A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

doi:10.3389/fgene.2018.00097

. 2018 Mar 23:9:97.

doi: 10.3389/fgene.2018.00097. eCollection 2018.

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Jiyang Jiang¹, Anbupalam Thalamuthu¹, Jennifer E Ho^{2

3}, Anubha Mahajan⁴, Weronica E Ek⁵, David A Brown^{6

7}, Samuel N Breit⁶, Thomas J Wang⁸, Ulf Gyllensten⁵, Ming-Huei Chen^{9

10}, Stefan Enroth⁵, James L Januzzi Jr³, Lars Lind¹¹, Nicola J Armstrong^{1

12}, John B Kwok^{13

14}, Peter R Schofield^{13

14}, Wei Wen^{1

15}, Julian N Trollor^{1

16}, Åsa Johansson⁵, Andrew P Morris^{4

17}, Ramachandran S Vasan^{18

19}, Perminder S Sachdev^{1

15}, Karen A Mather¹

Affiliations

¹ Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.
² Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, United States.
³ Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.
⁴ Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
⁵ Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
⁶ St. Vincent's Centre for Applied Medical Research, St. Vincent's Hospital, Darlinghurst, NSW, Australia.
⁷ Westmead Institute for Medical Research, The Institute for Clinical Pathology and Medical Research and Westmead Hospital, Westmead, NSW, Australia.
⁸ Division of Cardiology, Department of Medicine, Vanderbilt University, Nashville, TN, United States.
⁹ Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA, United States.
¹⁰ The Framingham Heart Study, Framingham, MA, United States.
¹¹ Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
¹² Mathematics and Statistics, Murdoch University, Perth, WA, Australia.
¹³ Neuroscience Research Australia, Randwick, NSW, Australia.
¹⁴ School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia.
¹⁵ Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.
¹⁶ Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.
¹⁷ Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
¹⁸ Sections of Preventive Medicine and Epidemiology and Cardiology, Department of Medicine, Boston University School of Medicine, and Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States.
¹⁹ National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Boston University, Boston, MA, United States.

PMID: 29628937
PMCID: PMC5876753
DOI: 10.3389/fgene.2018.00097

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Jiyang Jiang et al. Front Genet. 2018.

. 2018 Mar 23:9:97.

doi: 10.3389/fgene.2018.00097. eCollection 2018.

Authors

Affiliations

¹ Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.
² Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, United States.
³ Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States.
⁴ Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
⁵ Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
⁶ St. Vincent's Centre for Applied Medical Research, St. Vincent's Hospital, Darlinghurst, NSW, Australia.
⁷ Westmead Institute for Medical Research, The Institute for Clinical Pathology and Medical Research and Westmead Hospital, Westmead, NSW, Australia.
⁸ Division of Cardiology, Department of Medicine, Vanderbilt University, Nashville, TN, United States.
⁹ Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA, United States.
¹⁰ The Framingham Heart Study, Framingham, MA, United States.
¹¹ Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
¹² Mathematics and Statistics, Murdoch University, Perth, WA, Australia.
¹³ Neuroscience Research Australia, Randwick, NSW, Australia.
¹⁴ School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia.
¹⁵ Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.
¹⁶ Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia.
¹⁷ Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
¹⁸ Sections of Preventive Medicine and Epidemiology and Cardiology, Department of Medicine, Boston University School of Medicine, and Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States.
¹⁹ National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Boston University, Boston, MA, United States.

PMID: 29628937
PMCID: PMC5876753
DOI: 10.3389/fgene.2018.00097

Abstract

Blood levels of growth differentiation factor-15 (GDF-15), also known as macrophage inhibitory cytokine-1 (MIC-1), have been associated with various pathological processes and diseases, including cardiovascular disease and cancer. Prior studies suggest genetic factors play a role in regulating blood MIC-1/GDF-15 concentration. In the current study, we conducted the largest genome-wide association study (GWAS) to date using a sample of ∼5,400 community-based Caucasian participants, to determine the genetic variants associated with MIC-1/GDF-15 blood concentration. Conditional and joint (COJO), gene-based association, and gene-set enrichment analyses were also carried out to identify novel loci, genes, and pathways. Consistent with prior results, a locus on chromosome 19, which includes nine single nucleotide polymorphisms (SNPs) (top SNP, rs888663, p = 1.690 × 10^-35), was significantly associated with blood MIC-1/GDF-15 concentration, and explained 21.47% of its variance. COJO analysis showed evidence for two independent signals within this locus. Gene-based analysis confirmed the chromosome 19 locus association and in addition, a putative locus on chromosome 1. Gene-set enrichment analyses showed that the"COPI-mediated anterograde transport" gene-set was associated with MIC-1/GDF15 blood concentration with marginal significance after FDR correction (p = 0.067). In conclusion, a locus on chromosome 19 was associated with MIC-1/GDF-15 blood concentration with genome-wide significance, with evidence for a new locus (chromosome 1). Future studies using independent cohorts are needed to confirm the observed associations especially for the chromosomes 1 locus, and to further investigate and identify the causal SNPs that contribute to MIC-1/GDF-15 levels.

Keywords: chromosome 19; community-based individuals; genome-wide association study; growth differentiation factor-15; macrophage inhibitory cytokine-1.

PubMed Disclaimer

Figures

**FIGURE 1**
**(A)** Manhattan and **(B)** QQ plot for the discovery meta-analysis (Model 1).

**FIGURE 2**
Regional association plot of 100 kb window around the *MIC-1/GDF15* gene. Different colors represent the strength of the LD of each SNP with the most significant SNP rs888663.

See this image and copyright information in PMC

Cited by

Correlations between growth differentiation factor 15 (GDF-15) serum levels and gene polymorphism with type 2 diabetes mellitus.
Liu Q, Qin L, Liang Y, Xu M, Zhang J, Mo X, Tang X, Lu Y, Wang X, Cao J, Huang C, Rong J, Teng K, Zhao L, Wu S, Luo L, Guan Q, Zhang T, Jin W, Qin J, Cai J, Zhang Z. Liu Q, et al. Heliyon. 2024 Jun 13;10(12):e33044. doi: 10.1016/j.heliyon.2024.e33044. eCollection 2024 Jun 30. Heliyon. 2024. PMID: 38988547 Free PMC article.
Integrated analyses of growth differentiation factor-15 concentration and cardiometabolic diseases in humans.
Lemmelä S, Wigmore EM, Benner C, Havulinna AS, Ong RMY, Kempf T, Wollert KC, Blankenberg S, Zeller T, Peters JE, Salomaa V, Fritsch M, March R, Palotie A, Daly M, Butterworth AS, Kinnunen M, Paul DS, Matakidou A. Lemmelä S, et al. Elife. 2022 Aug 2;11:e76272. doi: 10.7554/eLife.76272. Elife. 2022. PMID: 35916366 Free PMC article.
Major Adverse Cardiovascular Events and Mortality Prediction by Circulating GDF-15 in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis.
Xie S, Li Q, Luk AOY, Lan HY, Chan PKS, Bayés-Genís A, Chan FKL, Fung E. Xie S, et al. Biomolecules. 2022 Jul 4;12(7):934. doi: 10.3390/biom12070934. Biomolecules. 2022. PMID: 35883490 Free PMC article. Review.
Evaluation of GDF15 as a therapeutic target of cardiometabolic diseases in human: A Mendelian randomization study.
Cheung CL, Tan KCB, Au PCM, Li GHY, Cheung BMY. Cheung CL, et al. EBioMedicine. 2019 Mar;41:85-90. doi: 10.1016/j.ebiom.2019.02.021. Epub 2019 Feb 13. EBioMedicine. 2019. PMID: 30772304 Free PMC article.
Growth differentiation factor 15 as a potential therapeutic for treating obesity.
Hale C, Véniant MM. Hale C, et al. Mol Metab. 2021 Apr;46:101117. doi: 10.1016/j.molmet.2020.101117. Epub 2020 Nov 18. Mol Metab. 2021. PMID: 33220493 Free PMC article. Review.

See all "Cited by" articles

References

1. Assarsson E., Lundberg M., Holmquist G., Bjorkesten J., Thorsen S. B., Ekman D., et al. (2014). Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One 9:e95192. 10.1371/journal.pone.0095192 - DOI - PMC - PubMed
1. Aulchenko Y. S., Struchalin M. V., Van Duijn C. M. (2010). ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11:134. 10.1186/1471-2105-11-134 - DOI - PMC - PubMed
1. Bauskin A. R., Brown D. A., Junankar S., Rasiah K. K., Eggleton S., Hunter M., et al. (2005). The propeptide mediates formation of stromal stores of PROMIC-1: role in determining prostate cancer outcome. Cancer Res. 65 2330–2336. 10.1158/0008-5472.CAN-04-3827 - DOI - PubMed
1. Bootcov M. R., Bauskin A. R., Valenzuela S. M., Moore A. G., Bansal M., He X. Y., et al. (1997). MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-β superfamily. Proc. Natl. Acad. Sci. U.S.A. 94 11514–11519. 10.1073/pnas.94.21.11514 - DOI - PMC - PubMed
1. Boyle A. P., Hong E. L., Hariharan M., Cheng Y., Schaub M. A., Kasowski M., et al. (2012). Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22 1790–1797. 10.1101/gr.137323.112 - DOI - PMC - PubMed

Grants and funding

LinkOut - more resources

Full Text Sources
Other Literature Sources
- scite Smart Citations

[1] Assarsson E., Lundberg M., Holmquist G., Bjorkesten J., Thorsen S. B., Ekman D., et al. (2014). Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One 9:e95192. 10.1371/journal.pone.0095192 - DOI - PMC - PubMed

[2] Assarsson E., Lundberg M., Holmquist G., Bjorkesten J., Thorsen S. B., Ekman D., et al. (2014). Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One 9:e95192. 10.1371/journal.pone.0095192 - DOI - PMC - PubMed

[3] Aulchenko Y. S., Struchalin M. V., Van Duijn C. M. (2010). ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11:134. 10.1186/1471-2105-11-134 - DOI - PMC - PubMed

[4] Aulchenko Y. S., Struchalin M. V., Van Duijn C. M. (2010). ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11:134. 10.1186/1471-2105-11-134 - DOI - PMC - PubMed

[5] Bauskin A. R., Brown D. A., Junankar S., Rasiah K. K., Eggleton S., Hunter M., et al. (2005). The propeptide mediates formation of stromal stores of PROMIC-1: role in determining prostate cancer outcome. Cancer Res. 65 2330–2336. 10.1158/0008-5472.CAN-04-3827 - DOI - PubMed

[6] Bauskin A. R., Brown D. A., Junankar S., Rasiah K. K., Eggleton S., Hunter M., et al. (2005). The propeptide mediates formation of stromal stores of PROMIC-1: role in determining prostate cancer outcome. Cancer Res. 65 2330–2336. 10.1158/0008-5472.CAN-04-3827 - DOI - PubMed

[7] Bootcov M. R., Bauskin A. R., Valenzuela S. M., Moore A. G., Bansal M., He X. Y., et al. (1997). MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-β superfamily. Proc. Natl. Acad. Sci. U.S.A. 94 11514–11519. 10.1073/pnas.94.21.11514 - DOI - PMC - PubMed

[8] Bootcov M. R., Bauskin A. R., Valenzuela S. M., Moore A. G., Bansal M., He X. Y., et al. (1997). MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-β superfamily. Proc. Natl. Acad. Sci. U.S.A. 94 11514–11519. 10.1073/pnas.94.21.11514 - DOI - PMC - PubMed

[9] Boyle A. P., Hong E. L., Hariharan M., Cheng Y., Schaub M. A., Kasowski M., et al. (2012). Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22 1790–1797. 10.1101/gr.137323.112 - DOI - PMC - PubMed

[10] Boyle A. P., Hong E. L., Hariharan M., Cheng Y., Schaub M. A., Kasowski M., et al. (2012). Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22 1790–1797. 10.1101/gr.137323.112 - DOI - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Affiliations

A Meta-Analysis of Genome-Wide Association Studies of Growth Differentiation Factor-15 Concentration in Blood

Authors

Affiliations

Abstract

Figures

Similar articles

Cited by

References

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Abstract

Figures

Similar articles

Cited by

References

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources