Cited by 104Genetics, Aging, and Longevity in Model OrganismsAging and Gerontology ResearchTelomeres, Telomerase, and Senescence

The DOI matches its Crossref record; 277 of the 277 references it cites were found in a registry or an index.

Accelerating research on biological aging and mental health: Current challenges and future directions.

Open access

Han, Laura K.M., Verhoeven, Josine E., Tyrka, Audrey R., Penninx, Brenda W.J.H., Wolkowitz, Owen M., Månsson, Kristoffer N.T., Lindqvist, Daniel, Boks, Marco P., Révész, Dóra, Mellon, Synthia H., Picard, Martin·2019·Psychoneuroendocrinology

DOI 10.1016/j.psyneuen.2019.04.004PMC PMC6589133

Open this paper in CoChat — free account

Abstract

Aging is associated with complex biological changes that can be accelerated, slowed, or even temporarily reversed by biological and non-biological factors. This article focuses on the link between biological aging, psychological stressors, and mental illness. Rather than comprehensively reviewing this rapidly expanding field, we highlight challenges in this area of research and propose potential strategies to accelerate progress in this field. This effort requires the interaction of scientists across disciplines - including biology, psychiatry, psychology, and epidemiology; and across levels of analysis that emphasize different outcome measures - functional capacity, physiological, cellular, and molecular. Dialogues across disciplines and levels of analysis naturally lead to new opportunities for discovery but also to stimulating challenges. Some important challenges consist of 1) establishing the best objective and predictive biological age indicators or combinations of indicators, 2) identifying the basis for inter-individual differences in the rate of biological aging, and 3) examining to what extent interventions can delay, halt or temporarily reverse aging trajectories. Discovering how psychological states influence biological aging, and vice versa, has the potential to create novel and exciting opportunities for healthcare and possibly yield insights into the fundamental mechanisms that drive human aging.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1016/j.psyneuen.2019.04.004

Cites

277 of 277 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Untitled work
(2008) · Journal of Machine Learning Research · Cited by 33,051
The Hallmarks of Aging
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075 · cited 2×
“While the validity of different methylation-based predictors is questioned, applications of the original pan-tissue Horvath clock (Horvath, 2013) have been successful across tissue types and proven accurate even in embryonic brain samples (Spiers et al., 2015).”
Inflamm‐aging: An Evolutionary Perspective on Immunosenescence
FRANCESCHI, C., BONAFÈ, M., VALENSIN, S., OLIVIERI, F., DE LUCA, M., OTTAVIANI, E., & DE BENEDICTIS, G. (2000) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2000.tb06651.x · Cited by 5,358
Genome-wide methylation profiles reveal quantitative views of human aging rates
Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.-B., Gao, Y., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.016 · Cited by 4,270
An epigenetic biomarker of aging for lifespan and healthspan
Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimes, T. L., Bandinelli, S., Hou, L., Baccarelli, A. A., Stewart, J. D., Li, Y., et al. (2018) · Aging · doi:10.18632/aging.101414 · Cited by 3,675 · cited 2×
“whole blood (Hannum et al., 2013; Levine et al., 2018; Weidner et al., 2014), neonatal cord blood and blood spots (Knight et al.”
Inflammaging: a new immune–metabolic viewpoint for age-related diseases
Franceschi, C., Garagnani, P., Parini, P., Giuliani, C., & Santoro, A. (2018) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0059-4 · Cited by 3,586
Telomere measurement by quantitative PCR
Cawthon, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.10.e47 · Cited by 3,538
DNA methylation-based biomarkers and the epigenetic clock theory of ageing
Horvath, S., & Raj, K. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0004-3 · Cited by 3,095 · cited 1×
“Here, rather than providing an exhaustive overview that can be found in recent reviews (Engelfriet et al., 2013; Horvath and Raj, 2018; Jylhava et al., 2017; López-Otín et al., 2013; Wagner et al., 2016; Xia et al., 2017), we provide a selective overview of aging indicators commonly studied in relation to mental healt…”
Toward the future of psychiatric diagnosis: the seven pillars of RDoC
Cuthbert, B. N., & Insel, T. R. (2013) · BMC Medicine · doi:10.1186/1741-7015-11-126 · Cited by 3,053
Accelerated telomere shortening in response to life stress
Epel, E. S., Blackburn, E. H., Lin, J., Dhabhar, F. S., Adler, N. E., Morrow, J. D., & Cawthon, R. M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407162101 · Cited by 3,002
Mortality in Mental Disorders and Global Disease Burden Implications: A Systematic Review and Meta-analysis
Walker, E. R., McGee, R. E., & Druss, B. G. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.2502 · Cited by 2,976 · cited 1×
“, 2013; Viron and Stern, 2010), and early mortality (Walker et al., 2015).”
MetaboAnalyst 3.0—making metabolomics more meaningful
Xia, J., Sinelnikov, I. V., Han, B., & Wishart, D. S. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv380 · Cited by 2,680 · cited 1×
“sions and to assess whether subsets of individuals in the sample naturally cluster together (van der Maaten and Hinton, 2008; Xia et al., 2015).”
Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning
Yarkoni, T., & Westfall, J. (2017) · Perspectives on Psychological Science · doi:10.1177/1745691617693393 · Cited by 2,088 · cited 2×
“When not possible to replicate findings on sufficiently large independent datasets, use crossvalidation methods to avoid overfitting (Yarkoni and Westfall, 2017).”
Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection
Blackburn, E. H., Epel, E. S., & Lin, J. (2015) · Science · doi:10.1126/science.aab3389 · Cited by 1,596 · cited 1×
“Thus, while telomerase activation may hold the promise of reducing the risk of aging-related disease, the risk of less common but very serious cancer outcomes must be carefully weighed (Blackburn et al., 2015).”
High levels of mitochondrial DNA deletions in substantia nigra neurons in aging and Parkinson disease
Bender, A., Krishnan, K. J., Morris, C. M., Taylor, G. A., Reeve, A. K., Perry, R. H., Jaros, E., Hersheson, J. S., Betts, J., Klopstock, T., et al. (2006) · Nature Genetics · doi:10.1038/ng1769 · Cited by 1,570 · cited 1×
“between brain regions (Bender et al., 2006; Corral-Debrinski et al., 1992; Picard and Hirano, 2016) and even between cells of a given organ (Vincent et al.”
Statistics versus machine learning
Bzdok, D., Altman, N., & Krzywinski, M. (2018) · Nature Methods · doi:10.1038/nmeth.4642 · Cited by 1,508 · cited 1×
“tifies generalizable predictive patterns (Bzdok et al., 2018).”
Longevity increased by positive self-perceptions of aging
Levy, B. R., Slade, M. D., Kunkel, S. R., & Kasl, S. V. (2002) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.83.2.261 · Cited by 1,508 · cited 1×
“, 2018), selfreported perception of aging (Levy et al., 2002), more specific brain measures (Cole, 2018), or inflammatory markers (Franceschi et al.”
Immunosenescence and Inflamm-Aging As Two Sides of the Same Coin: Friends or Foes?
Fulop, T., Larbi, A., Dupuis, G., Le Page, A., Frost, E. H., Cohen, A. A., Witkowski, J. M., & Franceschi, C. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01960 · Cited by 1,364
DNA methylation age of blood predicts all-cause mortality in later life
Marioni, R. E., Shah, S., McRae, A. F., Chen, B. H., Colicino, E., Harris, S. E., Gibson, J., Henders, A. K., Redmond, P., Cox, S. R., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0584-6 · Cited by 1,261
Biological Age Predictors
Jylhävä, J., Pedersen, N. L., & Hägg, S. (2017) · EBioMedicine · doi:10.1016/j.ebiom.2017.03.046 · Cited by 1,240
Objectively measured physical capability levels and mortality: systematic review and meta-analysis
Cooper, R., Kuh, D., Hardy, R., Mortality Review Group, & teams, O. B. O. T. F. A. H. S. (2010) · BMJ · doi:10.1136/bmj.c4467 · Cited by 1,166 · cited 1×
“S ys te m at ic re vi ew s an d m et aan al yt ic st ud ie s ar e in di ca te d by † . between brain regions (Bender et al., 2006; Corral-Debrinski et al., 1992; Picard and Hirano, 2016) and even between cells of a given organ (Vincent et al., 2018).”
Methods and measures: growth mixture modeling: a method for identifying differences in longitudinal change among unobserved groups
Ram, N., & Grimm, K. J. (2009) · International Journal of Behavioral Development · doi:10.1177/0165025409343765 · Cited by 1,143 · cited 1×
“Other statistical approaches to identify different subgroups exhibiting different trajectories in biological aging or in clinical course include growth mixture modeling (Ram and Grimm, 2009), and random coefficients linear regression models to”
DNA methylation-based measures of biological age: meta-analysis predicting time to death
Chen, B. H., Marioni, R. E., Colicino, E., Peters, M. J., Ward-Caviness, C. K., Tsai, P.-C., Roetker, N. S., Just, A. C., Demerath, E. W., Guan, W., et al. (2016) · Aging · doi:10.18632/aging.101020 · Cited by 1,126
Mitochondrial DNA in innate immune responses and inflammatory pathology
West, A. P., & Shadel, G. S. (2017) · Nature Reviews Immunology · doi:10.1038/nri.2017.21 · Cited by 1,115 · cited 1×
“Released mtDNA molecules thereby act as damage-associated molecular patterns (DAMPs) recognized by toll-like receptors on immune cells and trigger immune cell activation (West and Shadel, 2017).”
More than a feeling: A unified view of stress measurement for population science
Epel, E. S., Crosswell, A. D., Mayer, S. E., Prather, A. A., Slavich, G. M., Puterman, E., & Mendes, W. B. (2018) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2018.03.001 · Cited by 1,077
Differential DNA Methylation in Purified Human Blood Cells: Implications for Cell Lineage and Studies on Disease Susceptibility
Reinius, L. E., Acevedo, N., Joerink, M., Pershagen, G., Dahlén, S., Greco, D., Söderhäll, C., Scheynius, A., & Kere, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041361 · Cited by 1,037 · cited 1×
“example, different blood cell types have different epigenomes (Reinius et al., 2012), telomerase activity and TL (Boeck et al.”
Quantification of biological aging in young adults
Belsky, D. W., Caspi, A., Houts, R., Cohen, H. J., Corcoran, D. L., Danese, A., Harrington, H., Israel, S., Levine, M. E., Schaefer, J. D., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1506264112 · Cited by 1,012 · cited 1×
“Other examples include multivariate indicators of aging incorporating multiple physiological and functional measures (Belsky et al., 2015) and indices integrating multiple enzymatic and molecular measures of mitochondrial content and function in blood leukocytes as the MHI in association to psychological states (i.”
Hand-Grip Dynamometry Predicts Future Outcomes in Aging Adults
Bohannon, R. W. (2008) · Journal of Geriatric Physical Therapy · doi:10.1519/00139143-200831010-00002 · Cited by 951
Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers
Cole, J. H., & Franke, K. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2017.10.001 · Cited by 939 · cited 1×
“A popular approach in neuroscience is to use statistical approaches to translate complex whole-brain multivariate patterns of aging into a single outcome (Luders et al., 2016), the so-called “brain age” (see Cole and Franke, 2017 for details).”
Inflammation and immunity in schizophrenia: implications for pathophysiology and treatment
Khandaker, G. M., Cousins, L., Deakin, J., Lennox, B. R., Yolken, R., & Jones, P. B. (2015) · The Lancet Psychiatry · doi:10.1016/s2215-0366(14)00122-9 · Cited by 926 · cited 1×
“An increase in the inflammatory response, together with microglial activation, in turn, can contribute to psychiatric diseases, such as MDD, schizophrenia, BD, and autism (Khandaker et al., 2015; Martínez-Cengotitabengoa et al., 2016; Réus et al., 2015).”
Mitochondrial DNA deletions in human brain: regional variability and increase with advanced age
Corral-Debrinski, M., Horton, T., Lott, M. T., Shoffner, J. M., Flint Beal, M., & Wallace, D. C. (1992) · Nature Genetics · doi:10.1038/ng1292-324 · Cited by 890
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
Cole, J. H., Poudel, R. P. K., Tsagkrasoulis, D., Caan, M. W. A., Steves, C., Spector, T. D., & Montana, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.059 · Cited by 872
Telomerase reactivation reverses tissue degeneration in aged telomerase-deficient mice
Jaskelioff, M., Muller, F. L., Paik, J.-H., Thomas, E., Jiang, S., Adams, A. C., Sahin, E., Kost-Alimova, M., Protopopov, A., Cadiñanos, J., et al. (2011) · Nature · doi:10.1038/nature09603 · Cited by 857 · cited 1×
“Animal and in-vitro research provided evidence that telomerase-associated recovery of TL is to some extent possible (Batista et al., 2011; Jaskelioff et al., 2011).”
Brain age predicts mortality
Cole, J. H., Ritchie, S. J., Bastin, M. E., Hernández, M. C. V., Maniega, S. M., Royle, N. A., Corley, J., Pattie, A., Harris, S. E., Zhang, Q., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.62 · Cited by 848
Brain disorders? Precisely
Insel, T. R., & Cuthbert, B. N. (2015) · Science · doi:10.1126/science.aab2358 · Cited by 840 · cited 1×
“This notion converges with the precision medicine agenda that aims to identify individualized predictors of future mental health and disease states (Insel and Cuthbert, 2015; Abi-Dargham and Horga, 2016).”
Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile
Penninx, B. W., Milaneschi, Y., Lamers, F., & Vogelzangs, N. (2013) · BMC Medicine · doi:10.1186/1741-7015-11-129 · Cited by 839 · cited 1×
“related medical conditions, including cardiovascular disease, stroke, dementia, diabetes, and obesity (Penninx et al., 2013; Viron and Stern, 2010), and early mortality (Walker et al.”
Self-citation
The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data
the Alzheimer’s Disease Neuroimaging Initiative, E. C., Thompson, P. M., Stein, J. L., Medland, S. E., Hibar, D. P., Vasquez, A. A., Renteria, M. E., Toro, R., Jahanshad, N., Schumann, G., et al. (2014) · Brain Imaging and Behavior · doi:10.1007/s11682-013-9269-5 · Cited by 838
Self-citation
Aging of blood can be tracked by DNA methylation changes at just three CpG sites
Weidner, C. I., Lin, Q., Koch, C. M., Eisele, L., Beier, F., Ziegler, P., Bauerschlag, D. O., Jöckel, K.-H., Erbel, R., Mühleisen, T. W., et al. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r24 · Cited by 837 · cited 2×
“whole blood (Hannum et al., 2013; Levine et al., 2018; Weidner et al., 2014), neonatal cord blood and blood spots (Knight et al.”
Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies
Horvath, S., Oshima, J., Martin, G. M., Lu, A. T., Quach, A., Cohen, H., Felton, S., Matsuyama, M., Lowe, D., Kabacik, S., et al. (2018) · Aging · doi:10.18632/aging.101508 · Cited by 815 · cited 2×
“, 2017), and skin and blood cells (Horvath et al., 2018).”
Epigenetic clock analysis of diet, exercise, education, and lifestyle factors
Quach, A., Levine, M. E., Tanaka, T., Lu, A. T., Chen, B. H., Ferrucci, L., Ritz, B., Bandinelli, S., Neuhouser, M. L., Beasley, J. M., et al. (2017) · Aging · doi:10.18632/aging.101168 · Cited by 801 · cited 1×
“Longitudinal data shows that increasing BMI is associated with increasing epigenetic age (Quach et al., 2017), but in another report, epigenetic age from the liver was”
A Brain-Wide Study of Age-Related Changes in Functional Connectivity
Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M., & Lorist, M. M. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu012 · Cited by 788
Obesity accelerates epigenetic aging of human liver
Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., Schönfels, W. V., Ahrens, M., Heits, N., Bell, J. T., Tsai, P.-C., Spector, T. D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1412759111 · Cited by 760 · cited 1×
“not “decelerated” after successful weight loss over a 9-month period through bariatric surgery (Horvath et al., 2014).”
The transcriptional landscape of age in human peripheral blood
Peters, M. J., Joehanes, R., Pilling, L. C., Schurmann, C., Conneely, K. N., Powell, J., Reinmaa, E., Sutphin, G. L., Zhernakova, A., Schramm, K., et al. (2015) · Nature Communications · doi:10.1038/ncomms9570 · Cited by 725
The effects of acute psychological stress on circulating and stimulated inflammatory markers: a systematic review and meta-analysis
Marsland, A. L., Walsh, C., Lockwood, K., & John-Henderson, N. A. (2017) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2017.01.011 · Cited by 691 · cited 1×
“, 2018), and of psychoneuroimmunology and the pro-inflammatory effects of psychological stress (Marsland et al., 2017) has led to the idea that acute psychological stress may rapidly trigger immunogenic mtDNA”
Inflammation and clinical response to treatment in depression: A meta-analysis
Strawbridge, R., Arnone, D., Danese, A., Papadopoulos, A., Herane Vives, A., & Cleare, A. J. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.06.007 · Cited by 666
Robust research needs many lines of evidence
Munafò, M. R., & Davey Smith, G. (2018) · Nature · doi:10.1038/d41586-018-01023-3 · Cited by 666
Muscle strength and body mass index as long-term predictors of mortality in initially healthy men
Rantanen, T., Harris, T., Leveille, S. G., Visser, M., Foley, D., Masaki, K., & Guralnik, J. M. (2000) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/55.3.m168 · Cited by 647 · cited 1×
“, 2010) and in middleaged populations (Rantanen et al., 2000).”
Modern Approaches to Conceptualizing and Measuring Human Life Stress
Monroe, S. M. (2008) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.4.022007.141207 · Cited by 621 · cited 1×
“Broadly defined, “stress” is the condition of being subjected to a stimulus (i.e., stressor) that invokes a response requiring the use of resources to adapt or cope (Monroe, 2008; Shields and Slavich, 2017).”
The role of inflammation and microglial activation in the pathophysiology of psychiatric disorders
Réus, G. Z., Fries, G. R., Stertz, L., Badawy, M., Passos, I. C., Barichello, T., Kapczinski, F., & Quevedo, J. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.05.018 · Cited by 594 · cited 1×
“An increase in the inflammatory response, together with microglial activation, in turn, can contribute to psychiatric diseases, such as MDD, schizophrenia, BD, and autism (Khandaker et al., 2015; Martínez-Cengotitabengoa et al., 2016; Réus et al., 2015).”
Hand classification of fMRI ICA noise components
Griffanti, L., Douaud, G., Bijsterbosch, J. D., Evangelisti, S., Alfaro‐Almagro, F., Glasser, M. F., Duff, E. P., Fitzgibbon, S. P., Westphal, R., Carone, D., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.036 · Cited by 577
Common brain disorders are associated with heritable patterns of apparent aging of the brain
Kaufmann, T., van der Meer, D., Doan, N. T., Schwarz, E., Lund, M. J., Agartz, I., Alnæs, D., Barch, D. M., Baur‐Streubel, R., Bertolino, A., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0471-7 · Cited by 575
Plasma proteomic signature of age in healthy humans
Tanaka, T., Biancotto, A., Moaddel, R., Moore, A. Z., Gonzalez‐Freire, M., Aon, M. A., Candia, J., Zhang, P., Cheung, F., Fantoni, G., et al. (2018) · Aging Cell · doi:10.1111/acel.12799 · Cited by 562 · cited 1×
“Although exciting new findings from proteomic (Menni et al., 2015; Tanaka et al., 2018) and metabolomic (Chaleckis et al.”
BrainAGE in Mild Cognitive Impaired Patients: Predicting the Conversion to Alzheimer’s Disease
Gaser, C., Franke, K., Klöppel, S., Koutsouleris, N., Sauer, H., & Initiative, A. D. N. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067346 · Cited by 555
Muscular strength in male adolescents and premature death: cohort study of one million participants
Ortega, F. B., Silventoinen, K., Tynelius, P., & Rasmussen, F. (2012) · BMJ · doi:10.1136/bmj.e7279 · Cited by 555 · cited 1×
“associations between handgrip strength and mortality in male adolescents (Ortega et al., 2012), whether functional capacity measures such as walking speed are sensitive to aging and predictive of morbidity and mortality in younger populations largely remains to be established.”
Predicting brain-age from multimodal imaging data captures cognitive impairment
Liem, F., Varoquaux, G. P., Kynast, J., Beyer, F., Masouleh, S. K., Huntenburg, J. M., Lampe, L., Rahim, M., Abraham, A., Craddock, R. C., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.005 · Cited by 522 · cited 1×
“Brain age algorithms (Aycheh et al., 2018; Ball et al., 2017; Cole et al., 2016; Gaser et al., 2013; Liem, 2016; Schnack et al., 2016) generate accurate individual age predictions in healthy controls, but show greater prediction errors when applied to patient groups (Cole et al.”
Telomere shortening and mood disorders: preliminary support for a chronic stress model of accelerated aging
Simon, N. M., Smoller, J. W., McNamara, K. L., Maser, R. S., Zalta, A. K., Pollack, M. H., Nierenberg, A. A., Fava, M., & Wong, K.-K. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.02.004 · Cited by 516 · cited 1×
“Associations of psychiatric disorders and biological age indicators Simon and colleagues (Simon et al., 2006) were the first to report a”
Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models
Wolfers, T., Doan, N. T., Kaufmann, T., Alnæs, D., Moberget, T., Agartz, I., Buitelaar, J. K., Ueland, T., Melle, I., Franke, B., et al. (2018) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.2467 · Cited by 508
Grip Strength Predicts Cause-Specific Mortality in Middle-Aged and Elderly Persons
Sasaki, H., Kasagi, F., Yamada, M., & Fujita, S. (2007) · The American Journal of Medicine · doi:10.1016/j.amjmed.2006.04.018 · Cited by 500
Exposure to violence during childhood is associated with telomere erosion from 5 to 10 years of age: a longitudinal study
Shalev, I., Moffitt, T. E., Sugden, K., Williams, B., Houts, R. M., Danese, A., Mill, J., Arseneault, L., & Caspi, A. (2013) · Molecular Psychiatry · doi:10.1038/mp.2012.32 · Cited by 489 · cited 1×
“In addition to cross-sectional investigations, a longitudinal study (Shalev et al., 2012) found that exposure to violence over a 5-year”
Embodiment of Sadness and Depression—Gait Patterns Associated With Dysphoric Mood
Michalak, J., Troje, N. F., Fischer, J., Vollmar, P., Heidenreich, T., & Schulte, D. (2009) · Psychosomatic Medicine · doi:10.1097/psy.0b013e3181a2515c · Cited by 478
Lifetime stress accelerates epigenetic aging in an urban, African American cohort: Relevance of glucocorticoid signaling
Zannas, A. S., Arloth, J., Carrillo-Roa, T., Iurato, S., Röh, S., Ressler, K. J., Nemeroff, C. B., Smith, A. K., Bradley, B., Heim, C., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0828-5 · Cited by 469 · cited 2×
“tween PTSD and epigenetic aging using the Horvath predictor (Boks et al., 2015; Mehta et al., 2018; Zannas et al., 2015).”
Brain age and other bodily ‘ages’: implications for neuropsychiatry
Cole, J. H., Marioni, R. E., Harris, S. E., & Deary, I. J. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0098-1 · Cited by 450 · cited 1×
“A meta-analysis including 1100 subjects from 7 studies found no difference in TL between BD cases and controls (Colpo et al., 2015).”
Accelerated brain aging in schizophrenia and beyond: a neuroanatomical marker of psychiatric disorders
Koutsouleris, N., Davatzikos, C., Borgwardt, S., Gaser, C., Bottlender, R., Frodl, T., Falkai, P., Riecher-Rossler, A., Moller, H.-J., Reiser, M., et al. (2014) · Schizophrenia Bulletin · doi:10.1093/schbul/sbt142 · Cited by 448 · cited 1×
“2017), schizophrenia (Koutsouleris et al., 2014; Nenadic et al., 2017; Schnack et al., 2016), and first-episode psychosis (Kolenic et al.”
Circulating Mitochondrial DNA in Patients in the ICU as a Marker of Mortality: Derivation and Validation
Nakahira, K., Kyung, S.-Y., Rogers, A. J., Gazourian, L., Youn, S., Massaro, A. F., Quintana, C., Osorio, J. C., Wang, Z., Zhao, Y., et al. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001577 · Cited by 445
Reference-free cell mixture adjustments in analysis of DNA methylation data
Houseman, E. A., Molitor, J., & Marsit, C. J. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu029 · Cited by 441
Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing?
Belsky, D. W., Moffitt, T. E., Cohen, A. A., Corcoran, D. L., Levine, M. E., Prinz, J. A., Schaefer, J. D., Sugden, K., Williams, B. S., Poulton, R., et al. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx346 · Cited by 436 · cited 1×
“37) in independent studies (Belsky et al., 2018; Chen et al., 2016), and both clocks showed modest correlations (0.”
Analyses and comparisons of telomerase activity and telomere length in human T and B cells: Insights for epidemiology of telomere maintenance
Lin, J., Epel, E., Cheon, J., Kroenke, C., Sinclair, E., Bigos, M., Wolkowitz, O., Mellon, S., & Blackburn, E. (2010) · Journal of Immunological Methods · doi:10.1016/j.jim.2009.09.012 · Cited by 426 · cited 2×
“, 2012), telomerase activity and TL (Boeck et al., 2018b, 2018d; Lin et al., 2010), and mitochondrial respiratory capacity (Chacko et al.”
Understanding how we age: insights into inflammaging
Baylis, D., Bartlett, D. B., Patel, H. P., & Roberts, H. C. (2013) · Longevity & Healthspan · doi:10.1186/2046-2395-2-8 · Cited by 413 · cited 1×
“Notably, inflammation is also a widely-used indicator of biological aging (Baylis et al., 2013), coined as “inflammaging” by Franceschi et al.”
Circulating mitochondrial DNA increases with age and is a familiar trait: Implications for “inflamm-aging”
Pinti, M., Cevenini, E., Nasi, M., De Biasi, S., Salvioli, S., Monti, D., Benatti, S., Gibellini, L., Cotichini, R., Stazi, M. A., et al. (2014) · European Journal of Immunology · doi:10.1002/eji.201343921 · Cited by 409
Mitochondrial allostatic load puts the 'gluc' back in glucocorticoids
Picard, M., Juster, R.-P., & McEwen, B. S. (2014) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2014.22 · Cited by 405 · cited 1×
“More recently, an appreciation of the role of mitochondria in the acute stress response and chronic allostatic load (Picard et al., 2014; Picard and McEwen, 2018a, 2018b) has led to investigations of the association of psychological states, stress exposure in relation to mitochondrial functions and mtDNA (Boeck et al.”
Stress and telomere biology: a lifespan perspective
Shalev, I., Entringer, S., Wadhwa, P. D., Wolkowitz, O. M., Puterman, E., Lin, J., & Epel, E. S. (2013) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2013.03.010 · Cited by 400 · cited 1×
“Several excellent qualitative reviews describe and critically review this literature (Entringer et al., 2018; Epel and Prather, 2018; Price et al., 2013; Shalev et al., 2013; Shields and Slavich, 2017) and meta-analyses now quantify the magnitude of these associations and identify potential moderators of effects (e.”
Glycans Are a Novel Biomarker of Chronological and Biological Ages
Krištić, J., Vučković, F., Menni, C., Klarić, L., Keser, T., Beceheli, I., Pučić-Baković, M., Novokmet, M., Mangino, M., Thaqi, K., et al. (2014) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glt190 · Cited by 400
Blood Oxygen Level-Dependent Signal Variability Is More than Just Noise
Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5166-09.2010 · Cited by 396
Ageing and the telomere connection: An intimate relationship with inflammation
Zhang, J., Rane, G., Dai, X., Shanmugam, M. K., Arfuso, F., Samy, R. P., Lai, M. K. P., Kappei, D., Kumar, A. P., & Sethi, G. (2015) · Ageing Research Reviews · doi:10.1016/j.arr.2015.11.006 · Cited by 396 · cited 1×
“These include increased inflammation, oxidative stress markers, dysregulated HPA-axis, and metabolic dysregulations (Lee et al., 2011; Monickaraj et al., 2012; Wikgren et al., 2012; Zhang et al., 2016).”
Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study
Schnack, H. G., van Haren, N. E. M., Nieuwenhuis, M., Pol, H. E. H., Cahn, W., & Kahn, R. S. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2015.15070922 · Cited by 376 · cited 2×
“Brain age algorithms (Aycheh et al., 2018; Ball et al., 2017; Cole et al., 2016; Gaser et al., 2013; Liem, 2016; Schnack et al., 2016) generate accurate individual age predictions in healthy controls, but show greater prediction errors when applied to patient groups (Cole et al.”
Individual variability in human blood metabolites identifies age-related differences
Chaleckis, R., Murakami, I., Takada, J., Kondoh, H., & Yanagida, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1603023113 · Cited by 373 · cited 1×
“, 2018) and metabolomic (Chaleckis et al., 2016; Hertel et al., 2016) signatures of aging are beginning to”
Mitochondrial DNA copy number in peripheral blood cells declines with age and is associated with general health among elderly
Mengel‐From, J., Thinggaard, M., Dalgård, C., Kyvik, K. O., Christensen, K., & Christiansen, L. (2014) · Human Genetics · doi:10.1007/s00439-014-1458-9 · Cited by 371
Psychological Stress and Mitochondria: A Systematic Review
Picard, M. A., & McEwen, B. S. (2018) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000545 · Cited by 360
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L. I., Aghajani, M., Aleman, A., Baune, B. T., Berger, K., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0754-0 · Cited by 351
Impartial comparative analysis of measurement of leukocyte telomere length/DNA content by Southern blots and qPCR
Aviv, A., Hunt, S. C., Lin, J., Cao, X., Kimura, M., & Blackburn, E. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr634 · Cited by 343
Telomere length measurement-caveats and a critical assessment of the available technologies and tools
Aubert, G., Hills, M., & Lansdorp, P. M. (2012) · Mutation research. Fundamental and molecular mechanisms of mutagenesis · doi:10.1016/j.mrfmmm.2011.04.003 · Cited by 342 · cited 2×
“presented elsewhere (Aubert et al., 2012) and will not be discussed in detail here.”
Telomeres and early-life stress: an overview
Price, L. H., Kao, H.-T., Burgers, D. E., Carpenter, L. L., & Tyrka, A. R. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.06.025 · Cited by 339 · cited 1×
“Several excellent qualitative reviews describe and critically review this literature (Entringer et al., 2018; Epel and Prather, 2018; Price et al., 2013; Shalev et al., 2013; Shields and Slavich, 2017) and meta-analyses now quantify the magnitude of these associations and identify potential moderators of effects (e.”
Telomere Length and All-Cause Mortality: A Meta-analysis
Wang, Q., Zhan, Y., Pedersen, N. L., Fang, F., & Hägg, S. (2018) · Ageing Research Reviews · doi:10.1016/j.arr.2018.09.002 · Cited by 333
Precise determination of mitochondrial DNA copy number in human skeletal and cardiac muscle by a PCR-based assay: lack of change of copy number with age
Miller, F. J. (2003) · Nucleic Acids Research · doi:10.1093/nar/gng060 · Cited by 332
Psychological Stress and Mitochondria: A Conceptual Framework
Picard, M. A., & McEwen, B. S. (2018) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000544 · Cited by 328
T Cell Replicative Senescence in Human Aging
P. Chou, J., & B. Effros, R. (2013) · Current Pharmaceutical Design · doi:10.2174/138161213805219711 · Cited by 323 · cited 1×
“thermore, TL differs across leukocyte cell types, such as naïve vs mature T cells (Chou and Effros, 2013; Lin et al., 2016), and differs in different regions of the brain (Mamdani et al.”
Biomarkers of Aging: From Function to Molecular Biology
Wagner, K., Cameron‐Smith, D., Wessner, B., & Franzke, B. (2016) · Nutrients · doi:10.3390/nu8060338 · Cited by 322 · cited 1×
“Here, rather than providing an exhaustive overview that can be found in recent reviews (Engelfriet et al., 2013; Horvath and Raj, 2018; Jylhava et al., 2017; López-Otín et al., 2013; Wagner et al., 2016; Xia et al., 2017), we provide a selective overview of aging indicators commonly studied in relation to mental healt…”
Stress, cell senescence and organismal ageing
de Magalhães, J. P., & Passos, J. F. (2018) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2017.07.001 · Cited by 316
The search for imaging biomarkers in psychiatric disorders
Abi-Dargham, A., & Horga, G. (2016) · Nature Medicine · doi:10.1038/nm.4190 · Cited by 311 · cited 2×
“By definition, biomarkers must exhibit both sensitivity and specificity in relation to the outcome we design them to predict (Abi-Dargham and Horga, 2016).”
DNA methylation age is associated with mortality in a longitudinal Danish twin study
Christiansen, L., Lenart, A. G., Tan, Q., Vaupel, J. W., Aviv, A., McGue, M. K., & Christensen, K. (2015) · Aging Cell · doi:10.1111/acel.12421 · Cited by 309
Frailty is associated with the epigenetic clock but not with telomere length in a German cohort
Breitling, L. P., Saum, K.-U., Perna, L., Schöttker, B., Holleczek, B., & Brenner, H. (2016) · Clinical Epigenetics · doi:10.1186/s13148-016-0186-5 · Cited by 304
Methods for defining distinct bioenergetic profiles in platelets, lymphocytes, monocytes, and neutrophils, and the oxidative burst from human blood
Chacko, B. K., Kramer, P. A., Ravi, S., Johnson, M. S., Hardy, R. W., Ballinger, S. W., & Darley-Usmar, V. M. (2013) · Laboratory Investigation · doi:10.1038/labinvest.2013.53 · Cited by 299
Exercise training and DNA methylation in humans
Voisin, S. A. C., Eynon, N., Yan, X., & Bishop, D. J. (2014) · Acta Physiologica · doi:10.1111/apha.12414 · Cited by 297 · cited 1×
“Physical activity may slow age-related DNAm changes in humans (Ren et al., 2012; Voisin et al., 2015).”
Use of Mendelian randomisation to assess potential benefit of clinical intervention.
Burgess, S., Butterworth, A., Malarstig, A., & Thompson, S. G. (2012) · BMJ · doi:10.1136/bmj.e7325 · Cited by 292 · cited 1×
“, 2017) and genomic methods including Mendelian randomization (Burgess et al., 2012; Wium-Andersen et al., 2017) can substantially reinforce our confidence regarding the direction of effects.”
Effectiveness of sodium fluoride as a preservative of glucose in blood
Chan, A. Y., Swaminathan, R., & Cockram, C. S. (1989) · Clinical Chemistry · doi:10.1093/clinchem/35.2.315 · Cited by 289 · cited 1×
“minutes to days, blood glucose concentration decreases within minutes when the blood is left at room temperature (Chan et al., 1989), owing to metabolic activities of white and red blood cells.”
Methylomic trajectories across human fetal brain development
Spiers, H., Hannon, E., Schalkwyk, L. C., Smith, R., Wong, C. C. Y., O’Donovan, M. C., Bray, N. J., & Mill, J. (2015) · Genome Research · doi:10.1101/gr.180273.114 · Cited by 287 · cited 1×
“While the validity of different methylation-based predictors is questioned, applications of the original pan-tissue Horvath clock (Horvath, 2013) have been successful across tissue types and proven accurate even in embryonic brain samples (Spiers et al., 2015).”
Psychiatric disorders and leukocyte telomere length: Underlying mechanisms linking mental illness with cellular aging
Lindqvist, D., Epel, E. S., Mellon, S. H., Penninx, B. W., Révész, D., Verhoeven, J. E., Reus, V. I., Lin, J., Mahan, L., Hough, C. M., et al. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.05.007 · Cited by 285 · cited 1×
“This indicates that different DSM-based diagnoses may not be associated with meaningful differences in biological aging (Lindqvist et al., 2015).”
Self-citation
Differences in smoking associated DNA methylation patterns in south asians and europeans
Elliott, H. R., Tillin, T., McArdle, W. L., Ho, K., Duggirala, A., Frayling, T. M., Davey Smith, G., Hughes, A. D., Chaturvedi, N., & Relton, C. L. (2014) · Clinical Epigenetics · doi:10.1186/1868-7083-6-4 · Cited by 282
The epigenetic clock and telomere length are independently associated with chronological age and mortality
Marioni, R. E., Harris, S. E., Shah, S. H., McRae, A. F., von Zglinicki, T., Martin-Ruiz, C. M., Wray, N. R., Visscher, P. M., & Deary, I. J. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw041 · Cited by 280
Grip strength and mortality: a biomarker of ageing?
Sayer, A. A., & Kirkwood, T. B. L. (2015) · The Lancet · doi:10.1016/s0140-6736(14)62349-7 · Cited by 279
Major depressive disorder and accelerated cellular aging: results from a large psychiatric cohort study
Verhoeven, J. E., Révész, D., Epel, E. S., Lin, J., Wolkowitz, O. M., & Penninx, B. W. J. H. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.151 · Cited by 278
Molecular Signatures of Major Depression
Cai, N., Chang, S., Li, Y., Li, Q., Hu, J., Liang, J., Song, L., Kretzschmar, W. W., Gan, X., Nicod, J., et al. (2015) · Current Biology · doi:10.1016/j.cub.2015.03.008 · Cited by 274
Early life adversity and telomere length: a meta-analysis
Ridout, K. K., Levandowski, M., Ridout, S. J., Gantz, L., Goonan, K., Palermo, D., Price, L. H., & Tyrka, A. R. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.26 · Cited by 273 · cited 3×
“Meta-analyses of the association between TL and childhood psychosocial stressors document significant effects that vary from small to medium in size (Hanssen et al., 2017; Li et al., 2017a, b; Ridout et al., 2018).”
Influential
Diagnostic utility of telomere length testing in a hospital-based setting
Alder, J. K., Hanumanthu, V. S., Strong, M. A., Dezern, A. E., Stanley, S. E., Takemoto, C. M., Danilova, L., Applegate, C. D., Bolton, S. G., Mohr, D. W., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1720427115 · Cited by 272 · cited 1×
“reported reproducible and definable upper and lower normal boundaries for TL in a hospital population (Alder et al., 2018), indicating that standardization of these measures may be achievable.”
Telomere shortening and loss of self-renewal in dyskeratosis congenita induced pluripotent stem cells
Batista, L. F. Z., Pech, M. F., Zhong, F. L., Nguyen, H. N., Xie, K. T., Zaug, A. J., Crary, S. M., Choi, J., Sebastiano, V., Cherry, A. M., et al. (2011) · Nature · doi:10.1038/nature10084 · Cited by 267
Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease
Franke, K., & Gaser, C. (2012) · GeroPsych · doi:10.1024/1662-9647/a000074 · Cited by 262 · cited 2×
“have high reliability in terms of test-retest performance at both same and different scanners (Cole et al., 2016; Franke and Gaser, 2012), and have shown biologically meaningful associations with health, clinical, and neuropsychiatric phenotypes (Cole et al.”
Epigenetic aging in major depressive disorder
Han, L. K. M., Aghajani, M., Clark, S. L., Chan, R. F., Hattab, M. W., Shabalin, A. A., Zhao, M., Kumar, G., Xie, L. Y., Jansen, R., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.17060595 · Cited by 260
Self-citation
Alterations of mitochondrial DNA copy number and telomere length with early adversity and psychopathology
Tyrka, A. R., Parade, S. H., Price, L. H., Kao, H.-T., Porton, B., Philip, N. S., Welch, E. S., & Carpenter, L. L. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.12.025 · Cited by 259 · cited 3×
“adult psychopathology have been linked to higher mtDNAcn (Cai et al., 2015; Tyrka et al., 2016).”
Self-citation
Depression and telomere length: a meta-analysis
Ridout, K. K., Ridout, S. J., Price, L. H., Sen, S., & Tyrka, A. R. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.11.052 · Cited by 258 · cited 1×
“Several meta-analyses, the largest one containing>34,000 subjects from 38 studies, summarized the results and provided consistent evidence of an inverse association between TL and depression, generally with small to medium effect sizes (Darrow et al., 2016; Ridout et al., 2016; Schutte and Malouff, 2015).”
Perceived stress and telomere length: a systematic review, meta-analysis, and methodologic considerations for advancing the field
Mathur, M. B., Epel, E., Kind, S., Desai, M., Parks, C. G., Sandler, D. P., & Khazeni, N. (2016) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2016.02.002 · Cited by 252 · cited 2×
“meta-analyses, though this effect ranged from very small (Mathur et al., 2016) to modest (Schutte and Malouff, 2016) in size.”
Prenatal and early life influences on epigenetic age in children: A study of mother–offspring pairs from two cohort studies
Simpkin, A. J., Hemani, G., Suderman, M., Gaunt, T. R., Lyttleton, O., Mcardle, W. L., Ring, S. M., Sharp, G. C., Tilling, K., Horvath, S., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddv456 · Cited by 246 · cited 1×
“, 2014), sex, and prenatal factors (Simpkin et al., 2016).”
Traumatic stress and accelerated DNA methylation age: a meta-analysis
Wolf, E. J., Maniates, H., Nugent, N., Maihofer, A. X., Armstrong, D., Ratanatharathorn, A., Ashley-Koch, A. E., Garrett, M., Kimbrel, N. A., Lori, A., et al. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2017.12.007 · Cited by 245
Self-citation
Lifetime stress exposure and health: A review of contemporary assessment methods and biological mechanisms
Shields, G. S., & Slavich, G. M. (2017) · Social and Personality Psychology Compass · doi:10.1111/spc3.12335 · Cited by 244 · cited 1×
“Several excellent qualitative reviews describe and critically review this literature (Entringer et al., 2018; Epel and Prather, 2018; Price et al., 2013; Shalev et al., 2013; Shields and Slavich, 2017) and meta-analyses now quantify the magnitude of these associations and identify potential moderators of effects (e.”
Spatiotemporal gait patterns during over ground locomotion in major depression compared with healthy controls
Lemke, M. R., Wendorff, T., Mieth, B., Buhl, K., & Linnemann, M. (2000) · Journal of Psychiatric Research · doi:10.1016/s0022-3956(00)00017-0 · Cited by 243
Association of walking pace and handgrip strength with all-cause, cardiovascular, and cancer mortality: a UK Biobank observational study
Yates, T. E., Zaccardi, F., Dhalwani, N. N., Davies, M. J., Bakrania, K., Celis-Morales, C. A., Gill, J. M. R., Franks, P. W., & Khunti, K. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx449 · Cited by 243
Mitochondrial respiration in peripheral blood mononuclear cells correlates with depressive subsymptoms and severity of major depression
Karabatsiakis, A., Böck, C., Salinas-Manrique, J., Kolassa, S., Calzia, E., Dietrich, D. E., & Kolassa, I. (2014) · Translational Psychiatry · doi:10.1038/tp.2014.44 · Cited by 242
Quantitative assessment of markers for cell senescence
Lawless, C., Wang, C., Jurk, D., Merz, A., Zglinicki, T. V., & Passos, J. F. (2010) · Experimental Gerontology · doi:10.1016/j.exger.2010.01.018 · Cited by 240
Is Post-Traumatic Stress Disorder Associated with Premature Senescence? A Review of the Literature
Lohr, J. B., Palmer, B. W., Eidt, C. A., Aailaboyina, S., Mausbach, B. T., Wolkowitz, O. M., Thorp, S. R., & Jeste, D. V. (2015) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2015.04.001 · Cited by 239 · cited 1×
“particularly in early life where the measured rate of aging may be more rapid than across adult life (Cole et al., 2018; Lohr et al., 2015).”
Differences between chronological and brain age are related to education and self-reported physical activity
Steffener, J., Habeck, C. G., O’Shea, D. M., Razlighi, Q. R., Bherer, L., & Stern, Y. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.01.014 · Cited by 234 · cited 1×
“Higher physical activity levels are associated with lower brain age (Steffener et al., 2016), and “younger brains” are seen in those that learn to play an instrument (Rogenmoser et al.”
Longitudinal changes of telomere length and epigenetic age related to traumatic stress and post-traumatic stress disorder
Boks, M. P., Mierlo, H. C. V., Rutten, B. P. F., Radstake, T. R. D. J., De Witte, L., Geuze, E., Horvath, S., Schalkwyk, L. C., Vinkers, C. H., Broen, J. C. A., et al. (2015) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2014.07.011 · Cited by 231 · cited 1×
“tween PTSD and epigenetic aging using the Horvath predictor (Boks et al., 2015; Mehta et al., 2018; Zannas et al., 2015).”
The association between psychiatric disorders and telomere length: a meta-analysis involving 14,827 persons
Darrow, S. M., Verhoeven, J. E., Révész, D., Lindqvist, D., Penninx, B. W. J. H., Delucchi, K. L., Wolkowitz, O. M., & Mathews, C. A. (2016) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000356 · Cited by 229
Self-citation
Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters
Schnack, H. G., & Kahn, R. S. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00050 · Cited by 228 · cited 1×
“(Schnack and Kahn, 2016) argue that larger sample sizes will have more generalization power.”
The Impact of Serious Mental Illness on Health and Healthcare
Viron, M., & Stern, T. A. (2010) · Psychosomatics · doi:10.1016/s0033-3182(10)70737-4 · Cited by 223
Inverse association between adiposity and telomere length: The fels longitudinal study
Lee, M., Martin, H. B., Firpo, M. A., & Demerath, E. W. (2010) · American Journal of Human Biology · doi:10.1002/ajhb.21109 · Cited by 213 · cited 1×
“These include increased inflammation, oxidative stress markers, dysregulated HPA-axis, and metabolic dysregulations (Lee et al., 2011; Monickaraj et al., 2012; Wikgren et al., 2012; Zhang et al., 2016).”
Commentary: The seven plagues of epigenetic epidemiology
Heijmans, B. T., & Mill, J. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr225 · Cited by 208 · cited 1×
“Many potential confounders may cause technical variation in DNAm studies, of which population stratification and genetic ancestry are major contributors (Heijmans and Mill, 2012; Ratanatharathorn et al., 2017; Susser et al., 2016).”
GWAS of epigenetic aging rates in blood reveals a critical role for TERT
Lu, A. T.-H., Xue, L., Salfati, E., Chen, B. H., Ferrucci, L., Levy, D. A., Joehanes, R., Murabito, J. M., Kiel, D. P., Tsai, P.-C., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02697-5 · Cited by 208
BrainAGE score indicates accelerated brain aging in schizophrenia, but not bipolar disorder
Nenadić, I., Dietzek, M., Langbein, K., Sauer, H., & Christian Gaser, B. (2017) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2017.05.006 · Cited by 203 · cited 1×
“2017), schizophrenia (Koutsouleris et al., 2014; Nenadic et al., 2017; Schnack et al., 2016), and first-episode psychosis (Kolenic et al.”
A comparison of voxel and surface based cortical thickness estimation methods
Clarkson, M. J., Cardoso, M. J., Ridgway, G. R., Marc Modat, A., Leung, K. K., Rohrer, J. D., Fox, N. C., & Sebastien Ourselin, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.053 · Cited by 195
The fetal programming of telomere biology hypothesis: an update
Entringer, S., de Punder, K., Buß, C., & Wadhwa, P. D. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0151 · Cited by 194
The cerebellum ages slowly according to the epigenetic clock
Horvath, S., Mah, V., Lu, A. T., Woo, J. S., Choi, O.-W., Jasinska, A. J., Riancho, J. A., Tung, S., Coles, N. S., Braun, J., et al. (2015) · Aging · doi:10.18632/aging.100742 · Cited by 191 · cited 1×
“Tissues from multiple organs have been found to age at different rates in terms of epigenetic age (Horvath et al., 2015).”
Cell-type deconvolution from DNA methylation: a review of recent applications
Titus, A., Gallimore, R. M., Salas, L. A., & Christensen, B. C. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx275 · Cited by 190 · cited 1×
“type proportions (Titus et al., 2017) and adjust results accordingly.”
Molecular and phenotypic biomarkers of aging
Xia, X., Chen, W., McDermott, J., & Han, J.-D. J. (2017) · F1000Research · doi:10.12688/f1000research.10692.1 · Cited by 188
Circulating cell-free mitochondrial DNA, but not leukocyte mitochondrial DNA copy number, is elevated in major depressive disorder
Lindqvist, D., Wolkowitz, O. M., Picard, M., Ohlsson, L., Bersani, F. S., Fernström, J., Westrin, Å., Hough, C. M., Lin, J., Reus, V. I., et al. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-017-0001-9 · Cited by 188 · cited 14×
“MDD is among the most frequently studied disorders in this context, possibly as a consequence of its relatively well-documented associations with dysregulated physical health (Penninx et al., 2013).”
InfluentialSelf-citation
Telomere length and cortisol reactivity in children of depressed mothers
Gotlib, I. H., LeMoult, J., Colich, N. L., Foland-Ross, L. C., Hallmayer, J., Joormann, J., Lin, J., & Wolkowitz, O. M. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.119 · Cited by 186
Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners
Eileen Luders, A., Cherbuin, N., & Christian Gaser, B. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.007 · Cited by 183 · cited 1×
“A popular approach in neuroscience is to use statistical approaches to translate complex whole-brain multivariate patterns of aging into a single outcome (Luders et al., 2016), the so-called “brain age” (see Cole and Franke, 2017 for details).”
Short Telomeres in Depression and the General Population Are Associated with a Hypocortisolemic State
Wikgren, M., Maripuu, M., Karlsson, T., Nordfjäll, K., Bergdahl, J., Hultdin, J., Del‐Favero, J., Roos, G., Nilsson, L., Adolfsson, R., et al. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.09.015 · Cited by 181 · cited 1×
“These include increased inflammation, oxidative stress markers, dysregulated HPA-axis, and metabolic dysregulations (Lee et al., 2011; Monickaraj et al., 2012; Wikgren et al., 2012; Zhang et al., 2016).”
Measuring Biological Age via Metabonomics: The Metabolic Age Score
Hertel, J., Friedrich, N., Wittfeld, K., Pietzner, M., Budde, K., Van der Auwera, S., Lohmann, T., Teumer, A., Völzke, H., Nauck, M., et al. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00561 · Cited by 181 · cited 2×
“, 2018) and metabolomic (Chaleckis et al., 2016; Hertel et al., 2016) signatures of aging are beginning to”
Skeletal muscle ex vivo mitochondrial respiration parallels decline in vivo oxidative capacity, cardiorespiratory fitness, and muscle strength: The Baltimore Longitudinal Study of Aging
González‐Freire, M., Scalzo, P., D’Agostino, J., Moore, A. Z., Díaz‐Ruiz, A., Fabbri, E., Zane, A. C., Chen, B. H., Becker, K. G., Lehrmann, E., et al. (2018) · Aging Cell · doi:10.1111/acel.12725 · Cited by 181
Long-term lithium treatment in bipolar disorder is associated with longer leukocyte telomeres
Martinsson, L., Wei, Y., Xu, D., Melas, P. A., Mathé, A. A., Schalling, M., Lavebratt, C., & Backlund, L. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.37 · Cited by 179 · cited 1×
“Turning to other disorders, in a group of bipolar and schizophrenia/psychosis patients, lithium nonresponders had shorter telomeres than responders (Martinsson et al., 2013), and similar associations were found linking short TL to poor”
Independent impacts of aging on mitochondrial DNA quantity and quality in humans
Zhang, R., Wang, Y., Ye, K., Picard, M. A., & Gu, Z. (2017) · BMC Genomics · doi:10.1186/s12864-017-4287-0 · Cited by 178
Cell-free DNA release under psychosocial and physical stress conditions
Hummel, E. M., Hessas, E.-M., Müller, S., Beiter, T., Fisch, M. R., Eibl, A., Wolf, O. T., Giebel, B., Platen, P., Kumsta, R., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0264-x · Cited by 177
Accelerated epigenetic aging and mitochondrial DNA copy number in bipolar disorder
Fries, G. R., Bauer, I. E., Scaini, G., Wu, M., Kazimi, I. F., Valvassori, S. S., Zunta‐Soares, G. B., Walss‐Bass, C., Soares, J. C., & Quevedo, J. (2017) · Translational Psychiatry · doi:10.1038/s41398-017-0048-8 · Cited by 174
A meta-analytic review of the effects of mindfulness meditation on telomerase activity
Schutte, N. S., & Malouff, J. M. (2014) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2013.12.017 · Cited by 171 · cited 1×
“, cognitive behavioral therapy), although preliminary evidence suggests a positive correlation between mindfulness/ meditation practices and telomere biology, including increased telomerase activity (Conklin et al., 2018; Schutte and Malouff, 2014).”
Age‐associated micro RNA expression in human peripheral blood is associated with all‐cause mortality and age‐related traits
Huan, T., Chen, G., Liu, C., Bhattacharya, A., Rong, J., Chen, B. H., Seshadri, S. S., Tanrıverdi, K., Freedman, J. E., Larson, M. G., et al. (2017) · Aging Cell · doi:10.1111/acel.12687 · Cited by 171 · cited 1×
“The microRNA age indicator of Huan et al. (2018) was modestly correlated to epigenetic age (r=0.3) and microRNA expression (r=0.2).”
Influential
Lifespan adversity and later adulthood telomere length in the nationally representative US Health and Retirement Study
Puterman, E., Gemmill, A., Karasek, D., Weir, D., Adler, N. E., Prather, A. A., & Epel, E. S. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1525602113 · Cited by 165 · cited 1×
“Although some studies suggest that childhood adversity may account for associations between TL and adult stressors (Puterman et al., 2016; Révész et al., 2016), there is also evidence that stressors experienced in adulthood prospectively predict telomere attrition (Puterman et al.”
Internalizing disorders and leukocyte telomere erosion: a prospective study of depression, generalized anxiety disorder and post-traumatic stress disorder
Shalev, I., Moffitt, T. E., Braithwaite, A. W., Danese, A., Fleming, N. I., Goldman-Mellor, S., Harrington, H. L., Houts, R. M., Israel, S., Poulton, R., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2013.183 · Cited by 155
Keeping brains young with making music
Rogenmoser, L., Kernbach, J. M., Schlaug, G., & Gaser, C. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1491-2 · Cited by 153 · cited 1×
“, 2016), and “younger brains” are seen in those that learn to play an instrument (Rogenmoser et al., 2018) and those who have practiced meditation for long periods”
Stress, telomeres, and psychopathology: toward a deeper understanding of a triad of early aging
Epel, E. S., & Prather, A. A. (2018) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032816-045054 · Cited by 153 · cited 6×
“alternatively, that the psychiatric and medical conditions may be primarily responsible for some of the telomere effect (Epel and Prather, 2018).”
Influential
Brain Age in Early Stages of Bipolar Disorders or Schizophrenia
Hájek, T., Franke, K., Kolenič, M., Capkova, J., Matějka, M., Propper, L., Uher, R., Stopková, P., Novák, T., Paus, T., et al. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx172 · Cited by 153
Determinants of telomere attrition over 1 year in healthy older women: stress and health behaviors matter
Puterman, E., Lin, J., Krauss, J., Blackburn, E. H., & Epel, E. S. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.70 · Cited by 150 · cited 1×
“, 2016), there is also evidence that stressors experienced in adulthood prospectively predict telomere attrition (Puterman et al., 2015; van Ockenburg et al., 2015).”
Programmatic features of aging originating in development: aging mechanisms beyond molecular damage?
de Magalhães, J. P. (2012) · The FASEB Journal · doi:10.1096/fj.12-210872 · Cited by 150
Mitochondrial DNA as a non-invasive biomarker: Accurate quantification using real time quantitative PCR without co-amplification of pseudogenes and dilution bias
Malik, A. N., Shahni, R., Rodriguez-de-Ledesma, A., Laftah, A. H., & Cunningham, P. (2011) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2011.06.067 · Cited by 148 · cited 1×
“multiplied by 2 to account for the diploid nature of the nuclear genome and taken as mtDNAcn (Malik et al., 2011).”
Acute psychological stress increases serum circulating cell-free mitochondrial DNA
Trumpff, C., Marsland, A. L., Basualto-Alarcón, C., Martin, J. L., Carroll, J. E., Sturm, G., Vincent, A. E., Mosharov, E. V., Gu, Z., Kaufman, B. A., et al. (2019) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2019.03.026 · Cited by 147 · cited 2×
“…study using psychological stress induction in healthy middle-aged individuals also demonstrated that an acute bout of psychological stress may be sufficient to elicit a 2–3 fold increase in serum ccf-mtDNA within 30min, suggesting that ccf-mtDNA is dynamically regulated (Trumpff et al., 2019).”
THE ASSOCIATION BETWEEN DEPRESSION AND LEUKOCYTE TELOMERE LENGTH: A META-ANALYSIS
Schutte, N. S., & Malouff, J. M. (2015) · Depression and Anxiety · doi:10.1002/da.22351 · Cited by 144 · cited 1×
“Several meta-analyses, the largest one containing>34,000 subjects from 38 studies, summarized the results and provided consistent evidence of an inverse association between TL and depression, generally with small to medium effect sizes (Darrow et al., 2016; Ridout et al., 2016; Schutte and Malouff, 2015).”
Circulating Proteomic Signatures of Chronological Age
Menni, C., Kiddle, S. J., Mangino, M., Viñuela, A., Psatha, M., Steves, C., Sattlecker, M., Buil, A., Newhouse, S., Nelson, S., et al. (2015) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glu121 · Cited by 144 · cited 1×
“Although exciting new findings from proteomic (Menni et al., 2015; Tanaka et al., 2018) and metabolomic (Chaleckis et al.”
Associations Between Lifestyle and Depressed Mood: Longitudinal Results From the Maastricht Aging Study
van Gool, C. H., Kempen, G. I. J. M., Bosma, H., van Boxtel, M. P. J., Jolles, J., & van Eijk, J. T. M. (2007) · American Journal of Public Health · doi:10.2105/ajph.2004.053199 · Cited by 135
Handgrip Strength Cannot Be Assumed a Proxy for Overall Muscle Strength
Yeung, S. S. Y., Reijnierse, E. M., Trappenburg, M. C., Hogrel, J., McPhee, J. S., Piasecki, M., Sipilä, S., Salpakoski, A., Butler-Browne, G. S., Pääsuke, M., et al. (2018) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2018.04.019 · Cited by 130 · cited 2×
“agreement between muscle strength measured from handgrip or knee extension, suggesting that the most commonly used metric of muscle strength - handgrip strength - is not a proxy for overall muscle strength (Yeung et al., 2018).”
Profiling IgG N-glycans as potential biomarker of chronological and biological ages
Yu, X., Wang, Y., Krištić, J., Dong, J., Chu, X., Ge, S., Wang, H., Fang, H., Gao, Q., Liu, D., et al. (2016) · Medicine · doi:10.1097/md.0000000000004112 · Cited by 129
Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity
Tardif, C. L., Gauthier, C. J., Steele, C. J., Bazin, P.-L., Schäfer, A., Schaefer, A., Turner, R., & Villringer, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.047 · Cited by 127 · cited 1×
“Moreover, the macroscopic volumetric changes observed in T1and T2-weighted MR imaging reflect microscopic changes at the tissue and cellular levels, and in many circumstances possibly represent an aggregate of multiple cellular mechanisms related to synapses, neurons, and glial cells (Tardif et al., 2016).”
Cell‐free DNA as a biomarker of aging
Teo, Y. V., Capri, M., Morsiani, C., Pizza, G., Faria, A. M. C., Franceschi, C., & Neretti, N. (2019) · Aging Cell · doi:10.1111/acel.12890 · Cited by 127 · cited 1×
“, 2004), age-related elevation in circulating DNA (Teo et al., 2018), and of psychoneuroimmunology and the pro-inflammatory effects of psychological stress (Marsland et al.”
Inflammation in adult women with a history of child maltreatment: The involvement of mitochondrial alterations and oxidative stress
Boeck, C., Koenig, A. M., Schury, K., Geiger, M. L., Karabatsiakis, A., Wilker, S., Waller, C., Gündel, H., Fegert, J. M., Calzia, E., et al. (2016) · Mitochondrion · doi:10.1016/j.mito.2016.08.006 · Cited by 126
Resting leukocyte telomerase activity is elevated in major depression and predicts treatment response
Wolkowitz, O. M., Mellon, S. H., Epel, E. S., Lin, J., Reus, V. I., Rosser, R., Burke, H., Compagnone, M., Nelson, J. C., Dhabhar, F. S., et al. (2011) · Molecular Psychiatry · doi:10.1038/mp.2010.133 · Cited by 125 · cited 1×
“The first study suggesting such a link showed in a small sample of previously unmedicated MDD subjects that low baseline telomerase activity, and a greater increase in telomerase activity during eight weeks of selective serotonin reuptake inhibitors (SSRI) treatment were associated to superior clinical outcome (Wolkow…”
Association of telomere length and mitochondrial DNA copy number in a community sample of healthy adults
Tyrka, A. R., Carpenter, L. L., Kao, H.-T., Porton, B., Philip, N. S., Ridout, S. J., Ridout, K. K., & Price, L. H. (2015) · Experimental Gerontology · doi:10.1016/j.exger.2015.04.002 · Cited by 125
Lung function, smoking and mortality in a 26-year follow-up of healthy middle-aged males
Stavem, K., Aaser, E., Sandvik, L., Bjørnholt, J. V., Erikssen, G., Thaulow, E., & Erikssen, J. E. (2005) · European Respiratory Journal · doi:10.1183/09031936.05.00008504 · Cited by 124
Marked aging‐related decline in efficiency of oxidative phosphorylation in human skin fibroblasts
Gréco, M., Villani, G., Mazzucchelli, F., Bresolin, N., Papa, S., & Attardi, G. M. (2003) · The FASEB Journal · doi:10.1096/fj.02-1009fje · Cited by 122
Systematic and Cell Type-Specific Telomere Length Changes in Subsets of Lymphocytes
Lin, J., Cheon, J., Brown, R. R., Coccia, M., Puterman, E. M., Aschbacher, K., Sinclair, E., Epel, E. S., & Blackburn, E. H. (2016) · Journal of Immunology Research · doi:10.1155/2016/5371050 · Cited by 121 · cited 1×
“thermore, TL differs across leukocyte cell types, such as naïve vs mature T cells (Chou and Effros, 2013; Lin et al., 2016), and differs in different regions of the brain (Mamdani et al.”
T Cell Replicative Senescence in Human Aging
Chou, J. P., & Effros, R. B. (2013) · Current Pharmaceutical Design · doi:10.2174/1381612811319090016 · Cited by 118
The Longitudinal Study of Aging in Human Young Adults: Knowledge Gaps and Research Agenda
Moffitt, T. E., Belsky, D. W., Danese, A., Poulton, R., & Caspi, A. (2017) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glw191 · Cited by 117 · cited 1×
“First, future studies should include longitudinal designs to increase the reliability and accuracy of measuring aging (Moffitt et al., 2017).”
Adjusting for Batch Effects in DNA Methylation Microarray Data, a Lesson Learned
Price, E. M., & Robinson, W. P. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00083 · Cited by 117 · cited 1×
“statistically correct for these prior to analyses (Akulenko et al., 2016; Price and Robinson, 2018).”
A Mitochondrial Health Index Sensitive to Mood and Caregiving Stress
Picard, M. A., Prather, A. A., Puterman, E. M., Cuillerier, A., Coccia, M., Aschbacher, K., Burelle, Y., & Epel, E. S. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.01.012 · Cited by 117 · cited 7×
“Using this composite index as an outcome, this study found that positive mood was associated with higher MHI and was a mediator of the association between caregiving and MHI (Picard et al., 2018).”
Influential
The relationship between circulating mitochondrial DNA and inflammatory cytokines in patients with major depression
Kageyama, Y., Kasahara, T., Kato, M., Sakai, S., Deguchi, Y., Tani, M., Kuroda, K., Hattori, K., Yoshida, S., Goto, Y., et al. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.06.001 · Cited by 116 · cited 1×
“Recent evidence suggests that ccf-mtDNA could contribute to this pro-inflammatory state, although evidence is mixed (Kageyama et al., 2018; Lindqvist et al., 2018, 2016).”
Subjective Age and Mortality in Three Longitudinal Samples
Stéphan, Y., Sutin, A. R., & Terracciano, A. (2018) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000613 · Cited by 112 · cited 1×
“limitation, we do not cover self-reported age (Stephan et al., 2018), selfreported perception of aging (Levy et al.”
Increased plasma levels of circulating cell-free mitochondrial DNA in suicide attempters: associations with HPA-axis hyperactivity
Lindqvist, D., Fernström, J., Grudet, C., Ljunggren, L., Träskman-Bendz, L., Ohlsson, L., & Westrin, Å. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.236 · Cited by 111 · cited 3×
“Another study found that suicide attempters have significantly higher plasma levels of ccfmtDNA (Lindqvist et al., 2016) and another study found elevated ccfmtDNA levels in individuals with major depressive disorder (MDD) (Lindqvist et al.”
InfluentialSelf-citation
Questioning causal involvement of telomeres in aging
Simons, M. J. P. (2015) · Ageing Research Reviews · doi:10.1016/j.arr.2015.08.002 · Cited by 108
Aerobic exercise lengthens telomeres and reduces stress in family caregivers: A randomized controlled trial - Curt Richter Award Paper 2018
Puterman, E. M., Weiss, J., Lin, J., Schilf, S., Slusher, A. L., Johansen, K. L., & Epel, E. S. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.08.002 · Cited by 107 · cited 2×
“…recent small controlled studies have shown elongation of telomeres in response to highly controlled aerobic exercise verified with actigraphy (Puterman et al., 2018), losing and maintaining a weight loss of 10% or greater (Mason et al., 2018), and meditation-based interventions (Conklin et…”
Effects of Vitamin D3 Supplementation on Epigenetic Aging in Overweight and Obese African Americans With Suboptimal Vitamin D Status: A Randomized Clinical Trial
Chen, L., Dong, Y., Bhagatwala, J., Raed, A., Huang, Y., & Zhu, H. (2019) · The Journals of Gerontology: Series A · doi:10.1093/gerona/gly223 · Cited by 106
Inflammaging 2018: An update and a model
Franceschi, C., Zaikin, A. A., Gordleeva, S., Ivanchenko, M., Bonifazi, F., Storci, G., & Bonafè, M. (2018) · Seminars in Immunology · doi:10.1016/j.smim.2018.10.008 · Cited by 105 · cited 1×
“For example, different blood cell types have different epigenomes (Reinius et al., 2012), telomerase activity and TL (Boeck et al., 2018b, 2018d; Lin et al., 2010), and mitochondrial respiratory capacity (Chacko et al., 2013).”
Biological Brain Age Prediction Using Cortical Thickness Data: A Large Scale Cohort Study
Aycheh, H. M., Seong, J., Shin, J., Na, D. L., Kang, B., Seo, S. W., & Sohn, K.-A. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00252 · Cited by 102
The Impact of Serious Mental Illness on Health and Healthcare
Viron, M., & Stern, T. A. (2010) · Psychosomatics · doi:10.1176/appi.psy.51.6.458 · Cited by 102 · cited 1×
“related medical conditions, including cardiovascular disease, stroke, dementia, diabetes, and obesity (Penninx et al., 2013; Viron and Stern, 2010), and early mortality (Walker et al.”
Variable telomere length across post-mortem human brain regions and specific reduction in the hippocampus of major depressive disorder
Mamdani, F., Rollins, B. L., Morgan, L., Myers, R., Barchas, J. D., Schatzberg, A. F., Watson, S. J., Akil, H., Potkin, S. G., Bunney, W. E., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.134 · Cited by 99 · cited 2×
“, 2016), and differs in different regions of the brain (Mamdani et al., 2015).”
Short telomeres in patients with chronic schizophrenia who show a poor response to treatment
Yu, W., Chang, H., Lin, C., & Cho, C.-L. (2008) · Journal of Psychiatry and Neuroscience · doi:10.1139/jpn.0825 · Cited by 98 · cited 1×
“treatment response in schizophrenia (Li et al., 2015; Yu et al., 2008).”
Obesity, dyslipidemia and brain age in first-episode psychosis
Kolenič, M., Franke, K., Hlinka, J., Matějka, M., Capkova, J., Pausová, Z., Uher, R., Alda, M., Španiel, F., & Hájek, T. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.02.012 · Cited by 98 · cited 1×
“, 2016), and first-episode psychosis (Kolenic et al., 2018), but findings were less consistent in BD.”
Mitochondrial DNA copy number is reduced in male combat veterans with PTSD
Bersani, F. S., Morley, C., Lindqvist, D., Epel, E. S., Picard, M. A., Yehuda, R., Flory, J. D., Bierer, L. M., Makotkine, I., Amara, D. A., et al. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.06.012 · Cited by 93
The relationship between childhood psychosocial stressor level and telomere length: a meta-analysis
M. Hanssen, L., S. Schutte, N., M. Malouff, J., & S. Epel, E. (2017) · Health Psychology Research · doi:10.4081/hpr.2017.6378 · Cited by 93
Respirometric Profiling of Muscle Mitochondria and Blood Cells Are Associated With Differences in Gait Speed Among Community-Dwelling Older Adults
Tyrrell, D. J., Bharadwaj, M. S., Horn, C. G. V., Kritchevsky, S. B., Nicklas, B. J., & Molina, A. J. A. (2014) · The Journals of Gerontology Series A · doi:10.1093/gerona/glu096 · Cited by 92 · cited 1×
“, 2015) and isolated mitochondria where the intrinsic function of the organelle can be directly assessed independent of cellular contributions (Tyrrell et al., 2015).”
The Relationship Between Perceived Stress and Telomere Length: A Meta‐analysis
Schutte, N. S., & Malouff, J. M. (2014) · Stress and Health · doi:10.1002/smi.2607 · Cited by 91
Epigenome‐wide association of PTSD from heterogeneous cohorts with a common multi‐site analysis pipeline
Ratanatharathorn, A. D., Boks, M. P., Maihofer, A. X., Aiello, A. E., Amstadter, A. B., Ashley‐Koch, A. E., Baker, D. G., Beckham, J. C., Bromet, E. J., Dennis, M. F., et al. (2017) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32568 · Cited by 91
Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II)
Vetter, V. M., Meyer, A., Karbasiyan, M., Steinhagen‐Thiessen, E., Hopfenmüller, W., & Demuth, I. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly184 · Cited by 90
Depression, telomeres and mitochondrial DNA: between- and within-person associations from a 10-year longitudinal study
Verhoeven, J. E., Révész, D., Picard, M. A., Epel, E. S., Wolkowitz, O. M., Matthews, K. A., Penninx, B. W. J. H., & Puterman, E. M. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.48 · Cited by 87
Personalized Antidepressant Selection and Pathway to Novel Treatments: Clinical Utility of Targeting Inflammation
Jha, M. K., & Trivedi, M. H. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19010233 · Cited by 87
Leukocyte mitochondrial DNA (mtDNA) content is associated with depression in old women
Kim, M.-Y., Lee, J., Kang, H., Kim, E., & Lee, D. (2010) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2010.11.019 · Cited by 85
Peripheral Inflammatory Parameters in Late-Life Depression: A Systematic Review
Martínez-Cengotitabengoa, M., Carrascón, L., O’Brien, J., Díaz-Gutiérrez, M.-J., Bermúdez-Ampudia, C., Sanada, K., Arrasate, M., & González-Pinto, A. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17122022 · Cited by 85 · cited 1×
“An increase in the inflammatory response, together with microglial activation, in turn, can contribute to psychiatric diseases, such as MDD, schizophrenia, BD, and autism (Khandaker et al., 2015; Martínez-Cengotitabengoa et al., 2016; Réus et al., 2015).”
Systematic analysis of the gerontome reveals links between aging and age-related diseases
Fernandes, M., Wan, C., Tăcutu, R., Barardo, D., Rajput, A. B., Wang, J., Thoppil, H., Thornton, D., Yang, C., Freitas, A. A., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw307 · Cited by 84
Association between childhood trauma and accelerated telomere erosion in adulthood: a meta-analytic study
Li, Z., He, Y., Wang, D., Tang, J., & Chen, X. (2017) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2017.06.002 · Cited by 84
Adjusting MtDNA Quantification in Whole Blood for Peripheral Blood Platelet and Leukocyte Counts
Hurtado-Roca, Y., Ledesma, M., González‐Lázaro, M., Moreno‐Loshuertos, R., Fernández‐Silva, P., Enrı́quez, J. A., & Laclaustra, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0163770 · Cited by 81 · cited 1×
“Platelets do not have nDNA, but have mtDNA, which artificially inflates mtDNA copy number in whole blood preparations (Hurtado-Roca et al., 2016; Urata et al., 2008).”
Subcellular origin of mitochondrial DNA deletions in human skeletal muscle
Vincent, A. E., Rosa, H. S., Pabis, K., Lawless, C., Chen, C., Grünewald, A., Rygiel, K. A., Rocha, M. C., Reeve, A. K., Falkous, G., et al. (2018) · Annals of Neurology · doi:10.1002/ana.25288 · Cited by 81 · cited 1×
“, 1992; Picard and Hirano, 2016) and even between cells of a given organ (Vincent et al., 2018).”
Erratum: Variable telomere length across post-mortem human brain regions and specific reduction in the hippocampus of major depressive disorder
Mamdani, F., Rollins, B. L., Morgan, L., Myers, R., Barchas, J. D., Schatzberg, A. F., Watson, S. J., Akil, H., Potkin, S. G., Bunney, W. E., et al. (2016) · Translational Psychiatry · doi:10.1038/tp.2015.164 · Cited by 78
Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor
Li, X., Li, W., & Xu, Y. (2018) · Genes · doi:10.3390/genes9090424 · Cited by 78
Leukocyte telomere length in patients with schizophrenia: A meta-analysis
Polho, G. B., de Paula, V. D. J. R., Cardillo, G. D. M., dos Santos, B., & Kerr, D. S. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.04.025 · Cited by 76 · cited 1×
“Two meta-analyses on schizophrenia of 1200 and 1600 subjects, respectively, found small effects for TL differences (Polho et al., 2015; Rao et al., 2016).”

Flagged first, then by citations

Research works printed but not linked: 1

Cawthon, 2002, 30, 1

Sorted by citations

A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration
Oblak, L., van der Zaag, J., Higgins‐Chen, A., Levine, M. E., & Boks, M. P. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101348 · Cited by 610
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L. I., Aghajani, M., Aleman, A., Baune, B. T., Berger, K., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0754-0 · Cited by 351
Biological factors influencing depression in later life: role of aging processes and treatment implications
Szymkowicz, S. M., Gerlach, A., Homiack, D., & Taylor, W. D. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02464-9 · Cited by 227
“As the difference between calculated brain age and chronological age differs between midlife adult depressed samples and LLD [198, 203, 204, 209], depression may be associated with an altered trajectory of biological aging [210].”
Background
Childhood Trauma in Adult Depressive and Anxiety Disorders: An Integrated Review on Psychological and Biological Mechanisms in the NESDA Cohort
Kuzminskaite, E., Penninx, B. W. J. H., van Harmelen, A., Elzinga, B. M., Hovens, J. G. F. M., & Vinkers, C. H. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.01.054 · Cited by 194
Stress and Psychiatric Disorders: The Role of Mitochondria
Daniels, T. E., Olsen, E. M., & Tyrka, A. R. (2020) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-082719-104030 · Cited by 157

See all 104

Authors: Han, L. K. M., Verhoeven, J. E., Tyrka, A. R., Penninx, B. W. J. H., Wolkowitz, O. M., Månsson, K. N. T., Lindqvist, D., Boks, M. P., Révész, D., Mellon, S. H., & Picard, M.
Affiliations: Amsterdam Neuroscience (NL)
Amsterdam Public Health (NL)
Brown University (US)
University of California, San Francisco (US)
Uppsala University (SE)
University Medical Center Utrecht (NL)
Tilburg University (NL)
Columbia University Irving Medical Center (US)
Corresponding author: Picard, Martin
ORCID: Han, Laura K.M.
Verhoeven, Josine E.
Tyrka, Audrey R.
Penninx, Brenda W.J.H.
Wolkowitz, Owen M.
Månsson, Kristoffer N.T.
Lindqvist, Daniel
Boks, Marco P.
Révész, Dóra
Mellon, Synthia H.
Picard, Martin
Venue: Psychoneuroendocrinology
Publisher: Elsevier BV
Published: 2019-08
Volume: 106
Pages: 293-311
ISSN: 0306-4530 (ISSN-L)
DOI: 10.1016/j.psyneuen.2019.04.004
PMC: PMC6589133
OpenAlex: W2929049496
Cited by: 104
References: 275
Citations by year: 2026: 10 · 2025: 15 · 2024: 17 · 2023: 17 · 2022: 22 · 2021: 11 · 2020: 6 · 2019: 4
FWCI: 0.93
Type: journal article
Language: en
Open access: green
pure.amsterdamumc.nl
Licence: other-oa
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Psychoneuroendocrinology (publishedVersion)
Research portal (Tilburg University) (publishedVersion)
PubMed (publishedVersion)
Pure Amsterdam UMC (publishedVersion, other-oa)
Pure Amsterdam UMC (publishedVersion)
Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
PubMed Central (acceptedVersion)
Data Archiving and Networked Services (DANS) (submittedVersion)
Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
eScholarship (California Digital Library) (submittedVersion)
Minerva Access (University of Melbourne) (submittedVersion)
Lund University Publications (Lund University) (submittedVersion)
Utrecht University Repository (Utrecht University) (submittedVersion)
Funders: Nathaniel Wharton Fund
National Institutes of Health (GM119793, MH113011, MH083784, MH101107, HD086487)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
Keywords: biological aging, mental health, psychological stress, mental illness, aging interventions, accelerated aging, multidisciplinary research, levels of analysis
MeSH terms: Aging, Mental Disorders, Humans, Mental Health, Stress, Psychological

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Accelerating research on biological aging and mental health: Current challenges and future directions.

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks