1. Theo Vos, Stephen S Lim & Cristiana Abbafati. et al. (GBD 2019 Diseases and
Injuries Collaborators). Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of
Disease Study 2019. Lancet 396, 1204–1222 (2020).
2. Lepine, J. P. & Briley, M. The increasing burden of depression. Neuropsychiatr. Dis.
Treat 7, 3–7 (2011).
3. Darrow, S. M. et al. The association between psychiatric disorders and telomere
length: a meta-analysis involving 14,827 persons. Psychosom. Med. 78, 776–787
(2016).
4. Ridout, K. K., Ridout, S. J., Price, L. H., Sen, S. & Tyrka, A. R. Depression and
telomere length: a meta-analysis. J. Affect. Disord. 191, 237–247 (2016).
5. Richmond-Rakerd, L. S., D’Souza, S., Milne, B. J., Caspi, A. & Moffitt, T. E. Longitudinal associations of mental disorders with dementia: 30-year analysis of 1.7
million New Zealand citizens. JAMA Psychiatry 79, 333–340 (2022).
6. Yang, L. et al. Depression, depression treatments, and risk of incident dementia: a
prospective cohort study of 354,313 participants. Biol. Psychiatry https://doi.org/
10.1016/j.biopsych.2022.08.026 (2022).
7. Bartels, C. et al. Impact of SSRI therapy on risk of conversion from mild cognitive
impairment to alzheimer’s dementia in individuals with previous depression. Am.
J. Psychiatry 175, 232–241 (2018).
8. Wolkowitz, O. M. et al. Resting leukocyte telomerase activity is elevated in major
depression and predicts treatment response. Mol. Psychiatry 17, 164–172 (2012).
9. Hannum, G. et al. Genome-wide methylation profiles reveal quantitative views of
human aging rates. Mol. Cell 49, 359–367 (2013).
10. Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol.
10, R115 (2013).
11. Horvath, S. et al. Epigenetic clock for skin and blood cells applied to Hutchinson
Gilford Progeria Syndrome and ex vivo studies. Aging 10, 1758–1775 (2018).
12. Levine, M. E. et al. An epigenetic biomarker of aging for lifespan and healthspan.
Aging 10, 573–591 (2018).
13. Lu, A. T. et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging 11, 303–327 (2019).
14. Lu, A. T. et al. DNA methylation-based estimator of telomere length. Aging 11,
5895–5923 (2019).
15. Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell
mixture distribution. BMC Bioinformatics 13, https://doi.org/10.1186/1471-210513-86 (2012).
16. Cao, X. et al. Accelerated biological aging in COVID-19 patients. Nat. Commun. 13,
2135 (2022).
17. Kresovich, J. K. et al. Epigenetic mortality predictors and incidence of breast
cancer. Aging 11, 11975–11987 (2019).
18. Lind, L., Ingelsson, E., Sundstrom, J., Siegbahn, A. & Lampa, E. Methylation-based
estimated biological age and cardiovascular disease. Eur. J. Clin. Invest. 48, https://
doi.org/10.1111/eci.12872 (2018).
19. Fraszczyk, E. et al. DNA methylation trajectories and accelerated epigenetic aging
in incident type 2 diabetes. Geroscience 44, 2671–2684 (2022).
20. Whalley, H. C. et al. Accelerated epigenetic ageing in major depressive disorder.
https://www.biorxiv.org/content/10.1101/210666v1 (2017).
21. Tanifuji, T. et al. Epigenetic clock analysis reveals increased plasma cystatin C
levels based on DNA methylation in major depressive disorder. Psychiatry Res.
https://doi.org/10.1016/j.psychres.2023.115103 (2023).
22. Rampersaud, R. et al. Dimensions of childhood adversity differentially affect
biological aging in major depression. Transl. Psychiatry 12, 431 (2022).
23. Protsenko, E. et al. "GrimAge," an epigenetic predictor of mortality, is accelerated
in major depressive disorder. Transl. Psychiatry 11, 193 (2021).
24. Luo, A. et al. Epigenetic aging is accelerated in alcohol use disorder and regulated
by genetic variation in APOL2. Neuropsychopharmacology 45, 327–336 (2020).
25. Li, Z., He, Y., Ma, X. & Chen, X. Epigenetic age analysis of brain in major depressive
disorder. Psychiatry Res. 269, 621–624 (2018).
26. Okazaki, S. et al. Decelerated epigenetic aging associated with mood stabilizers in
the blood of patients with bipolar disorder. Transl. Psychiatry 10, 129 (2020).
27. Okazaki, S. et al. Epigenetic clock analysis of blood samples from Japanese
schizophrenia patients. NPJ. Schizophr. 5, 4 (2019).
Published in partnership with the Japanese Society of Anti-Aging Medicine
R. Shindo et al.
28. Katrinli, S. et al. Evaluating the impact of trauma and PTSD on epigenetic prediction of lifespan and neural integrity. Neuropsychopharmacology 45, 1609–1616
(2020).
29. Okazaki, S. et al. Accelerated extrinsic epigenetic aging and increased natural
killer cells in blood of suicide completers. Prog. Neuropsychopharmacol. Biol.
Psychiatry 98, 109805 (2020).
30. Marioni, R. E. et al. DNA methylation age of blood predicts all-cause mortality in
later life. Genome. Biol. 16, 1–12 (2015).
31. Ryan, C. P. "Epigenetic clocks": Theory and applications in human biology. Am. J.
Hum. Biol. 33, e23488 (2021).
32. Han, L. K. M. et al. Epigenetic aging in major depressive disorder. Am. J. Psychiatry
175, 774–782 (2018).
33. Liu, C. et al. Association between depression and epigenetic age acceleration: a
co-twin control study. Depress Anxiety 39, 741–750 (2022).
34. McKenna, B. G. et al. Maternal prenatal depression and epigenetic age deceleration: testing potentially confounding effects of prenatal stress and SSRI use.
Epigenetics 16, 327–337 (2021).
35. Collins, K. & Mitchell, J. R. Telomerase in the human organism. Oncogene 21,
564–579 (2002).
36. Blackburn, E. H. Switching and signaling at the telomere. Cell 106, 661–673 (2001).
37. Blasco, M. A. Telomeres and human disease: ageing, cancer and beyond. Nat. Rev.
Genet. 6, 611–622 (2005).
38. Wolkowitz, O. M. et al. Leukocyte telomere length in major depression: correlations with chronicity, inflammation and oxidative stress–preliminary findings.
PLoS ONE 6, e17837 (2011).
39. Simon, N. M. et al. Telomere shortening and mood disorders: preliminary support for
a chronic stress model of accelerated aging. Biol. Psychiatry 60, 432–435 (2006).
40. Garcia-Rizo, C. et al. Abnormal glucose tolerance, white blood cell count, and
telomere length in newly diagnosed, antidepressant-naive patients with
depression. Brain Behav. Immun. 28, 49–53 (2013).
41. Tian, Y. E. et al. Evaluation of brain-body health in individuals with common
neuropsychiatric
disorders.
JAMA
Psychiatry
https://doi.org/10.1001/
jamapsychiatry.2023.0791 (2023).
42. Jokinen, J. & Nordstrom, P. HPA axis hyperactivity and cardiovascular mortality in
mood disorder inpatients. J. Affect. Disord. 116, 88–92 (2009).
43. McKay, M. S. & Zakzanis, K. K. The impact of treatment on HPA axis activity in
unipolar major depression. J. Psychiatr. Res. 44, 183–192 (2010).
44. Sun, T., Chen, Q. & Li, Y. Associations of serum cystatin C with depressive symptoms
and suicidal ideation in major depressive disorder. BMC Psychiatry 21, 576 (2021).
45. Li, H. et al. Cystatin C and risk of new-onset depressive symptoms among individuals with a normal creatinine-based estimated glomerular filtration rate: a
prospective cohort study. Psychiatry Res. 273, 75–81 (2019).
46. Huang, Y., Huang, W., Wei, J., Yin, Z. & Liu, H. Increased serum cystatin C levels
were associated with depressive symptoms in patients with type 2 diabetes.
Diabetes Metab Syndr Obes 14, 857–863 (2021).
47. Evangelopoulos, A. A. et al. Association between serum cystatin C, monocytes
and other inflammatory markers. Intern. Med. J. 42, 517–522 (2012).
48. Zi, M. & Xu, Y. Involvement of cystatin C in immunity and apoptosis. Immunol.
Lett. 196, 80–90 (2018).
49. Colasanto, M., Madigan, S. & Korczak, D. J. Depression and inflammation among
children and adolescents: a meta-analysis. J. Affect. Disord. 277, 940–948 (2020).
50. Jokela, M., Virtanen, M., Batty, G. D. & Kivimaki, M. Inflammation and specific
symptoms of depression. JAMA Psychiatry 73, 87–88 (2016).
51. Kiecolt-Glaser, J. K., Derry, H. M. & Fagundes, C. P. Inflammation: depression fans
the flames and feasts on the heat. Am. J. Psychiatry 172, 1075–1091 (2015).
52. Ishikawa, Y. et al. Repeated social defeat stress induces neutrophil mobilization in
mice: maintenance after cessation of stress and strain-dependent difference in
response. Br. J. Pharmacol. 178, 827–844 (2021).
53. Maydych, V. et al. Impact of chronic and acute academic stress on lymphocyte
subsets and monocyte function. PLoS ONE 12, e0188108 (2017).
54. Suzuki, H. et al. Altered populations of natural killer cells, cytotoxic T lymphocytes,
and regulatory T cells in major depressive disorder: Association with sleep disturbance. Brain Behav. Immun. 66, 193–200 (2017).
55. Kim, Y. K. et al. Differences in cytokines between non-suicidal patients and suicidal patients in major depression. Prog. Neuropsychopharmacol. Biol. Psychiatry
32, 356–361 (2008).
56. Cooper, M. A., Fehniger, T. A. & Caligiuri, M. A. The biology of human natural killercell subsets. Trends Immunol. 22, 633–640 (2001).
57. Breen, M. S. et al. Acute psychological stress induces short-term variable immune
response. Brain Behav. Immun. 53, 172–182 (2016).
Published in partnership with the Japanese Society of Anti-Aging Medicine
58. Zhou, D. et al. A novel joint index based on peripheral blood CD4+/CD8+ T cell
ratio, albumin level, and monocyte count to determine the severity of major
depressive disorder. BMC Psychiatry 22, 248 (2022).
59. Khan, S., Michaud, D., Moody, T. W., Anisman, H. & Merali, Z. Effects of acute
restraint stress on endogenous adrenomedullin levels. NeuroReport 10,
2829–2833 (1999).
60. Akpinar, A., Yaman, G. B., Demirdas, A. & Onal, S. Possible role of adrenomedullin
and nitric oxide in major depression. Prog. Neuropsychopharmacol. Biol. Psychiatry
46, 120–125 (2013).
61. Jiang, H. et al. Plasminogen activator inhibitor-1 in depression: results from animal and clinical studies. Sci. Rep. 6, 30464 (2016).
62. Lahlou-Laforet, K. et al. Relation of depressive mood to plasminogen activator
inhibitor, tissue plasminogen activator, and fibrinogen levels in patients with
versus without coronary heart disease. Am. J. Cardiol. 97, 1287–1291 (2006).
63. Chan, M. K. et al. Blood-based immune-endocrine biomarkers of treatment
response in depression. J. Psychiatr. Res. 83, 249–259 (2016).
64. Xiu, J. et al. Elevated BICD2 DNA methylation in blood of major depressive disorder patients and reduction of depressive-like behaviors in hippocampal Bicd2knockdown mice. Proc. Natl Acad. Sci. USA 119, e2201967119 (2022).
65. Kanda, Y. Investigation of the freely available easy-to-use software ‘EZR’ for
medical statistics. Bone Marrow Transplant 48, 452–458 (2013).
ACKNOWLEDGEMENTS
This work was partially supported by JSPS KAKENHI grant numbers JP18K15483,
JP21K07520 (S.O.), JP17H04249, and JP21H02852 (A.H.).
AUTHOR CONTRIBUTIONS
S.O. and A.H. designed the study. S.O. and A.H. conducted the research. R.S., T.T., S.O.,
I.O., T.S., K.M., and T.H. collected data. R.S., T.T., I.O., T.S., K.M., and T.H. performed
statistical analysis. T.T. investigated and visualized the data. R.S. and T.T. wrote and
structured the first draft of the manuscript. S.O. and A.H. reviewed the manuscript. All
authors contributed to and approved the final manuscript. R.S. and T.T. equally
contributed to the work and are co-first authors.
COMPETING INTERESTS
The authors declare no competing interests.
ADDITIONAL INFORMATION
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1038/s41514-023-00117-1.
Correspondence and requests for materials should be addressed to Satoshi Okazaki.
Reprints and permission information is available at http://www.nature.com/
reprints
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims
in published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article’s Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly
from the copyright holder. To view a copy of this license, visit http://
creativecommons.org/licenses/by/4.0/.
© The Author(s) 2023
npj Aging (2023) 19
...
論文の公開元へ
