REFERENCES.

1. Almasy L, Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998; 62:1198–211. https://doi.org/10.1086/301844 [PubMed]

2. Anton, S. et al (2018). Flipping the Metabolic Switch: Understanding and Applying the Health Benefits of Fasting. https://pubmed.ncbi.nlm.nih.gov/29086496/

3. Altayyar, M. et al (2022). The Implication of Physiological Ketosis on The Cognitive Brain: A Narrative Review. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840718/

4. Andersson C, Enserro D, Sullivan L, Wang TJ, Januzzi JLJr, Benjamin EJ, Vita JA, Hamburg NM, Larson MG, Mitchell GF, Vasan RS. Relations of circulating GDF-15, soluble ST2, and troponin-I concentrations with vascular function in the community: The Framingham Heart Study. Atherosclerosis. 2016; 248:245–51. https://doi.org/10.1016/j.atherosclerosis.2016.02.013 [PubMed]

5. Ashutosh CC, Chao C, Borgmann K, Brew K, Ghorpade A. Tissue inhibitor of metalloproteinases-1 protects human neurons from staurosporine and HIV-1-induced apoptosis: mechanisms and relevance to HIV-1-associated dementia. Cell Death Dis. 2012; 3:e332. https://doi.org/10.1038/cddis.2012.54 [PubMed]

6. Aung T, Halsey J, Kromhout D, Gerstein HC, Marchioli R, Tavazzi L, Geleijnse JM, Rauch B, Ness A, Galan P, Chew EY, Bosch J, Collins R, et al, and Omega-3 Treatment Trialists’ Collaboration. Associations of Omega-3 Fatty Acid Supplement Use With Cardiovascular Disease Risks: Meta-analysis of 10 Trials Involving 77 917 Individuals. JAMA Cardiol. 2018; 3:225–34. https://doi.org/10.1001/jamacardio.2017.5205 [PubMed]

7. Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, Roetker NS, Just AC, Demerath EW, Guan W, Bressler J, Fornage M, Studenski S, et al. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY). 2016; 8:1844–65. https://doi.org/10.18632/aging.101020 [PubMed]

8. Carlstrom, M. et al (2018). Coffee Consumption and Reduced Risk of Developing Type 2 Diabetes: A Systematic Review With Meta-Analysis. https://pubmed.ncbi.nlm.nih.gov/29590460/ 

9. Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, Ohannesian JP, Marco CC, McKee LJ, Bauer TL, Caro JF. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med. 1996; 334:292–95. https://doi.org/10.1056/NEJM199602013340503 [PubMed]

10. Cesari M, Pahor M, Incalzi RA. Plasminogen activator inhibitor-1 (PAI-1): a key factor linking fibrinolysis and age-related subclinical and clinical conditions. Cardiovasc Ther. 2010; 28:e72–91. https://doi.org/10.1111/j.1755-5922.2010.00171.x [PubMed]

12. Dawber TR, Meadors GF, Moore FEJr. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health Nations Health. 1951; 41:279–81. https://doi.org/10.2105/AJPH.41.3.279 [PubMed

15. Fortin JP, Triche TJJr, Hansen KD. Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi. Bioinformatics. 2017; 33:558–60. https://doi.org/10.1093/bioinformatics/btw691 [PubMed]

16. Ferguson TW, Komenda P, Tangri N. Cystatin C as a biomarker for estimating glomerular filtration rate. Curr Opin Nephrol Hypertens. 2015; 24:295–300. https://doi.org/10.1097/MNH.0000000000000115 [PubMed]

17. Fujita Y, Taniguchi Y, Shinkai S, Tanaka M, Ito M. Secreted growth differentiation factor 15 as a potential biomarker for mitochondrial dysfunctions in aging and age-related disorders. Geriatr Gerontol Int. 2016 (Suppl 1); 16:17–29. https://doi.org/10.1111/ggi.12724 [PubMed]

18. Framingham Heart Study – Wikipedia https://en.wikipedia.org/wiki/Framingham_Heart_Study

21. Gao X, Jia M, Zhang Y, Breitling LP, Brenner H. DNA methylation changes of whole blood cells in response to active smoking exposure in adults: a systematic review of DNA methylation studies. Clin Epigenetics. 2015; 7:113. https://doi.org/10.1186/s13148-015-0148-3 [PubMed]

23. Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013; 14:R115. https://doi.org/10.1186/gb-2013-14-10-r115 [PubMed]

24. Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, Klotzle B, Bibikova M, Fan JB, Gao Y, Deconde R, Chen M, Rajapakse I, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013; 49:359–67. https://doi.org/10.1016/j.molcel.2012.10.016 [PubMed]

25. Horvath S, Oshima J, Martin GM, Lu AT, Quach A, Cohen H, Felton S, Matsuyama M, Lowe D, Kabacik S, Wilson JG, Reiner AP, Maierhofer A, et al. Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies. Aging (Albany NY). 2018; 10:1758–75. https://doi.org/10.18632/aging.101508 [PubMed]

26. Horvath S, Ritz BR. Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients. Aging (Albany NY). 2015; 7:1130–42. https://doi.org/10.18632/aging.100859 [PubMed]

27. Horvath S, Langfelder P, Kwak S, Aaronson J, Rosinski J, Vogt TF, Eszes M, Faull RL, Curtis MA, Waldvogel HJ, Choi OW, Tung S, Vinters HV, et al. Huntington’s disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels. Aging (Albany NY). 2016; 8:1485–512. https://doi.org/10.18632/aging.101005 [PubMed]

28. Horvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018; 19:371–84. https://doi.org/10.1038/s41576-018-0004-3 [PubMed]

29. Horvath S, Garagnani P, Bacalini MG, Pirazzini C, Salvioli S, Gentilini D, Di Blasio AM, Giuliani C, Tung S, Vinters HV, Franceschi C. Accelerated epigenetic aging in Down syndrome. Aging Cell. 2015; 14:491–95. https://doi.org/10.1111/acel.12325 [PubMed]

30. Horvath S, Pirazzini C, Bacalini MG, Gentilini D, Di Blasio AM, Delledonne M, Mari D, Arosio B, Monti D, Passarino G, De Rango F, D’Aquila P, Giuliani C, et al. Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring. Aging (Albany NY). 2015; 7:1159–70. https://doi.org/10.18632/aging.100861 [PubMed]

31. Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, Ritz BR, Chen B, Lu AT, Rickabaugh TM, Jamieson BD, Sun D, Li S, et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol. 2016; 17:171. https://doi.org/10.1186/s13059-016-1030-0 [PubMed]

32. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012; 13:86. https://doi.org/10.1186/1471-2105-13-86 [PubMed]

33. Horvath S, Levine AJ. HIV-1 infection accelerates age according to the epigenetic clock. J Infect Dis. 2015; 212:1563–73. https://doi.org/10.1093/infdis/jiv277 [PubMed]

34. Horvath S, Erhart W, Brosch M, Ammerpohl O, von Schönfels W, Ahrens M, Heits N, Bell JT, Tsai PC, Spector TD, Deloukas P, Siebert R, Sipos B, et al. Obesity accelerates epigenetic aging of human liver. Proc Natl Acad Sci USA. 2014; 111:15538–43. https://doi.org/10.1073/pnas.1412759111 [PubMed]

35. Ignjatovic V, Lai C, Summerhayes R, Mathesius U, Tawfilis S, Perugini MA, Monagle P. Age-related differences in plasma proteins: how plasma proteins change from neonates to adults. PLoS One. 2011; 6:e17213. https://doi.org/10.1371/journal.pone.0017213 [PubMed]

36. Jung M, Pfeifer GP. Aging and DNA methylation. BMC Biol. 2015; 13:7. https://doi.org/10.1186/s12915-015-0118-4 [PubMed]

37. Jylhävä J, Pedersen NL, Hägg S. Biological Age Predictors. EBioMedicine. 2017; 21:29–36. https://doi.org/10.1016/j.ebiom.2017.03.046 [PubMed]

38. Khan SS, Shah SJ, Klyachko E, Baldridge AS, Eren M, Place AT, Aviv A, Puterman E, Lloyd-Jones DM, Heiman M, Miyata T, Gupta S, Shapiro AD, et al. A null mutation in SERPINE1 protects against biological aging in humans. Sci Adv. 2017; 3:eaao1617. https://doi.org/10.1126/sciadv.aao1617 [PubMed]

39. Kabacik S, Horvath S, Cohen H, Raj K. Epigenetic ageing is distinct from senescence-mediated ageing and is not prevented by telomerase expression. Aging (Albany NY). 2018; 10:2800–15. https://doi.org/10.18632/aging.101588 [PubMed]

42. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008; 9:559. https://doi.org/10.1186/1471-2105-9-559 [PubMed]

43. Lu AT, Hannon E, Levine ME, Hao K, Crimmins EM, Lunnon K, Kozlenkov A, Mill J, Dracheva S, Horvath S. Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum. Nat Commun. 2016; 7:10561. https://doi.org/10.1038/ncomms10561 [PubMed]

44. Lu AT, Hannon E, Levine ME, Crimmins EM, Lunnon K, Mill J, Geschwind DH, Horvath S. Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nat Commun. 2017; 8:15353. https://doi.org/10.1038/ncomms15353 [PubMed]

45. Lu AT, Xue L, Salfati EL, Chen BH, Ferrucci L, Levy D, Joehanes R, Murabito JM, Kiel DP, Tsai PC, Yet I, Bell JT, Mangino M, et al. GWAS of epigenetic aging rates in blood reveals a critical role for TERT. Nat Commun. 2018; 9:387. https://doi.org/10.1038/s41467-017-02697-5 [PubMed]

46. Lowe D, Horvath S, Raj K. Epigenetic clock analyses of cellular senescence and ageing. Oncotarget. 2016; 7:8524–31. https://doi.org/10.18632/oncotarget.7383 [PubMed]

47. Liabeuf S, Lenglet A, Desjardins L, Neirynck N, Glorieux G, Lemke HD, Vanholder R, Diouf M, Choukroun G, Massy ZA, and European Uremic Toxin Work Group (EUTox). Plasma beta-2 microglobulin is associated with cardiovascular disease in uremic patients. Kidney Int. 2012; 82:1297–303. https://doi.org/10.1038/ki.2012.301 [PubMed]

39. Almasy L, Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 1998; 62:1198–211. https://doi.org/10.1086/301844 [PubMed]

40. Larrayoz IM, Ferrero H, Martisova E, Gil-Bea FJ, Ramírez MJ, Martínez A. Adrenomedullin Contributes to Age-Related Memory Loss in Mice and Is Elevated in Aging Human Brains. Front Mol Neurosci. 2017; 10:384. https://doi.org/10.3389/fnmol.2017.00384 [PubMed]

40. Loewenthal, J. et al (2023). Effect of Yoga on Frailty in Older Adults.

41. Lee JJ, Pedley A, Hoffmann U, Massaro JM, Keaney JFJr, Vasan RS, Fox CS. Cross-Sectional Associations of Computed Tomography (CT)-Derived Adipose Tissue Density and Adipokines: The Framingham Heart Study. J Am Heart Assoc. 2016; 5:e002545. https://doi.org/10.1161/JAHA.115.002545 [PubMed]

42. Long MT, Pedley A, Massaro JM, Hoffmann U, Fox CS. The Association between Non-Invasive Hepatic Fibrosis Markers and Cardiometabolic Risk Factors in the Framingham Heart Study. PLoS One. 2016; 11:e0157517. https://doi.org/10.1371/journal.pone.0157517 [PubMed]

43. Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018; 10:573–91. https://doi.org/10.18632/aging.101414 [PubMed]

44. Levine ME, Lu AT, Bennett DA, Horvath S. Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning. Aging (Albany NY). 2015; 7:1198–211. https://doi.org/10.18632/aging.100864 [PubMed]

45. Levine ME, Hosgood HD, Chen B, Absher D, Assimes T, Horvath S. DNA methylation age of blood predicts future onset of lung cancer in the women’s health initiative. Aging (Albany NY). 2015; 7:690–700. https://doi.org/10.18632/aging.100809 [PubMed]

46. Levine ME, Lu AT, Chen BH, Hernandez DG, Singleton AB, Ferrucci L, Bandinelli S, Salfati E, Manson JE, Quach A, Kusters CD, Kuh D, Wong A, et al. Menopause accelerates biological aging. Proc Natl Acad Sci USA. 2016; 113:9327–32. https://doi.org/10.1073/pnas.1604558113 [PubMed]

47. Lin Q, Weidner CI, Costa IG, Marioni RE, Ferreira MR, Deary IJ, Wagner W. DNA methylation levels at individual age-associated CpG sites can be indicative for life expectancy. Aging (Albany NY). 2016; 8:394–401. https://doi.org/10.18632/aging.100908 [PubMed]

48. Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, Pattie A, Corley J, Murphy L, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015; 16:25. https://doi.org/10.1186/s13059-015-0584-6 [PubMed]

49.Mattson, M. et al (2017). Impact of Intermittent Fasting on Health and Disease Process. https://www.sciencedirect.com/science/article/pii/S1568163716302513

50. Maierhofer A, Flunkert J, Oshima J, Martin GM, Haaf T, Horvath S. Accelerated epigenetic aging in Werner syndrome. Aging (Albany NY). 2017; 9:1143–52. https://doi.org/10.18632/aging.101217 [PubMed]

51. Marioni RE, Shah S, McRae AF, Ritchie SJ, Muniz-Terrera G, Harris SE, Gibson J, Redmond P, Cox SR, Pattie A, Corley J, Taylor A, Murphy L, et al. The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936. Int J Epidemiol. 2015; 44:1388–96. https://doi.org/10.1093/ije/dyu277 [PubMed]

52. McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, Wenger AM, Bejerano G. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010; 28:495–501. https://doi.org/10.1038/nbt.1630 [PubMed]

52. Moore, L., Le, T. & Fan, G. (2013). DNA Methylation and Its Basic Function.

53. Nwanaji-Enwerem JC, Weisskopf MG, Baccarelli AA. Multi-tissue DNA methylation age: molecular relationships and perspectives for advancing biomarker utility. Ageing Res Rev. 2018; 45:15–23. https://doi.org/10.1016/j.arr.2018.04.005 [PubMed]

54. Nehlig, A (2016). Effects of Coffee/Caffeine on Brain Health and Disease: What Should I Tell My Patients? https://pubmed.ncbi.nlm.nih.gov/26677204/

55. Perna L, Zhang Y, Mons U, Holleczek B, Saum KU, Brenner H. Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort. Clin Epigenetics. 2016; 8:64. https://doi.org/10.1186/s13148-016-0228-z [PubMed]

56. Paiva, C. et al (2019). Consumption of Coffee or Caffeine and Serum Concentration of Inflammatory Markers: A Systematic Review. https://pubmed.ncbi.nlm.nih.gov/28967799/

56. Pandi-Perumal, S. et al (2022). The Origin and Clinical Relevance of Yoga Nidra.

57. Quach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, Ritz B, Bandinelli S, Neuhouser ML, Beasley JM, Snetselaar L, Wallace RB, Tsao PS, et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging (Albany NY). 2017; 9:419–46. https://doi.org/10.18632/aging.101168 [PubMed]

58. Ridker PM, Buring JE, Cook NR, Rifai N. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of 14 719 initially healthy American women. Circulation. 2003; 107:391–97. https://doi.org/10.1161/01.CIR.0000055014.62083.05 [PubMed]

59. Rizos EC, Ntzani EE, Bika E, Kostapanos MS, Elisaf MS. Association between omega-3 fatty acid supplementation and risk of major cardiovascular disease events: a systematic review and meta-analysis. JAMA. 2012; 308:1024–33. https://doi.org/10.1001/2012.jama.11374 [PubMed]

60. Rizos EC, Elisaf MS. Does Supplementation with Omega-3 PUFAs Add to the Prevention of Cardiovascular Disease? Curr Cardiol Rep. 2017; 19:47. https://doi.org/10.1007/s11886-017-0856-8 [PubMed]

61. Ridker PM. High-sensitivity C-reactive protein: potential adjunct for global risk assessment in the primary prevention of cardiovascular disease. Circulation. 2001; 103:1813–18. https://doi.org/10.1161/01.CIR.103.13.1813 [PubMed]

62. Rosenbaum M, Nicolson M, Hirsch J, Heymsfield SB, Gallagher D, Chu F, Leibel RL. Effects of gender, body composition, and menopause on plasma concentrations of leptin. J Clin Endocrinol Metab. 1996; 81:3424–27. https://doi.org/10.1210/jcem.81.9.8784109 [PubMed]

63. Smith LK, He Y, Park JS, Bieri G, Snethlage CE, Lin K, Gontier G, Wabl R, Plambeck KE, Udeochu J, Wheatley EG, Bouchard J, Eggel A, et al. β2-microglobulin is a systemic pro-aging factor that impairs cognitive function and neurogenesis. Nat Med. 2015; 21:932–37. https://doi.org/10.1038/nm.3898 [PubMed]

64. Strength, But Not Muscle Mass, Is Associated With Mortality in the Health, Aging and Body Composition Study Cohort https://academic.oup.com/biomedgerontology/article/61/1/72/549632#.Y_MHv0cL-Kw.mailto

65. Stote, K. et al (2009). A controlled trial of reduced meal frequency without caloric restriction in healthy, normal-weight, middle-aged adults. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2645638/

66. Triche TJJr, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-level processing of Illumina Infinium DNA Methylation BeadArrays. Nucleic Acids Res. 2013; 41:e90. https://doi.org/10.1093/nar/gkt090 [PubMed]

66. Volpi, E. et al (2010). Muscle Tissue Changes With Aging.

67. Wong HK, Cheung TT, Cheung BM. Adrenomedullin and cardiovascular diseases. JRSM Cardiovasc Dis. 2012; 1:1–7. https://doi.org/10.1258/cvd.2012.012003 [PubMed]

67. Yashin, A. et al (2013). Antioxidant and Antiradical Activity of Coffee. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665516/

68. Zheng SC, Widschwendter M, Teschendorff AE. Epigenetic drift, epigenetic clocks and cancer risk. Epigenomics. 2016; 8:705–19. https://doi.org/10.2217/epi-2015-0017 [PubMed]

69. Zhang Y, Wilson R, Heiss J, Breitling LP, Saum KU, Schöttker B, Holleczek B, Waldenberger M, Peters A, Brenner H. DNA methylation signatures in peripheral blood strongly predict all-cause mortality. Nat Commun. 2017; 8:14617. https://doi.org/10.1038/ncomms14617 [PubMed]

70. Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Series B Stat Methodol. 2005; 67:301–20. https://doi.org/10.1111/j.1467-9868.2005.00503.x

71. Ziyatdinov A, Brunel H, Martinez-Perez A, Buil A, Perera A, Soria JM. solarius: an R interface to SOLAR for variance component analysis in pedigrees. Bioinformatics. 2016; 32:1901–02. https://doi.org/10.1093/bioinformatics/btw080 [PubMed]

72. Zajac, I. et al (2021). Modified Fasting Compared to True Fasting Improves Blood Glucose Levels and Subjective Experiences of Hunger, Food Cravings and Mental Fatigue, But Not Cognitive Function: Results of an Acute Randomised Cross-Over Trial. https://www.mdpi.com/2072-6643/13/1/65