Skip to main content Accessibility help
×
Home

Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study

  • Marzyeh Amini (a1), Judith M. Vonk (a1) (a2), Ali Abbasi (a1), Bram P. Prins (a1), Marcel Bruinenberg (a3), Lude Franke (a4), Pim van der Harst (a5), Gerjan Navis (a6), Gerard H. Koppelman (a2) (a7), Bruce H. R. Wolffenbuttel (a8), H. Marike Boezen (a1) (a2), Harold Snieder (a1), Daniel I. Chasman (a9) and Behrooz Z. Alizadeh (a1)...

Abstract

Blood eosinophil count is associated with a variety of common complex outcomes in epidemiological observation. The aim of this study was to explore the causal association between determined blood eosinophil count and 20 common complex outcomes (10 metabolic, 6 cardiac, and 4 pulmonary). Through Mendelian randomization, we investigated genetic evidence for the genetically determined eosinophil in association with each outcomes using individual-level LifeLines cohort data (n = 13,301), where a weighted eosinophil genetic risk score comprising five eosinophil associated variants was created. We further examined the associations of the genetically determined eosinophil with those outcomes using summary statistics obtained from genome-wide association study consortia (6 consortia and 14 outcomes). Blood eosinophil count, by a 1-SD genetically increased, was not statistically associated with common complex outcomes in the LifeLines. Using the summary statistics, we showed that a higher genetically determined eosinophil count had a significant association with lower odds of obesity (odds ratio (OR) 0.81, 95% confidence interval (CI) [0.74, 0.89]) but not with the other traits and diseases. To conclude, an elevated eosinophil count is unlikely to be causally associated to higher risk of metabolic, cardiac, and pulmonary outcomes. Further studies with a stronger genetic risk score for eosinophil count may support these results.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Blood Eosinophil Count and Metabolic, Cardiac and Pulmonary Outcomes: A Mendelian Randomization Study
      Available formats
      ×

Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

address for correspondence: Marzyeh Amini MSc PhD Fellow, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, PO Box 30001, 9700 RB Groningen, The Netherlands. E-mail: m.amini@umcg.nl

References

Hide All
Abbasi, A., Deetman, P. E., Corpeleijn, E., Gansevoort, R. T., Gans, R. O., Hillege, H. L., . . . Bakker, S. J. (2015). Bilirubin as a potential causal factor in type 2 diabetes risk: A Mendelian randomization study. Diabetes, 64, 14591469.
Aghabozorg Afjeh, S. S., Ghaderian, S. M., Mirfakhraie, R., Piryaei, M., & Zaim Kohan, H. (2014). Association study of rs3184504 C>T polymorphism in patients with coronary artery disease. International Journal of Molecular and Cellular Medicine, 3, 157165.
Akhabir, L., Berube, J. C., Bosse, Y., Laviolette, M., Hao, K., Nickle, D. C., . . . Sandford, A. J. (2014). Lung expression quantitative trait loci data set identifies important functional polymorphisms in the asthma-associated IL1RL1 region. The Journal of Allergy and Clinical Immunology, 134, 729731.
Alcina, A., Vandenbroeck, K., Otaegui, D., Saiz, A., Gonzalez, J. R., Fernandez, O., . . . Matesanz, F. (2010). The autoimmune disease-associated KIF5A, CD226 and SH2B3 gene variants confer susceptibility for multiple sclerosis. Genes and Immunity, 11, 439445.
Ali, M., Zhang, G., Thomas, W. R., McLean, C. J., Bizzintino, J. A., Laing, I. A., . . . Hayden, C. M. (2009). Investigations into the role of ST2 in acute asthma in children. Tissue Antigens, 73, 206212.
Amini, M., Bashirova, D., Prins, B. P., Corpeleijn, E., LifeLines Cohort Study, Bruinenberg, M., . . . Alizadeh, B. Z. (2016). Eosinophil count is a common factor for complex metabolic and pulmonary traits and diseases: The LifeLines cohort study. PLoS One, 11, e0168480.
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., . . . Soranzo, N. (2016). The allelic landscape of human blood cell trait variation and links to common complex disease. Cell, 167, 14151429.e19.
Babio, N., Ibarrola-Jurado, N., Bullo, M., Martinez-Gonzalez, M., Warnberg, J., Salaverria, I., . . . PREDIMED Study Investigators. (2013). White blood cell counts as risk markers of developing metabolic syndrome and its components in the PREDIMED study. PLoS One, 8, e58354–e58354.
Bafadhel, M., McKenna, S., Terry, S., Mistry, V., Pancholi, M., Venge, P., . . . Brightling, C. E. (2012). Blood eosinophils to direct corticosteroid treatment of exacerbations of chronic obstructive pulmonary disease: A randomized placebo-controlled trial. American Journal of Respiratory and Critical Care Medicine, 186, 4855.
Barrett, J. C., Clayton, D. G., Concannon, P., Akolkar, B., Cooper, J. D., Erlich, H. A., . . . Type 1 Diabetes Genetics Consortium. (2009). Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, 41, 703707.
Berndt, S. I., Gustafsson, S., Magi, R., Ganna, A., Wheeler, E., Feitosa, M. F., . . . Ingelsson, E. (2013). Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nature Genetics, 45, 501512.
Burgess, S., Butterworth, A., & Thompson, S. G. (2013). Mendelian randomization analysis with multiple genetic variants using summarized data. Genetic Epidemiology, 37, 658665.
Burgess, S., Scott, R. A., Timpson, N. J., Davey Smith, G., Thompson, S. G., & EPIC-InterAct Consortium. (2015). Using published data in Mendelian randomization: A blueprint for efficient identification of causal risk factors. European Journal of Epidemiology, 30, 543552.
Burgess, S., Small, D. S., & Thompson, S. G. (2017). A review of instrumental variable estimators for Mendelian randomization. Statistical Methods in Medical Research, 26, 23332355.
Cole, T. J. (2000). Sympercents: Symmetric percentage differences on the 100 log(e) scale simplify the presentation of log transformed data. Statistics in Medicine, 19, 31093125.
Coronary Artery Disease (C4D) Genetics Consortium, Peden, J. F., Hopewell, J. C., Saleheen, D., Chambers, J. C., Hager, J., . . . Collins, R. (2011). A genome-wide association study in europeans and south asians identifies five new loci for coronary artery disease. Nature Genetics, 43, 339344.
Dastani, Z., Hivert, M. F., Timpson, N., Perry, J. R., Yuan, X., Scott, R. A., . . . Kathiresan, S. (2012). Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: A multi-ethnic meta-analysis of 45,891 individuals. PLoS Genetics, 8, e1002607.
Davey Smith, G., & Ebrahim, S. (2003). ‘Mendelian randomization’: Can genetic epidemiology contribute to understanding environmental determinants of disease? International Journal of Epidemiology, 32, 122.
Davey Smith, G., & Ebrahim, S. (2005). What can Mendelian randomisation tell us about modifiable behavioural and environmental exposures? BMJ, 330, 10761079.
Davey Smith, G., & Hemani, G. (2014). Mendelian randomization: Genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics, 23, R89–R98.
Didelez, V., & Sheehan, N. (2007). Mendelian randomization as an instrumental variable approach to causal inference. Statistical Methods in Medical Research, 16, 309330.
Ding, K., & Kullo, I. J. (2011). Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease. BMC Medical Genetics, 12, 55.
Dupuis, J., Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., Jackson, A. U., . . . Morris, A. P. (2010). New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nature Genetic, 42, 105116.
Fahy, J. V. (2015). Type 2 inflammation in asthma – Present in most, absent in many. Nature Reviews Immunology, 15, 5765.
Fukui, M., Tanaka, M., Hamaguchi, M., Senmaru, T., Sakabe, K., Shiraishi, E., . . . Nakamura, N. (2009). Eosinophil count is positively correlated with albumin excretion rate in men with type 2 diabetes. Clinical Journal of the American Society of Nephrology, 4, 17611765.
Ganesh, S. K., Zakai, N. A., van Rooij, F. J., Soranzo, N., Smith, A. V., Nalls, M. A., . . . Lin, J. P. (2009). Multiple loci influence erythrocyte phenotypes in the CHARGE consortium. Nature Genetics, 41, 11911198.
Gkrania-Klotsas, E., Ye, Z., Cooper, A. J., Sharp, S. J., Luben, R., Biggs, M. L., . . . Langenberg, C. (2010). Differential white blood cell count and type 2 diabetes: Systematic review and meta-analysis of cross-sectional and prospective studies. PLoS One, 5, e13405–e13405.
Global Lipids Genetics Consortium, Willer, C. J., Schmidt, E. M., Sengupta, S., Peloso, G. M., Gustafsson, S., . . . Abecasis, G. R. (2013). Discovery and refinement of loci associated with lipid levels. Nature Genetics, 45, 12741283.
Gudbjartsson, D. F., Bjornsdottir, U. S., Halapi, E., Helgadottir, A., Sulem, P., Jonsdottir, G. M., . . . Stefansson, K. (2009). Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nature Genetics, 4, 342347.
Hospers, J. J., Schouten, J. P., Weiss, S. T., Postma, D. S., & Rijcken, B. (2000). Eosinophilia is associated with increased all-cause mortality after a follow-up of 30 years in a general population sample. Epidemiology, 11, 261268.
International Consortium for Blood Pressure Genome-Wide Association Studies, Ehret, G. B., Munroe, P. B., Rice, K. M., Bochud, M., Johnson, A. D., . . . Johnson, T. (2011). Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature, 478, 103109.
Jacobsen, E. A., Zellner, K. R., Colbert, D., Lee, N. A., & Lee, J. J. (2011). Eosinophils regulate dendritic cells and Th2 pulmonary immune responses following allergen provocation. Journal of Immunology, 187, 60596068.
Kim, D. J., Noh, J. H., Lee, B. W., Choi, Y. H., Chung, J. H., Min, Y. K., . . . Kim, K. W. (2008). The associations of total and differential white blood cell counts with obesity, hypertension, dyslipidemia and glucose intolerance in a Korean population. Journal of Korean Medical Science, 23, 193198.
Kim, J. A., Choi, Y. S., Hong, J. I., Kim, S. H., Jung, H. H., & Kim, S. M. (2006). Association of metabolic syndrome with white blood cell subtype and red blood cells. Endocrine Journal, 53, 133139.
Li, N., van der Sijde, M. R., LifeLines Cohort Study Group, Bakker, S. J., Dullaart, R. P., van der Harst, P., . . . . Fu, J. (2014). Pleiotropic effects of lipid genes on plasma glucose, HbA1c, and HOMA-IR levels. Diabetes, 63, 31493158.
Lian, J., Huang, Y., Huang, R. S., Xu, L., Le, Y., Yang, X., . . . Duan, S. (2013). Meta-analyses of four eosinophil related gene variants in coronary heart disease. Journal of Thrombosis and Thrombolysis, 36, 394401.
Meng, W., Zhang, C., Zhang, Q., Song, X., Lin, H., Zhang, D., . . . Xue, F. (2012). Association between leukocyte and metabolic syndrome in urban Han Chinese: A longitudinal cohort study. PLoS One, 7, e49875–e49875.
Mensinga, T. T., Schouten, J. P., Weiss, S. T., & Van der Lende, R. (1992). Relationship of skin test reactivity and eosinophilia to level of pulmonary function in a community-based population study. The American Review of Respiratory Disease, 146, 638643.
Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segre, A. V., Steinthorsdottir, V., . . . DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium (2012). Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nature Genetics, 44, 981990.
Pickrell, J. K., Coop, G., Novembre, J., Kudaravalli, S., Li, J. Z., Absher, D., . . . Pritchard, J. K. (2009). Signals of recent positive selection in a worldwide sample of human populations. Genome Research, 19, 826837.
Prins, B. P., Abbasi, A., Wong, A., Vaez, A., Nolte, I., Franceschini, N., . . . Alizadeh, B. Z. (2016). Investigating the causal relationship of C-reactive protein with 32 complex somatic and psychiatric outcomes: A large-scale cross-consortium Mendelian randomization study. PLoS Medicine, 13, e1001976.
Reijmerink, N. E., Postma, D. S., Bruinenberg, M., Nolte, I. M., Meyers, D. A., Bleecker, E. R., & Koppelman, G. H. (2008). Association of IL1RL1, IL18R1, and IL18RAP gene cluster polymorphisms with asthma and atopy. The Journal of Allergy and Clinical Immunology, 122, 6514.e8.
Rice, J. A. (1995). Mathematical statistics and data analysis (2nd ed.). Belmont, CA: Duxbury Press.
Savenije, O. E., Kerkhof, M., Reijmerink, N. E., Brunekreef, B., de Jongste, J. C., Smit, H. A., . . . Koppelman, G. H. (2011). Interleukin-1 receptor-like 1 polymorphisms are associated with serum IL1RL1-a, eosinophils, and asthma in childhood. The Journal of Allergy and Clinical Immunology, 127, 750–6.e1-5.
Schunkert, H., Konig, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., . . . Samani, N. J. (2011). Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nature Genetics, 43, 333338.
Shim, W. S., Kim, H. J., Kang, E. S., Ahn, C. W., Lim, S. K., Lee, H. C., & Cha, B. S. (2006). The association of total and differential white blood cell count with metabolic syndrome in type 2 diabetic patients. Diabetes Research and Clinical Practice, 73, 284291.
Siva, R., Green, R. H., Brightling, C. E., Shelley, M., Hargadon, B., McKenna, S., . . . Pavord, I. D. (2007). Eosinophilic airway inflammation and exacerbations of COPD: A randomised controlled trial. The European Respiratory Journal, 29, 906913.
Soranzo, N., Spector, T. D., Mangino, M., Kuhnel, B., Rendon, A., Teumer, A., . . . Gieger, C. (2009). A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nature Genetics, 41, 11821190.
Stahl, E. A., Raychaudhuri, S., Remmers, E. F., Xie, G., Eyre, S., Thomson, B. P., . . . Plenge, R. M. (2010). Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nature Genetics, 42, 508514.
Talmud, P. J., Drenos, F., Shah, S., Shah, T., Palmen, J., Verzilli, C., . . . BRIGHT Consortium. (2009). Gene-centric association signals for lipids and apolipoproteins identified via the HumanCVD BeadChip. American Journal of Human Genetics, 85, 628642.
Tin, A., Astor, B. C., Boerwinkle, E., Hoogeveen, R. C., Coresh, J., & Kao, W. H. (2013). Genome-wide association study identified the human leukocyte antigen region as a novel locus for plasma beta-2 microglobulin. Human Genetics, 132, 619627.
Torgerson, D. G., Ampleford, E. J., Chiu, G. Y., Gauderman, W. J., Gignoux, C. R., Graves, P. E., . . . Nicolae, D. L. (2011). Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations. Nature Genetics, 43, 887892.
Tulah, A. S., Holloway, J. W., & Sayers, I. (2013). Defining the contribution of SNPs identified in asthma GWAS to clinical variables in asthmatic children. BMC Medical Genetics, 14, 100.
van der Harst, P., Zhang, W., Mateo Leach, I., Rendon, A., Verweij, N., Sehmi, J., . . . Chambers, J. C. (2012). Seventy-five genetic loci influencing the human red blood cell. Nature, 492, 369375.
Wain, L. V., Verwoert, G. C., O'Reilly, P. F., Shi, G., Johnson, T., Johnson, A. D., . . . van Duijn, C. M. (2011). Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure. Nature Genetics, 43, 10051011.
Wu, D., Molofsky, A. B., Liang, H. E., Ricardo-Gonzalez, R., Jouihan, H. A., Bando, J. K., . . . Locksley, R. M. (2011). Eosinophils sustain adipose alternatively activated macrophages associated with glucose homeostasis. Science, 332, 243247.
Yang, J., Loos, R. J., Powell, J. E., Medland, S. E., Speliotes, E. K., Chasman, D. I., . . . Visscher, P. M. (2012). FTO genotype is associated with phenotypic variability of body mass index. Nature, 490, 267272.
Ye, H., Hong, Q., Li, Y., Xu, X., Huang, Y. I., Xu, L., . . . Duan, S. (2015). A lack of association between the IKZF2 rs12619285 polymorphism and coronary heart disease. Experimental and Therapeutic Medicine, 9, 13091313.

Keywords

Type Description Title
WORD
Supplementary materials

Amini et al. supplementary material
Amini et al. supplementary material 1

 Word (494 KB)
494 KB

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed