Skip to main content

Advertisement

Log in

Genetic Variability and Trajectories of DNA Methylation May Support a Role for HAMP in Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage

  • Original Work
  • Published:
Neurocritical Care Aims and scope Submit manuscript

Abstract

Background/Objective

Preclinical evidence suggests that iron homeostasis is an important biological mechanism following aneurysmal subarachnoid hemorrhage (aSAH); however, this concept is underexplored in humans. This study examined the relationship between patient outcomes following aSAH and genetic variants and DNA methylation in the hepcidin gene (HAMP), a key regulator of iron homeostasis.

Methods

In this exploratory, longitudinal observational study, participants with verified aSAH were monitored for acute outcomes including cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) and evaluated post-discharge at 3 and 12 months for long-term outcomes of death and functional status using the Modified Rankin Scale (mRS; poor = 3–6) and Glasgow Outcome Scale (GOS; poor = 1–3). Participants were genotyped for two genetic variants, and DNA methylation data were collected from serial cerebrospinal fluid over 14 days post-aSAH at eight methylation sites within HAMP. Participants were grouped based on their site-specific DNA methylation trajectory, with and without correcting for cell-type heterogeneity (CTH), and the associations between genetic variants and inferred DNA methylation trajectory groups and patient outcomes were tested. To correct for multiple testing, an empirical significance threshold was computed using permutation testing.

Results

Genotype data for rs10421768 and rs7251432 were available for 241 and 371 participants, respectively, and serial DNA methylation data were available for 260 participants. Acute outcome prevalence included CV in 45% and DCI in 37.1% of the overall sample. Long-term outcome prevalence at 3 and 12 months included poor GOS in 23% and 21%, poor mRS in 31.6% and 27.3%, and mortality in 15.1% and 18.2%, respectively, in the overall sample. Being homozygous for the rs7251432 variant allele was significantly associated with death at 3 months (p = 0.003) and was the only association identified that passed adjustment for multiple testing mentioned above. Suggestive associations (defined as trending toward significance, p value < 0.05, but not meeting empirical significance thresholds) were identified between the homozygous variant allele for rs7251432 and poor GOS and mRS at 3 months (both p = 0.04) and death at 12 months (p = 0.02). For methylation trajectory groups, no associations remained significant after correction for multiple testing. However, for methylation trajectory groups not adjusted for CTH, suggestive associations were identified between cg18149657 and poor GOS and mRS at 3 months (p = 0.003 and p = 0.04, respectively) and death at 3 months (p = 0.04), and between cg26283059 and DCI (p = 0.01). For methylation trajectory groups adjusted for CTH, suggestive associations were identified between cg02131995 and good mRS at 12 months (p = 0.02), and between cg26283059 and DCI (p = 0.01).

Conclusions

This exploratory pilot study offers preliminary evidence that HAMP may play a role in patient outcomes after aSAH. Replication of this study and mechanistic investigation of the role of HAMP in patient outcomes after aSAH are needed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Zacharia BE, Hickman ZL, Grobelny BT, et al. Epidemiology of aneurysmal subarachnoid hemorrhage. Neurosurg Clin N Am. 2010;21(2):221–33. https://doi.org/10.1016/j.nec.2009.10.002.

    Article  PubMed  Google Scholar 

  2. Rosenbaum BP, Kelly ML, Kshettry VR, Weil RJ. Neurologic disorders, in-hospital deaths, and years of potential life lost in the USA, 1988–2011. J Clin Neurosci. 2014;21(11):1874–80. https://doi.org/10.1016/j.jocn.2014.05.006.

    Article  PubMed  Google Scholar 

  3. le Roux AA, Wallace MC. Outcome and cost of aneurysmal subarachnoid hemorrhage. Neurosurg Clin N Am. 2010;21(2):235–46. https://doi.org/10.1016/j.nec.2009.10.014.

    Article  PubMed  Google Scholar 

  4. Lantigua H, Ortega-Gutierrez S, Schmidt JM, et al. Subarachnoid hemorrhage: who dies, and why? Crit Care. 2015;19(1):309. https://doi.org/10.1186/s13054-015-1036-0.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Gomes JA, Selim M, Cotleur A, et al. Brain iron metabolism and brain injury following subarachnoid hemorrhage: iCeFISH-pilot (CSF iron in SAH). Neurocrit Care. 2014;21(2):285–93. https://doi.org/10.1007/s12028-014-9977-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Wagner KR, Sharp FR, Ardizzone TD, Lu A, Clark JF. Heme and iron metabolism: role in cerebral hemorrhage. J Cereb Blood Flow Metab. 2003;23(6):629–52. https://doi.org/10.1097/01.WCB.0000073905.87928.6D.

    Article  CAS  PubMed  Google Scholar 

  7. Ganz T. Hepcidin and iron regulation, 10 years later. Blood. 2011;117(17):4425–33. https://doi.org/10.1182/blood-2011-01-258467.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bishop GM, Robinson SR. Quantitative analysis of cell death and ferritin expression in response to cortical iron: implications for hypoxia-ischemia and stroke. Brain Res. 2001;907(1–2):175–87. https://doi.org/10.1016/S0006-8993(01)02303-4.

    Article  CAS  PubMed  Google Scholar 

  9. Hänninen MM, Haapasalo J, Haapasalo H, et al. Expression of iron-related genes in human brain and brain tumors. BMC Neurosci. 2009;10(1):36. https://doi.org/10.1186/1471-2202-10-36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Nemeth E, Tuttle MS, Powelson J, et al. Hepcidin regulates cellular iron efflux by binding to ferroportin and inducing its internalization. Science. 2004;306(5704):2090–3. https://doi.org/10.1126/science.1104742.

    Article  CAS  PubMed  Google Scholar 

  11. Vela D. Hepcidin, an emerging and important player in brain iron homeostasis. J Transl Med. 2018;16(1):25. https://doi.org/10.1186/s12967-018-1399-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Tan G, Liu L, He Z, Sun J, Xing W, Sun X. Role of hepcidin and its downstream proteins in early brain injury after experimental subarachnoid hemorrhage in rats. Mol Cell Biochem. 2016;418(1–2):31–8. https://doi.org/10.1007/s11010-016-2730-1.

    Article  CAS  PubMed  Google Scholar 

  13. Xiong X-YY, Chen J, Zhu W-YY, et al. Serum hepcidin concentrations correlate with serum iron level and outcome in patients with intracerebral hemorrhage. Neurol Sci. 2015;36(10):1843–9. https://doi.org/10.1007/s10072-015-2266-2.

    Article  PubMed  Google Scholar 

  14. Zhao H, Han Z, Ji X, Luo Y. Epigenetic regulation of oxidative stress in ischemic stroke. Aging Dis. 2016;7(3):295–306. https://doi.org/10.14336/AD.2015.1009.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sciences NI of EH. LD TAG SNP Selection (TagSNP). https://snpinfo.niehs.nih.gov/snpinfo/snptag.html.

  16. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. https://analysistools.nci.nih.gov/LDlink/?var1=rs7251432&var2=rs10421768&pop=CEU&tab=ldpair. Accessed 2 Apr 2018.

  17. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16(3):1215. https://doi.org/10.1093/nar/16.3.1215.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kim H, Crago E, Kim M, et al. Cerebral vasospasm after sub-arachnoid hemorrhage as a clinical predictor and phenotype for genetic association study. Int J Stroke. 2013;8(8):620–5. https://doi.org/10.1111/j.1747-4949.2012.00823.x.

    Article  PubMed  Google Scholar 

  19. Little J, Higgins JPT, Ioannidis JPA, et al. STrengthening the REporting of Genetic Association studies (STREGA)–an extension of the STROBE statement. Eur J Clin Invest. 2009;39(4):247-266. http://www.ncbi.nlm.nih.gov/pubmed/19297801. Accessed 12 Sep 2017.

  20. Groen K, Lea RA, Maltby VE, Scott RJ, Lechner-Scott J. Letter to the editor: blood processing and sample storage have negligible effects on methylation. Clin Epigenet. 2018;10(1):22. https://doi.org/10.1186/s13148-018-0455-6.

    Article  CAS  Google Scholar 

  21. Aryee MJ, Jaffe AE, Corrada-Bravo H, et al. Minfi: a flexible and comprehensive bioconductor package for the analysis of infinium DNA methylation microarrays. Bioinformatics. 2014;30(10):1363–9. https://doi.org/10.1093/bioinformatics/btu049.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Xu Z, Niu L, Li L, Taylor JA. ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. Nucleic Acids Res. 2016;44(3):e20. https://doi.org/10.1093/nar/gkv907.

    Article  CAS  PubMed  Google Scholar 

  23. Houseman EA, Molitor J, Marsit CJ. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics. 2014;30(10):1431–9. https://doi.org/10.1093/bioinformatics/btu029.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Jennett B, Bond M. Assessment of outcome after severe brain damage. Lancet (London, England). 1975;1(7905):480-484. http://www.ncbi.nlm.nih.gov/pubmed/46957. Accessed 3 Jan 2017.

  25. van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988;19(5):604-607. http://www.ncbi.nlm.nih.gov/pubmed/3363593. Accessed 15 May 2017.

  26. Banks JL, Marotta CA. Outcomes validity and reliability of the modified rankin scale: implications for stroke clinical trials - A literature review and synthesis. Stroke. 2007;38(3):1091–6. https://doi.org/10.1161/01.STR.0000258355.23810.c6.

    Article  PubMed  Google Scholar 

  27. Van Swieten JC, Koudstaal PJ, Visser MC, Schouten H, Van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988;19(5):604–7. https://doi.org/10.1161/01.STR.19.5.604.

    Article  PubMed  Google Scholar 

  28. Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating developmental trajectories. Sociol Methods Res. 2001;29(3):374–93. https://doi.org/10.1177/0049124101029003005.

    Article  Google Scholar 

  29. Jones BL, Nagin DS. Advances in group-based trajectory modeling and an SAS procedure for estimating them. Sociol Methods Res. 2007;35(4):542–71. https://doi.org/10.1177/0049124106292364.

    Article  Google Scholar 

  30. Titus AJ, Gallimore RM, Salas LA, Christensen BC. Cell-type deconvolution from DNA methylation: a review of recent applications. Hum Mol Genet. 2017;26(R2):R216–24. https://doi.org/10.1093/hmg/ddx275.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hou Y, Zhang S, Wang L, et al. Estrogen regulates iron homeostasis through governing hepatic hepcidin expression via an estrogen response element. Gene. 2012;511(2):398–403. https://doi.org/10.1016/j.gene.2012.09.060.

    Article  CAS  PubMed  Google Scholar 

  32. Lillvis JH, Kyo Y, Tromp G, et al. Analysis of positional candidate genes in the AAA1 susceptibility locus for abdominal aortic aneurysms on chromosome 19. BMC Med Genet. 2011;12(1):14. https://doi.org/10.1186/1471-2350-12-14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Huang Y-H, Yang KD, Hsu Y-W, et al. Correlation of HAMP gene polymorphisms and expression with the susceptibility and length of hospital stays in Taiwanese children with Kawasaki disease. Oncotarget. July 2017. https://doi.org/10.18632/oncotarget.17700.

  34. Ishida A, Matsuo S, Kawamura S, Nishikawa T. Subarachnoid hemorrhage due to nonbranching aneurysm of the middle cerebral artery in a young adult with a history of Kawasaki disease. Surg Neurol Int. 2014;5:5. https://doi.org/10.4103/2152-7806.125285.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Ahn JH, Phi JH, Kang H-S, et al. A ruptured middle cerebral artery aneurysm in a 13-month-old boy with Kawasaki disease. J Neurosurg Pediatr. 2010;6(2):150–3. https://doi.org/10.3171/2010.5.PEDS1012.

    Article  PubMed  Google Scholar 

  36. Tanaka S, Sagiuchi T, Kobayashi I. Ruptured pediatric posterior cerebral artery aneurysm 9 years after the onset of Kawasaki disease: a case report. Child’s Nerv Syst. 2007;23(6):701–6. https://doi.org/10.1007/s00381-006-0263-8.

    Article  Google Scholar 

  37. Tanweer O, Wilson TA, Metaxa E, Riina HA, Meng H. A comparative review of the hemodynamics and pathogenesis of cerebral and abdominal aortic aneurysms: lessons to learn from each other. J Cerebrovasc Endovasc Neurosurg. 2014;16(4):335–49. https://doi.org/10.7461/jcen.2014.16.4.335.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Gerile W, Yang H, Longyan Y, Jing N, Jingling W, Hongshu J. Association between rs7251432 Polymorphism in hepcidin gene and change in hemogram after the HiHiLo training in men of Han Nationality. Chin J Sport Med. 2010;29(4):386-390. http://caod.oriprobe.com/articles/25996307/Association_between_rs7251432_Polymorphism_in_Hepcidin_Gene_and_Change.htm. Accessed June 6, 2017.

  39. Chen Y, Jiang C, Luo Y, Liu F, Gao Y. Interaction of CARD14, SENP1 and VEGFA polymorphisms on susceptibility to high altitude polycythemia in the Han Chinese population at the Qinghai-Tibetan Plateau. Blood Cells Mol Dis. 2016;57:13–22. https://doi.org/10.1016/j.bcmd.2015.11.005.

    Article  CAS  PubMed  Google Scholar 

  40. Festic E, Rabinstein AA, Freeman WD, et al. Blood transfusion is an important predictor of hospital mortality among patients with aneurysmal subarachnoid hemorrhage. Neurocrit Care. 2013;18(2):209–15. https://doi.org/10.1007/s12028-012-9777-y.

    Article  PubMed  Google Scholar 

  41. Rebel A, Ulatowski JA, Kwansa H, Bucci E, Koehler RC. Cerebrovascular response to decreased hematocrit: effect of cell-free hemoglobin, plasma viscosity, and CO2. Am J Physiol Heart Circ Physiol. 2003;285(4):H1600–8. https://doi.org/10.1152/ajpheart.00077.2003.

    Article  CAS  PubMed  Google Scholar 

  42. Hoffman WE, Wheeler P, Edelman G, Charbel FT, Torres NJ, Ausman JI. Hypoxic brain tissue following subarachnoid hemorrhage. Anesthesiology. 2000;92(2):442–446. http://www.ncbi.nlm.nih.gov/pubmed/10691231. Accessed 3 April 2018.

  43. Andreani M, Radio FC, Testi M, et al. Association of hepcidin promoter c.-582 A > G variant and iron overload in thalassemia major. Haematologica. 2009;94(9):1293–1296. https://doi.org/10.3324/haematol.2009.006270.

  44. Huang YH, Kuo HC, Li SC, Cai XY, Liu SF, Kuo HC. HAMP promoter hypomethylation and increased hepcidin levels as biomarkers for Kawasaki disease. J Mol Cell Cardiol. 2018;117:82–7. https://doi.org/10.1016/j.yjmcc.2018.02.017.

    Article  CAS  PubMed  Google Scholar 

  45. Bickford JS, Ali NF, Nick JA, et al. Endothelin-1-mediated vasoconstriction alters cerebral gene expression in iron homeostasis and eicosanoid metabolism. Brain Res. 2014;1588:25–36. https://doi.org/10.1016/j.brainres.2014.09.022.

    Article  CAS  PubMed  Google Scholar 

  46. Liu J, Sun B, Yin H, Liu S. Hepcidin: a promising therapeutic target for iron disorders: a systematic review. Medicine (Baltimore). 2016;95(14):e3150. https://doi.org/10.1097/MD.0000000000003150.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Thampatty BP, Sherwood PR, Gallek MJ, et al. Role of endothelin-1 in human aneurysmal subarachnoid hemorrhage: associations with vasospasm and delayed cerebral ischemia. Neurocrit Care. 2011;15(1):19–27. https://doi.org/10.1007/s12028-011-9508-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li S, Wong EM, Bui M, et al. Inference about causation between body mass index and DNA methylation in blood from a twin family study. International Journal of Obesity. https://www.biorxiv.org/content/early/2017/11/21/223040. Published November 21, 2018. Accessed 26 Aug 2018.

  49. Li S, Wong EM, Bui M, et al. Causal effect of smoking on DNA methylation in peripheral blood: a twin and family study. Clin Epigenetics. 2018;10(1):18. https://doi.org/10.1186/s13148-018-0452-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would also like to acknowledge the anonymous reviewers who took the time to critically evaluate this paper. Their detailed feedback greatly improved the clarity and quality of this work for the scientific community.

Funding

Research reported in this publication was supported by the National Instiute of Nursing Research of the National Institutes of Health under Award Numbers F31NR017311, R01NR004339, R01NR013610, and T32NR009759 and with additional support from the International Society of Nurses in Genetics, University of Pittsburgh Leslie A. Hoffman Endowed Research Award, Nightingale Awards of Pennsylvania, and Eta Chapter, Sigma Theta Tau, Inc. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or supporting foundations.

Author information

Authors and Affiliations

Authors

Contributions

LWH contributed to the study conception and design, analysis and interpretation of data, and drafted, critically revised, and gave final approval for the manuscript. AIA contributed to the analysis of data and critically revised and gave final approval for the manuscript. EAC contributed to the acquisition and interpretation of data and critically revised and gave final approval for the manuscript. DR contributed to the analysis and interpretation of data and critically revised and gave final approval for the manuscript. JRS contributed to analysis and interpretation of the data and critically revised and gave final approval for the manuscript. PRS contributed to the acquisition of data and critically revised and gave final approval for the manuscript. SMS contributed to the analysis and interpretation of data and critically revised and gave final approval for the manuscript. DEW contributed to the study design, analysis and interpretation of data, and critically revised and gave final approval for the manuscript. YPC contributed to the study conception and design, interpretation of data, and critically revised and gave final approval for the manuscript. All authors agree to be accountable for all aspects of the work in ensuring that questions relating to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors meet authorship criteria, have read and approved the published work, and certify that they have participated sufficiently in the work to take responsibility for the content including the concept, design, analysis, writing, or revision (see author contributions above).

Corresponding author

Correspondence to Lacey W. Heinsberg.

Ethics declarations

Conflict of interest

LW Heinsberg reports grants from the National Institute of Nursing Research, University of Pittsburgh, Eta Chapter, Sigma Theta Tau, Inc., and International Society of Nurses in Genetics during the conduct of this study. YP Conley and PR Sherwood reports grants from the National Institute of Nursing Research. EA Crago reports grants from the University of Pittsburgh. The remaining authors report no conflicts of interest to disclose.

Ethical Approval

Institutional review board approval at the University of Pittsburgh has been obtained (IRB Approval Number 021039), and we have adhered to ethical considerations in the protection of all human subjects involved.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 11539 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Heinsberg, L.W., Arockiaraj, A.I., Crago, E.A. et al. Genetic Variability and Trajectories of DNA Methylation May Support a Role for HAMP in Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage. Neurocrit Care 32, 550–563 (2020). https://doi.org/10.1007/s12028-019-00787-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-019-00787-4

Keywords

Navigation