Skip to main content Accessibility help

Heritability and GWAS Studies for Monocyte–Lymphocyte Ratio

  • Bochao D. Lin (a1), Gonneke Willemsen (a1), Iryna O. Fedko (a1), Rick Jansen (a2), Brenda Penninx (a2), E. de Geus (a1), C. Kluft (a3), JoukeJan Hottenga (a1) and Dorret I. Boomsma (a1)...


The monocyte–lymphocyte ratio (MLR) is a useful biomarker for disease development, but little is known about the extent to which genetic and environmental factors influence MLR variation. Here, we study the genetic architecture of MLR and determine the influence of demographic and lifestyle factors on MLR in data from a Dutch non-patient twin-family population. Data were obtained in 9,501 individuals from the Netherlands Twin Register. We used regression analyses to determine the effects of age, sex, smoking, and body mass index (BMI) on MLR and its subcomponents. Data on twins, siblings and parents (N = 7,513) were analyzed by genetic structural equation modeling to establish heritability and genome wide single nucleotide polymorphism (SNP) data from a genotyped subsample (N = 5,892) and used to estimate heritability explained by SNPs. SNP and phenotype data were also analyzed in a genome-wide association study to identify the genes involved in MLR. Linkage disequilibrium (LD) score regression and expression quantitative trait loci (eQTL) analyses were performed to further explore the genetic findings. Results showed that age, sex, and age × sex interaction effects were present for MLR and its subcomponents. Variation in MLR was not related to BMI, but smoking was positively associated with MLR. Heritability was estimated at 40% for MLR, 58% for monocyte, and 58% for lymphocyte count. The Genome-wide association study (GWAS) identified a locus on ITGA4 that was associated with MLR and only marginally significantly associated with monocyte count. For monocyte count, additional genetic variants were identified on ITPR3, LPAP1, and IRF8. For lymphocyte count, GWAS provided no significant findings. Taking all measured SNPs together, their effects accounted for 13% of the heritability of MLR, while all known and identified genetic loci explained 1.3% of variation in MLR. eQTL analyses showed that these genetic variants were unlikely to be eQTLs. In conclusion, variation in MLR level in the general population is heritable and influenced by age, sex, and smoking. We identified gene variants in the ITGA4 gene associated with variation in MLR. The significant SNP-heritability indicates that more genetic variants are likely to be involved.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure 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 or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ 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.

      Heritability and GWAS Studies for Monocyte–Lymphocyte Ratio
      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.

      Heritability and GWAS Studies for Monocyte–Lymphocyte Ratio
      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.

      Heritability and GWAS Studies for Monocyte–Lymphocyte Ratio
      Available formats


Corresponding author

address for correspondence: D. I. Boomsma, Department of Biological Psychology, Vrije Universiteit, Van der Boechorststraat 1, 1081 BT, Amsterdam, the Netherlands. E-mail:


Hide All
Abdellaoui, A., Hottenga, J. J., de Knijff, P., Nivard, M. G., Xiao, X., & Scheet, P. (2013). Population structure, migration, and diversifying selection in the Netherlands. European Journal of Human Genetics, 21, 12771285.
Al-Sufyani, A. A., & Mahassni, S. H. (2011). Obesity and immune cells in Saudi females. Innate Immunity, 17, 439450.
Alvarez-Navarro, C., Martin-Esteban, A., Barnea, E., Admon, A., & de Castro, J. A. L. (2015). Endoplasmic reticulum aminopeptidase 1 (ERAP1) polymorphism relevant to inflammatory disease shapes the peptidome of the birdshot chorioretinopathy-associated HLA-A*29:02 antigen. Molecular & Cellular Proteomics, 14, 17701780.
Azab, B., Camacho-Rivera, M., & Taioli, E. (2014). Average values and racial differences of neutrophil lymphocyte ratio among a nationally representative sample of United States subjects. PLoS One, 9, e112361.
Boker, S., Neale, M., Maes, H., Wilde, M., Spiegel, M., & Brick, T. (2011). OpenMx: An open source extended structural equation modeling framework. Psychometrika, 76, 306317.
Boomsma, D. I., Willemsen, G., Sullivan, P. F., Heutink, P., Meijer, P., & Sondervan, D. (2008). Genome-wide association of major depression: Description of samples for the GAIN major depressive disorder study: NTR and NESDA biobank projects. European Journal of Human Genetics, 16, 335342.
Bulik-Sullivan, B. K., Loh, P. R., Finucane, H. K., Ripke, S., Yang, J., & Patterson, N. (2015). LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47, 291295.
Bulik-Sullivan, B., Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., & Loh, P. R. (2015). An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47, 12361241.
Crosslin, D. R., McDavid, A., Weston, N., Zheng, X. W., Hart, E., & Andrade, M. (2013). Genetic variation associated with circulating monocyte count in the eMERGE Network. Human Molecular Genetics, 22, 21192127.
De Jager, P. L., Jia, X., Wang, J., de Bakker, P. I., Ottoboni, L., & Aggarwal, N. T. (2009). Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nature Genetics, 41, 776782.
Evans, D. M., Frazer, I. H., & Martin, N. G. (1999). Genetic and environmental causes of variation in basal levels of blood cells. Twin Research, 2, 250257.
Farragher, T. M., Goodson, N. J., Naseem, H., Silman, A. J., Thomson, W., & Symmons, D. (2008). Association of the HLA-DRB1 gene with premature death, particularly from cardiovascular disease, in patients with rheumatoid arthritis and inflammatory polyarthritis. Arthritis and Rheumatism, 58, 359369.
Ferreira, M. A., Hottenga, J. J., Warrington, N. M., Medland, S. E., Willemsen, G., & Lawrence, R. W. (2009). Sequence variants in three loci influence monocyte counts and erythrocyte volume. American Journal of Human Genetics, 85, 745749.
Finucane, H. K., Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., & Loh, P. R. (2015). Partitioning heritability by functional annotation using genome-wide association summary statistics. Nature Genetics, 47, 12281235.
Hall, M. A., Ahmadi, K. R., Norman, P., Snieder, H., MacGregor, A. J., & Vaughan, R. W. (2000). Genetic influence on peripheral blood T lymphocyte levels. Genes & Immunity, 1, 423427.
Hanifin, J. M., & Cline, M. J. (1970). Human monocytes and macrophages. Interaction with antigen and lymphocytes. Journal of Cell Biology, 46, 97105.
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012). Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet, 44 (8), 955959.
Iqbal, S., Umbreen, A., & Zaidi, S. B. H. (2014). Monocyte lymphocyte ratio as a possible prognostic marker in antituberculous therapy. JRMC, 18 (2), 178181.
Jansen, R., Hottenga, J. J., Nivard, M., abdellaoui, A., Laport, B., & de Geus, E. J. (in press). Conditional eQTL analysis reveals allelic heterogeneity of gene expression. Human Molecular Genetics.
Kamatani, Y., Matsuda, K., Okada, Y., Kubo, M., Hosono, N., & Daigo, Y. (2010). Genome-wide association study of hematological and biochemical traits in a Japanese population. Nature Genetics, 42, 210215.
Keller, M. F., Reiner, A. P., Okada, Y., van Rooij, F. J., Johnson, A. D., & Chen, M. H. (2014). Trans-ethnic meta-analysis of white blood cell phenotypes. Human Molecular Genetics, 23, 69446960.
Kurotaki, D., Osato, N., Nishiyama, A., Yamamoto, M., Ban, T., & Sato, H. (2013). Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation. Blood, 121, 18391849.
Li, J., Chen, Q. Y., Luo, X. H., Hong, J., Pan, K. Y., & Lin, X. H. (2015). Neutrophil-to-lymphocyte ratio positively correlates to age in healthy population. Journal of Clinical Laboratory Analysis, 29, 437443.
Li, Y., Willer, C. J., Ding, J., Scheet, P., & Abecasis, G. R. (2010). MaCH: Using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genetic Epidemiology, 34, 816834.
Lin, B. D., Hottenga, J. J., Abdellaoui, A., Dolan, C. V., de Geus, E. J., & Kluft, C. (2016). Causes of variation in the neutrophil-lymphocyte and platelet-lymphocyte ratios: A twin-family study. Biomarkers In Medicine, 10, 10611072.
Lin, B. D., Montoro, E., Bell, J., Boomsma, D. I., de Geus, E. J., & Jansen, R. (2016). SNP heritability and effects of genetic variants for neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio. Manuscript submitted for publication.
Liu, E. Y., Li, M., Wang, W., & Li, Y. (2013). MaCH-admix: Genotype imputation for admixed populations. Genetic Epidemiology, 37, 2537.
Maugeri, N., Powell, J. E., Hoen, P. A., de Geus, E. J., Willemsen, G., & Kattenberg, M. (2011). LPAR1 and ITGA4 regulate peripheral blood monocyte counts. Human Mutation, 32, 873876.
Nalls, M. A., Couper, D. J., Tanaka, T., van Rooij, F. J., Chen, M. H., & Smith, A. V. (2011). Multiple loci are associated with white blood cell phenotypes. Plos Genetics, 7, e1002113.
Nishijima, T. F., Muss, H. B., Shachar, S. S., Tamura, K., & Takamatsu, Y. (2015). Prognostic value of lymphocyte-to-monocyte ratio in patients with solid tumors: A systematic review and meta-analysis. Cancer Treatment Reviews, 41, 971978.
Oishi, T., Iida, A., Otsubo, S., Kamatani, Y., Usami, M., & Takei, T. (2008). A functional SNP in the NKX2.5-binding site of ITPR3 promoter is associated with susceptibility to systemic lupus erythematosus in Japanese population. Journal of Human Genetics, 53, 151162.
Okada, Y., Hirota, T., Kamatani, Y., Takahashi, A., Ohmiya, H., & Kumasaka, N. (2011). Identification of nine novel loci associated with white blood cell subtypes in a Japanese population. PLOS Genetics, 7 (6), e1002067.
Pe'er, I., Yelensky, R., Altshuler, D., & Daly, M. J. (2008). Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genetic Epidemiology, 32, 381385. doi:10.1002/gepi.20303.
Perez-de-Heredia, F., Gomez-Martinez, S., Diaz, L. E., Veses, A. M., Nova, E., & Warnberg, J. (2015). Influence of sex, age, pubertal maturation and body mass index on circulating white blood cell counts in healthy European adolescents-the HELENA study. European Journal of Pediatrics, 174, 9991014.
R Core Team. (2014). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
Reiner, A. P., Lettre, G., Nalls, M. A., Ganesh, S. K., Mathias, R., & Austin, M. A. (2011). Genome-wide association study of white blood cell count in 16,388 African Americans: The Continental Origins and Genetic Epidemiology Network (COGENT). PLOS Genetics, 7, e1002108.
Schwartz, J., & Weiss, S. T. (1994). Cigarette smoking and peripheral blood leukocyte differentials. Annals of Epidemiology, 4, 236242.
Shabalin, A. A. (2012). Matrix eQTL: Ultra fast eQTL analysis via large matrix operations. Bioinformatics, 28, 13531358.
Sirota, M., Willemsen, G., Sundar, P., Pitts, S. J., Potluri, S., & Prifti, E. (2015). Effect of genome and environment on metabolic and inflammatory profiles. PLoS One, 10, e0120898.
Stata Corp. (2013). Stata statistical software: Release 13. College Station, TX: StataCorp LP.
Tenorio, T. R., Farah, B. Q., Ritti-Dias, R. M., Botero, J. P., Brito, D. C., & Moura, P. M. (2014). Relation between leukocyte count, adiposity, and cardiorespiratory fitness in pubertal adolescents. Einstein, 12, 420424.
Terry, R. L., Deffrasnes, C., Getts, D. R., Minten, C., van Vreden, C., & Ashhurst, T. M. (2015). Defective inflammatory monocyte development in IRF8-deficient mice abrogates migration to the west nile virus-infected brain. Journal of Innate Immunity, 7, 102112.
Thomas, D., Gazouli, M., Karantanos, T., Rigoglou, S., Karamanolis, G., & Bramis, K. (2014). Association of rs1568885, rs1813443 and rs4411591 polymorphisms with anti-TNF medication response in Greek patients with Crohn's disease. World Journal of Gastroenterology, 20, 36093614.
Tucker, G., Loh, P. R., MacLeod, I. M., Hayes, B. J., Goddard, M. E., & Berger, B. (2015). Two-variance component model improves genetic prediction in family datasets. American Journal of Human Genetics, 97, 677690.
Willemsen, G., de Geus, E. J., Bartels, M., van Beijsterveldt, C. E., Brooks, A. I., & Estourgie-van Burk, G. F. (2010). The netherlands twin register biobank: A resource for genetic epidemiological studies. Twin Research and Human Genetics, 13, 231245.
Willemsen, G., Vink, J. M., Abdellaoui, A., den Braber, A., van Beek, J. H., & Draisma, H. H. (2013). The adult netherlands twin register: Twenty-five years of survey and biological data collection. Twin Research and Human Genetics, 16 (1), 271281.
Wright, F. A., Sullivan, P. F., Brooks, A. I., Zou, F., Sun, W., & Xia, K. (2014). Heritability and genomics of gene expression in peripheral blood. Nature Genetics, 46, 430437.
Yanez, A., Ng, M. Y., Hassanzadeh-Kiabi, N., & Goodridge, H. S. (2015). IRF8 acts in lineage-committed rather than oligopotent progenitors to control neutrophil vs monocyte production. Blood, 125, 14521459.
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: A tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88, 7682.
Zaitlen, N., Kraft, P., Patterson, N., Pasaniuc, B., Bhatia, G., Pollack, S., & Price, A. L. (2013). Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLOS Genetics, 9, e1003520.
Zaldivar, F., McMurray, R. G., Nemet, D., Galassetti, P., Mills, P. J., & Cooper, D. M. (2006). Body fat and circulating leukocytes in children. International Journal of Obesity, 30, 906911.


Heritability and GWAS Studies for Monocyte–Lymphocyte Ratio

  • Bochao D. Lin (a1), Gonneke Willemsen (a1), Iryna O. Fedko (a1), Rick Jansen (a2), Brenda Penninx (a2), E. de Geus (a1), C. Kluft (a3), JoukeJan Hottenga (a1) and Dorret I. Boomsma (a1)...


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