a causal association between increased levels of LDL-C, total cholesterol, triglycerides (TG) and decreased levels of TT, sex hormone-binding globulin, and estradiol. CONCLUSIONS The use of HMGCR inhibitor will reduce testosterone levels and the risk of prostate cancer without the side effect of erectile dysfunction. LDL-C, total cholesterol, and TG levels were protective factors for TT, sex hormone-binding globulin, and estradiol.
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Affiliation(s)
- Zhaoqi Yan
- Jiangxi University of Traditional Chinese Medicine, Graduate School, Nanchang, Jiangxi, China
| | - Yifeng Xu
- Jiangxi University of Traditional Chinese Medicine, Graduate School, Nanchang, Jiangxi, China
| | - Keke Li
- Jiangxi University of Traditional Chinese Medicine, Graduate School, Nanchang, Jiangxi, China
| | - Liangji Liu
- Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Pneumology Department, Nanchang, Jiangxi, China
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Hamilton OS, Iob E, Ajnakina O, Kirkbride JB, Steptoe A. Immune-Neuroendocrine Patterning and Response to Stress. A latent profile analysis in the English Longitudinal Study of Ageing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.07.23292378. [PMID: 37461452 PMCID: PMC10350138 DOI: 10.1101/2023.07.07.23292378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants with a median age of 65 years over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36%, 40%, and 24% of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61% greater risk of belonging to the high-risk profile (RRR: 1.61; 95%CI=1.23-2.12, p=0.001), but not the moderate-risk profile (RRR=1.10, 95%CI=0.89-1.35, p=0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time.
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Affiliation(s)
- Odessa S. Hamilton
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
- Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London, UK
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Eleonora Iob
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
- Social, Genetic & Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, Memory Lane, London SE5 8AF, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - James B. Kirkbride
- Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Road, London, UK
| | - Andrew Steptoe
- Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
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Sun Z, Ji J, Zuo L, Hu Y, Wang K, Xu T, Wang Q, Cheng F. Causal relationship between nonalcoholic fatty liver disease and different sleep traits: a bidirectional Mendelian randomized study. Front Endocrinol (Lausanne) 2023; 14:1159258. [PMID: 37334291 PMCID: PMC10272397 DOI: 10.3389/fendo.2023.1159258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 05/19/2023] [Indexed: 06/20/2023] Open
Abstract
Background and aims Non-alcoholic fatty liver disease(NAFLD) is common worldwide and has previously been reported to be associated with sleep traits. However, it is not clear whether NAFLD changes sleep traits or whether the changes in sleep traits lead to the onset of NAFLD. The purpose of this study was to investigate the causal relationship between NAFLD and changes in sleep traits using Mendelian randomization. Methods We proposed a bidirectional Mendelian randomization (MR) analysis and performed validation analyses to dissect the association between NAFLD and sleep traits. Genetic instruments were used as proxies for NAFLD and sleep. Data of genome-wide association study(GWAS) were obtained from the center for neurogenomics and cognitive research database, Open GWAS database and GWAS catalog. Three MR methods were performed, including inverse variance weighted method(IVW), MR-Egger, weighted median. Results In total,7 traits associated with sleep and 4 traits associated with NAFLD are used in this study. A total of six results showed significant differences. Insomnia was associated with NAFLD (OR(95% CI)= 2.25(1.18,4.27), P = 0.01), Alanine transaminase levels (OR(95% CI)= 2.79(1.70, 4.56), P =4.71×10-5) and percent liver fat(OR(95% CI)= 1.31(1.03,1.69), P = 0.03). Snoring was associated with percent liver fat (1.15(1.05,1.26), P =2×10-3), alanine transaminase levels (OR(95% CI)= 1.27(1.08,1.50), P =0.04).And dozing was associated with percent liver fat(1.14(1.02,1.26), P =0.02).For the remaining 50 outcomes, no significant or definitive association was yielded in MR analysis. Conclusion Genetic evidence suggests putative causal relationships between NAFLD and a set of sleep traits, indicating that sleep traits deserves high priority in clinical practice. Not only the confirmed sleep apnea syndrome, but also the sleep duration and sleep state (such as insomnia) deserve clinical attention. Our study proves that the causal relationship between sleep characteristics and NAFLD is the cause of the change of sleep characteristics, while the onset of non-NAFLD is the cause of the change of sleep characteristics, and the causal relationship is one-way.
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Petersen J, Englmaier L, Artemov AV, Poverennaya I, Mahmoud R, Bouderlique T, Tesarova M, Deviatiiarov R, Szilvásy-Szabó A, Akkuratov EE, Pajuelo Reguera D, Zeberg H, Kaucka M, Kastriti ME, Krivanek J, Radaszkiewicz T, Gömöryová K, Knauth S, Potesil D, Zdrahal Z, Ganji RS, Grabowski A, Buhl ME, Zikmund T, Kavkova M, Axelson H, Lindgren D, Kramann R, Kuppe C, Erdélyi F, Máté Z, Szabó G, Koehne T, Harkany T, Fried K, Kaiser J, Boor P, Fekete C, Rozman J, Kasparek P, Prochazka J, Sedlacek R, Bryja V, Gusev O, Adameyko I. A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology. Nat Commun 2023; 14:3092. [PMID: 37248239 DOI: 10.1038/s41467-023-38663-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 05/11/2023] [Indexed: 05/31/2023] Open
Abstract
In this study we use comparative genomics to uncover a gene with uncharacterized function (1700011H14Rik/C14orf105/CCDC198), which we hereby name FAME (Factor Associated with Metabolism and Energy). We observe that FAME shows an unusually high evolutionary divergence in birds and mammals. Through the comparison of single nucleotide polymorphisms, we identify gene flow of FAME from Neandertals into modern humans. We conduct knockout experiments on animals and observe altered body weight and decreased energy expenditure in Fame knockout animals, corresponding to genome-wide association studies linking FAME with higher body mass index in humans. Gene expression and subcellular localization analyses reveal that FAME is a membrane-bound protein enriched in the kidneys. Although the gene knockout results in structurally normal kidneys, we detect higher albumin in urine and lowered ferritin in the blood. Through experimental validation, we confirm interactions between FAME and ferritin and show co-localization in vesicular and plasma membranes.
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Affiliation(s)
- Julian Petersen
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany.
| | - Lukas Englmaier
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090, Vienna, Austria
- Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, 1090, Vienna, Austria
| | - Artem V Artemov
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Irina Poverennaya
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Ruba Mahmoud
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - Thibault Bouderlique
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Marketa Tesarova
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Ruslan Deviatiiarov
- Regulatory Genomics Research Center, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia
- Endocrinology Research Center, Moscow, Russia
| | - Anett Szilvásy-Szabó
- Laboratory of Integrative Neuroendocrinology, Institute of Experimental Medicine, 1083, Budapest, Hungary
| | - Evgeny E Akkuratov
- Department of Applied Physics, Royal Institute of Technology, Science for Life Laboratory, 171 65, Stockholm, Sweden
- University of Oxford, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, Oxford, OX3 9DS, UK
| | - David Pajuelo Reguera
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Hugo Zeberg
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Marketa Kaucka
- Max Planck Institute for Evolutionary Biology, Plön, 24306, Germany
| | - Maria Eleni Kastriti
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jan Krivanek
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Tomasz Radaszkiewicz
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Kristína Gömöryová
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Sarah Knauth
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - David Potesil
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Zbynek Zdrahal
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ranjani Sri Ganji
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Anna Grabowski
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Miriam E Buhl
- Institute of Pathology & Electron Microscopy Facility, RWTH Aachen University Hospital, Aachen, Germany
| | - Tomas Zikmund
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Michaela Kavkova
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Håkan Axelson
- Translational Cancer Research, Department of Laboratory Medicine, Lund University, Medicon Village, Scheelevägen 2, Lund, Sweden
| | - David Lindgren
- Translational Cancer Research, Department of Laboratory Medicine, Lund University, Medicon Village, Scheelevägen 2, Lund, Sweden
| | - Rafael Kramann
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Christoph Kuppe
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Ferenc Erdélyi
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Zoltán Máté
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Gábor Szabó
- Medical Gene Technology Unit, Institute of Experimental Medicine, Budapest, Hungary
| | - Till Koehne
- Department of Orthodontics, University Leipzig Medical Center, Leipzig, Germany
| | - Tibor Harkany
- Department of Molecular Neurosciences, Center for Brain Research, Medical University Vienna, Vienna, Austria
| | - Kaj Fried
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Jozef Kaiser
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic
| | - Peter Boor
- Institute of Pathology & Electron Microscopy Facility, RWTH Aachen University Hospital, Aachen, Germany
| | - Csaba Fekete
- Laboratory of Integrative Neuroendocrinology, Institute of Experimental Medicine, 1083, Budapest, Hungary
| | - Jan Rozman
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6, avenue du Swing, 4367, Belvaux, Luxembourg
| | - Petr Kasparek
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Jan Prochazka
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Radislav Sedlacek
- Institute of Molecular Genetics of the Czech Academy of Science, Czech Centre for Phenogenomics, Vestec, Czech Republic
| | - Vitezslav Bryja
- Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Oleg Gusev
- Endocrinology Research Center, Moscow, Russia
- Intractable Disease Research Center, Graduate School of Medicine, Juntendo University, Tokyo, Japan
- Center for Integrative Medical Sciences, RIKEN, Yokohama City, Kanagawa, Japan
| | - Igor Adameyko
- Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, Vienna, Austria.
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
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18
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Gibson MJ, Lawlor DA, Millard LAC. Identifying the potential causal role of insomnia symptoms on 11,409 health-related outcomes: a phenome-wide Mendelian randomisation analysis in UK Biobank. BMC Med 2023; 21:128. [PMID: 37013595 PMCID: PMC10071698 DOI: 10.1186/s12916-023-02832-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/13/2023] [Indexed: 04/05/2023] Open
Abstract
BACKGROUND Insomnia symptoms are widespread in the population and might have effects on many chronic conditions and their risk factors but previous research has focused on select hypothesised associations/effects rather than taking a systematic hypothesis-free approach across many health outcomes. METHODS We performed a Mendelian randomisation (MR) phenome-wide association study (PheWAS) in 336,975 unrelated white-British UK Biobank participants. Self-reported insomnia symptoms were instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). A total of 11,409 outcomes from UK Biobank were extracted and processed by an automated pipeline (PHESANT) for the MR-PheWAS. Potential causal effects (those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. RESULTS Four hundred thirty-seven potential causal effects of insomnia symptoms were observed for a diverse range of outcomes, including anxiety, depression, pain, body composition, respiratory, musculoskeletal and cardiovascular traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across main and sensitivity analyses) for 30 of these. These included novel findings (by which we mean not extensively explored in conventional observational studies and not previously explored using MR based on a systematic search) of an adverse effect on risk of spondylosis (OR [95%CI] = 1.55 [1.33, 1.81]) and bronchitis (OR [95%CI] = 1.12 [1.03, 1.22]), among others. CONCLUSIONS Insomnia symptoms potentially cause a wide range of adverse health-related outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.
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Affiliation(s)
- Mark J Gibson
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK.
- School of Psychological Science, University of Bristol, Bristol, UK.
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Louise A C Millard
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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19
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Zhai Z, Deng Y, He Y, Chen L, Chen X, Zuo L, Liu M, Mao M, Li S, Hu H, Chen H, Wei Y, Zhou Q, Hao G, Peng S. Association between serum calcium level and type 2 diabetes: An NHANES analysis and Mendelian randomization study. Diabet Med 2023:e15080. [PMID: 36883871 DOI: 10.1111/dme.15080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 03/09/2023]
Abstract
AIMS This study investigated the association between serum calcium levels and the prevalence of T2D using a cross-sectional study and Mendelian randomization analysis. METHODS Cross-sectional data were obtained from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. Serum calcium levels were divided into three groups (low, medium and high groups) according to the tertiles. Logistic regression was used to estimate the association between serum calcium levels and T2D prevalence. Instrumental variables for serum calcium levels were obtained from the UK Biobank and a two-sample MR analysis was performed to examine the causal relationship between genetically predicted serum calcium levels and the risk of T2D. RESULTS A total of 39,645 participants were available for cross-sectional analysis. After adjusting for covariates, participants in the high serum calcium group had significantly higher odds of T2D (OR = 1.18, 95% CI = 1.07, 1.30, p = 0.001) than those in the moderate group. Restricted cubic spline plots showed a J-shaped curve relationship between serum calcium level and prevalence of T2D. Consistently, Mendelian randomization analysis showed that higher genetically predicted serum calcium levels were causally associated with a higher risk of T2D (OR = 1.16, 95% CI: 1.01, 1.33, p = 0.031). CONCLUSIONS The results of this study suggest that higher serum calcium levels are causally associated with a higher risk of T2D. Further studies are needed to clarify whether intervening in high serum calcium could reduce the risk of T2D.
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Affiliation(s)
- Zhiyu Zhai
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Yun Deng
- Community Health Service Center of Xiagang Street, Guangzhou, China
| | - Yunbiao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Li Chen
- Department of Medicine, Medical College of Georgia, Georgia Prevention Institute, Augusta University, Augusta, Georgia, USA
| | - Xia Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Lei Zuo
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Mingliang Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Minzhi Mao
- Community Health Service Center of Xiagang Street, Guangzhou, China
| | - Sha Li
- Community Health Service Center of Xiagang Street, Guangzhou, China
| | - Haiping Hu
- Community Health Service Center of Xiagang Street, Guangzhou, China
| | - Haiyan Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yuan Wei
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Guangzhou Sport University, Guangzhou, China
| | - Qin Zhou
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Guang Hao
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- Guangdong Key Laboratory of Environmental Exposure and Health, Jinan University, Guangzhou, China
| | - Shuang Peng
- School of Sport and Health Sciences, Guangzhou Sport University, Guangzhou, China
- Key Laboratory of Sports Technique, Tactics and Physical Function of General Administration of Sport of China, Scientific Research Center, Guangzhou Sport University, Guangzhou, China
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20
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Nag A, Dhindsa RS, Middleton L, Jiang X, Vitsios D, Wigmore E, Allman EL, Reznichenko A, Carss K, Smith KR, Wang Q, Challis B, Paul DS, Harper AR, Petrovski S. Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank. Am J Hum Genet 2023; 110:487-498. [PMID: 36809768 PMCID: PMC10027475 DOI: 10.1016/j.ajhg.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/30/2023] [Indexed: 02/22/2023] Open
Abstract
Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.
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Affiliation(s)
- Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S Dhindsa
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX 77030, USA
| | - Lawrence Middleton
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Xiao Jiang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dimitrios Vitsios
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Eleanor Wigmore
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Erik L Allman
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Anna Reznichenko
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Katherine R Smith
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Benjamin Challis
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Andrew R Harper
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK; Early Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK; Department of Medicine, University of Melbourne, Austin Health, Melbourne, VIC, Australia.
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21
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Herrera-Rivero M, Hofer E, Maceski A, Leppert D, Benkert P, Kuhle J, Schmidt R, Khalil M, Wiendl H, Stoll M, Berger K. Evidence of polygenic regulation of the physiological presence of neurofilament light chain in human serum. Front Neurol 2023; 14:1145737. [PMID: 36970523 PMCID: PMC10030935 DOI: 10.3389/fneur.2023.1145737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 02/20/2023] [Indexed: 03/29/2023] Open
Abstract
Introduction The measurement of neurofilament light chain (NfL) in blood is a promising biomarker of neurological injury and disease. We investigated the genetic factors that underlie serum NfL levels (sNfL) of individuals without neurological conditions. Methods We performed a discovery genome-wide association study (GWAS) of sNfL in participants of the German BiDirect Study (N = 1,899). A secondary GWAS for meta-analysis was performed in a small Austrian cohort (N = 287). Results from the meta-analysis were investigated in relation with several clinical variables in BiDirect. Results Our discovery GWAS identified 12 genomic loci at the suggestive threshold ((p < 1 × 10-5). After meta-analysis, 7 loci were suggestive of an association with sNfL. Genotype-specific differences in sNfL were observed for the lead variants of meta-analysis loci (rs34523114, rs114956339, rs529938, rs73198093, rs34372929, rs10982883, and rs1842909) in BiDirect participants. We identified potential associations in meta-analysis loci with markers of inflammation and renal function. At least 6 protein-coding genes (ACTG2, TPRKB, DMXL1, COL23A1, NAT1, and RIMS2) were suggested as genetic factors contributing to baseline sNfL levels. Discussion Our findings suggest that polygenic regulation of neuronal processes, inflammation, metabolism and clearance modulate the variability of NfL in the circulation. These could aid in the interpretation of sNfL measurements in a personalized manner.
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Affiliation(s)
- Marisol Herrera-Rivero
- Department of Genetic Epidemiology, Institute of Human Genetics, University of Münster, Münster, Germany
- *Correspondence: Marisol Herrera-Rivero
| | - Edith Hofer
- Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Aleksandra Maceski
- Neurologic Clinic and Polyclinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital of Basel, Basel, Switzerland
| | - David Leppert
- Neurologic Clinic and Polyclinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital of Basel, Basel, Switzerland
| | - Pascal Benkert
- Clinical Trial Unit, Department of Clinical Research, University Hospital of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurologic Clinic and Polyclinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital of Basel, Basel, Switzerland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Michael Khalil
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Heinz Wiendl
- Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Monika Stoll
- Department of Genetic Epidemiology, Institute of Human Genetics, University of Münster, Münster, Germany
- Department of Biochemistry, Genetic Epidemiology and Statistical Genetics, Maastricht University, Maastricht, Netherlands
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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22
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Machlitt-Northen S, Keers R, Munroe PB, Howard DM, Pluess M. Polygenic risk scores for schizophrenia and major depression are associated with socio-economic indicators of adversity in two British community samples. Transl Psychiatry 2022; 12:477. [PMID: 36376270 PMCID: PMC9663827 DOI: 10.1038/s41398-022-02247-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 10/26/2022] [Accepted: 10/31/2022] [Indexed: 11/16/2022] Open
Abstract
Schizophrenia (SCZ) and major depressive disorder (MDD) are complex psychiatric disorders which contribute substantially to the global burden of disease. Both psychopathologies are heritable with some genetic overlap between them. Importantly, SCZ and MDD have also been found to be associated with environmental risk factors. However, rather than being independent of genetic influences, exposure to environmental risk factors may be under genetic control, known as gene-environment correlation (rGE). In this study we investigated rGE in relation to polygenic risk scores for SCZ and MDD in adults, derived from large genome-wide association studies, across two different British community samples: Understanding Society (USoc) and the National Child Development Study (NCDS). We tested whether established environmental risk factors for SCZ and/or MDD are correlated with polygenic scores in adults and whether these associations differ between the two disorders and cohorts. Findings partially overlapped between disorders and cohorts. In NCDS, we identified a significant correlation between the genetic risk for MDD and an indicator of low socio-economic status, but no significant findings emerged for SCZ. In USoc, we replicated associations between indicators of low socio-economic status and the genetic propensity for MDD. In addition, we identified associations between the genetic susceptibility for SCZ and being single or divorced. Results across both studies provide further evidence that the genetic risk for SCZ and MDD were associated with common environmental risk factors, specifically MDD's association with lower socio-economic status.
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Affiliation(s)
- Sandra Machlitt-Northen
- grid.4868.20000 0001 2171 1133Department of Biological and Experimental Psychology, Queen Mary University of London, London, UK
| | - Robert Keers
- grid.4868.20000 0001 2171 1133Department of Biological and Experimental Psychology, Queen Mary University of London, London, UK
| | - Patricia B. Munroe
- grid.4868.20000 0001 2171 1133Department of Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, UK
| | - David M. Howard
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK ,grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Michael Pluess
- Department of Biological and Experimental Psychology, Queen Mary University of London, London, UK.
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23
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Hodel F, Naret O, Bonnet C, Brenner N, Bender N, Waterboer T, Marques-Vidal P, Vollenweider P, Fellay J. The combined impact of persistent infections and human genetic variation on C-reactive protein levels. BMC Med 2022; 20:416. [PMID: 36320076 PMCID: PMC9623937 DOI: 10.1186/s12916-022-02607-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 10/13/2022] [Indexed: 01/24/2023] Open
Abstract
Multiple human pathogens establish chronic, sometimes life-long infections. Even if they are often latent, these infections can trigger some degree of local or systemic immune response, resulting in chronic low-grade inflammation. There remains an incomplete understanding of the potential contribution of both persistent infections and human genetic variation on chronic low-grade inflammation. We searched for potential associations between seropositivity for 13 persistent pathogens and the plasma levels of the inflammatory biomarker C-reactive protein (CRP), using data collected in the context of the UK Biobank and the CoLaus|PsyCoLaus Study, two large population-based cohorts. We performed backward stepwise regression starting with the following potential predictors: serostatus for each pathogen, polygenic risk score for CRP, and demographic and clinical factors known to be associated with CRP. We found evidence for an association between Chlamydia trachomatis (P-value = 5.04e - 3) and Helicobacter pylori (P-value = 8.63e - 4) seropositivity and higher plasma levels of CRP. We also found an association between pathogen burden and CRP levels (P-value = 4.12e - 4). These results improve our understanding of the relationship between persistent infections and chronic inflammation, an important determinant of long-term morbidity in humans.
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Affiliation(s)
- Flavia Hodel
- Global Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olivier Naret
- Global Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Clara Bonnet
- Global Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Nicole Brenner
- Division of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Noemi Bender
- Division of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Tim Waterboer
- Division of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jacques Fellay
- Global Health Institute, School of Life Sciences, EPFL, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Chen K, Zheng J, Shao C, Zhou Q, Yang J, Huang T, Tang YD. Causal effects of genetically predicted type 2 diabetes mellitus on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses: A two-sample Mendelian randomization study. Front Cardiovasc Med 2022; 9:965995. [PMID: 36312274 PMCID: PMC9606322 DOI: 10.3389/fcvm.2022.965995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 09/20/2022] [Indexed: 12/02/2022] Open
Abstract
Background Observational studies have shown inconsistent results of the associations between type 2 diabetes mellitus (T2DM) and blood lipid profiles, while there is also a lack of evidence from randomized controlled trials (RCTs) for the causal effects of T2DM on blood lipid profiles and lipoprotein subclasses. Objectives Our study aimed at investigating the causal effects of T2DM on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses by using the two-sample Mendelian randomization (MR) method. Methods We obtained genetic variants for T2DM and blood lipid profiles including high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from international genome-wide association studies (GWASs). Two-sample MR method was applied to explore the potential causal effects of genetically predicted T2DM on blood lipid profiles based on different databases, respectively, and results from each MR analysis were further meta-analyzed to obtain the summary results. The causal effects of genetically predicted T2DM on the concentration of different subclasses of lipoproteins that are determined by particle size were also involved in MR analysis. Results Genetically predicted 1-unit higher log odds of T2DM had a significant causal effect on a higher level of TG (estimated β coefficient: 0.03, 95% confidence interval [CI]: 0.00 to 0.06) and lower level of HDL-C (estimated β coefficient: −0.09, 95% CI: −0.11 to −0.06). The causality of T2DM on the level of TC or LDL-C was not found (estimated β coefficient: −0.01, 95% CI: −0.02 to 0.01 for TC and estimated β coefficient: 0.01, 95% CI: −0.01 to 0.02 for LDL-C). For different sizes of lipoprotein particles, 1-unit higher log odds of T2DM was causally associated with higher level of small LDL particles, and lower level of medium HDL particles, large HDL particles, and very large HDL particles. Conclusion Evidence from our present study showed causal effects of T2DM on the level of TG, HDL-C, and concentration of different particle sizes of lipoprotein subclasses comprehensively, which might be particularly helpful in illustrating dyslipidemia experienced by patients with T2DM, and further indicate new treatment targets for these patients to prevent subsequent excessive cardiovascular events from a genetic point of view.
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Affiliation(s)
- Ken Chen
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jilin Zheng
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
| | - Chunli Shao
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qing Zhou
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Yang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tao Huang
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China,Department of Global Health, School of Public Health, Peking University, Beijing, China,Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
| | - Yi-Da Tang
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,*Correspondence: Yi-Da Tang
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25
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Nounu A, Kar SP, Relton CL, Richmond RC. Sex steroid hormones and risk of breast cancer: a two-sample Mendelian randomization study. Breast Cancer Res 2022; 24:66. [PMID: 36209141 PMCID: PMC9548139 DOI: 10.1186/s13058-022-01553-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 08/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Breast cancer (BC) has the highest cancer incidence and mortality in women worldwide. Observational epidemiological studies suggest a positive association between testosterone, estradiol, dehydroepiandrosterone sulphate (DHEAS) and other sex steroid hormones with postmenopausal BC. We used a two-sample Mendelian randomization analysis to investigate this association. METHODS Genetic instruments for nine sex steroid hormones and sex hormone-binding globulin (SHBG) were obtained from genome-wide association studies (GWAS) of UK Biobank (total testosterone (TT) N: 230,454, bioavailable testosterone (BT) N: 188,507 and SHBG N: 189,473), The United Kingdom Household Longitudinal Study (DHEAS N: 9722), the LIFE-Adult and LIFE-Heart cohorts (estradiol N: 2607, androstenedione N: 711, aldosterone N: 685, progesterone N: 1259 and 17-hydroxyprogesterone N: 711) and the CORtisol NETwork (CORNET) consortium (cortisol N: 25,314). Outcome GWAS summary statistics were obtained from the Breast Cancer Association Consortium (BCAC) for overall BC risk (N: 122,977 cases and 105,974 controls) and subtype-specific analyses. RESULTS We found that a standard deviation (SD) increase in TT, BT and estradiol increased the risk of overall BC (OR 1.14, 95% CI 1.09-1.21, OR 1.19, 95% CI 1.07-1.33 and OR 1.03, 95% CI 1.01-1.06, respectively) and ER + BC (OR 1.19, 95% CI 1.12-1.27, OR 1.25, 95% CI 1.11-1.40 and OR 1.06, 95% CI 1.03-1.09, respectively). An SD increase in DHEAS also increased ER + BC risk (OR 1.09, 95% CI 1.03-1.16). Subtype-specific analyses showed similar associations with ER+ expressing subtypes: luminal A-like BC, luminal B-like BC and luminal B/HER2-negative-like BC. CONCLUSIONS TT, BT, DHEAS and estradiol increase the risk of ER+ type BCs similar to observational studies. Understanding the role of sex steroid hormones in BC risk, particularly subtype-specific risks, highlights the potential importance of attempts to modify and/or monitor hormone levels in order to prevent BC.
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Affiliation(s)
- Aayah Nounu
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Siddhartha P Kar
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
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Çildağ MB, Şahin T, Ceylan E, Şavk ŞÖ. The Effect of Atherosclerotic Load on Transmetatarsal Amputation Failure in Patients with Diabetic Foot. MEANDROS MEDICAL AND DENTAL JOURNAL 2022. [DOI: 10.4274/meandros.galenos.2022.68815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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27
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Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations. BMC Med Genomics 2022; 15:192. [PMID: 36088317 PMCID: PMC9464371 DOI: 10.1186/s12920-022-01352-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 09/02/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations. METHODS Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals. RESULTS Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation. CONCLUSIONS Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.
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Cupido AJ, Reeskamp LF, Hingorani AD, Finan C, Asselbergs FW, Hovingh GK, Schmidt AF. Joint Genetic Inhibition of PCSK9 and CETP and the Association With Coronary Artery Disease: A Factorial Mendelian Randomization Study. JAMA Cardiol 2022; 7:955-964. [PMID: 35921096 PMCID: PMC9350849 DOI: 10.1001/jamacardio.2022.2333] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 05/29/2022] [Indexed: 12/30/2022]
Abstract
Importance Cholesteryl ester transfer protein inhibition (CETP) has been shown to increase levels of high-density lipoprotein cholesterol (HDL-C) and reduce levels of low-density lipoprotein cholesterol (LDL-C). Current LDL-C target attainment is low, and novel phase 3 trials are underway to investigate whether CETP inhibitors result in reduction of cardiovascular disease risk in high-risk patients who may be treated with PCSK9-inhibiting agents. Objective To explore the associations of combined reduction of CETP and PCSK9 concentrations with risk of coronary artery disease (CAD) and other clinical and safety outcomes. Design, Setting, and Participants Two-sample 2 × 2 factorial Mendelian randomization study in a general population sample that includes data for UK Biobank participants of European ancestry. Exposures Separate genetic scores were constructed for CETP and PCSK9 plasma protein concentrations, which were combined to determine the associations of combined genetically reduced CETP and PCSK9 concentrations with disease. Main Outcomes and Measures Blood lipid and lipoprotein concentrations, blood pressure, CAD, age-related macular degeneration, type 2 diabetes, any stroke and ischemic stroke, Alzheimer disease, vascular dementia, heart failure, atrial fibrillation, chronic kidney disease, asthma, and multiple sclerosis. Results Data for 425 354 UKB participants were included; the median (IQR) age was 59 years (51-64), and 229 399 (53.9%) were female. The associations of lower CETP and lower PCSK9 concentrations with CAD are similar when scaled per 10-mg/dL reduction in LDL-C concentrations (CETP: odds ratio [OR], 0.74; 95% CI, 0.67 to 0.81; PCSK9: OR, 0.75; 95% CI, 0.71 to 0.79). Combined exposure to lower CETP and PCSK9 concentrations was associated with an additive magnitude with lipids and all outcomes, and we did not observe any nonadditive interactions, most notably for LDL-C (CETP: effect size, -1.11 mg/dL; 95% CI, -1.40 to -0.82; PCSK9: effect size, -2.13 mg/dL; 95% CI, -2.43 to -1.84; combined: effect size, -3.47 mg/dL; 95% CI, -3.76 to -3.18; P = .34 for interaction) and CAD (CETP: OR, 0.96; 95% CI, 0.94 to 1.00; PCSK9: OR, 0.94; 95% CI, 0.91 to 0.97; combined: OR, 0.90; 95% CI, 0.87 to 0.93; P = .83 for interaction). In addition, when corrected for multiple testing, lower CETP concentrations were associated with increased age-related macular degeneration (OR, 1.11; 95% CI, 1.04 to 1.19). Conclusions and Relevance Our results suggest that joint inhibition of CETP and PCSK9 has additive effects on lipid traits and disease risk, including a lower risk of CAD. Further research may explore whether a combination of CETP- and PCSK9-related therapeutics can benefit high-risk patients who are unable to reach treatment targets with existing options.
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Affiliation(s)
- Arjen J. Cupido
- Amsterdam UMC location, University of Amsterdam, Department of Vascular Medicine, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, the Netherlands
- Division of Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Division of Cardiology, Department of Medicine, University of California, Los Angeles
| | - Laurens F. Reeskamp
- Amsterdam UMC location, University of Amsterdam, Department of Vascular Medicine, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, the Netherlands
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
| | - Chris Finan
- Division of Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
| | - Folkert W. Asselbergs
- Division of Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
| | - G. Kees Hovingh
- Amsterdam UMC location, University of Amsterdam, Department of Vascular Medicine, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Atherosclerosis & Ischemic Syndromes, Amsterdam, the Netherlands
| | - Amand F. Schmidt
- Division of Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
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Li GHY, Cheung CL, Chung AKK, Cheung BMY, Wong ICK, Fok MLY, Au PCM, Sham PC. Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study. Psychol Med 2022; 52:1765-1776. [PMID: 33032663 DOI: 10.1017/s0033291720003566] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Depression and cardiovascular disease (CVD) are associated with each other but their relationship remains unclear. We aim to determine whether genetic predisposition to depression are causally linked to CVD [including coronary artery disease (CAD), myocardial infarction (MI), stroke and atrial fibrillation (AF)]. METHODS Using summary statistics from the largest genome-wide association studies (GWAS) or GWAS meta-analysis of depression (primary analysis: n = 500 199), broad depression (help-seeking behavior for problems with nerves, anxiety, tension or depression; secondary analysis: n = 322 580), CAD (n = 184 305), MI (n = 171 875), stroke (n = 446 696) and AF (n = 1 030 836), genetic correlation was tested between two depression phenotypes and CVD [MI, stroke and AF (not CAD as its correlation was previously confirmed)]. Causality was inferred between correlated traits by Mendelian Randomization analyses. RESULTS Both depression phenotypes were genetically correlated with MI (depression: rG = 0.169; p = 9.03 × 10-9; broad depression: rG = 0.123; p = 1 × 10-4) and AF (depression: rG = 0.112; p = 7.80 × 10-6; broad depression: rG = 0.126; p = 3.62 × 10-6). Genetically doubling the odds of depression was causally associated with increased risk of CAD (OR = 1.099; 95% CI 1.031-1.170; p = 0.004) and MI (OR = 1.146; 95% CI 1.070-1.228; p = 1.05 × 10-4). Adjustment for blood lipid levels/smoking status attenuated the causality between depression and CAD/MI. Null causal association was observed for CVD on depression. A similar pattern of results was observed in the secondary analysis for broad depression. CONCLUSIONS Genetic predisposition to depression may have positive causal roles on CAD/MI. Genetic susceptibility to self-awareness of mood problems may be a strong causal risk factor of CAD/MI. Blood lipid levels and smoking may potentially mediate the causal pathway. Prevention and early diagnosis of depression are important in the management of CAD/MI.
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Affiliation(s)
- Gloria Hoi-Yee Li
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Ching-Lung Cheung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Albert Kar-Kin Chung
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Bernard Man-Yung Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Ian Chi-Kei Wong
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
| | - Marcella Lei Yee Fok
- Central and North West London NHS Foundation Trust, London, UK
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Philip Chun-Ming Au
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Pak-Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong
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Machlitt-Northen S, Keers R, Munroe PB, Howard DM, Pluess M. Gene–Environment Correlation over Time: A Longitudinal Analysis of Polygenic Risk Scores for Schizophrenia and Major Depression in Three British Cohorts Studies. Genes (Basel) 2022; 13:genes13071136. [PMID: 35885920 PMCID: PMC9320197 DOI: 10.3390/genes13071136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/12/2022] [Accepted: 06/16/2022] [Indexed: 11/16/2022] Open
Abstract
Research suggests that both genetic and environmental risk factors are involved in the aetiology of schizophrenia (SCZ) and major depressive disorder (MDD). Importantly, environmental and genetic risk factors are often related as evidenced in gene–environment correlation (rGE), which describes the observation that genetic and environmental factors are associated with each other. It is understood that rGE gets stronger over time as individuals select their environments more actively based on their genetic propensities. However, little is known whether rGEs remain stable over time or change across different development periods. Using data from three British longitudinal cohorts, we investigated whether rGE patterns of polygenic risk scores (PRS) for SCZ and MDD changed over time across childhood and adulthood, as well as across both from birth to age 55 and whether results differed between SCZ and MDD. Overall, the majority of rGEs remained stable across the investigated development periods. Furthermore, the few detected rGE changes which did differ between SCZ and MDD, could not be explained by the confounding of clinical cases and are therefore likely the result of actual changes in environmental and cultural risk factors with genetic susceptibility to SCZ and MDD likely playing a less significant role.
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Affiliation(s)
- Sandra Machlitt-Northen
- Department of Biological and Experimental Psychology, Queen Mary University of London, London E1 4NS, UK;
| | - Robert Keers
- Department of Biological and Experimental Psychology, Queen Mary University of London, London E1 4NS, UK;
| | - Patricia B. Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK;
| | - David M. Howard
- Social, Genetic and Developmental Psychiatry Centre, King’s College London, London SE5 8AF, UK;
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Michael Pluess
- Department of Biological and Experimental Psychology, Queen Mary University of London, London E1 4NS, UK;
- Correspondence: ; Tel.: +44-(0)207-882-8004
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31
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Gene-lifestyle interactions in the genomics of human complex traits. Eur J Hum Genet 2022; 30:730-739. [PMID: 35314805 PMCID: PMC9178041 DOI: 10.1038/s41431-022-01045-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/22/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
The role and biological significance of gene-environment interactions in human traits and diseases remain poorly understood. To address these questions, the CHARGE Gene-Lifestyle Interactions Working Group conducted series of genome-wide interaction studies (GWIS) involving up to 610,475 individuals across four ancestries for three lipids and four blood pressure traits, while accounting for interaction effects with drinking and smoking exposures. Here we used GWIS summary statistics from these studies to decipher potential differences in genetic associations and G×E interactions across phenotype-exposure-ancestry combinations, and to derive insights on the potential mechanistic underlying G×E through in-silico functional analyses. Our analyses show first that interaction effects likely contribute to the commonly reported ancestry-specific genetic effect in complex traits, and second, that some phenotype-exposures pairs are more likely to benefit from a greater detection power when accounting for interactions. It also highlighted modest correlation between marginal and interaction effects, providing material for future methodological development and biological discussions. We also estimated contributions to phenotypic variance, including in particular the genetic heritability conditional on the exposure, and heritability partitioned across a range of functional annotations and cell types. In these analyses, we found multiple instances of potential heterogeneity of functional partitions between exposed and unexposed individuals, providing new evidence for likely exposure-specific genetic pathways. Finally, along this work, we identified potential biases in methods used to jointly meta-analyze genetic and interaction effects. We performed simulations to characterize these limitations and to provide the community with guidelines for future G×E studies.
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32
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Choudhury A, Brandenburg JT, Chikowore T, Sengupta D, Boua PR, Crowther NJ, Agongo G, Asiki G, Gómez-Olivé FX, Kisiangani I, Maimela E, Masemola-Maphutha M, Micklesfield LK, Nonterah EA, Norris SA, Sorgho H, Tinto H, Tollman S, Graham SE, Willer CJ, Hazelhurst S, Ramsay M. Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits. Nat Commun 2022; 13:2578. [PMID: 35546142 PMCID: PMC9095599 DOI: 10.1038/s41467-022-30098-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 04/18/2022] [Indexed: 12/30/2022] Open
Abstract
Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10−8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10−8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data. Genetic associations and polygenic scores for lipid traits have low transferability to African individuals. Here, the authors perform a large sub-Sarahan African lipid GWAS and find that larger datasets and better global representation in discovery GWAS help to bridge this gap.
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Affiliation(s)
- Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Jean-Tristan Brandenburg
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Dhriti Sengupta
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Palwende Romuald Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Nigel J Crowther
- Department of Chemical Pathology, National Health Laboratory Service, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Godfred Agongo
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana.,C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
| | - Gershim Asiki
- African Population and Health Research Center, Nairobi, Kenya
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Eric Maimela
- Department of Public Health, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Matshane Masemola-Maphutha
- Department of Pathology and Medical Sciences, School of Health Care Sciences, Faculty of Health Sciences, University of Limpopo, Polokwane, South Africa
| | - Lisa K Micklesfield
- South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Shane A Norris
- South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Hermann Sorgho
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Halidou Tinto
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santè, Nanoro, Burkina Faso
| | - Stephen Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA.,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48019, USA
| | | | | | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. .,Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
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Hazelwood E, Sanderson E, Tan VY, Ruth KS, Frayling TM, Dimou N, Gunter MJ, Dossus L, Newton C, Ryan N, Pournaras DJ, O'Mara TA, Davey Smith G, Martin RM, Yarmolinsky J. Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis. BMC Med 2022; 20:125. [PMID: 35436960 PMCID: PMC9017004 DOI: 10.1186/s12916-022-02322-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/03/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR. METHODS Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10-8) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR. RESULTS In MR analyses, there was strong evidence that BMI (OR per standard deviation (SD) increase 1.88, 95% CI 1.69 to 2.09, P = 3.87 × 10-31), total testosterone (OR per inverse-normal transformed nmol/L increase 1.64, 95% CI 1.43 to 1.88, P = 1.71 × 10-12), bioavailable testosterone (OR per natural log transformed nmol/L increase: 1.46, 95% CI 1.29 to 1.65, P = 3.48 × 10-9), fasting insulin (OR per natural log transformed pmol/L increase: 3.93, 95% CI 2.29 to 6.74, P = 7.18 × 10-7) and sex hormone-binding globulin (SHBG, OR per inverse-normal transformed nmol/L increase 0.71, 95% CI 0.59 to 0.85, P = 2.07 × 10-4) had a causal effect on endometrial cancer risk. Additionally, there was suggestive evidence that total serum cholesterol (OR per mg/dL increase 0.90, 95% CI 0.81 to 1.00, P = 4.01 × 10-2) had an effect on endometrial cancer risk. In mediation analysis, we found evidence for a mediating role of fasting insulin (19% total effect mediated, 95% CI 5 to 34%, P = 9.17 × 10-3), bioavailable testosterone (15% mediated, 95% CI 10 to 20%, P = 1.43 × 10-8) and SHBG (7% mediated, 95% CI 1 to 12%, P = 1.81 × 10-2) in the relationship between BMI and endometrial cancer risk. CONCLUSIONS Our comprehensive MR analysis provides insight into potential causal mechanisms linking BMI with endometrial cancer risk and suggests targeting of insulinemic and hormonal traits as a potential strategy for the prevention of endometrial cancer.
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Affiliation(s)
- Emma Hazelwood
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Vanessa Y Tan
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Katherine S Ruth
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Niki Dimou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Claire Newton
- Department of Gynecology, St Michaels Hospital University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Neil Ryan
- Department of Gynecology, St Michaels Hospital University Hospitals Bristol NHS Foundation Trust, Bristol, UK
- The Academic Women's Health Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Dimitri J Pournaras
- Department of Upper GI and Bariatric/Metabolic Surgery, North Bristol NHS Trust, Southmead Hospital, Bristol, UK
| | - Tracy A O'Mara
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - James Yarmolinsky
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Bristol Medical School, University of Bristol, Bristol, UK.
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Miranda JP, Lardone MC, Rodríguez F, Cutler GB, Santos JL, Corvalán C, Pereira A, Mericq V. Genome-Wide Association Study and Polygenic Risk Scores of Serum DHEAS Levels in a Chilean Children Cohort. J Clin Endocrinol Metab 2022; 107:e1727-e1738. [PMID: 34748635 DOI: 10.1210/clinem/dgab814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Adrenarche reflects the developmental growth of the adrenal zona reticularis, which produces increasing adrenal androgen secretion (eg, dehydroepiandrosterone [DHEA]/dehydroepiandrosterone sulfate [DHEAS]) from approximately age 5 to 15 years. OBJECTIVE We hypothesized that the study of the genetic determinants associated with variations in serum DHEAS during adrenarche might detect genetic variants influencing the rate or timing of this process. METHODS Genome-wide genotyping was performed in participants of the Chilean pediatric Growth and Obesity Chilean Cohort Study (GOCS) cohort (n = 788). We evaluated the genetic determinants of DHEAS levels at the genome-wide level and in targeted genes associated with steroidogenesis. To corroborate our findings, we evaluated a polygenic risk score (PRS) for age at pubarche, based on the discovered variants, in children from the same cohort. RESULTS We identified one significant variant at the genome-wide level in the full cohort, close to the GALR1 gene (P = 3.81 × 10-8). In addition, variants suggestive of association (P < 1 × 10-5) were observed in PRLR, PITX1, PTPRD, NR1H4, and BCL11B. Stratifying by sex, we found variants suggestive of association in SERBP1 and CAMTA1/VAMP3 for boys and near ZNF98, TRPC6, and SULT2A1 for girls. We also found significant reductions in age at pubarche in those children with higher PRS for greater DHEAS based on these newly identified variants. CONCLUSION Our results disclose one variant associated with DHEAS concentrations at the level of genome-wide association study significance, and several variants with a suggestive association that may be involved in the genetic regulation of adrenarche.
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Affiliation(s)
- José Patricio Miranda
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Advanced Center for Chronic Diseases (ACCDiS), Pontificia Universidad Católica de Chile & Universidad de Chile, Santiago, Chile
| | - María Cecilia Lardone
- Institute of Maternal and Child Research, School of Medicine, Universidad de Chile, Santiago, Chile
| | - Fernando Rodríguez
- Institute of Maternal and Child Research, School of Medicine, Universidad de Chile, Santiago, Chile
| | | | - José Luis Santos
- Department of Nutrition, Diabetes, and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Camila Corvalán
- Institute of Nutrition and Food Technology (INTA), Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Ana Pereira
- Institute of Nutrition and Food Technology (INTA), Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Verónica Mericq
- Institute of Maternal and Child Research, School of Medicine, Universidad de Chile, Santiago, Chile
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Metz S, Krarup NT, Bryrup T, Støy J, Andersson EA, Christoffersen C, Neville MJ, Christiansen MR, Jonsson AE, Witte DR, Kampmann U, Nielsen LB, Jørgensen NR, Karpe F, Grarup N, Pedersen O, Kilpeläinen TO, Hansen T. The Arg82Cys polymorphism of the protein nepmucin implies a role in HDL metabolism. J Endocr Soc 2022; 6:bvac034. [PMID: 35382499 PMCID: PMC8974852 DOI: 10.1210/jendso/bvac034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Indexed: 12/02/2022] Open
Abstract
Context Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG, is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive. Objective Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism. Methods We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status. Results A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB (P = .004) and RbG studies (P = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 (P = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels. Conclusion Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation.
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Affiliation(s)
- Sophia Metz
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nikolaj T Krarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Aalborg University Hospital, Department of Cardiology, Aalborg, Denmark
| | - Thomas Bryrup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Julie Støy
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Ehm A Andersson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christina Christoffersen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matt J Neville
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Malene R Christiansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anna E Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Daniel R Witte
- Department of Public Health, Section of Epidemiology, Aarhus University, Denmark
| | - Ulla Kampmann
- Aarhus University Hospital, Steno Diabetes Center Aarhus, Aarhus, Denmark
| | - Lars B Nielsen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Faculty of Health, Aarhus University, Aarhus, Denmark
| | - Niklas R Jørgensen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen Denmark
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health, University of Southern Denmark, Odense, Denmark
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Chen K, Zhuang Z, Shao C, Zheng J, Zhou Q, Dong E, Huang T, Tang YD. Roles of Cardiometabolic Factors in Mediating the Causal Effect of Type 2 Diabetes on Cardiovascular Diseases: A Two-Step, Two-Sample Multivariable Mendelian Randomization Study. Front Cardiovasc Med 2022; 9:813208. [PMID: 35282373 PMCID: PMC8909643 DOI: 10.3389/fcvm.2022.813208] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/17/2022] [Indexed: 12/17/2022] Open
Abstract
ObjectiveThe objective of this study is to investigate the roles of cardiometabolic factors (including blood pressure, blood lipids, thyroid function, body mass, and insulin sensitivity) in mediating the causal effect of type 2 diabetes (T2DM) on cardiovascular disease (CVD) outcomes.DesignTwo-step, two-sample multivariable Mendelian randomization (MVMR) study.SettingInternational genome-wide association study (GWAS) consortia data.ExposureType 2 diabetes, blood pressure: systolic blood pressure (SBP), diastolic blood pressure (DBP); blood lipids: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), triglycerides (TG); thyroid function: hyperthyroidism, hypothyroidism; body mass index (BMI), waist-hip-ratio (WHR), and insulin sensitivity.Main OutcomesCardiovascular disease includes coronary heart disease (CHD), myocardial infarction (MI), and stroke.MethodsSummary-level data for exposures and main outcomes were extracted from GWAS consortia. We used two-sample MR to illustrate the causal effect of T2DM on CVD subtypes and regression-based MVMR to quantify the possible mediation effects of cardiometabolic factors on CVD.ResultsEach additional unit of log odds of T2DM increased 16% risk of CHD [odds ratio (OR): 1.16, 95% CI: 1.12–1.21], 15% risk of myocardial infarction (MI) (OR: 1.15, 95% CI: 1.10–1.20), and 10% risk of stroke (OR: 1.10, 95% CI: 1.06–1.13). In mediation analysis, SBP, DBP, and TG were found as main mediators, while the mediation effects of other cardiometabolic factors were not significant. The proportion of total effect of T2DM on CHD mediated by SBP, DBP, and TG was 16% (95% CI: 8–24%), 7% (95% CI: 1–13%) and 10% (95% CI: 2–18%), respectively. Mediation effect of SBP and DBP on MI and stroke, TG on MI was also prominent, while mediation effect of TG on stroke was not significant. The combined mediation effect of all the three mediators accounted for 29%, 26%, and 13% of the total effect of T2DM on CHD, MI, and stroke, respectively.ConclusionSystolic blood pressure, DBP, and TG mediate a substantial proportion of the causal effect of T2DM on CVD and thus interventions on these factors might reduce the considerable excess risk of CVD among patients with T2DM.
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Affiliation(s)
- Ken Chen
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunli Shao
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China
| | - Jilin Zheng
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qing Zhou
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Erdan Dong
- Department of Cardiology and Institute of Vascular Medicine, NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, The Institute of Cardiovascular Sciences, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Department of Global Health, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China
- Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
| | - Yi-Da Tang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China
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Yarmolinsky J, Díez-Obrero V, Richardson TG, Pigeyre M, Sjaarda J, Paré G, Walker VM, Vincent EE, Tan VY, Obón-Santacana M, Albanes D, Hampe J, Gsur A, Hampel H, Pai RK, Jenkins M, Gallinger S, Casey G, Zheng W, Amos CI, Smith GD, Martin RM, Moreno V. Genetically proxied therapeutic inhibition of antihypertensive drug targets and risk of common cancers: A mendelian randomization analysis. PLoS Med 2022; 19:e1003897. [PMID: 35113855 PMCID: PMC8812899 DOI: 10.1371/journal.pmed.1003897] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 12/21/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Epidemiological studies have reported conflicting findings on the potential adverse effects of long-term antihypertensive medication use on cancer risk. Naturally occurring variation in genes encoding antihypertensive drug targets can be used as proxies for these targets to examine the effect of their long-term therapeutic inhibition on disease outcomes. METHODS AND FINDINGS We performed a mendelian randomization analysis to examine the association between genetically proxied inhibition of 3 antihypertensive drug targets and risk of 4 common cancers (breast, colorectal, lung, and prostate). Single-nucleotide polymorphisms (SNPs) in ACE, ADRB1, and SLC12A3 associated (P < 5.0 × 10-8) with systolic blood pressure (SBP) in genome-wide association studies (GWAS) were used to proxy inhibition of angiotensin-converting enzyme (ACE), β-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC), respectively. Summary genetic association estimates for these SNPs were obtained from GWAS consortia for the following cancers: breast (122,977 cases, 105,974 controls), colorectal (58,221 cases, 67,694 controls), lung (29,266 cases, 56,450 controls), and prostate (79,148 cases, 61,106 controls). Replication analyses were performed in the FinnGen consortium (1,573 colorectal cancer cases, 120,006 controls). Cancer GWAS and FinnGen consortia data were restricted to individuals of European ancestry. Inverse-variance weighted random-effects models were used to examine associations between genetically proxied inhibition of these drug targets and risk of cancer. Multivariable mendelian randomization and colocalization analyses were employed to examine robustness of findings to violations of mendelian randomization assumptions. Genetically proxied ACE inhibition equivalent to a 1-mm Hg reduction in SBP was associated with increased odds of colorectal cancer (odds ratio (OR) 1.13, 95% CI 1.06 to 1.22; P = 3.6 × 10-4). This finding was replicated in the FinnGen consortium (OR 1.40, 95% CI 1.02 to 1.92; P = 0.035). There was little evidence of association of genetically proxied ACE inhibition with risk of breast cancer (OR 0.98, 95% CI 0.94 to 1.02, P = 0.35), lung cancer (OR 1.01, 95% CI 0.92 to 1.10; P = 0.93), or prostate cancer (OR 1.06, 95% CI 0.99 to 1.13; P = 0.08). Genetically proxied inhibition of ADRB1 and NCC were not associated with risk of these cancers. The primary limitations of this analysis include the modest statistical power for analyses of drug targets in relation to some less common histological subtypes of cancers examined and the restriction of the majority of analyses to participants of European ancestry. CONCLUSIONS In this study, we observed that genetically proxied long-term ACE inhibition was associated with an increased risk of colorectal cancer, warranting comprehensive evaluation of the safety profiles of ACE inhibitors in clinical trials with adequate follow-up. There was little evidence to support associations across other drug target-cancer risk analyses, consistent with findings from short-term randomized controlled trials for these medications.
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Affiliation(s)
- James Yarmolinsky
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Virginia Díez-Obrero
- Biomarkers and Susceptibility Unit, Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Tom G. Richardson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Marie Pigeyre
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada
| | - Jennifer Sjaarda
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Canada
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Ontario, Canada
| | - Venexia M. Walker
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Emma E. Vincent
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
| | - Vanessa Y. Tan
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mireia Obón-Santacana
- Biomarkers and Susceptibility Unit, Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Jochen Hampe
- Department of Medicine I, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Andrea Gsur
- Institute of Cancer Research, Department of Medicine I, Medical University Vienna, Vienna, Austria
| | - Heather Hampel
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, United States of America
| | - Rish K. Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, Arizona, United States of America
| | - Mark Jenkins
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Australia
| | - Steven Gallinger
- Division of General Surgery, University Health Network, University of Toronto, Toronto, Canada
| | - Graham Casey
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Wei Zheng
- Division of Epidemiology, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Christopher I. Amos
- Department of Medicine, Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas, United States of America
| | | | | | | | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Richard M. Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- University Hospitals Bristol, NHS Foundation Trust, National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, Bristol, United Kingdom
| | - Victor Moreno
- Biomarkers and Susceptibility Unit, Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
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Westerman KE, Lin J, Sevilla-Gonzalez MDR, Tadess B, Marchek C, Manning AK. Gene-Environment Interaction Analysis Incorporating Sex, Cardiometabolic Diseases, and Multiple Deprivation Index Reveals Novel Genetic Associations With COVID-19 Severity. Front Genet 2022; 12:782172. [PMID: 35096005 PMCID: PMC8790169 DOI: 10.3389/fgene.2021.782172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 12/07/2021] [Indexed: 01/20/2023] Open
Abstract
Increasing evidence indicates that specific genetic variants influence the severity of outcomes after infection with COVID-19. However, it is not clear whether the effect of these genetic factors is independent of the risk due to more established non-genetic demographic and metabolic risk factors such as male sex, poor cardiometabolic health, and low socioeconomic status. We sought to identify interactions between genetic variants and non-genetic risk factors influencing COVID-19 severity via a genome-wide interaction study in the UK Biobank. Of 378,051 unrelated individuals of European ancestry, 2,402 were classified as having experienced severe COVID-19, defined as hospitalization or death due to COVID-19. Exposures included sex, cardiometabolic risk factors [obesity and type 2 diabetes (T2D), tested jointly], and multiple deprivation index. Multiplicative interaction was tested using a logistic regression model, conducting both an interaction test and a joint test of genetic main and interaction effects. Five independent variants reached genome-wide significance in the joint test, one of which also reached significance in the interaction test. One of these, rs2268616 in the placental growth factor (PGF) gene, showed stronger effects in males and in individuals with T2D. None of the five variants showed effects on a similarly-defined phenotype in a lookup in the COVID-19 Host Genetics Initiative. These results reveal potential additional genetic loci contributing to COVID-19 severity and demonstrate the value of including non-genetic risk factors in an interaction testing approach for genetic discovery.
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Affiliation(s)
- Kenneth E. Westerman
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Joanna Lin
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
| | - Magdalena del Rocio Sevilla-Gonzalez
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Beza Tadess
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States
| | - Casey Marchek
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, United States
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
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Na-Ek N, Srithong J, Aonkhum A, Boonsom S, Charoen P, Demakakos P. Educational level as a cause of type 2 diabetes mellitus: Caution from triangulation of observational and genetic evidence. Acta Diabetol 2022; 59:127-135. [PMID: 34514530 PMCID: PMC8968222 DOI: 10.1007/s00592-021-01795-7] [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: 07/20/2021] [Accepted: 08/27/2021] [Indexed: 01/03/2023]
Abstract
UNLABELLED BACKGROUND AND OBJECTIVE: Education might be causal to type 2 diabetes mellitus (T2DM). We triangulated cohort and genetic evidence to consolidate the causality between education and T2DM. METHODS We obtained observational evidence from the English Longitudinal Study of Ageing (ELSA). Self-reporting educational attainment was categorised as high (post-secondary and higher), middle (secondary), and low (below secondary or no academic qualifications) in 6,786 community-dwelling individuals aged ≥ 50 years without diabetes at ELSA wave 2, who were followed until wave 8 for the first diabetes diagnosis. Additionally, we performed two-sample Mendelian randomisation (MR) using an inverse-variance weighted (IVW), MR-Egger, weighted median (WM), and weighted mode-based estimate (WMBE) method. Steiger filtering was further applied to exclude single-nucleotide polymorphisms (SNPs) that were correlated with an outcome (T2DM) stronger than exposure (education attainment). RESULTS We observed 598 new diabetes cases after 10.4 years of follow-up. The adjusted hazard ratios (95% CI) of T2DM were 1.20 (0.97-1.49) and 1.58 (1.28-1.96) in the middle- and low-education groups, respectively, compared to the high-education group. Low education was also associated with increased glycated haemoglobin levels. Psychosocial resources, occupation, and health behaviours fully explained these inverse associations. In the MR analysis of 210 SNPs (R2 = 0.0161), the odds ratio of having T2DM per standard deviation-decreasing years (4.2 years) of schooling was 1.33 (1.01-1.75; IVW), 1.23 (0.37-4.17; MR-Egger), 1.56 (1.09-2.27; WM), and 2.94 (0.98-9.09; WMBE). However, applying Steiger filtering attenuated most MR results towards the null. CONCLUSIONS Our inconsistent findings between cohort and genetic evidence did not support the causality between education and T2DM.
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Affiliation(s)
- Nat Na-Ek
- Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand.
- Unit of Excellence On Research in Health Outcomes and Patient Safety in Elderly (U-R-HOPE), School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand.
| | - Juthamanee Srithong
- Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand
| | - Authakorn Aonkhum
- Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand
| | - Suthida Boonsom
- Department of Pharmaceutical Care, School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand
- Unit of Excellence On Pharmacogenomic Pharmacokinetic and Pharmacotherapeutic Researches (UPPER), School of Pharmaceutical Sciences, University of Phayao, Phayao, 56000, Thailand
| | - Pimphen Charoen
- Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, 10400, Thailand
- Integrative Computational BioScience (ICBS) Center, Mahidol University, Bangkok, 10400, Thailand
| | - Panayotes Demakakos
- Department of Epidemiology and Public Health, University College London, London, WC1E 7HB, UK
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Zhang L, Liu W, Sun W, Wang X, Tian M, Pei LL, Liu K, Liang J, Zhou L, Lu J, Ning M, Buonanno FS, Xu Y, Song B. Heart Failure and Ischemic Stroke: A Bidirectional and Multivariable Mendelian Randomization Study. Front Genet 2021; 12:771044. [PMID: 34912375 PMCID: PMC8666512 DOI: 10.3389/fgene.2021.771044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/08/2021] [Indexed: 12/17/2022] Open
Abstract
Background: Heart failure (HF) is a potential cause of ischemic stroke (IS), and previous studies have reported an association between HF and IS. This study aimed to analyze the causal link between HF and IS using bidirectional and multivariable Mendelian randomization (MR) studies. Methods: Genetic variants significantly associated with HF and IS were selected in the MR analysis from two large genome-wide association studies. Bidirectional and multivariable MR analyses were performed to evaluate the effect of HF on IS or the effect of IS on HF. Results: Two-sample MR analysis showed causal effects of HF on IS of all causes [odds ratio (OR) = 1.555, 95% confidence interval (CI): 1.343–1.799, p = 3.35 × 10−9] and large artery atherosclerosis stroke (LAS) (OR = 1.678, 95% CI: 1.044–2.696, p = 3.03 × 10−5), while there was a suggestive effect of HF on cardioembolic stroke (CES) (OR = 3.355, 95% CI: 1.031–10.919, p = 0.044). Genetically predicted HF was not associated with small artery occlusion stroke. Bidirectional MR analysis showed causal effects of IS of all causes (OR = 1.211, 95% CI: 1.040–1.410, p = 0.014) and CES (OR = 1.277, 95% CI: 1.213–1.344, p = 6.73 × 10−21) on HF, while there were no causal effects of LAS on HF. Conclusion: This MR analysis provided evidence of the causal links between genetically predicted HF and IS. Subgroup analysis highlighted the causal or suggestive relationship between genetically predicted HF and LAS or CES. The potential causal links need further investigation with genetic information about other ancestries or etiologies of HF.
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Affiliation(s)
- Luyang Zhang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Weishi Liu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China.,Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenxian Sun
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Xin Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Mengke Tian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Lu-Lu Pei
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Kai Liu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Jing Liang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Lue Zhou
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Jie Lu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Mingming Ning
- Clinical Proteomics Research Center and Cardio-Neurology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Ferdinando S Buonanno
- Clinical Proteomics Research Center and Cardio-Neurology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Yuming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
| | - Bo Song
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Cerebrovascular Diseases, Zhengzhou, China
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Hakim A, Moll M, Brancale J, Liu J, Lasky-Su JA, Silverman EK, Vilarinho S, Jiang ZG, Pita-Juárez YH, Vlachos IS, Zhang X, Åberg F, Afdhal NH, Hobbs BD, Cho MH. Genetic Variation in the Mitochondrial Glycerol-3-Phosphate Acyltransferase Is Associated With Liver Injury. Hepatology 2021; 74:3394-3408. [PMID: 34216018 PMCID: PMC8639615 DOI: 10.1002/hep.32038] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 06/17/2021] [Accepted: 06/28/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND AND AIMS Most of the genetic basis of chronic liver disease remains undiscovered. APPROACH AND RESULTS To identify genetic loci that modulate the risk of liver injury, we performed genome-wide association studies on circulating levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and total bilirubin across 312,671 White British participants in the UK Biobank. We focused on variants associated with elevations in all four liver biochemistries at genome-wide significance (P < 5 × 10-8 ) and that replicated using Mass General Brigham Biobank in 19,323 European ancestry individuals. We identified a genetic locus in mitochondrial glycerol-3-phosphate acyltransferase (GPAM rs10787429) associated with increased levels of ALT (P = 1.4 × 10-30 ), AST (P = 3.6 × 10-10 ), ALP (P = 9.5 × 10-30 ), and total bilirubin (P = 2.9 × 10-12 ). This common genetic variant was also associated with an allele dose-dependent risk of alcohol-associated liver disease (odd ratio [OR] = 1.34, P = 2.6 × 10-5 ) and fatty liver disease (OR = 1.18, P = 5.8 × 10-4 ) by International Classification of Diseases, 10th Revision codes. We identified significant interactions between GPAM rs10787429 and elevated body mass index in association with ALT and AST (P = 7.1 × 10-9 and 3.95 × 10-8 , respectively), as well as between GPAM rs10787429 and weekly alcohol consumption in association with ALT, AST, and alcohol-associated liver disease (P = 4.0 × 10-2 , 1.6 × 10-2 , and 1.3 × 10-2 , respectively). Unlike previously described genetic variants that are associated with an increased risk of liver injury but confer a protective effect on circulating lipids, GPAM rs10787429 was associated with an increase in total cholesterol (P = 2.0 × 10-17 ), LDL cholesterol (P = 2.0 × 10-10 ), and HDL cholesterol (P = 6.6 × 10-37 ). Single-cell RNA-sequencing data demonstrated hepatocyte-predominant expression of GPAM in cells that co-express genes related to VLDL production (P = 9.4 × 10-103 ). CONCLUSIONS Genetic variation in GPAM is associated with susceptibility to liver injury. GPAM may represent a therapeutic target in chronic liver disease.
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Affiliation(s)
- Aaron Hakim
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center, Boston, MA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
| | - Matthew Moll
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA
| | - Joseph Brancale
- Departments of Internal Medicine, Section of Digestive Diseases, and of Pathology, Yale School of Medicine, New Haven, CT
| | - Jiangyuan Liu
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
| | - Jessica A. Lasky-Su
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA
| | - Silvia Vilarinho
- Departments of Internal Medicine, Section of Digestive Diseases, and of Pathology, Yale School of Medicine, New Haven, CT
| | - Z. Gordon Jiang
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Ioannis S. Vlachos
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
| | - Fredrik Åberg
- Transplantation and Liver Surgery Clinic, Helsinki University Hospital, Helsinki, Finland
| | - Nezam H. Afdhal
- Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center, Boston, MA
| | - Brian D. Hobbs
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA
| | - Michael H. Cho
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA
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Genetic overlap and causality between blood metabolites and migraine. Am J Hum Genet 2021; 108:2086-2098. [PMID: 34644541 DOI: 10.1016/j.ajhg.2021.09.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/17/2021] [Indexed: 12/11/2022] Open
Abstract
The availability of genome-wide association studies (GWASs) for human blood metabolome provides an excellent opportunity for studying metabolism in a heritable disease such as migraine. Utilizing GWAS summary statistics, we conduct comprehensive pairwise genetic analyses to estimate polygenic genetic overlap and causality between 316 unique blood metabolite levels and migraine risk. We find significant genome-wide genetic overlap between migraine and 44 metabolites, mostly lipid and organic acid metabolic traits (FDR < 0.05). We also identify 36 metabolites, mostly related to lipoproteins, that have shared genetic influences with migraine at eight independent genomic loci (posterior probability > 0.9) across chromosomes 3, 5, 6, 9, and 16. The observed relationships between genetic factors influencing blood metabolite levels and genetic risk for migraine suggest an alteration of metabolite levels in individuals with migraine. Our analyses suggest higher levels of fatty acids, except docosahexaenoic acid (DHA), a very long-chain omega-3, in individuals with migraine. Consistently, we found a causally protective role for a longer length of fatty acids against migraine. We also identified a causal effect for a higher level of a lysophosphatidylethanolamine, LPE(20:4), on migraine, thus introducing LPE(20:4) as a potential therapeutic target for migraine.
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The Transition Period Updated: A Review of the New Insights into the Adaptation of Dairy Cows to the New Lactation. DAIRY 2021. [DOI: 10.3390/dairy2040048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Recent research on the transition period (TP) of dairy cows has highlighted the pivotal role of immune function in affecting the severity of metabolic challenges the animals face when approaching calving. This suggests that the immune system may play a role in the etiology of metabolic diseases occurring in early lactation. Several studies have indicated that the roots of immune dysfunctions could sink way before the “classical” TP (e.g., 3 weeks before and 3 weeks after calving), extending the time frame deemed as “risky” for the development of early lactation disorders at the period around the dry-off. Several distressing events occurring during the TP (i.e., dietary changes, heat stress) can boost the severity of pre-existing immune dysfunctions and metabolic changes that physiologically affect this phase of the lactation cycle, further increasing the likelihood of developing diseases. Based on this background, several operational and nutritional strategies could be adopted to minimize the detrimental effects of immune dysfunctions on the adaptation of dairy cows to the new lactation. A suitable environment (i.e., optimal welfare) and a balanced diet (which guarantees optimal nutrient partitioning to improve immune functions in cow and calf) are key aspects to consider when aiming to minimize TP challenges at the herd level. Furthermore, several prognostic behavioral and physiological indicators could help in identifying subjects that are more likely to undergo a “bad transition”, allowing prompt intervention through specific modulatory treatments. Recent genomic advances in understanding the linkage between metabolic disorders and the genotype of dairy cows suggest that genetic breeding programs aimed at improving dairy cows’ adaptation to the new lactation challenges (i.e., through increasing immune system efficiency or resilience against metabolic disorders) could be expected in the future. Despite these encouraging steps forward in understanding the physiological mechanisms driving metabolic responses of dairy cows during their transition to calving, it is evident that these processes still require further investigation, and that the TP—likely extended from dry-off—continues to be “the final frontier” for research in dairy sciences.
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Yokomoto-Umakoshi M, Umakoshi H, Iwahashi N, Matsuda Y, Kaneko H, Ogata M, Fukumoto T, Terada E, Nakano Y, Sakamoto R, Ogawa Y. Protective Role of DHEAS in Age-related Changes in Bone Mass and Fracture Risk. J Clin Endocrinol Metab 2021; 106:e4580-e4592. [PMID: 34415029 DOI: 10.1210/clinem/dgab459] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE Dehydroepiandrosterone sulfate (DHEAS) from the adrenal cortex substantially decreases with age, which may accelerate osteoporosis. However, the association of DHEAS with bone mineral density (BMD) and fracture is inconclusive. We conducted a Mendelian randomization (MR) analysis to investigate the role of DHEAS in age-related changes in BMD and fracture risk. METHODS Single nucleotide polymorphisms (SNPs) associated with serum DHEAS concentrations were used as instrumental variables (4 SNPs for main analysis; 4 SNPs for men and 5 SNPs for women in sex-related analysis). Summary statistics were obtained from relevant genome-wide association studies. RESULTS A log-transformed unit (µmol/L) increase in serum DHEAS concentrations was associated with an SD increase in estimated BMD at the heel (estimate, 0.120; 95% CI, 0.081-0.158; P = 9 × 10-10), and decreased fracture (odds ratio, 0.989; 95% CI, 0.981-0.996; P = 0.005), consistent with dual-energy X-ray absorptiometry-derived BMD at the femoral neck and lumbar spine. Their associations remained even after adjusting for height, body mass index, testosterone, estradiol, sex hormone-binding globulin, and insulin-like growth factor 1. The association of DHEAS with fracture remained after adjusting for falls, grip strength, and physical activity but was attenuated after adjusting for BMD. The MR-Bayesian model averaging analysis showed BMD was the top mediating factor for association of DHEAS with fracture. The association between DHEAS and BMD was observed in men but not in women. CONCLUSION DHEAS was associated with increased BMD and decreased fracture. DHEAS may play a protective role in decreasing fracture risk, mainly by increasing bone mass.
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Affiliation(s)
- Maki Yokomoto-Umakoshi
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hironobu Umakoshi
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Norifusa Iwahashi
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yayoi Matsuda
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hiroki Kaneko
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masatoshi Ogata
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tazuru Fukumoto
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Eriko Terada
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yui Nakano
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Ryuichi Sakamoto
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshihiro Ogawa
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Wang J, Conti DV, Bogumil D, Sheng X, Noureddin M, Wilkens LR, Le Marchand L, Rosen HR, Haiman CA, Setiawan VW. Association of Genetic Risk Score With NAFLD in An Ethnically Diverse Cohort. Hepatol Commun 2021; 5:1689-1703. [PMID: 34558842 PMCID: PMC8485887 DOI: 10.1002/hep4.1751] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 05/03/2021] [Indexed: 12/15/2022] Open
Abstract
Most genetic studies of nonalcoholic fatty liver disease (NAFLD) have been conducted in Whites. In this large and ethnically diverse cohort, we assessed the transportability of previously identified genetic variants for NAFLD, built a genetic risk score (GRS), and examined its association with NAFLD risk in multiple ethnic groups. Thirty previously identified genome-wide association studies (GWAS) variants (P < 5 × 10-8 ) and 17 other variants associated with NAFLD were examined in a nested case-control study of NAFLD (1,448 cases/8,444 controls) in this multi-ethnic cohort study. We then built a GRS using 11 independent single-nucleotide polymorphisms from these prior studies and examined its association with NAFLD by cirrhosis status across multiple ethnic groups. Of the 30 GWAS SNPs, 20 (67%) were replicated (P < 0.05) in the pooled multi-ethnic population. The highest percentage of replication was seen in Latinos (43%), followed by Japanese Americans (37%), Whites (17%), and Native Hawaiians and African Americans (≤10%). Several genetic variants, including those in PNPLA3 (patatin-like phospholipase domain containing 3), HSD17B13 (hydroxysteroid 17-beta dehydrogenase 13), TM6SF2 (transmembrane 6 superfamily member 2), GATAD2A (GATA zinc finger domain containing 2A), GCKR (glucokinase regulator), SUGP1 (SURP and G-patch domain containing 1), MBOAT7 (membrane bound O-acyltransferase domain containing 7), TRIB1 (tribbles pseudokinase 1), SAMM50 (sorting and assembly machinery component), and ERLIN1 (ER lipid raft associated 1)-CHUK (component of inhibitor of nuclear factor kappa B kinase complex)-CWF19L1 (CWF19 like cell cycle control factor 1) gene cluster, were replicated in at least two ethnic groups. An 11-SNP weighted GRS was associated with NAFLD risk in the multi-ethnic population (odds ratio [OR] per SD increase = 1.41; 95% confidence interval [CI] = 1.32-1.50), as well as in each ethnic group (OR ranged from 1.30 in African Americans to 1.52 in Latinos). The GRS-NAFLD association was stronger for NAFLD with cirrhosis (OR = 1.67; 95% CI = 1.46-1.92) compared to NAFLD without cirrhosis (OR = 1.37; 95% CI = 1.28-1.46) (P heterogeneity = 0.003). Conclusion: In this ethnically diverse cohort, we replicated several key genetic variants for NAFLD and showed the utility of GRS based on the risk alleles for NAFLD risk stratification in multiple ethnic groups.
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Affiliation(s)
- Jun Wang
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - David V. Conti
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
- Center for Genetic EpidemiologyKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCAUSA
- Norris Comprehensive Cancer CenterKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - David Bogumil
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - Xin Sheng
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - Mazen Noureddin
- Division of Gastroenterology and HepatologyDepartment of MedicineCedars‐Sinai Medical CenterLos AngelesCAUSA
| | - Lynne R. Wilkens
- Epidemiology ProgramUniversity of Hawaii Cancer CenterHonoluluHIUSA
| | - Loic Le Marchand
- Epidemiology ProgramUniversity of Hawaii Cancer CenterHonoluluHIUSA
| | - Hugo R. Rosen
- Department of MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - Christopher A. Haiman
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
- Center for Genetic EpidemiologyKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCAUSA
- Norris Comprehensive Cancer CenterKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
| | - Veronica Wendy Setiawan
- Department of Preventive MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
- Center for Genetic EpidemiologyKeck School of MedicineUniversity of Southern CaliforniaLos AngelesCAUSA
- Norris Comprehensive Cancer CenterKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
- Department of MedicineKeck School of Medicine of University of Southern CaliforniaLos AngelesCAUSA
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Kosinski P, Kedzia M, Mostowska A, Gutaj P, Lipa M, Wender-Ozegowska E, Rozy A, Chorostowska-Wynimko J, Wielgos M, Jezela-Stanek A. Alpha-1 Antitrypsin Z Variant (AAT PI*Z) as a Risk Factor for Intrahepatic Cholestasis of Pregnancy. Front Genet 2021; 12:720465. [PMID: 34557220 PMCID: PMC8454405 DOI: 10.3389/fgene.2021.720465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 07/27/2021] [Indexed: 11/18/2022] Open
Abstract
Background: Intrahepatic cholestasis of pregnancy (ICP; prevalence 0.2–15.6%) is the most common pregnancy-related liver disorder. It may have serious consequences for a pregnancy, including increased risk of preterm delivery, meconium staining of amniotic fluid, fetal bradycardia, distress, and fetal demise. In cases of high bile acids (>100μmol/L), patients have 10-fold increase in the risk of stillbirth. Biophysical methods of fetal monitoring, such as cardiotocography, ultrasonography, or Doppler have been proven unreliable for risk prediction in the course of intrahepatic cholestasis. Therefore, we believe extensive research for more specific, especially early, markers should be carried out. By analogy with cholestasis in children with inherited alpha-1 antitrypsin deficiency (AATD), we hypothesized the SERPINA1 Z pathogenic variant might be related to a higher risk of cholestasis in pregnancy. This study aimed to investigate the most common AATD variants (Z and S SERPINA1 alleles) in a group of cholestatic pregnant women. Results: The Z carrier frequency was calculated to be 6.8%, which is much higher compared to the general population [2.3%; the Chi-squared test with Yates correction is 6.8774 (p=0.008)]. Conclusion: Increased prevalence of SERPINA1 PI*Z variant in a group of women with intrahepatic cholestasis may suggest a possible genetic origin of a higher risk of intrahepatic cholestasis in pregnancy.
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Affiliation(s)
- Przemyslaw Kosinski
- First Department of Obstetrics and Gynecology, Medical University of Warsaw, Warsaw, Poland.,"Club 35", Scientific Group of Polish Society of Obstetricians and Gynaecologists, Warsaw, Poland
| | - Malgorzata Kedzia
- Division of Reproduction, Department of Obstetrics, Gynecology, and Gynecologic Oncology, Poznan University of Medical Sciences, Poznań, Poland
| | - Adrianna Mostowska
- Department of Biochemistry and Molecular Biology, Poznan University of Medical Sciences, Poznań, Poland
| | - Pawel Gutaj
- "Club 35", Scientific Group of Polish Society of Obstetricians and Gynaecologists, Warsaw, Poland.,Division of Reproduction, Department of Obstetrics, Gynecology, and Gynecologic Oncology, Poznan University of Medical Sciences, Poznań, Poland
| | - Michal Lipa
- First Department of Obstetrics and Gynecology, Medical University of Warsaw, Warsaw, Poland.,"Club 35", Scientific Group of Polish Society of Obstetricians and Gynaecologists, Warsaw, Poland
| | - Ewa Wender-Ozegowska
- Division of Reproduction, Department of Obstetrics, Gynecology, and Gynecologic Oncology, Poznan University of Medical Sciences, Poznań, Poland
| | - Adriana Rozy
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - Joanna Chorostowska-Wynimko
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - Miroslaw Wielgos
- First Department of Obstetrics and Gynecology, Medical University of Warsaw, Warsaw, Poland
| | - Aleksandra Jezela-Stanek
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
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47
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Gao C, Marcketta A, Backman JD, O'Dushlaine C, Staples J, Ferreira MAR, Lotta LA, Overton JD, Reid JG, Mirshahi T, Regeneron Genetics Center, Geisinger Regeneron Discovehr Collaboration, Baras A, Abecasis G, Shuldiner AR, Van Hout CV, McCarthy S. Genome-wide association analysis of serum alanine and aspartate aminotransferase, and the modifying effects of BMI in 388k European individuals. Genet Epidemiol 2021; 45:664-681. [PMID: 34184762 PMCID: PMC8457092 DOI: 10.1002/gepi.22392] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/17/2021] [Accepted: 05/17/2021] [Indexed: 12/21/2022]
Abstract
Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are biomarkers for liver health. Here we report the largest genome-wide association analysis to date of serum ALT and AST levels in over 388k people of European ancestry from UK biobank and DiscovEHR. Eleven million imputed markers with a minor allele frequency (MAF) ≥ 0.5% were analyzed. Overall, 300 ALT and 336 AST independent genome-wide significant associations were identified. Among them, 81 ALT and 61 AST associations are reported for the first time. Genome-wide interaction study identified 9 ALT and 12 AST independent associations significantly modified by body mass index (BMI), including several previously reported potential liver disease therapeutic targets, for example, PNPLA3, HSD17B13, and MARC1. While further work is necessary to understand the effect of ALT and AST-associated variants on liver disease, the weighted burden of significant BMI-modified signals is significantly associated with liver disease outcomes. In summary, this study identifies genetic associations which offer an important step forward in understanding the genetic architecture of serum ALT and AST levels. Significant interactions between BMI and genetic loci not only highlight the important role of adiposity in liver damage but also shed light on the genetic etiology of liver disease in obese individuals.
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Affiliation(s)
- Chuan Gao
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Anthony Marcketta
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Joshua D. Backman
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Colm O'Dushlaine
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Jeffrey Staples
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | | | - Luca A. Lotta
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - John D. Overton
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Jeffrey G. Reid
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Tooraj Mirshahi
- Molecular and Functional GenomicsGeisinger ClinicDanvillePennsylvaniaUSA
| | | | | | - Aris Baras
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Gonçalo Abecasis
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | - Alan R. Shuldiner
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
| | | | - Shane McCarthy
- Regeneron Genetics CenterRegeneron PharmaceuticalsTarrytownNew YorkUSA
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48
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Ward LD, Tu HC, Quenneville CB, Tsour S, Flynn-Carroll AO, Parker MM, Deaton AM, Haslett PAJ, Lotta LA, Verweij N, Ferreira MAR, Baras A, Hinkle G, Nioi P. GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms. Nat Commun 2021; 12:4571. [PMID: 34315874 PMCID: PMC8316433 DOI: 10.1038/s41467-021-24563-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 06/23/2021] [Indexed: 02/07/2023] Open
Abstract
Understanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1.
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Affiliation(s)
- Lucas D. Ward
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | - Ho-Chou Tu
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | | | - Shira Tsour
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | | | - Margaret M. Parker
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | - Aimee M. Deaton
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | | | - Luca A. Lotta
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Niek Verweij
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | | | | | | | - Aris Baras
- grid.418961.30000 0004 0472 2713Regeneron Genetics Center, Tarrytown, NY USA
| | - Gregory Hinkle
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
| | - Paul Nioi
- grid.417897.40000 0004 0506 3000Alnylam Pharmaceuticals, Cambridge, MA USA
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49
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Nounu A, Walker V, Richmond RC. Letter regarding, "Association between the use of aspirin and risk of lung cancer: results from pooled cohorts and Mendelian randomization analyses". J Cancer Res Clin Oncol 2021; 147:2171-2173. [PMID: 33433658 DOI: 10.1007/s00432-020-03508-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 12/17/2020] [Indexed: 12/30/2022]
Affiliation(s)
- Aayah Nounu
- Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.
| | - Venexia Walker
- Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Rebecca C Richmond
- Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
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50
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de Souza TC, de Souza TC, Rovadoscki GA, Coutinho LL, Mourão GB, de Camargo GMF, Costa RB, de Carvalho GGP, Pedrosa VB, Pinto LFB. Genome-wide association for plasma urea concentration in sheep. Livest Sci 2021. [DOI: 10.1016/j.livsci.2021.104483] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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