REFERENCES
2. Johnson TE, Wood WB. Genetic analysis of life-span in Caenorhabditis elegans. Proc Natl Acad Sci U S A 1982;79:6603-7.
3. Johnson TE, Conley WL, Keller ML. Long-lived lines of Caenorhabditis elegans can be used to establish predictive biomarkers of aging. Exp Gerontol 1988;23:281-95.
4. Friedman DB, Johnson TE. Three mutants that extend both mean and maximum life span of the nematode, Caenorhabditis elegans, define the age-1 gene. J Gerontol 1988;43:B102-9.
6. Partridge L, Pletcher SD, Mair W. Dietary restriction, mortality trajectories, risk and damage. Mech Ageing Dev 2005;126:35-41.
7. Masoro EJ. Caloric restriction and aging: controversial issues. J Gerontol A Biol Sci Med Sci 2006;61:14-9.
8. Archer CR, Royle N, South S, Selman C, Hunt J. Nutritional geometry provides food for thought. J Gerontol A Biol Sci Med Sci 2009;64:956-9.
10. Couteur DG, Solon-Biet S, Cogger VC, et al. The impact of low-protein high-carbohydrate diets on aging and lifespan. Cell Mol Life Sci 2016;73:1237-52.
11. Seidelmann SB, Claggett B, Cheng S, et al. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health 2018;3:e419-e28.
12. Johnson AA, Stolzing A. The role of lipid metabolism in aging, lifespan regulation, and age-related disease. Aging Cell 2019;18:e13048.
13. Yoshida S, Yamahara K, Kume S, et al. Role of dietary amino acid balance in diet restriction-mediated lifespan extension, renoprotection, and muscle weakness in aged mice. Aging Cell 2018;17:e12796.
14. Kitada M, Ogura Y, Monno I, Koya D. The impact of dietary protein intake on longevity and metabolic health. EBioMedicine 2019;43:632-40.
15. Lee D, Hwang W, Artan M, Jeong DE, Lee SJ. Effects of nutritional components on aging. Aging Cell 2015;14:8-16.
16. Arganda S, Bouchebti S, Bazazi S, et al. Parsing the life-shortening effects of dietary protein: effects of individual amino acids. Proc Biol Sci 2017:284.
17. Ames BN. Prolonging healthy aging: longevity vitamins and proteins. Proc Natl Acad Sci U S A 2018;115:10836-44.
18. Altamura S, Muckenthaler MU. Iron toxicity in diseases of aging: Alzheimer's disease, Parkinson's disease and atherosclerosis. J Alzheimers Dis 2009;16:879-95.
19. Nie Y, Luo F. Dietary fiber: an opportunity for a global control of hyperlipidemia. Oxid Med Cell Longev 2021;2021:5542342.
20. Klass MR. A method for the isolation of longevity mutants in the nematode Caenorhabditis elegans and initial results. Mech Ageing Dev 1983;22:279-86.
21. Liao CY, Rikke BA, Johnson TE, Diaz V, Nelson JF. Genetic variation in the murine lifespan response to dietary restriction: from life extension to life shortening. Aging Cell 2010;9:92-5.
22. Jewell JL, Russell RC, Guan KL. Amino acid signalling upstream of mTOR. Nat Rev Mol Cell Biol 2013;14:133-9.
23. Goberdhan DC, Wilson C, Harris AL. Amino acid sensing by mTORC1: intracellular transporters mark the spot. Cell Metab 2016;23:580-9.
24. Averous J, Lambert-Langlais S, Mesclon F, et al. GCN2 contributes to mTORC1 inhibition by leucine deprivation through an ATF4 independent mechanism. Sci Rep 2016;6:27698.
25. Falcón P, Escandón M, Brito Á, Matus S. Nutrient sensing and redox balance: GCN2 as a new integrator in aging. Oxid Med Cell Longev 2019;2019:5730532.
26. Papadopoli D, Boulay K, Kazak L, et al. mTOR as a central regulator of lifespan and aging. F1000Res 2019:8.
27. Uppu S, Krishna A, Gopalan RP. A review on methods for detecting SNP interactions in high-dimensional genomic data. IEEE/ACM Trans Comput Biol Bioinform 2018;15:599-612.
28. Liu L, Wong KC. Epistasis analysis: classification through machine learning methods. Methods Mol Biol 2021;2212:337-45.
29. Manavalan R, Priya S. Genetic interactions effects for cancer disease identification using computational models: a review. Med Biol Eng Comput 2021;59:733-58.
30. Slim L, Chatelain C, Azencott CA, Vert JP. Novel methods for epistasis detection in genome-wide association studies. PLoS One 2020;15:e0242927.
31. Pan Q, Hu T, Moore JH. Epistasis, complexity, and multifactor dimensionality reduction. Methods Mol Biol 2013;1019:465-77.
32. Abegaz F, Van Lishout F, Mahachie John JM, et al. Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure. BioData Min 2021;14:16.
33. Yang CH, Lin YD, Chuang LY. Class balanced multifactor dimensionality reduction to detect gene-gene interactions. IEEE/ACM Trans Comput Biol Bioinform 2020;17:71-81.
34. Chen G, Yuan A, Cai T, et al. Measuring gene-gene interaction using Kullback-Leibler divergence. Ann Hum Genet 2019;83:405-17.
35. Malten J, König IR. Modified entropy-based procedure detects gene-gene-interactions in unconventional genetic models. BMC Med Genomics 2020;13:65.
36. Borzou A, Sadygov RG. A novel estimator of the interaction matrix in Graphical Gaussian Model of omics data using the entropy of non-equilibrium systems. Bioinformatics 2021;37:837-44.
37. Chicco D, Faultless T. Brief survey on machine learning in epistasis. Methods Mol Biol 2021;2212:169-79.
38. Petinrin OO, Wong KC. Protocol for epistasis detection with machine learning using genepi package. Methods Mol Biol 2021;2212:291-305.
39. Lin HY, Chen DT, Huang PY, et al. SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns. Bioinformatics 2017;33:822-33.
40. Sun R, Xia X, Chong KC, Zee BC, Wu WKK, Wang MH. wtest: an integrated R package for genetic epistasis testing. BMC Med Genomics 2019;12:180.
41. Cao X, Liu J, Guo M, Wang J. HiSSI: high-order SNP-SNP interactions detection based on efficient significant pattern and differential evolution. BMC Med Genomics 2019;12:139.
42. Carmelo VAO, Kogelman LJA, Madsen MB, Kadarmideen HN. WISH-R- a fast and efficient tool for construction of epistatic networks for complex traits and diseases. BMC Bioinformatics 2018;19:277.
43. Chang YC, Wu JT, Hong MY, et al. GenEpi: gene-based epistasis discovery using machine learning. BMC Bioinformatics 2020;21:68.
44. Huang Y, Wuchty S, Przytycka TM. eQTL Epistasis - challenges and computational approaches. Front Genet 2013;4:51.
45. Kwon M, Leem S, Yoon J, Park T. GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data. BMC Syst Biol 2018;12:19.
46. Herold C, Steffens M, Brockschmidt FF, Baur MP, Becker T. INTERSNP: genome-wide interaction analysis guided by a priori information. Bioinformatics 2009;25:3275-81.
47. Yashin AI, Wu D, Arbeev K, et al. Interplay between stress-related genes may influence Alzheimer's disease development: the results of genetic interaction analyses of human data. Mech Ageing Dev 2021;196:111477.
48. Niel C, Sinoquet C, Dina C, Rocheleau G. A survey about methods dedicated to epistasis detection. Front Genet 2015;6:285.
49. Costa-Mattioli M, Walter P. The integrated stress response: from mechanism to disease. Science 2020:368.
50. Bruhat A, Jousse C, Wang XZ, Ron D, Ferrara M, Fafournoux P. Amino acid limitation induces expression of CHOP, a CCAAT/enhancer binding protein-related gene, at both transcriptional and post-transcriptional levels. J Biol Chem 1997;272:17588-93.
51. Masuda M, Miyazaki-Anzai S, Levi M, Ting TC, Miyazaki M. PERK-eIF2α-ATF4-CHOP signaling contributes to TNFα-induced vascular calcification. J Am Heart Assoc 2013;2:e000238.
52. Pakos-Zebrucka K, Koryga I, Mnich K, Ljujic M, Samali A, Gorman AM. The integrated stress response. EMBO Rep 2016;17:1374-95.
53. Wang L, Tang W, Jiang T, et al. Endoplasmic reticulum stress is involved in the neuroprotective effect of propofol. Neurochem Res 2014;39:1741-52.
54. Oliveira MM, Lourenco MV. Integrated stress response: connecting ApoE4 to memory impairment in Alzheimer's disease. J Neurosci 2016;36:1053-5.
55. Bond S, Lopez-Lloreda C, Gannon PJ, Akay-Espinoza C, Jordan-Sciutto KL. The integrated stress response and phosphorylated eukaryotic initiation factor 2α in neurodegeneration. J Neuropathol Exp Neurol 2020;79:123-43.
56. Girardin SE, Cuziol C, Philpott DJ, Arnoult D. The eIF2α kinase HRI in innate immunity, proteostasis, and mitochondrial stress. Febs j :202010.1111/febs.15553.
57. Postnikoff SDL, Johnson JE, Tyler JK. The integrated stress response in budding yeast lifespan extension. Microb Cell 2017;4:368-75.
58. Derisbourg MJ, Wester LE, Baddi R, Denzel MS. Mutagenesis screen uncovers lifespan extension through integrated stress response inhibition without reduced mRNA translation. Nat Commun 2021;12:1678.
59. Wang Y, Ning Y, Alam GN, et al. Amino acid deprivation promotes tumor angiogenesis through the GCN2/ATF4 pathway. Neoplasia 2013;15:989-97.
60. Rozpedek W, Pytel D, Mucha B, Leszczynska H, Diehl JA, Majsterek I. The role of the PERK/eIF2α/ATF4/CHOP signaling pathway in tumor progression during endoplasmic reticulum stress. Curr Mol Med 2016;16:533-44.
61. Ye J, Kumanova M, Hart LS, et al. The GCN2-ATF4 pathway is critical for tumour cell survival and proliferation in response to nutrient deprivation. Embo j 2010;29:2082-96.
62. Emanuelli G, Nassehzadeh-Tabriz N, Morrell NW, Marciniak SJ. The integrated stress response in pulmonary disease. Eur Respir Rev 2020:29.
63. Fuster JJ. Integrated stress response inhibition in atherosclerosis: preventing the stressed-out plaque. J Am Coll Cardiol 2019;73:1170-2.
64. Onat UI, Yildirim AD, Tufanli Ö, et al. Intercepting the lipid-induced integrated stress response reduces atherosclerosis. J Am Coll Cardiol 2019;73:1149-69.
65. Xu X, Krumm C, So JS, et al. Preemptive activation of the integrated stress response protects mice from diet-induced obesity and insulin resistance by fibroblast growth factor 21 induction. Hepatology 2018;68:2167-81.
66. Henkel AS. Harnessing the integrated stress response to counteract metabolic disease. Hepatology 2018;68:2056-8.
67. Donnelly N, Gorman AM, Gupta S, Samali A. The eIF2α kinases: their structures and functions. Cell Mol Life Sci 2013;70:3493-511.
68. Gáll T, Balla G, Balla J. Heme, heme oxygenase, and endoplasmic reticulum stress-a new insight into the pathophysiology of vascular diseases. Int J Mol Sci 2019:20.
69. Rodrigues L, Graça RSF, Carneiro LAM. Integrated stress responses to bacterial pathogenesis patterns. Front Immunol 2018;9:1306.
70. Saelens X, Kalai M, Vandenabeele P. Translation inhibition in apoptosis: caspase-dependent PKR activation and eIF2-alpha phosphorylation. J Biol Chem 2001;276:41620-8.
71. Taylor SS, Haste NM, Ghosh G. PKR and eIF2alpha: integration of kinase dimerization, activation, and substrate docking. Cell 2005;122:823-5.
72. Chesnokova E, Bal N, Kolosov P. Kinases of eIF2a switch translation of mRNA subset during neuronal plasticity. Int J Mol Sci 2017:18.
73. Gal-Ben-Ari S, Barrera I, Ehrlich M, Rosenblum K. PKR: a kinase to remember. Front Mol Neurosci 2018;11:480.
74. Elvira R, Cha SJ, Noh GM, Kim K, Han J. PERK-mediated eIF2α phosphorylation contributes to the protection of dopaminergic neurons from chronic heat stress in drosophila. Int J Mol Sci 2020:21.
75. Klaus S, Ost M. Mitochondrial uncoupling and longevity - a role for mitokines? Exp Gerontol 2020;130:110796.
76. Wang R, McGrath BC, Kopp RF, et al. Insulin secretion and Ca2+ dynamics in β-cells are regulated by PERK (EIF2AK3) in concert with calcineurin. J Biol Chem 2013;288:33824-36.
77. Wang R, Munoz EE, Zhu S, McGrath BC, Cavener DR. Perk gene dosage regulates glucose homeostasis by modulating pancreatic β-cell functions. PLoS One 2014;9:e99684.
78. Kim MJ, Min SH, Shin SY, et al. Attenuation of PERK enhances glucose-stimulated insulin secretion in islets. J Endocrinol 2018;236:125-36.
79. Balsa E, Soustek MS, Thomas A, et al. ER and nutrient stress promote assembly of respiratory chain supercomplexes through the PERK-eIF2α axis. Mol Cell 2019;74:877-90.e6.
80. Endres K, Reinhardt S. ER-stress in Alzheimer's disease: turning the scale? Am J Neurodegener Dis 2013;2:247-65.
81. Wong TH, van der Lee SJ, van Rooij JGJ, et al. EIF2AK3 variants in Dutch patients with Alzheimer's disease. Neurobiol Aging 2019;73:229.e11-e18.
82. Hughes D, Mallucci GR. The unfolded protein response in neurodegenerative disorders - therapeutic modulation of the PERK pathway. FEBS J 2019;286:342-55.
83. Rozpędek-Kamińska W, Siwecka N, Wawrzynkiewicz A, et al. The PERK-dependent molecular mechanisms as a novel therapeutic target for neurodegenerative diseases. Int J Mol Sci 2020:21.
84. Hamanaka RB, Bennett BS, Cullinan SB, Diehl JA. PERK and GCN2 contribute to eIF2alpha phosphorylation and cell cycle arrest after activation of the unfolded protein response pathway. Mol Biol Cell 2005;16:5493-501.
86. Chikashige Y, Kato H, Thornton M, et al. Gcn2 eIF2α kinase mediates combinatorial translational regulation through nucleotide motifs and uORFs in target mRNAs. Nucleic Acids Res 2020;48:8977-92.
87. Yuan F, Jiang H, Yin H, et al. Activation of GCN2/ATF4 signals in amygdalar PKC-δ neurons promotes WAT browning under leucine deprivation. Nat Commun 2020;11:2847.
88. Augusto L, Amin PH, Wek RC, Sullivan WJ, Jr. Regulation of arginine transport by GCN2 eIF2 kinase is important for replication of the intracellular parasite Toxoplasma gondii. PLoS Pathog 2019;15:e1007746.
89. Hayner JN, Shan J, Kilberg MS. Regulation of the ATF3 gene by a single promoter in response to amino acid availability and endoplasmic reticulum stress in human primary hepatocytes and hepatoma cells. Biochim Biophys Acta Gene Regul Mech 2018;1861:72-9.
90. Harding HP, Novoa I, Zhang Y, et al. Regulated translation initiation controls stress-induced gene expression in mammalian cells. Mol Cell 2000;6:1099-108.
91. Kilberg MS, Shan J, Su N. ATF4-dependent transcription mediates signaling of amino acid limitation. Trends Endocrinol Metab 2009;20:436-43.
92. Rasmussen BB, Adams CM. ATF4 is a fundamental regulator of nutrient sensing and protein turnover. J Nutr 2020;150:979-80.
93. Tian F, Zhao J, Bu S, et al. KLF6 induces apoptosis in human lens epithelial cells through the ATF4-ATF3-CHOP axis. Drug Des Devel Ther 2020;14:1041-55.
94. Choy MS, Yusoff P, Lee IC, et al. Structural and functional analysis of the GADD34:PP1 eIF2α phosphatase. Cell Rep 2015;11:1885-91.
95. Joo JH, Ueda E, Bortner CD, Yang XP, Liao G, Jetten AM. Farnesol activates the intrinsic pathway of apoptosis and the ATF4-ATF3-CHOP cascade of ER stress in human T lymphoblastic leukemia Molt4 cells. Biochem Pharmacol 2015;97:256-68.
97. Pike LR, Phadwal K, Simon AK, Harris AL. ATF4 orchestrates a program of BH3-only protein expression in severe hypoxia. Mol Biol Rep 2012;39:10811-22.
98. Dey S, Baird TD, Zhou D, Palam LR, Spandau DF, Wek RC. Both transcriptional regulation and translational control of ATF4 are central to the integrated stress response. J Biol Chem 2010;285:33165-74.
99. Rzymski T, Milani M, Pike L, et al. Regulation of autophagy by ATF4 in response to severe hypoxia. Oncogene 2010;29:4424-35.
100. Frank CL, Ge X, Xie Z, Zhou Y, Tsai LH. Control of activating transcription factor 4 (ATF4) persistence by multisite phosphorylation impacts cell cycle progression and neurogenesis. J Biol Chem 2010;285:33324-37.
101. Mukherjee D, Bercz LS, Torok MA, Mace TA. Regulation of cellular immunity by activating transcription factor 4. Immunol Lett 2020;228:24-34.
102. Narita T, Ri M, Masaki A, et al. Lower expression of activating transcription factors 3 and 4 correlates with shorter progression-free survival in multiple myeloma patients receiving bortezomib plus dexamethasone therapy. Blood Cancer J 2015;5:e373.
103. Jousse C, Deval C, Maurin AC, et al. TRB3 inhibits the transcriptional activation of stress-regulated genes by a negative feedback on the ATF4 pathway. J Biol Chem 2007;282:15851-61.
104. Anderson CA, Pettersson FH, Clarke GM, Cardon LR, Morris AP, Zondervan KT. Data quality control in genetic case-control association studies. Nature Protocols 2010;5:1564-73.
105. Marees AT, de Kluiver H, Stringer S, et al. A tutorial on conducting genome-wide association studies: quality control and statistical analysis. Int J Methods Psychiatr Res 2018;27:e1608.
106. Akushevich I, Kravchenko J, Ukraintseva S, Arbeev K, Yashin AI. Age patterns of incidence of geriatric disease in the U.S. elderly population: medicare-based analysis. J Am Geriatr Soc 2012;60:323-7.
107. Ukraintseva S, Yashin A, Arbeev K, et al. Puzzling role of genetic risk factors in human longevity: "risk alleles" as pro-longevity variants. Biogerontology 2016;17:109-27.
108. Chasioti D, Yan J, Nho K, Saykin AJ. Progress in polygenic composite scores in Alzheimer's and other complex diseases. Trends Genet 2019;35:371-82.
109. Cruchaga C, Del-Aguila JL, Saef B, et al. Polygenic risk score of sporadic late-onset Alzheimer's disease reveals a shared architecture with the familial and early-onset forms. Alzheimers Dement 2018;14:205-14.
110. Leonenko G, Sims R, Shoai M, et al. Polygenic risk and hazard scores for Alzheimer's disease prediction. Ann Clin Transl Neurol 2019;6:456-65.
111. Tesi N, van der Lee SJ, Hulsman M, et al. Polygenic risk score of longevity predicts longer survival across an age continuum. J Gerontol A Biol Sci Med Sci 2021;76:750-9.
112. Zeng Y, Nie C, Min J, et al. Sex differences in genetic associations with longevity. JAMA Netw Open 2018;1:e181670.
113. Yashin AI, Wu D, Arbeev KG, Ukraintseva SV. Joint influence of small-effect genetic variants on human longevity. Aging (Albany NY) 2010;2:612-20.
114. Yashin AI, Wu D, Arbeev KG, Stallard E, Land KC, Ukraintseva SV. How genes influence life span: the biodemography of human survival. Rejuvenation Res 2012;15:374-80.
115. Yashin AI, Wu D, Arbeev KG, Ukraintseva SV. Polygenic effects of common single-nucleotide polymorphisms on life span: when association meets causality. Rejuvenation Res 2012;15:381-94.
116. Ala-Korpela M, Holmes MV. Polygenic risk scores and the prediction of common diseases. Int J Epidemiol 2020;49:1-3.
117. Yabluchanskiy A, Ungvari Z, Csiszar A, Tarantini S. Advances and challenges in geroscience research: an update. Physiol Int 2018;105:298-308.
118. McCay CM, Crowell MF, Maynard LA. The effect of retarded growth upon the length of life span and upon the ultimate body size. 1935. Nutrition 1989;5:155-71; discussion 72.
119. Fontana L, Partridge L. Promoting health and longevity through diet: from model organisms to humans. Cell 2015;161:106-18.
120. Balasubramanian P, Mattison JA, Anderson RM. Nutrition, metabolism, and targeting aging in nonhuman primates. Ageing Res Rev 2017;39:29-35.
121. Cummings NE, Lamming DW. Regulation of metabolic health and aging by nutrient-sensitive signaling pathways. Mol Cell Endocrinol 2017;455:13-22.
122. Edick AM, Audette J, Burgos SA. CRISPR-Cas9-mediated knockout of GCN2 reveals a critical role in sensing amino acid deprivation in bovine mammary epithelial cells. J Dairy Sci 2021;104:1123-35.
123. Xia X, Lei L, Qin W, Wang L, Zhang G, Hu J. GCN2 controls the cellular checkpoint: potential target for regulating inflammation. Cell Death Discov 2018;4:20.
124. Hu G, Yu Y, Tang YJ, Wu C, Long F, Karner CM. The amino acid sensor Eif2ak4/GCN2 is required for proliferation of osteoblast progenitors in mice. J Bone Miner Res 2020;35:2004-14.
125. Revelo XS, Winer S, Winer DA. Starving intestinal inflammation with the amino acid sensor GCN2. Cell Metab 2016;23:763-5.
126. Anand AA, Walter P. Structural insights into ISRIB, a memory-enhancing inhibitor of the integrated stress response. FEBS J 2020;287:239-45.
127. Chu HS, Peterson C, Jun A, Foster J. Targeting the integrated stress response in ophthalmology. Curr Eye Res 2021;46:1075-88.
128. Zyryanova AF, Kashiwagi K, Rato C, et al. ISRIB blunts the integrated stress response by allosterically antagonising the inhibitory effect of phosphorylated eIF2 on eIF2B. Mol Cell 2021;81:88-103.e6.
129. Fontana L, Partridge L, Longo VD. Extending healthy life span - from yeast to humans. Science 2010;328:321-6.
130. Antikainen H, Driscoll M, Haspel G, Dobrowolski R. TOR-mediated regulation of metabolism in aging. Aging Cell 2017;16:1219-33.
132. Jung J, Genau HM, Behrends C. Amino acid-dependent mTORC1 regulation by the lysosomal membrane protein SLC38A9. Mol Cell Biol 2015;35:2479-94.
133. Kucheryavenko O, Nelson G, von Zglinicki T, Korolchuk VI, Carroll B. The mTORC1-autophagy pathway is a target for senescent cell elimination. Biogerontology 2019;20:331-5.
134. Johnson SC, Rabinovitch PS, Kaeberlein M. mTOR is a key modulator of ageing and age-related disease. Nature 2013;493:338-45.
135. Longchamp A, Mirabella T, Arduini A, et al. Amino acid restriction triggers angiogenesis via GCN2/ATF4 regulation of VEGF and H(2)S production. Cell 2018;173:117-29.e14.
136. Pathak SS, Liu D, Li T, et al. The eIF2α Kinase GCN2 modulates period and rhythmicity of the circadian clock by translational control of Atf4. Neuron 2019;104:724-35.e6.
137. Pereira CM, Filev R, Dubiela FP, et al. The GCN2 inhibitor IMPACT contributes to diet-induced obesity and body temperature control. PLoS One 2019;14:e0217287.
138. Harding HP, Zhang Y, Zeng H, et al. An integrated stress response regulates amino acid metabolism and resistance to oxidative stress. Mol Cell 2003;11:619-33.
139. Rashidi A, Miska J, Lee-Chang C, et al. GCN2 is essential for CD8(+) T cell survival and function in murine models of malignant glioma. Cancer Immunol Immunother 2020;69:81-94.
140. Schmidt S, Gay D, Uthe FW, et al. A MYC-GCN2-eIF2α negative feedback loop limits protein synthesis to prevent MYC-dependent apoptosis in colorectal cancer. Nat Cell Biol 2019;21:1413-24.
141. Kanno A, Asahara SI, Furubayashi A, et al. GCN2 regulates pancreatic β cell mass by sensing intracellular amino acid levels. JCI Insight 2020;5:e128820.
142. B'Chir W, Chaveroux C, Carraro V, et al. Dual role for CHOP in the crosstalk between autophagy and apoptosis to determine cell fate in response to amino acid deprivation. Cell Signal 2014;26:1385-91.
143. B'Chir W, Maurin AC, Carraro V, et al. The eIF2α/ATF4 pathway is essential for stress-induced autophagy gene expression. Nucleic Acids Res 2013;41:7683-99.
144. Carroll B, Korolchuk VI, Sarkar S. Amino acids and autophagy: cross-talk and co-operation to control cellular homeostasis. Amino Acids 2015;47:2065-88.
145. Humeau J, Bezu L, Kepp O, Kroemer G. EIF2α phosphorylation: a hallmark of both autophagy and immunogenic cell death. Mol Cell Oncol 2020;7:1776570.
146. Kroemer G, Mariño G, Levine B. Autophagy and the integrated stress response. Mol Cell 2010;40:280-93.
147. Amaravadi R, Kimmelman AC, White E. Recent insights into the function of autophagy in cancer. Genes Dev 2016;30:1913-30.
148. Acevo-Rodríguez PS, Maldonado G, Castro-Obregón S, Hernández G. Autophagy regulation by the translation machinery and its implications in cancer. Front Oncol 2020;10:322.
149. Castrejón-Jiménez NS, Leyva-Paredes K, Hernández-González JC, Luna-Herrera J, García-Pérez BE. The role of autophagy in bacterial infections. Biosci Trends 2015;9:149-59.
150. Nakahira K, Pabon Porras MA, Choi AM. Autophagy in pulmonary diseases. Am J Respir Crit Care Med 2016;194:1196-207.
151. Andhavarapu S, Mubariz F, Arvas M, Bever C, Jr. , Makar TK. Interplay between ER stress and autophagy: a possible mechanism in multiple sclerosis pathology. Exp Mol Pathol 2019;108:183-90.
152. Bretin A, Carrière J, Dalmasso G, et al. Activation of the EIF2AK4-EIF2A/eIF2α-ATF4 pathway triggers autophagy response to Crohn disease-associated adherent-invasive Escherichia coli infection. Autophagy 2016;12:770-83.
153. Ryter SW, Lee SJ, Smith A, Choi AM. Autophagy in vascular disease. Proc Am Thorac Soc 2010;7:40-7.
155. Tan P, Ye Y, Mao J, He L. Autophagy and immune-related diseases. Adv Exp Med Biol 2019;1209:167-79.
156. Wu J, Ye J, Kong W, Zhang S, Zheng Y. Programmed cell death pathways in hearing loss: a review of apoptosis, autophagy and programmed necrosis. Cell Prolif 2020;53:e12915.
157. Escobar KA, Cole NH, Mermier CM, VanDusseldorp TA. Autophagy and aging: maintaining the proteome through exercise and caloric restriction. Aging Cell 2019;18:e12876.
158. Eskelinen EL, Saftig P. Autophagy: a lysosomal degradation pathway with a central role in health and disease. Biochim Biophys Acta 2009;1793:664-73.
159. Rajawat YS, Hilioti Z, Bossis I. Aging: central role for autophagy and the lysosomal degradative system. Ageing Res Rev 2009;8:199-213.
160. Hansen M, Rubinsztein DC, Walker DW. Autophagy as a promoter of longevity: insights from model organisms. Nat Rev Mol Cell Biol 2018;19:579-93.
161. Rubner M. Machinery of metabolism. JAMA 1916;66:1111.
162. Fontana L. The scientific basis of caloric restriction leading to longer life. Curr Opin Gastroenterol 2009;25:144-50.
163. Ferrucci L, Schrack JA, Knuth ND, Simonsick EM. Aging and the energetic cost of life. J Am Geriatr Soc 2012;60:1768-9.
164. Al-Regaiey KA. The effects of calorie restriction on aging: a brief review. Eur Rev Med Pharmacol Sci 2016;20:2468-73.
165. Bartke A, Evans TR, Musters CJM. Anti-aging interventions affect lifespan variability in sex, strain, diet and drug dependent fashion. Aging (Albany NY) 2019;11:4066-74.
166. Cantó C, Auwerx J. Calorie restriction: is AMPK a key sensor and effector? Physiology (Bethesda) 2011;26:214-24.
167. Colman RJ, Anderson RM. Nonhuman primate calorie restriction. Antioxid Redox Signal 2011;14:229-39.
168. Flanagan EW, Most J, Mey JT, Redman LM. Calorie restriction and aging in humans. Annu Rev Nutr 2020;40:105-33.
169. Green CL, Lamming DW. Regulation of metabolic health by essential dietary amino acids. Mech Ageing Dev 2019;177:186-200.
170. Ruggiero C, Metter EJ, Melenovsky V, et al. High basal metabolic rate is a risk factor for mortality: the Baltimore Longitudinal Study of Aging. J Gerontol A Biol Sci Med Sci 2008;63:698-706.
171. Jumpertz R, Hanson RL, Sievers ML, Bennett PH, Nelson RG, Krakoff J. Higher energy expenditure in humans predicts natural mortality. J Clin Endocrinol Metab 2011;96:E972-6.
172. Tan Q, Yashin AI, Bladbjerg EM, et al. A case-only approach for assessing gene by sex interaction in human longevity. J Gerontol A Biol Sci Med Sci 2002;57:B129-33.
173. Zeng Y, Cheng L, Chen H, et al. Effects of FOXO genotypes on longevity: a biodemographic analysis. J Gerontol A Biol Sci Med Sci 2010;65:1285-99.
174. Tan Q, Soerensen M, Kruse TA, Christensen K, Christiansen L. A novel permutation test for case-only analysis identifies epistatic effects on human longevity in the FOXO gene family. Aging Cell 2013;12:690-4.
175. Dato S, Soerensen M, De Rango F, et al. The genetic component of human longevity: new insights from the analysis of pathway-based SNP-SNP interactions. Aging Cell 2018;17:e12755.
176. Curk T, Rot G, Zupan B. SNPsyn: detection and exploration of SNP-SNP interactions. Nucleic Acids Res 2011;39:W444-9.
177. Ukraintseva S, Duan M, Arbeev K, et al. Interactions between genes from aging pathways may influence human lifespan and improve animal to human translation. Front Cell Dev Biol 2021;9:692020.
178. Ukraintseva S, Arbeev K, Duan M, et al. Decline in biological resilience as key manifestation of aging: potential mechanisms and role in health and longevity. Mech Ageing Dev 2021;194:111418.
179. Ukraintseva S, Yashin AI, Arbeev KG. Resilience versus robustness in aging. J Gerontol A Biol Sci Med Sci 2016;71:1533-4.
180. Galvin A, Ukraintseva S, Arbeev K, Feitosa M, Christensen K. Physical robustness and resilience among long-lived female siblings: a comparison with sporadic long-livers. Aging (Albany NY) 2020;12:15157-68.
181. Arbeev KG, Akushevich I, Kulminski AM, Ukraintseva SV, Yashin AI. Biodemographic analyses of longitudinal data on aging, health, and longevity: recent advances and future perspectives. Adv Geriatr 2014;2014:957073.
182. Arbeev KG, Ukraintseva SV, Bagley O, et al. "Physiological Dysregulation" as a promising measure of robustness and resilience in studies of aging and a new indicator of preclinical disease. J Gerontol A Biol Sci Med Sci 2019;74:462-8.
183. Yashin AI, Arbeev KG, Akushevich I, et al. The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. Phys Life Rev 2012;9:177-88.
184. Yashin AI, Arbeev KG, Arbeeva LS, et al. How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity. Biogerontology 2016;17:89-107.
185. Agler R, De Boeck P. On the interpretation and use of mediation: multiple perspectives on mediation analysis. Front Psychol 2017;8:1984.
186. Grover S, Del Greco MF, König IR. Evaluating the current state of Mendelian randomization studies: a protocol for a systematic review on methodological and clinical aspects using neurodegenerative disorders as outcome. Syst Rev 2018;7:145.
187. Allman PH, Aban IB, Tiwari HK, Cutter GR. An introduction to Mendelian randomization with applications in neurology. Multiple sclerosis and related disorders 2018;24:72-8.
188. Yashin AI, De Benedictis G, Vaupel JW, et al. Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity. Am J Hum Genet 1999;65:1178-93.
189. Yashin AI, De Benedictis G, Vaupel JW, et al. Genes and longevity: lessons from studies of centenarians. J Gerontol A Biol Sci Med Sci 2000;55:B319-28.
190. Bergman A, Atzmon G, Ye K, MacCarthy T, Barzilai N. Buffering mechanisms in aging: a systems approach toward uncovering the genetic component of aging. PLoS Comput Biol 2007;3:e170.
191. Beekman M, Nederstigt C, Suchiman HE, et al. Genome-wide association study (GWAS)-identified disease risk alleles do not compromise human longevity. Proc Natl Acad Sci U S A 2010;107:18046-9.
192. Ebbert MT, Ridge PG, Kauwe JS. Bridging the gap between statistical and biological epistasis in Alzheimer's disease. Biomed Res Int 2015;2015:870123.
