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204 results on '"Colicino, E."'

3. Cross-Cohort Mixture Analysis: A Data Integration Approach With Applications on Gestational Age and DNA-Methylation-Derived Gestational Age Acceleration Metrics

Author

Colicino, E, Ascari, R, Saddiki, H, Merced-Nieves, F, Foppa Pedretti, N, Huddleston, K, Wright, R, Wright, RO, Wright, RJ, Colicino, E, Ascari, R, Saddiki, H, Merced-Nieves, F, Foppa Pedretti, N, Huddleston, K, Wright, R, Wright, RO, and Wright, RJ

Abstract

Data integration of multiple studies can provide enhanced exposure contrast and statistical power to examine associations between environmental exposure mixtures and health outcomes. Extant research has combined populations and identified an overall mixture-outcome association, without accounting for differences across studies. We extended the Bayesian Weighted Quantile Sum (BWQS) regression to a hierarchical framework to analyze mixtures across cohorts. The hierarchical BWQS (HBWQS) approach aggregates sample size of multiple cohorts to calculate an overall mixture index, thereby identifying the most harmful exposure(s) across cohorts; and provides cohort-specific associations between the overall mixture index and the outcome. We showed results from 10 simulated scenarios including four mixture components in three, eight, and ten populations, and two real-case examples on the association between prenatal metal mixture exposure-comprising arsenic, cadmium, and lead-and both gestational age and epigenetic-derived gestational age acceleration metrics. Simulated scenarios showed good empirical coverage and little bias for all HBWQS-estimated parameters. The Watanabe-Akaike information criterion showed a better average performance for the HBWQS regression than the BWQS across scenarios. HBWQS results incorporating cohorts within the national Environmental influences on Child Health Outcomes (ECHO) program from three different sites showed that the environmental mixture was negatively associated with gestational age in a single site. The HBWQS approach facilitates the combination of multiple cohorts and accounts for individual cohort differences in mixture analyses. HBWQS findings can be used to develop regulations, policies, and interventions regarding multiple co-occurring environmental exposures and it will maximize the use of extant publicly available data.

Published
2024

4. Comparative efficacy of three Bayesian variable selection methods in the context of weight loss in obese women

Author

Pesenti, N, Quatto, P, Colicino, E, Cancello, R, Scacchi, M, Zambon, A, Pesenti N., Quatto P., Colicino E., Cancello R., Scacchi M., Zambon A., Pesenti, N, Quatto, P, Colicino, E, Cancello, R, Scacchi, M, Zambon, A, Pesenti N., Quatto P., Colicino E., Cancello R., Scacchi M., and Zambon A.

Abstract

The use of high-dimensional data has expanded in many fields, including in clinical research, thus making variable selection methods increasingly important compared to traditional statistical approaches. The work aims to compare the performance of three supervised Bayesian variable selection methods to detect the most important predictors among a high-dimensional set of variables and to provide useful and practical guidelines of their use. We assessed the variable selection ability of: (1) Bayesian Kernel Machine Regression (BKMR), (2) Bayesian Semiparametric Regression (BSR), and (3) Bayesian Least Absolute Shrinkage and Selection Operator (BLASSO) regression on simulated data of different dimensions and under three scenarios with disparate predictor-response relationships and correlations among predictors. This is the first study describing when one model should be preferred over the others and when methods achieve comparable results. BKMR outperformed all other models with small synthetic datasets. BSR was strongly dependent on the choice of its own intrinsic parameter, but its performance was comparable to BKMR with large datasets. BLASSO should be preferred only when it is reasonable to hypothesise the absence of synergies between predictors and the presence of monotonous predictor-outcome relationships. Finally, we applied the models to a real case study and assessed the relationships among anthropometric, biochemical, metabolic, cardiovascular, and inflammatory variables with weight loss in 755 hospitalised obese women from the Follow Up OBese patients at AUXOlogico institute (FUOBAUXO) cohort.

Published
2023

6. Epigenome-wide meta-analysis of prenatal maternal stressful life events and newborn DNA methylation

Author

Kotsakis Ruehlmann, A., Sammallahti, S., Cortés Hidalgo, A.P., Bakulski, K.M., Binder, E.B., Campbell, M.L., Caramaschi, D., Cecil, C., Colicino, E., Cruceanu, C., Czamara, D., Dieckmann, L., Dou, J., Felix, J.F., Frank, J., Håberg, S.E., Herberth, Gunda, Hoang, T.T., Houtepen, L.C., Hüls, A., Koen, N., London, S.J., Magnus, M.C., Mancano, G., Mulder, R.H., Page, C.M., Räikkönen, K., Röder, Stefan, Schmidt, R.J., Send, T.S., Sharp, G., Stein, D.J., Streit, F., Tuhkanen, J., Witt, S.H., Zar, H.J., Zenclussen, Ana Claudia, Zhang, Y., Zillich, L., Wright, R., Lahti, J., Brunst, K.J., Kotsakis Ruehlmann, A., Sammallahti, S., Cortés Hidalgo, A.P., Bakulski, K.M., Binder, E.B., Campbell, M.L., Caramaschi, D., Cecil, C., Colicino, E., Cruceanu, C., Czamara, D., Dieckmann, L., Dou, J., Felix, J.F., Frank, J., Håberg, S.E., Herberth, Gunda, Hoang, T.T., Houtepen, L.C., Hüls, A., Koen, N., London, S.J., Magnus, M.C., Mancano, G., Mulder, R.H., Page, C.M., Räikkönen, K., Röder, Stefan, Schmidt, R.J., Send, T.S., Sharp, G., Stein, D.J., Streit, F., Tuhkanen, J., Witt, S.H., Zar, H.J., Zenclussen, Ana Claudia, Zhang, Y., Zillich, L., Wright, R., Lahti, J., and Brunst, K.J.

Abstract

Prenatal maternal stressful life events are associated with adverse neurodevelopmental outcomes in offspring. Biologic mechanisms underlying these associations are largely unknown, but DNA methylation likely plays a role. This meta-analysis included twelve datasets from ten pregnancy cohorts (N=5,496) within the international Pregnancy and Childhood Epigenetics consortium to examine maternal stressful life events during pregnancy and DNA methylation in cord blood. Children whose mothers reported higher levels of cumulative maternal stressful life events during pregnancy exhibited differential methylation of cg26579032 in ALKBH3. Stressor-specific domains of conflict with family/friends, abuse (physical, sexual, and emotional), and death of a close friend/relative were also associated with differential methylation of CpGs in APTX, MyD88, and both UHRF1 and SDCCAG8, respectively; these genes are implicated in neurodegeneration, immune and cellular functions, regulation of global methylation levels, metabolism, and schizophrenia risk. Thus, differences in DNA methylation at these loci may provide novel insights into potential mechanisms of neurodevelopment in offspring.

Published
2023

8. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases

Author

Wielscher, M. (Matthias), Mandaviya, P. R. (Pooja R.), Kuehnel, B. (Brigitte), Joehanes, R. (Roby), Mustafa, R. (Rima), Robinson, O. (Oliver), Zhang, Y. (Yan), Bodinier, B. (Barbara), Walton, E. (Esther), Mishra, P. P. (Pashupati P.), Schlosser, P. (Pascal), Wilson, R. (Rory), Tsai, P.-C. (Pei-Chien), Palaniswamy, S. (Saranya), Marioni, R. E. (Riccardo E.), Fiorito, G. (Giovanni), Cugliari, G. (Giovanni), Karhunen, V. (Ville), Ghanbari, M. (Mohsen), Psaty, B. M. (Bruce M.), Loh, M. (Marie), Bis, J. C. (Joshua C.), Lehne, B. (Benjamin), Sotoodehnia, N. (Nona), Deary, I. J. (Ian J.), Chadeau-Hyam, M. (Marc), Brody, J. A. (Jennifer A.), Cardona, A. (Alexia), Selvin, E. (Elizabeth), Smith, A. K. (Alicia K.), Miller, A. H. (Andrew H.), Torres, M. A. (Mylin A.), Marouli, E. (Eirini), Gao, X. (Xin), van Meurs, J. B. (Joyce B. J.), Graf-Schindler, J. (Johanna), Rathmann, W. (Wolfgang), Koenig, W. (Wolfgang), Peters, A. (Annette), Weninger, W. (Wolfgang), Farlik, M. (Matthias), Zhang, T. (Tao), Chen, W. (Wei), Xia, Y. (Yujing), Teumer, A. (Alexander), Nauck, M. (Matthias), Grabe, H. J. (Hans J.), Doerr, M. (Macus), Lehtimaki, T. (Terho), Guan, W. (Weihua), Milani, L. (Lili), Tanaka, T. (Toshiko), Fisher, K. (Krista), Waite, L. L. (Lindsay L.), Kasela, S. (Silva), Vineis, P. (Paolo), Verweij, N. (Niek), van der Harst, P. (Pim), Iacoviello, L. (Licia), Sacerdote, C. (Carlotta), Panico, S. (Salvatore), Krogh, V. (Vittorio), Tumino, R. (Rosario), Tzala, E. (Evangelia), Matullo, G. (Giuseppe), Hurme, M. A. (Mikko A.), Raitakari, O. T. (Olli T.), Colicino, E. (Elena), Baccarelli, A. A. (Andrea A.), Kahonen, M. (Mika), Herzig, K.-H. (Karl-Heinz), Li, S. (Shengxu), BIOS consortium, Conneely, K. N. (Karen N.), Kooner, J. S. (Jaspal S.), Kottgen, A. (Anna), Heijmans, B. T. (Bastiaan T.), Deloukas, P. (Panos), Relton, C. (Caroline), Ong, K. K. (Ken K.), Bell, J. T. (Jordana T.), Boerwinkle, E. (Eric), Elliott, P. (Paul), Brenner, H. (Hermann), Beekman, M. (Marian), Levy, D. (Daniel), Waldenberger, M. (Melanie), Chambers, J. C. (John C.), Dehghan, A. (Abbas), Järvelin, M.-R. (Marjo-Riitta), Wielscher, M. (Matthias), Mandaviya, P. R. (Pooja R.), Kuehnel, B. (Brigitte), Joehanes, R. (Roby), Mustafa, R. (Rima), Robinson, O. (Oliver), Zhang, Y. (Yan), Bodinier, B. (Barbara), Walton, E. (Esther), Mishra, P. P. (Pashupati P.), Schlosser, P. (Pascal), Wilson, R. (Rory), Tsai, P.-C. (Pei-Chien), Palaniswamy, S. (Saranya), Marioni, R. E. (Riccardo E.), Fiorito, G. (Giovanni), Cugliari, G. (Giovanni), Karhunen, V. (Ville), Ghanbari, M. (Mohsen), Psaty, B. M. (Bruce M.), Loh, M. (Marie), Bis, J. C. (Joshua C.), Lehne, B. (Benjamin), Sotoodehnia, N. (Nona), Deary, I. J. (Ian J.), Chadeau-Hyam, M. (Marc), Brody, J. A. (Jennifer A.), Cardona, A. (Alexia), Selvin, E. (Elizabeth), Smith, A. K. (Alicia K.), Miller, A. H. (Andrew H.), Torres, M. A. (Mylin A.), Marouli, E. (Eirini), Gao, X. (Xin), van Meurs, J. B. (Joyce B. J.), Graf-Schindler, J. (Johanna), Rathmann, W. (Wolfgang), Koenig, W. (Wolfgang), Peters, A. (Annette), Weninger, W. (Wolfgang), Farlik, M. (Matthias), Zhang, T. (Tao), Chen, W. (Wei), Xia, Y. (Yujing), Teumer, A. (Alexander), Nauck, M. (Matthias), Grabe, H. J. (Hans J.), Doerr, M. (Macus), Lehtimaki, T. (Terho), Guan, W. (Weihua), Milani, L. (Lili), Tanaka, T. (Toshiko), Fisher, K. (Krista), Waite, L. L. (Lindsay L.), Kasela, S. (Silva), Vineis, P. (Paolo), Verweij, N. (Niek), van der Harst, P. (Pim), Iacoviello, L. (Licia), Sacerdote, C. (Carlotta), Panico, S. (Salvatore), Krogh, V. (Vittorio), Tumino, R. (Rosario), Tzala, E. (Evangelia), Matullo, G. (Giuseppe), Hurme, M. A. (Mikko A.), Raitakari, O. T. (Olli T.), Colicino, E. (Elena), Baccarelli, A. A. (Andrea A.), Kahonen, M. (Mika), Herzig, K.-H. (Karl-Heinz), Li, S. (Shengxu), BIOS consortium, Conneely, K. N. (Karen N.), Kooner, J. S. (Jaspal S.), Kottgen, A. (Anna), Heijmans, B. T. (Bastiaan T.), Deloukas, P. (Panos), Relton, C. (Caroline), Ong, K. K. (Ken K.), Bell, J. T. (Jordana T.), Boerwinkle, E. (Eric), Elliott, P. (Paul), Brenner, H. (Hermann), Beekman, M. (Marian), Levy, D. (Daniel), Waldenberger, M. (Melanie), Chambers, J. C. (John C.), Dehghan, A. (Abbas), and Järvelin, M.-R. (Marjo-Riitta)

Abstract

We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

Published
2022

12. Maternal anxiety during pregnancy and newborn epigenome-wide DNA methylation

Author

Sammallahti, S. (Sara), Cortes Hidalgo, A. P. (Andrea P.), Tuominen, S. (Samuli), Malmberg, A. (Anni), Mulder, R. H. (Rosa H.), Brunst, K. J. (Kelly J.), Alemany, S. (Silvia), McBride, N. S. (Nancy S.), Yousefi, P. (Paul), Heiss, J. A. (Jonathan A.), McRae, N. (Nia), Page, C. M. (Christian M.), Jin, J. (Jianping), Pesce, G. (Giancarlo), Caramaschi, D. (Doretta), Rifas-Shiman, S. L. (Sheryl L.), Koen, N. (Nastassja), Adams, C. D. (Charleen D.), Magnus, M. C. (Maria C.), Baiz, N. (Nour), Ratanatharathorn, A. (Andrew), Czamara, D. (Darina), Haberg, S. E. (Siri E.), Colicino, E. (Elena), Baccarelli, A. A. (Andrea A.), Cardenas, A. (Andres), DeMeo, D. L. (Dawn L.), Lawlor, D. A. (Deborah A.), Relton, C. L. (Caroline L.), Felix, J. F. (Janine F.), van IJzendoorn, M. H. (Marinus H.), Bakermans-Kranenburg, M. J. (Marian J.), Kajantie, E. (Eero), Raikkonen, K. (Katri), Sunyer, J. (Jordi), Sharp, G. C. (Gemma C.), Houtepen, L. C. (Lotte C.), Nohr, E. A. (Ellen A.), Sorensen, T. I. (Thorkild I. A.), Tellez-Rojo, M. M. (Martha M.), Wright, R. O. (Robert O.), Annesi-Maesano, I. (Isabella), Wright, J. (John), Hivert, M.-F. (Marie-France), Wright, R. J. (Rosalind J.), Zar, H. J. (Heather J.), Stein, D. J. (Dan J.), London, S. J. (Stephanie J.), Cecil, C. A. (Charlotte A. M.), Tiemeier, H. (Henning), Lahti, J. (Jari), Sammallahti, S. (Sara), Cortes Hidalgo, A. P. (Andrea P.), Tuominen, S. (Samuli), Malmberg, A. (Anni), Mulder, R. H. (Rosa H.), Brunst, K. J. (Kelly J.), Alemany, S. (Silvia), McBride, N. S. (Nancy S.), Yousefi, P. (Paul), Heiss, J. A. (Jonathan A.), McRae, N. (Nia), Page, C. M. (Christian M.), Jin, J. (Jianping), Pesce, G. (Giancarlo), Caramaschi, D. (Doretta), Rifas-Shiman, S. L. (Sheryl L.), Koen, N. (Nastassja), Adams, C. D. (Charleen D.), Magnus, M. C. (Maria C.), Baiz, N. (Nour), Ratanatharathorn, A. (Andrew), Czamara, D. (Darina), Haberg, S. E. (Siri E.), Colicino, E. (Elena), Baccarelli, A. A. (Andrea A.), Cardenas, A. (Andres), DeMeo, D. L. (Dawn L.), Lawlor, D. A. (Deborah A.), Relton, C. L. (Caroline L.), Felix, J. F. (Janine F.), van IJzendoorn, M. H. (Marinus H.), Bakermans-Kranenburg, M. J. (Marian J.), Kajantie, E. (Eero), Raikkonen, K. (Katri), Sunyer, J. (Jordi), Sharp, G. C. (Gemma C.), Houtepen, L. C. (Lotte C.), Nohr, E. A. (Ellen A.), Sorensen, T. I. (Thorkild I. A.), Tellez-Rojo, M. M. (Martha M.), Wright, R. O. (Robert O.), Annesi-Maesano, I. (Isabella), Wright, J. (John), Hivert, M.-F. (Marie-France), Wright, R. J. (Rosalind J.), Zar, H. J. (Heather J.), Stein, D. J. (Dan J.), London, S. J. (Stephanie J.), Cecil, C. A. (Charlotte A. M.), Tiemeier, H. (Henning), and Lahti, J. (Jari)

Abstract

Maternal anxiety during pregnancy is associated with adverse foetal, neonatal, and child outcomes, but biological mechanisms remain unclear. Altered foetal DNA methylation (DNAm) has been proposed as a potential underlying mechanism. In the current study, we performed a meta-analysis to examine the associations between maternal anxiety, measured prospectively during pregnancy, and genome-wide DNAm from umbilical cord blood. Sixteen non-overlapping cohorts from 12 independent longitudinal studies of the Pregnancy And Childhood Epigenetics Consortium participated, resulting in a combined dataset of 7243 mother-child dyads. We examined prenatal anxiety in relation to genome-wide DNAm and differentially methylated regions. We observed no association between the general symptoms of anxiety during pregnancy or pregnancy-related anxiety, and DNAm at any of the CpG sites, after multiple-testing correction. Furthermore, we identify no differentially methylated regions associated with maternal anxiety. At the cohort-level, of the 21 associations observed in individual cohorts, none replicated consistently in the other cohorts. In conclusion, contrary to some previous studies proposing cord blood DNAm as a promising potential mechanism explaining the link between maternal anxiety during pregnancy and adverse outcomes in offspring, we found no consistent evidence for any robust associations between maternal anxiety and DNAm in cord blood. Larger studies and analysis of DNAm in other tissues may be needed to establish subtle or subgroup-specific associations between maternal anxiety and the foetal epigenome.

Published
2021

17. Prenatal exposure to multiple persistent organic pollutants and childhood BMI trajectories- a comparison of three different methods for exposure mixture analysis in a mixed model framework

Author

Colicino, E., primary, Margetaki, K., additional, Stratakis, N., additional, Vafeiadi, M., additional, Roumeliotaki, T., additional, Kyrtopoulos, S., additional, Kiviranta, H., additional, Stephanou, E., additional, Kogevinas, M., additional, McConnell, R., additional, Berhane, K., additional, Chatzi, L., additional, and Conti, D., additional

Published
2020
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19. Benefits and challenges of combining data from the CHEAR consortia

Author

Busgang, S.A., primary, Colicino, E., additional, Mazzella, M.J., additional, Hauptman, M., additional, Schiltz, A.M., additional, Hamlington, K.L., additional, Andra, S.S., additional, Wright, R.O., additional, Boyd Barr, D., additional, Panuwet, P., additional, Phipatanakul, W., additional, Liu, A.H., additional, Teitelbaum, S., additional, and Gennings, C., additional

Published
2020
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21. Blood-based DNA methylation biomarkers for cumulative lead exposure: associations with cardiovascular disease incidence and mortality in the Strong Heart Study

Author

Gao, X., primary, Domingo-Relloso, A., additional, Colicino, E., additional, Cole, S. A., additional, Haack, K., additional, Best, L. G., additional, Umans, J. G., additional, Fallin, M. D., additional, Tellez-Plaza, M., additional, Baccarelli, A. A., additional, and Navas-Acien, A., additional

Published
2020
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23. Untargeted metabolomic profiles of air pollution exposure during pregnancy and postpartum depression risk: a pilot study

Author

Niedzwiecki, M. M., primary, Joshi, A., additional, Just, A. C., additional, Kloog, I., additional, Colicino, E., additional, Solano González, M., additional, Martínez-Medina, S., additional, Schnaas, L., additional, Téllez-Rojo, M. M., additional, Wright, R. J., additional, Wright, R. O., additional, and Petrick, L., additional

Published
2020
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24. Meta-analysis of epigenome-wide association studies of cognitive abilities

Author

Marioni, RE, McRae, AF, Bressler, J, Colicino, E, Hannon, E, Li, S, Prada, D, Smith, JA, Trevisi, L, Tsai, P-C, Vojinovic, D, Simino, J, Levy, D, Liu, C, Mendelson, M, Satizabal, CL, Yang, Q, Jhun, MA, Kardia, SLR, Zhao, W, Bandinelli, S, Ferrucci, L, Hernandez, DG, Singleton, AB, Harris, SE, Starr, JM, Kiel, DP, McLean, RR, Just, AC, Schwartz, J, Spiro, A, Vokonas, P, Amin, N, Ikram, MA, Uitterlinden, AG, Van Meurs, JBJ, Spector, TD, Steves, C, Baccarelli, AA, Bell, JT, Van Duijn, CM, Fornage, M, Hsu, Y-H, Mill, J, Mosley, TH, Seshadri, S, Deary, IJ, Epidemiology, Gastroenterology & Hepatology, Neurology, Radiology & Nuclear Medicine, and Internal Medicine

Subjects
Adult, Aged, 80 and over, Male, Genomics, DNA Methylation, Middle Aged, Epigenesis, Genetic, Cohort Studies, Cognition, Humans, CpG Islands, Female, Immediate Communication, Aged, Genome-Wide Association Study
Abstract

Cognitive functions are important correlates of health outcomes across the life-course. Individual differences in cognitive functions are partly heritable. Epigenetic modifications, such as DNA methylation, are susceptible to both genetic and environmental factors and may provide insights into individual differences in cognitive functions. Epigenome-wide meta-analyses for blood-based DNA methylation levels at ~420,000 CpG sites were performed for seven measures of cognitive functioning using data from 11 cohorts. CpGs that passed a Bonferroni correction, adjusting for the number of CpGs and cognitive tests, were assessed for: longitudinal change; being under genetic control (methylation QTLs); and associations with brain health (structural MRI), brain methylation and Alzheimer's disease pathology. Across the seven measures of cognitive functioning (meta-analysis n range: 2557-6809), there were epigenome-wide significant (P

Published
2018
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25. Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Author

Fiorito, G., Mccrory, C., Robinson, O., Carmeli, C., Rosales, C. O., Zhang, Y., Colicino, E., Dugue, P. -A., Artaud, F., Mckay, G. J., Jeong, A., Mishra, P. P., Nost, T. H., Krogh, V., Panico, S., Sacerdote, C., Tumino, R., Palli, D., Matullo, G., Guarrera, S., Gandini, M., Bochud, M., Dermitzakis, E., Muka, T., Schwartz, J., Vokonas, P. S., Just, A., Hodge, A. M., Giles, G. G., Southey, M. C., Hurme, M. A., Young, I., Mcknight, A. J., Kunze, S., Waldenberger, M., Peters, A., Schwettmann, L., Lund, E., Baccarelli, A., Milne, R. L., Kenny, R. A., Elbaz, A., Brenner, H., Kee, F., Voortman, T., Probst-Hensch, N., Lehtimaki, T., Elliot, P., Stringhini, S., Vineis, P., Polidoro, S., Alberts, J., Alenius, H., Avendano, M., Baltar, V., Bartley, M., Barros, H., Bellone, M., Berger, E., Blane, D., Candiani, G., Carra, L., Castagne, R., Chadeau-Hyam, M., Cima, S., Clavel-Chapelon, F., Costa, G., Courtin, E., Delpierre, C., D'Errico, A., Dermitzakis, M., Elovainio, M., Elliott, P., Fagherazzi, G., Fraga, S., Gares, V., Gerbouin-Rerolle, P., Giles, G., Goldberg, M., Greco, D., Guessous, I., Haba-Rubio, J., Heinzer, R., Hodge, A., Joost, S., Karimi, M., Kelly-Irving, M., Kahonen, M., Karisola, P., Khenissi, L., Kivimaki, M., Laine, J., Lang, T., Laurent, A., Layte, R., Lepage, B., Lorsch, D., Macguire, F., Machell, G., Mackenbach, J., Marmot, M., de Mestral, C., Miller, C., Milne, R., Muennig, P., Nusselder, W., Petrovic, D., Pilapil, L., Preisig, M., Pulkki-Raback, L., Raitakari, O., Ribeiro, A. I., Ricceri, F., Recalcati, P., Reinhard, E., Valverde, J. R., Saba, S., Santegoets, F., Satolli, R., Simmons, T., Severi, G., Shipley, M. J., Tabak, A., Terhi, V., Tieulent, J., Vaccarella, S., Vigna-Taglianti, F., Vollenweider, P., Vuilleumier, N., Zins, M., Medical Research Council (MRC), Commission of the European Communities, BIOS Consortium, Lifepath consortium, Epidemiology, Dermitzakis, Emmanouil, and Stringhini, Silvia

Subjects
Male, Aging, Geriatrics & Gerontology, Disease, epigenetic clocks, Bioinformatics, 0601 Biochemistry and Cell Biology, DISEASE, Epigenesis, Genetic, Cohort Studies, 0302 clinical medicine, Risk Factors, DNA METHYLATION, media_common, 0303 health sciences, education, Lifepath consortium, VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801, CARDIOVASCULAR RISK, Aged, Aging/genetics, Aging/psychology, DNA Methylation, Educational Status, Female, Humans, Life Style, Mutation, Social Class, biological aging, socioeconomic position, Longevity, ASSOCIATION, Biological aging, Education, Epigenetic clocks, Socioeconomic position, 3. Good health, WIDE METHYLATION, Aging/genetics/psychology, DNA methylation, Biomarker (medicine), HEALTH, BIOS Consortium, Life Sciences & Biomedicine, Research Paper, Cohort study, VDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Medisinsk genetikk: 714, media_common.quotation_subject, CANCER-RISK, 610 Medicine & health, VDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710::Medical genetics: 714, Biology, PERIPHERAL-BLOOD, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genetic, 360 Social problems & social services, 1112 Oncology and Carcinogenesis, Epigenetics, ddc:613, 030304 developmental biology, Science & Technology, Mechanism (biology), MUTATIONS, dNaM, Socioeconomic Position, Biological Aging, Epigenetic Clocks, Cell Biology, 0606 Physiology, DRIFT, VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801, 030217 neurology & neurosurgery, Epigenesis
Abstract

Source at https://doi.org/10.18632/aging.101900. Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Published
2019
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26. Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis.

Author

Kee F., Rosales C.O., Zhang Y., Colicino E., Dugue P.-A., Artaud F., McKay G.J., Jeong A., Mishra P.P., Elbaz A., Brenner H., Carmeli C., Voortman T., Probst-Hensch N., Lehtimaki T., Elliot P., Stringhini S., Vineis P., Polidoro S., Fiorito G., McCrory C., Robinson O., Nost T.H., Krogh V., Panico S., Sacerdote C., Tumino R., Palli D., Matullo G., Guarrera S., Gandini M., Bochud M., Dermitzakis E., Muka T., Schwartz J., Vokonas P.S., Just A., Hodge A.M., Giles G.G., Southey M.C., Hurme M.A., Young I., McKnight A.J., Kunze S., Waldenberger M., Peters A., Schwettmann L., Lund E., Baccarelli A., Milne R.L., Kenny R.A., Kee F., Rosales C.O., Zhang Y., Colicino E., Dugue P.-A., Artaud F., McKay G.J., Jeong A., Mishra P.P., Elbaz A., Brenner H., Carmeli C., Voortman T., Probst-Hensch N., Lehtimaki T., Elliot P., Stringhini S., Vineis P., Polidoro S., Fiorito G., McCrory C., Robinson O., Nost T.H., Krogh V., Panico S., Sacerdote C., Tumino R., Palli D., Matullo G., Guarrera S., Gandini M., Bochud M., Dermitzakis E., Muka T., Schwartz J., Vokonas P.S., Just A., Hodge A.M., Giles G.G., Southey M.C., Hurme M.A., Young I., McKnight A.J., Kunze S., Waldenberger M., Peters A., Schwettmann L., Lund E., Baccarelli A., Milne R.L., and Kenny R.A.

Abstract

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Published
2019

27. Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Author

Fiorito, G, McCrory, C, Robinson, O, Carmeli, C, Rosales, CO, Zhang, Y, Colicino, E, Dugue, P-A, Artaud, F, Mckay, GJ, Jeong, A, Mishra, PP, Nost, TH, Krogh, V, Panico, S, Sacerdote, C, Tumino, R, Palli, D, Matullo, G, Guarrera, S, Gandini, M, Bochud, M, Dermitzakis, E, Muka, T, Schwartz, J, Vokonas, PS, Just, A, Hodge, AM, Giles, GG, Southey, MC, Hurme, MA, Young, I, McKnight, AJ, Kunze, S, Waldenberger, M, Peters, A, Schwettmann, L, Lund, E, Baccarelli, A, Milne, RL, Kenny, RA, Elbaz, A, Brenner, H, Kee, F, Voortman, T, Probst-Hensch, N, Lehtimaki, T, Elliot, P, Stringhini, S, Vineis, P, Polidoro, S, Alberts, J, Alenius, H, Avendano, M, Baltar, V, Bartley, M, Barros, H, Bellone, M, Berger, E, Blane, D, Candiani, G, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Clavel-Chapelon, F, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Manolis, Dermitzakis, Elovainio, M, Elliott, P, Fagherazzi, G, Fraga, S, Gares, V, Gerbouin-Rerolle, P, Giles, G, Goldberg, M, Greco, D, Guessous, I, Haba-Rubio, J, Heinzer, R, Hodge, A, Joost, S, Karimi, M, Kelly-Irving, M, Kahonen, M, Karisola, P, Khenissi, L, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Layte, R, Lepage, B, Lorsch, D, MacGuire, F, Machell, G, Mackenbach, J, Marmot, M, de Mestral, C, Miller, C, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Lourdes, Pilapil, Preisig, M, Pulkki-Raback, L, Raitakari, O, Ribeiro, AI, Ricceri, F, Recalcati, P, Reinhard, E, Valverde, JR, Saba, S, Santegoets, F, Satolli, R, Simmons, T, Severi, G, Shipley, MJ, Tabak, A, Terhi, V, Tieulent, J, Vaccarella, S, Vigna-Taglianti, F, Vollenweider, P, Vuilleumier, N, Zins, M, Fiorito, G, McCrory, C, Robinson, O, Carmeli, C, Rosales, CO, Zhang, Y, Colicino, E, Dugue, P-A, Artaud, F, Mckay, GJ, Jeong, A, Mishra, PP, Nost, TH, Krogh, V, Panico, S, Sacerdote, C, Tumino, R, Palli, D, Matullo, G, Guarrera, S, Gandini, M, Bochud, M, Dermitzakis, E, Muka, T, Schwartz, J, Vokonas, PS, Just, A, Hodge, AM, Giles, GG, Southey, MC, Hurme, MA, Young, I, McKnight, AJ, Kunze, S, Waldenberger, M, Peters, A, Schwettmann, L, Lund, E, Baccarelli, A, Milne, RL, Kenny, RA, Elbaz, A, Brenner, H, Kee, F, Voortman, T, Probst-Hensch, N, Lehtimaki, T, Elliot, P, Stringhini, S, Vineis, P, Polidoro, S, Alberts, J, Alenius, H, Avendano, M, Baltar, V, Bartley, M, Barros, H, Bellone, M, Berger, E, Blane, D, Candiani, G, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Clavel-Chapelon, F, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Manolis, Dermitzakis, Elovainio, M, Elliott, P, Fagherazzi, G, Fraga, S, Gares, V, Gerbouin-Rerolle, P, Giles, G, Goldberg, M, Greco, D, Guessous, I, Haba-Rubio, J, Heinzer, R, Hodge, A, Joost, S, Karimi, M, Kelly-Irving, M, Kahonen, M, Karisola, P, Khenissi, L, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Layte, R, Lepage, B, Lorsch, D, MacGuire, F, Machell, G, Mackenbach, J, Marmot, M, de Mestral, C, Miller, C, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Lourdes, Pilapil, Preisig, M, Pulkki-Raback, L, Raitakari, O, Ribeiro, AI, Ricceri, F, Recalcati, P, Reinhard, E, Valverde, JR, Saba, S, Santegoets, F, Satolli, R, Simmons, T, Severi, G, Shipley, MJ, Tabak, A, Terhi, V, Tieulent, J, Vaccarella, S, Vigna-Taglianti, F, Vollenweider, P, Vuilleumier, N, and Zins, M

Abstract

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Published
2019

31. Association of methylation signals with incident coronary heart disease in an epigenome-wide assessment of circulating tumor necrosis factor α

Author

Aslibekyan, S. (Stella), Agha, G. (Golareh), Colicino, E. (Elena), Do, A. N. (Anh N.), Lahti, J. (Jari), Ligthart, S. (Symen), Marioni, R. E. (Riccardo E.), Marzi, C. (Carola), Mendelson, M. M. (Michael M.), Tanaka, T. (Toshiko), Wielscher, M. (Matthias), Absher, D. M. (Devin M.), Ferrucci, L. (Luigi), Franco, O. H. (Oscar H.), Gieger, C. (Christian), Grallert, H. (Harald), Hernandez, D. (Dena), Huan, T. (Tianxiao), Iurato, S. (Stella), Joehanes, R. (Roby), Just, A. C. (Allan C.), Kunze, S. (Sonja), Lin, H. (Honghuang), Liu, C. (Chunyu), Meigs, J. B. (James B.), van Meurs, J. B. (Joyce B.J.), Moore, A. Z. (Ann Zenobia), Peters, A. (Annette), Prokisch, H. (Holger), Räikkönen, K. (Katri), Rathmann, W. (Wolfgang), Roden, M. (Michael), Schramm, K. (Katharina), Schwartz, J. D. (Joel D.), Starr, J. M. (John M.), Uitterlinden, A. G. (André G.), Vokonas, P. (Pantel), Waldenberger, M. (Melanie), Yao, C. (Chen), Zhi, D. (Degui), Baccarelli, A. A. (Andrea A.), Bandinelli, S. (Stefania), Deary, I. J. (Ian J.), Dehghan, A. (Abbas), Eriksson, J. (Johan), Herder, C. (Christian), Järvelin, M.-R. (Marjo-Riitta), Levy, D. (Daniel), Arnett, D. K. (Donna K.), Aslibekyan, S. (Stella), Agha, G. (Golareh), Colicino, E. (Elena), Do, A. N. (Anh N.), Lahti, J. (Jari), Ligthart, S. (Symen), Marioni, R. E. (Riccardo E.), Marzi, C. (Carola), Mendelson, M. M. (Michael M.), Tanaka, T. (Toshiko), Wielscher, M. (Matthias), Absher, D. M. (Devin M.), Ferrucci, L. (Luigi), Franco, O. H. (Oscar H.), Gieger, C. (Christian), Grallert, H. (Harald), Hernandez, D. (Dena), Huan, T. (Tianxiao), Iurato, S. (Stella), Joehanes, R. (Roby), Just, A. C. (Allan C.), Kunze, S. (Sonja), Lin, H. (Honghuang), Liu, C. (Chunyu), Meigs, J. B. (James B.), van Meurs, J. B. (Joyce B.J.), Moore, A. Z. (Ann Zenobia), Peters, A. (Annette), Prokisch, H. (Holger), Räikkönen, K. (Katri), Rathmann, W. (Wolfgang), Roden, M. (Michael), Schramm, K. (Katharina), Schwartz, J. D. (Joel D.), Starr, J. M. (John M.), Uitterlinden, A. G. (André G.), Vokonas, P. (Pantel), Waldenberger, M. (Melanie), Yao, C. (Chen), Zhi, D. (Degui), Baccarelli, A. A. (Andrea A.), Bandinelli, S. (Stefania), Deary, I. J. (Ian J.), Dehghan, A. (Abbas), Eriksson, J. (Johan), Herder, C. (Christian), Järvelin, M.-R. (Marjo-Riitta), Levy, D. (Daniel), and Arnett, D. K. (Donna K.)

Abstract

Importance: Tumor necrosis factor α (TNF-α) is a proinflammatory cytokine with manifold consequences for mammalian pathophysiology, including cardiovascular disease. A deeper understanding of TNF-α biology may enhance treatment precision. Objective: To conduct an epigenome-wide analysis of blood-derived DNA methylation and TNF-α levels and to assess the clinical relevance of findings. Design, Setting, and Participants: This meta-analysis assessed epigenome-wide associations in circulating TNF-α concentrations from 5 cohort studies and 1 interventional trial, with replication in 3 additional cohort studies. Follow-up analyses investigated associations of identified methylation loci with gene expression and incident coronary heart disease; this meta-analysis included 11 461 participants who experienced 1895 coronary events. Exposures: Circulating TNF-α concentration. Main Outcomes and Measures: DNA methylation at approximately 450 000 loci, neighboring DNA sequence variation, gene expression, and incident coronary heart disease. Results: The discovery cohort included 4794 participants, and the replication study included 816 participants (overall mean [SD] age, 60.7 [8.5] years). In the discovery stage, circulating TNF-α levels were associated with methylation of 7 cytosine-phosphate-guanine (CpG) sites, 3 of which were located in or near DTX3L-PARP9 at cg00959259 (β [SE] = −0.01 [0.003]; P = 7.36×10⁻⁸), cg08122652 (β [SE] = −0.008 [0.002]; P = 2.24×10⁻⁷), and cg22930808(β [SE] = −0.01 [0.002]; P = 6.92×10⁻⁸); NLRC5 at cg16411857 (β [SE] = −0.01 [0.002]; P = 2.14×10⁻¹³) and cg07839457 (β [SE] = −0.02 [0.003]; P = 6.31×10⁻¹⁰); or ABO, at cg13683939 (β [SE] = 0.04 [0.008]; P = 1.42×10⁻⁷) and cg24267699 (β [SE] = −0.009 [0.002]; P = 1.67 × 10⁻⁷), after accounting for multiple testing. Of these, negative associations between TNF-α concentration and methylation of 2 loci in NLRC5 and 1 in DTX3L-14 PARP9 were replicated. Replicated TNF-α–linked CpG sites were associ

Published
2018

32. Causal analysis of the relation between epigenetic pathways and air pollution based on the joint use of mixed latent Markov models and the propensity score method

Author

PENNONI, FULVIA, Bartolucci, F, Baccarelli, A, Colicino, E, VITTADINI, GIORGIO, Pennoni, F, Bartolucci, F, Baccarelli, A, Colicino, E, and Vittadini, G

Subjects
Expectation-Maximization algorithm, Missing data, Multivariate binary data, State space model
Abstract

We propose a novel model for longitudinal studies based on random effects to capture unobserved heterogeneity. We propose an extension of the latent Markov Rasch model, which is specially tailored to deal with confounders and missing data on the primary response. The model is based on both time-fixed and time-varying latent variables having a discrete distribution. In particular, time-varying latent variables are assumed to follow a Markov chain. The model estimation is performed by the maximum likelihood procedure through the EM algorithm. This estimation based on a set of weights associated to each subject to balance the composition of different subsamples corresponding to different treatments/exposures in a perspective of causal inference. These weights are computed by the propensity score method. The model is applied to the analysis of epidemiological and molecular data from the Normative Aging Study (NAS), a longitudinal cohort of older individuals to identify key epigenetic pathways in humans that reflect air pollution exposure and predict worse cognitive decline. The participants are assigned estimates of black carbon exposure, a measure of diesel particles, since 2010; have epigenome-wide Illumina Infinium 450K Methylation BeadChip data for methylation at ~486,000 DNA sites measured at two different time points; and are administered cognitive testing assessing multiple functional domains every 3-5 years. We will consider DNA methylation as a possible intermediate variable mediating the effects of air pollution on cognitive aging. Epigenetic profiles may represent cumulative biomarkers of air pollution exposures and aid in the early diagnosis and prevention of air pollution-related diseases.

Published
2015

33. DNA methylation signatures in the Normative Aging Study:Epigenome-wide association analyses of air pollution exposure,biological aging, metabolism, and lung function decline

Author

Carmona, JJ, Barfield, RT, Just, AC, Colicino, E, Testa, P, Mehta, AJ, Peng, C, Chen, J, Schwartz, J, Lin, X, Baccarelli, A., PAFUNDI, PIA CLARA, Carmona, J, Barfield, R, Just, A, Colicino, E, Testa, P, Pafundi, P, Mehta, A, Peng, C, Chen, J, Schwartz, J, Lin, X, and Baccarelli, A

Subjects
SECS-S/01 - STATISTICA, aging, pollution, GWAS, R Cran, MED/01 - STATISTICA MEDICA
Abstract

Epigenetic modifications may serve as indicators of past toxic exposures and predict future disease risk. We propose to discover and validate novel methylomic biomarkers of air pollution exposure and related phenotypic outcomes of interest. Our understanding about the complex interplay of epigene-environment interactions remains rudimentary, and it often based on high-exposure animal models. This array-based methylomics study employs the Normative Aging Study (NAS) cohort, followed for over 40+ years, to identify key epigenetic pathways in humans; the Illumina HumanMethylation450 BeadChip was used to query the methylation status of ~480K CpG sites across the human genome. These epigenetic marks may aid in the early diagnosis and prevention of air pollution-related diseases and the study of basic biological processes in vivo.

Published
2013

34. Epigenetic Signatures of Cigarette Smoking

Author

Joehanes, R. (Roby), Just, A.C. (Allan C.), Marioni, R.E. (Riccardo), Pilling, L.C. (Luke), Reynolds, L.M. (Lindsay), Mandaviya, P.R. (Pooja R.), Guan, W. (Weihua), Xu, T. (Tao), Elks, C.E. (Cathy), Aslibekyan, S. (Stella), Moreno-Macías, H. (Hortensia), Smith, J.A. (Jennifer A), Brody, J.A. (Jennifer A.), Dhingra, R. (Radhika), Yousefi, P. (Paul), Pankow, J.S. (James), Kunze, S. (Sonja), Shah, S.H. (Sonia H.), McRae, A.F. (Allan F.), Lohman, K. (Kurt), Sha, J. (Jin), Absher, D. (Devin), Ferrucci, L. (Luigi), Zhao, W. (Wei), Demerath, E.W. (Ellen), Bressler, J. (Jan), Grove, M.L. (Megan), Huan, T. (Tianxiao), Liu, C. (Chunyu), Mendelson, M.M. (Michael M.), Yao, C. (Chen), Kiel, D.P. (Douglas P.), Peters, A. (Annette), Wang-Sattler, R. (Rui), Visscher, P.M. (Peter), Wray, N.R. (Naomi), Starr, J.M. (John), Ding, J. (Jingzhong), Rodriguez, C.J. (Carlos J.), Wareham, N.J. (Nick), Irvin, M.R. (Marguerite R.), Zhi, D. (Degui), Barrdahl, M. (Myrto), Vineis, P. (Paolo), Ambatipudi, S. (Srikant), Uitterlinden, A.G. (André), Hofman, A. (Albert), Schwartz, J. (Joel), Colicino, E. (Elena), Hou, L. (Lifang), Vokonas, P.S. (Pantel S.), Hernandez, D.G. (Dena), Singleton, A. (Andrew), Bandinelli, S. (Stefania), Turner, S.T. (Stephen), Ware, E.B. (Erin B.), Smith, A.K. (Alicia K.), Klengel, T. (Torsten), Binder, E.B. (Elisabeth B.), Psaty, B.M. (Bruce), Taylor, K.D. (Kent), Gharib, S.A. (Sina), Swenson, B.R. (Brenton R.), Liang, L. (Liming), Demeo, D.L. (Dawn), O'Connor, G.T. (George), Herceg, Z. (Zdenko), Ressler, K.J. (Kerry J.), Conneely, K.N. (Karen N.), Sotoodehnia, N. (Nona), Kardia, S.L.R. (Sharon L. R.), Melzer, D. (David), Baccarelli, A.A. (Andrea), Meurs, J.B.J. (Joyce) van, Romieu, I. (Isabelle), Arnett, D.K. (Donna), Ong, K.K. (Ken K.), Liu, Y. (YongMei), Waldenberger, M. (Melanie), Deary, I.J. (Ian), Fornage, M. (Myriam), Levy, D. (Daniel), London, S.J. (Stephanie J.), Joehanes, R. (Roby), Just, A.C. (Allan C.), Marioni, R.E. (Riccardo), Pilling, L.C. (Luke), Reynolds, L.M. (Lindsay), Mandaviya, P.R. (Pooja R.), Guan, W. (Weihua), Xu, T. (Tao), Elks, C.E. (Cathy), Aslibekyan, S. (Stella), Moreno-Macías, H. (Hortensia), Smith, J.A. (Jennifer A), Brody, J.A. (Jennifer A.), Dhingra, R. (Radhika), Yousefi, P. (Paul), Pankow, J.S. (James), Kunze, S. (Sonja), Shah, S.H. (Sonia H.), McRae, A.F. (Allan F.), Lohman, K. (Kurt), Sha, J. (Jin), Absher, D. (Devin), Ferrucci, L. (Luigi), Zhao, W. (Wei), Demerath, E.W. (Ellen), Bressler, J. (Jan), Grove, M.L. (Megan), Huan, T. (Tianxiao), Liu, C. (Chunyu), Mendelson, M.M. (Michael M.), Yao, C. (Chen), Kiel, D.P. (Douglas P.), Peters, A. (Annette), Wang-Sattler, R. (Rui), Visscher, P.M. (Peter), Wray, N.R. (Naomi), Starr, J.M. (John), Ding, J. (Jingzhong), Rodriguez, C.J. (Carlos J.), Wareham, N.J. (Nick), Irvin, M.R. (Marguerite R.), Zhi, D. (Degui), Barrdahl, M. (Myrto), Vineis, P. (Paolo), Ambatipudi, S. (Srikant), Uitterlinden, A.G. (André), Hofman, A. (Albert), Schwartz, J. (Joel), Colicino, E. (Elena), Hou, L. (Lifang), Vokonas, P.S. (Pantel S.), Hernandez, D.G. (Dena), Singleton, A. (Andrew), Bandinelli, S. (Stefania), Turner, S.T. (Stephen), Ware, E.B. (Erin B.), Smith, A.K. (Alicia K.), Klengel, T. (Torsten), Binder, E.B. (Elisabeth B.), Psaty, B.M. (Bruce), Taylor, K.D. (Kent), Gharib, S.A. (Sina), Swenson, B.R. (Brenton R.), Liang, L. (Liming), Demeo, D.L. (Dawn), O'Connor, G.T. (George), Herceg, Z. (Zdenko), Ressler, K.J. (Kerry J.), Conneely, K.N. (Karen N.), Sotoodehnia, N. (Nona), Kardia, S.L.R. (Sharon L. R.), Melzer, D. (David), Baccarelli, A.A. (Andrea), Meurs, J.B.J. (Joyce) van, Romieu, I. (Isabelle), Arnett, D.K. (Donna), Ong, K.K. (Ken K.), Liu, Y. (YongMei), Waldenberger, M. (Melanie), Deary, I.J. (Ian), Fornage, M. (Myriam), Levy, D. (Daniel), and London, S.J. (Stephanie J.)

Abstract

Background-DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. Methods and Results-To comprehensively determine the association between cigarette smoki

Published
2016
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35. DNA methylation-based measures of biological age: Meta-analysis predicting time to death

Author

Chen, B.H. (Brian), Marioni, R.E. (Riccardo), Colicino, E. (Elena), Peters, M.J. (Marjolein), Ward-Caviness, C.K. (Cavin K.), Tsai, P.-C. (Pei-Chien), Roetker, N.S. (Nicholas S.), Just, A.C. (Allan C.), Demerath, E.W. (Ellen), Guan, W. (Weihua), Bressler, J. (Jan), Fornage, M. (Myriam), Studenski, S. (Stephanie), Vandiver, A.R. (Amy R.), Moore, A.Z. (Ann Zenobia), Tanaka, T. (Toshiko), Kiel, D.P. (Douglas P.), Liang, L. (Liming), Vokonas, P. (Pantel), Schwartz, J. (Joel), Lunetta, K.L. (Kathryn), Murabito, J. (Joanne), Bandinelli, S. (Stefania), Hernandez, D.G. (Dena), Melzer, D. (David), Nalls, M.A. (Michael), Pilling, L.C. (Luke), Price, T.R. (Timothy R.), Singleton, A. (Andrew), Gieger, C. (Christian), Holle, R. (Rolf), Kretschmer, A. (Anja), Kronenberg, F. (Florian), Kunze, S. (Sonja), Linseisen, J. (Jakob), Meisinger, C. (Christine), Rathmann, W. (Wolfgang), Waldenberger, M. (Melanie), Visscher, P.M. (Peter), Shah, S. (Sonia), Wray, N.R. (Naomi), McRae, A.F. (Allan F.), Franco, O.H. (Oscar), Hofman, A. (Albert), Uitterlinden, A.G. (André), Absher, D. (Devin), Assimes, T.L. (Themistocles), Levine, M.E. (Morgan E.), Lu, A.T. (Ake T.), Tsao, P.S. (Philip S.), Hou, L. (Lifang), Manson, J.E. (Joann), Carty, C. (Cara), LaCroix, A.Z. (Andrea Z.), Reiner, A. (Alexander), Spector, T.D. (Timothy), Feinberg, A.P. (Andrew P.), Levy, D. (Daniel), Baccarelli, A.A. (Andrea), Meurs, J. (Joyce van), Bell, J.T. (Jordana), Peters, A. (Annette), Deary, I.J. (Ian), Pankow, J.S. (James), Ferrucci, L. (Luigi), Horvath, S. (Steve), Chen, B.H. (Brian), Marioni, R.E. (Riccardo), Colicino, E. (Elena), Peters, M.J. (Marjolein), Ward-Caviness, C.K. (Cavin K.), Tsai, P.-C. (Pei-Chien), Roetker, N.S. (Nicholas S.), Just, A.C. (Allan C.), Demerath, E.W. (Ellen), Guan, W. (Weihua), Bressler, J. (Jan), Fornage, M. (Myriam), Studenski, S. (Stephanie), Vandiver, A.R. (Amy R.), Moore, A.Z. (Ann Zenobia), Tanaka, T. (Toshiko), Kiel, D.P. (Douglas P.), Liang, L. (Liming), Vokonas, P. (Pantel), Schwartz, J. (Joel), Lunetta, K.L. (Kathryn), Murabito, J. (Joanne), Bandinelli, S. (Stefania), Hernandez, D.G. (Dena), Melzer, D. (David), Nalls, M.A. (Michael), Pilling, L.C. (Luke), Price, T.R. (Timothy R.), Singleton, A. (Andrew), Gieger, C. (Christian), Holle, R. (Rolf), Kretschmer, A. (Anja), Kronenberg, F. (Florian), Kunze, S. (Sonja), Linseisen, J. (Jakob), Meisinger, C. (Christine), Rathmann, W. (Wolfgang), Waldenberger, M. (Melanie), Visscher, P.M. (Peter), Shah, S. (Sonia), Wray, N.R. (Naomi), McRae, A.F. (Allan F.), Franco, O.H. (Oscar), Hofman, A. (Albert), Uitterlinden, A.G. (André), Absher, D. (Devin), Assimes, T.L. (Themistocles), Levine, M.E. (Morgan E.), Lu, A.T. (Ake T.), Tsao, P.S. (Philip S.), Hou, L. (Lifang), Manson, J.E. (Joann), Carty, C. (Cara), LaCroix, A.Z. (Andrea Z.), Reiner, A. (Alexander), Spector, T.D. (Timothy), Feinberg, A.P. (Andrew P.), Levy, D. (Daniel), Baccarelli, A.A. (Andrea), Meurs, J. (Joyce van), Bell, J.T. (Jordana), Peters, A. (Annette), Deary, I.J. (Ian), Pankow, J.S. (James), Ferrucci, L. (Luigi), and Horvath, S. (Steve)

Abstract

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p ≤ 8.2 x 10-9), independent of chronological age, even after adjusting for additional risk factors (p < 5.4 x 10-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p≤ 7.5 x 10-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

Published
2016
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36. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

Author

Ligthart, S. (Symen), Marzi, C. (Carola), Aslibekyan, S. (Stella), Mendelson, M.M. (Michael M.), Conneely, K.N. (Karen N.), Tanaka, T. (Toshiko), Colicino, E. (Elena), Waite, L. (Lindsay), Joehanes, R. (Roby), Guan, W. (Weihua), Brody, J.A. (Jennifer A.), Elks, C.E. (Cathy), Marioni, R.E. (Riccardo), Jhun, M.A. (Min A.), Agha, G. (Golareh), Bressler, J. (Jan), Ward-Caviness, C.K. (Cavin K.), Chen, B.H. (Brian), Huan, T. (Tianxiao), Bakulski, K.M. (Kelly M.), Salfati, E. (Elias), Fiorito, G. (Giovanni), Wahl, S. (Simone), Schramm, K. (Katharina), Sha, J. (Jin), Hernandez, D.G. (Dena), Just, A.C. (Allan C.), Smith, J.A. (Jennifer A), Sotoodehnia, N. (Nona), Pilling, L.C. (Luke), Pankow, J.S. (James), Tsao, P.S. (Phil S.), Liu, C. (Chunyu), Zhao, W. (Wei), Guarrera, S. (Simonetta), Michopoulos, V.J. (Vasiliki J.), Smith, A.K. (Alicia K.), Peters, M.J. (Marjolein), Melzer, D. (David), Vokonas, P. (Pantel), Fornage, M. (Myriam), Prokisch, H. (Holger), Bis, J.C. (Joshua), Chu, A.Y. (Audrey), Herder, C. (Christian), Grallert, H. (Harald), Yao, C. (Chen), Shah, S. (Sonia), McRae, A.F. (Allan F.), Lin, H., Horvath, S. (Steve), Fallin, D. (Daniele), Hofman, A. (Albert), Wareham, N.J. (Nick), Wiggins, K.L. (Kerri), Feinberg, A.P. (Andrew P.), Starr, J.M. (John), Visscher, P.M. (Peter), Murabito, J. (Joanne), Kardia, S.L.R. (Sharon L.R.), Absher, D. (Devin), Binder, E.B. (Elisabeth), Singleton, A. (Andrew), Bandinelli, S. (Stefania), Peters, A. (Annette), Waldenberger, M. (Melanie), Matullo, G., Schwartz, J.D. (Joel D.), Demerath, E.W. (Ellen), Uitterlinden, A.G. (André), Meurs, J.B.J. (Joyce B.J.), Franco, O.H. (Oscar), Chen, Y.D. (Y.), Levy, D. (Daniel), Turner, S.T. (Stephen), Deary, I.J. (Ian), Ressler, K.J. (Kerry), Dupuis, J. (Josée), Ferrucci, L. (Luigi), Ong, K.K. (Ken K.), Assimes, T.L. (Themistocles), Boerwinkle, E.A. (Eric), Koenig, W. (Wolfgang), Arnett, D.K. (Donna), Baccarelli, A.A. (Andrea), Benjamin, E.J. (Emelia), Dehghan, A. (Abbas), Ligthart, S. (Symen), Marzi, C. (Carola), Aslibekyan, S. (Stella), Mendelson, M.M. (Michael M.), Conneely, K.N. (Karen N.), Tanaka, T. (Toshiko), Colicino, E. (Elena), Waite, L. (Lindsay), Joehanes, R. (Roby), Guan, W. (Weihua), Brody, J.A. (Jennifer A.), Elks, C.E. (Cathy), Marioni, R.E. (Riccardo), Jhun, M.A. (Min A.), Agha, G. (Golareh), Bressler, J. (Jan), Ward-Caviness, C.K. (Cavin K.), Chen, B.H. (Brian), Huan, T. (Tianxiao), Bakulski, K.M. (Kelly M.), Salfati, E. (Elias), Fiorito, G. (Giovanni), Wahl, S. (Simone), Schramm, K. (Katharina), Sha, J. (Jin), Hernandez, D.G. (Dena), Just, A.C. (Allan C.), Smith, J.A. (Jennifer A), Sotoodehnia, N. (Nona), Pilling, L.C. (Luke), Pankow, J.S. (James), Tsao, P.S. (Phil S.), Liu, C. (Chunyu), Zhao, W. (Wei), Guarrera, S. (Simonetta), Michopoulos, V.J. (Vasiliki J.), Smith, A.K. (Alicia K.), Peters, M.J. (Marjolein), Melzer, D. (David), Vokonas, P. (Pantel), Fornage, M. (Myriam), Prokisch, H. (Holger), Bis, J.C. (Joshua), Chu, A.Y. (Audrey), Herder, C. (Christian), Grallert, H. (Harald), Yao, C. (Chen), Shah, S. (Sonia), McRae, A.F. (Allan F.), Lin, H., Horvath, S. (Steve), Fallin, D. (Daniele), Hofman, A. (Albert), Wareham, N.J. (Nick), Wiggins, K.L. (Kerri), Feinberg, A.P. (Andrew P.), Starr, J.M. (John), Visscher, P.M. (Peter), Murabito, J. (Joanne), Kardia, S.L.R. (Sharon L.R.), Absher, D. (Devin), Binder, E.B. (Elisabeth), Singleton, A. (Andrew), Bandinelli, S. (Stefania), Peters, A. (Annette), Waldenberger, M. (Melanie), Matullo, G., Schwartz, J.D. (Joel D.), Demerath, E.W. (Ellen), Uitterlinden, A.G. (André), Meurs, J.B.J. (Joyce B.J.), Franco, O.H. (Oscar), Chen, Y.D. (Y.), Levy, D. (Daniel), Turner, S.T. (Stephen), Deary, I.J. (Ian), Ressler, K.J. (Kerry), Dupuis, J. (Josée), Ferrucci, L. (Luigi), Ong, K.K. (Ken K.), Assimes, T.L. (Themistocles), Boerwinkle, E.A. (Eric), Koenig, W. (Wolfgang), Arnett, D.K. (Donna), Baccarelli, A.A. (Andrea), Benjamin, E.J. (Emelia), and Dehghan, A. (Abbas)

Abstract

Background: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is as

Published
2016
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37. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

Author

Ligthart, Symen, Marzi, C, Aslibekyan, S, Mendelson, MM, Conneely, KN, Tanaka, T, Colicino, E, Waite, LL, Joehanes, R, Guan, WH, Brody, JA, Elks, C, Marioni, R, Jhun, MA, Agha, G, Bressler, J, Ward-Caviness, CK, Chen, BH, Huan, TX, Bakulski, K, Salfati, EL, Wahl, S, Schramm, K, Sha, J, Hernandez, DG, Just, AC, Smith, JA, Sotoodehnia, N, Pilling, LC, Pankow, JS, Tsao, PS, Liu, CY, Zhao, W, Guarrera, S, Michopoulos, VJ, Smith, AK, Peters, Marjolein, Melzer, D, Vokonas, P, Fornage, M, Prokisch, H, Bis, JC, Chu, AY, Herder, Cindy, Grallert, H, Yao, C, Shah, S, Mcrae, AF, Lin, HH, Horvath, S, Fallin, D, Hofman, Bert, Wareham, NJ, Wiggins, KL, Feinberg, AP, Starr, JM, Visscher, PM, Murabito, JM, Kardia, SLR, Absher, DM, Binder, EB, Singleton, AB, Bandinelli, S, Peters, A, Waldenberger, M, Matullo, G, Schwartz, JD, Demerath, EW, Uitterlinden, André, van Meurs, Joyce, Franco Duran, OH, Chen, YDI, Levy, D, Turner, ST, Deary, IJ, Ressler, KJ, Dupuis, J, Ferrucci, L, Ong, KK, Assimes, TL, Boerwinkle, E, Koenig, W, Arnett, DK, Baccarelli, AA, Benjamin, EJ, Dehghan, Abbas, Ligthart, Symen, Marzi, C, Aslibekyan, S, Mendelson, MM, Conneely, KN, Tanaka, T, Colicino, E, Waite, LL, Joehanes, R, Guan, WH, Brody, JA, Elks, C, Marioni, R, Jhun, MA, Agha, G, Bressler, J, Ward-Caviness, CK, Chen, BH, Huan, TX, Bakulski, K, Salfati, EL, Wahl, S, Schramm, K, Sha, J, Hernandez, DG, Just, AC, Smith, JA, Sotoodehnia, N, Pilling, LC, Pankow, JS, Tsao, PS, Liu, CY, Zhao, W, Guarrera, S, Michopoulos, VJ, Smith, AK, Peters, Marjolein, Melzer, D, Vokonas, P, Fornage, M, Prokisch, H, Bis, JC, Chu, AY, Herder, Cindy, Grallert, H, Yao, C, Shah, S, Mcrae, AF, Lin, HH, Horvath, S, Fallin, D, Hofman, Bert, Wareham, NJ, Wiggins, KL, Feinberg, AP, Starr, JM, Visscher, PM, Murabito, JM, Kardia, SLR, Absher, DM, Binder, EB, Singleton, AB, Bandinelli, S, Peters, A, Waldenberger, M, Matullo, G, Schwartz, JD, Demerath, EW, Uitterlinden, André, van Meurs, Joyce, Franco Duran, OH, Chen, YDI, Levy, D, Turner, ST, Deary, IJ, Ressler, KJ, Dupuis, J, Ferrucci, L, Ong, KK, Assimes, TL, Boerwinkle, E, Koenig, W, Arnett, DK, Baccarelli, AA, Benjamin, EJ, and Dehghan, Abbas

Abstract

Background: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation. Results: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 x 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 x 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 x 10(-5)), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 x 10(-3)), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58x 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R-2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants. Conclusion: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

Published
2016

38. Causal analysis of the relation between epigenetic pathways and air pollution based on the joint use of mixed latent Markov models and the propensity score method

Author

Pennoni, F, Bartolucci, F, Baccarelli, A, Colicino, E, Vittadini, G, PENNONI, FULVIA, VITTADINI, GIORGIO, Pennoni, F, Bartolucci, F, Baccarelli, A, Colicino, E, Vittadini, G, PENNONI, FULVIA, and VITTADINI, GIORGIO

Abstract

We propose a novel model for longitudinal studies based on random effects to capture unobserved heterogeneity. We propose an extension of the latent Markov Rasch model, which is specially tailored to deal with confounders and missing data on the primary response. The model is based on both time-fixed and time-varying latent variables having a discrete distribution. In particular, time-varying latent variables are assumed to follow a Markov chain. The model estimation is performed by the maximum likelihood procedure through the EM algorithm. This estimation based on a set of weights associated to each subject to balance the composition of different subsamples corresponding to different treatments/exposures in a perspective of causal inference. These weights are computed by the propensity score method. The model is applied to the analysis of epidemiological and molecular data from the Normative Aging Study (NAS), a longitudinal cohort of older individuals to identify key epigenetic pathways in humans that reflect air pollution exposure and predict worse cognitive decline. The participants are assigned estimates of black carbon exposure, a measure of diesel particles, since 2010; have epigenome-wide Illumina Infinium 450K Methylation BeadChip data for methylation at ~486,000 DNA sites measured at two different time points; and are administered cognitive testing assessing multiple functional domains every 3-5 years. We will consider DNA methylation as a possible intermediate variable mediating the effects of air pollution on cognitive aging. Epigenetic profiles may represent cumulative biomarkers of air pollution exposures and aid in the early diagnosis and prevention of air pollution-related diseases.

Published
2015

39. DNA methylation signatures in the Normative Aging Study:Epigenome-wide association analyses of air pollution exposure,biological aging, metabolism, and lung function decline

Author

Carmona, J, Barfield, R, Just, A, Colicino, E, Testa, P, Pafundi, P, Mehta, A, Peng, C, Chen, J, Schwartz, J, Lin, X, Baccarelli, A, Carmona, JJ, Barfield, RT, Just, AC, Mehta, AJ, Baccarelli, A., PAFUNDI, PIA CLARA, Carmona, J, Barfield, R, Just, A, Colicino, E, Testa, P, Pafundi, P, Mehta, A, Peng, C, Chen, J, Schwartz, J, Lin, X, Baccarelli, A, Carmona, JJ, Barfield, RT, Just, AC, Mehta, AJ, Baccarelli, A., and PAFUNDI, PIA CLARA

Abstract

Epigenetic modifications may serve as indicators of past toxic exposures and predict future disease risk. We propose to discover and validate novel methylomic biomarkers of air pollution exposure and related phenotypic outcomes of interest. Our understanding about the complex interplay of epigene-environment interactions remains rudimentary, and it often based on high-exposure animal models. This array-based methylomics study employs the Normative Aging Study (NAS) cohort, followed for over 40+ years, to identify key epigenetic pathways in humans; the Illumina HumanMethylation450 BeadChip was used to query the methylation status of ~480K CpG sites across the human genome. These epigenetic marks may aid in the early diagnosis and prevention of air pollution-related diseases and the study of basic biological processes in vivo.

Published
2013

42. The role of outdoor and indoor air quality in the spread of SARS-CoV-2: Overview and recommendations by the research group on COVID-19 and particulate matter (RESCOP commission)

Author

Prisco Piscitelli, Alessandro Miani, Leonardo Setti, Gianluigi De Gennaro, Xavier Rodo, Begona Artinano, Elena Vara, Lisa Rancan, Javier Arias, Fabrizio Passarini, Pierluigi Barbieri, Alberto Pallavicini, Alessandro Parente, Edoardo Cavalieri D'Oro, Claudio De Maio, Francesco Saladino, Massimo Borelli, Elena Colicino, Luiz Marcos G. Gonçalves, Gianluca Di Tanna, Annamaria Colao, Giovanni S. Leonardi, Andrea Baccarelli, Francesca Dominici, John P.A. Ioannidis, Josè L. Domingo, Piscitelli P., Miani A., Setti L., De Gennaro G., Rodo X., Artinano B., Vara E., Rancan L., Arias J., Passarini F., Barbieri P., Pallavicini A., Parente A., D'Oro E.C., De Maio C., Saladino F., Borelli M., Colicino E., Goncalves L.M.G., Di Tanna G., Colao A., Leonardi G.S., Baccarelli A., Dominici F., Ioannidis J.P.A., Domingo J.L., Piscitelli, P., Miani, A., Setti, L., De Gennaro, G., Rodo, X., Artinano, B., Vara, E., Rancan, L., Arias, J., Passarini, F., Barbieri, P., Pallavicini, A., Parente, A., D'Oro, E. C., De Maio, C., Saladino, F., Borelli, M., Colicino, E., Goncalves, L. M. G., Di Tanna, G., Colao, A., Leonardi, G. S., Baccarelli, A., Dominici, F., Ioannidis, J. P. A., and Domingo, J. L.

Subjects
SARS-CoV-2, Air pollution, Indoor environment, COVID-19, Air quality, CO2 monitoring, Indoor environments, Ventilation, Biochemistry, Air Pollution, Indoor, Humans, RNA, Viral, Particulate Matter, Pandemics, General Environmental Science
Abstract

There are important questions surrounding the potential contribution of outdoor and indoor air quality in the transmission of SARS-CoV-2 and perpetuation of COVID-19 epidemic waves. Environmental health may be a critical component of COVID-19 prevention. The public health community and health agencies should consider the evolving evidence in their recommendations and statements, and work to issue occupational guidelines. Evidence coming from the current epidemiological and experimental research is expected to add knowledge about virus diffusion, COVID-19 severity in most polluted areas, inter-personal distance requirements and need for wearing face masks in indoor or outdoor environments. The COVID-19 pandemic has highlighted the need for maintaining particulate matter concentrations at low levels for multiple health-related reasons, which may also include the spread of SARS-CoV-2. Indoor environments represent even a more crucial challenge to cope with, as it is easier for the SARS-COV2 to spread, remain vital and infect other subjects in closed spaces in the presence of already infected asymptomatic or mildly symptomatic people. The potential merits of preventive measures, such as CO2 monitoring associated with natural or controlled mechanical ventilation and air purification, for schools, indoor public places (restaurants, offices, hotels, museums, theatres/cinemas etc.) and transportations need to be carefully considered. Hospital settings and nursing/retirement homes as well as emergency rooms, infectious diseases divisions and ambulances represent higher risk indoor environments and may require additional monitoring and specific decontamination strategies based on mechanical ventilation or air purification.

Published
2022

43. Identifying critical windows of susceptibility to perinatal lead exposure on child serum vaccine antibody levels.

Author

Colicino E, Feiler MO, Austin C, Rosa MJ, McRae N, Quataert SA, Thevenet-Morrison K, Téllez-Rojo MM, Lamadrid-Figueroa H, Tavarez ZQ, Shim YK, Arora M, Wright RO, and Jusko TA

Abstract

Background: Mounting evidence suggests that early-life lead exposure alters immune system functions, including T-cell dependent antibody responses to childhood immunizations. However, no studies have identified critical windows of susceptibility to lead exposure., Aim: To identify perinatal critical windows of lead exposure that are associated with antibody responses to anti-MMR (anti-measles, -mumps, and -rubella virus) and anti-DTP (anti-diphtheria, -tetanus, and -pertussis toxoids) vaccinations in Hispanic school-aged (mean± standard deviation: 4.8±0.6 years) children., Methods: Weekly lead exposure-from 16 weeks before to 14 weeks after birth-was measured in deciduous teeth from 271 children enrolled in the PROGRESS study. Serum levels of anti-MMR and anti-DTP antibodies were measured by a Luminex-multiplexed-microbead-array immunoassay. Time-varying associations between log2-transformed dentine lead concentrations and log2-transformed antibody levels were estimated by fitting distributed lag non-linear models., Results: A two-fold higher dentine lead concentration in the first three weeks postpartum was associated with an average -4.29% lower anti-tetanus level (95%confidence interval(CI):-8.22,-0.20). A perinatal (one week before to one week after birth) critical window of lead exposure demonstrated an average -3.44% (95%CI:-7.05;0.30) lower anti-diphtheria antibody level., Conclusions: Our study suggests that early-life lead exposure may contribute to immune dysfunction by reducing children's antibody responses to scheduled vaccinations., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2025
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44. Household Air Pollution Exposures Over Pregnancy and Maternal Blood Pressure Trajectories through 8 Years Postpartum: Evidence from the Ghana Randomized Air Pollution and Health Study (GRAPHS).

Author

Kaali S, Li M, Mujtaba MN, Colicino E, Awuni S, Wylie B, Osei M, Tsotetsi K, Yussif T, Chillrud S, Jack D, Asante KP, and Lee A

Abstract

Background: Household air pollution is a major contributor to cardiovascular disease burden in women in Sub-Saharan Africa. However, little is known about exposures during pregnancy or the effect of clean cooking interventions on postpartum blood pressure trajectories., Methods: The Ghana Randomized Air Pollution and Health Study (GRAPHS) randomized 1414 non-smoking women in the first and second trimesters to liquefied petroleum gas (LPG) or improved biomass stoves - vs control (traditional three-stone open fire). Personal exposure to carbon monoxide was measured at four prenatal timepoints and three times over the first postpartum year. Participants were prospectively followed with annual resting BP measurements at 2, 4, 5, 6, 7, and 8 years postpartum. We employed linear mixed effects models to determine effect of GRAPHS interventions on postpartum BP, and to examine associations between prenatal and postnatal CO and postpartum BP., Results: LPG intervention was associated with 3.54mmHg (95% CI -5.55, -1.53) lower change in systolic BP from enrolment through 8 years postpartum, and 2.27mmHg (95% CI -3.61, -0.93) lower change in diastolic BP from enrolment through 8 years postpartum, as compared to control. In exposure-response analysis, average prenatal CO was positively associated with change in systolic BP from enrolment (β=0.71mmHg, 95% CI 0.08, 1.30, per doubling of CO)., Conclusions: LPG cookstove intervention initiated in early pregnancy and maintained through the first postpartum year was associated with lower systolic and diastolic BP trajectories through 8 years postpartum. These findings support the need to integrate clean cooking solutions into existing antenatal care packages., Competing Interests: Disclosures All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The results, conclusions and recommendations in this paper are those of the authors and do not represent the official position US National Institutes of Health.

Published
2025
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45. Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study.

Author

Knobel P, Colicino E, Kloog I, Litke R, Lane K, Federman A, Mobbs C, and Yitshak Sade M

Abstract

Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging. Social Vulnerability Index (SVI) is a composite index accounting for different facets of the social, economic, and demographic environment grouped into four themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. We aim to assess the concurrent and combined associations of the four SVI themes on PhenoAgeAccel and the differential effects on disadvantaged groups. We use electronic health records data from 31,913 patients from the Mount Sinai Health System (116,952 person-years) and calculate PhenoAge for years with available laboratory results (2011-2022). PhenoAge is calculated as a weighted linear combination of lab results, and PhenoAgeAccel is the differential between PhenoAge and chronological age. A decile increase in the mixture of SVI dimensions was associated with an increase of 0.23 years (95% CI 0.21, 0.25) in PhenoAgeAccel. The socioeconomic status dimension was the main driver of the association, accounting for 61% of the weight. Interaction models revealed a more substantial detrimental association for women and racial and ethnic minorities with differences in leading SVI themes. These findings suggest that neighborhood-level social vulnerability increases the biological age of its residents, increasing morbidity and mortality risks. Socioeconomic status has the larger detrimental role among the different facets of social environment., (© 2025. The Author(s).)

Published
2025
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46. Impact of metabolism-disrupting chemicals and folic acid supplementation on liver injury and steatosis in mother-child pairs.

Author

India-Aldana S, Midya V, Betanzos-Robledo L, Yao M, Alcalá C, Andra SS, Arora M, Calafat AM, Chu J, Deierlein A, Estrada-Gutierrez G, Jagani R, Just AC, Kloog I, Landero J, Oulhote Y, Walker RW, Yelamanchili S, Baccarelli AA, Wright RO, Téllez Rojo MM, Colicino E, Cantoral A, and Valvi D

Abstract

Background & Aims: Scarce knowledge about the impact of metabolism-disrupting chemicals (MDCs) on steatotic liver disease limits opportunities for intervention. We evaluated pregnancy MDC-mixture associations with liver outcomes, and effect modification by folic acid (FA) supplementation in mother-child pairs., Methods: We studied ∼200 mother-child pairs from the Mexican PROGRESS cohort, with 43 MDCs measured during pregnancy (estimated air pollutants, blood/urine metals or metalloids, urine high- and low-molecular-weight phthalate [HMWPs, LMWPs] and organophosphate-pesticide metabolites), and serum liver enzymes (ALT, AST) at ∼9 years post-parturition. Outcomes included elevated liver enzymes in children and established clinical scores for steatosis and fibrosis in mothers (i.e., , Ast: ALT, FLI, HSI, FIB-4). Bayesian-weighted quantile sum regression assessed MDC-mixture associations with liver outcomes. We further examined chemical-chemical interactions and effect modification by self-reported FA supplementation., Results: In children, many MDC-mixtures were associated with liver injury. Per quartile HMWP-mixture increase, ALT increased by 10.1% (95% CI 1.67%, 19.4%) and AST by 5.27% (95% CI 0.80%, 10.1%). LMWP-mixtures and air pollutant-mixtures were associated with higher AST and ALT, respectively. Air pollutant and non-essential metal/element associations with liver enzymes were attenuated by maternal cobalt blood concentrations (p-interactions <0.05). In mothers, only the LMWP-mixture was associated with odds for steatosis (odds ratio = 1.53, 95% CI 1.01-2.28 for HSI >36, and odds ratio 1.62, 95% CI 1.05-2.49 for AST:ALT <1). In mothers and children, most associations were attenuated (null) at FA supplementation ≥600 μg/day (p-interactions <0.05)., Conclusions: Pregnancy MDC exposures may increase risk of liver injury and steatosis, particularly in children. Adequate FA supplementation and maternal cobalt levels may attenuate these associations., Impact and Implications: The effects of environmental chemical exposures on steatotic liver diseases are not well understood. In a parallel investigation of mothers and children, we found that pregnancy exposures to metabolism-disrupting chemicals may increase the risk of liver injury and steatosis, especially in the child, and that these associations could be attenuated by higher folic acid and/or cobalt levels. These findings can inform policies to decrease environmental chemical pollution and contribute to the design of clinical interventions addressing the metabolic dysfunction-associated steatotic liver disease epidemic., Competing Interests: Conflict of interest The authors of this study declare that they do not have any conflict of interest. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2024 European Association for the Study of the Liver. All rights reserved.)

Published
2024
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47. The World Trade Center exposome and health effects in 9/11 rescue and recovery workers.

Author

Rechtman E, Rodriguez MA, Colicino E, Hahn CJ, Navarro E, Invernizzi A, Dasaro CR, Teitelbaum SL, Todd AC, and Horton MK

Abstract

Background: In the aftermath of the World Trade Center (WTC) attack on 11 September 2001, rescue and recovery workers faced hazardous conditions and toxic agents. Prior research linked these exposures to adverse health effects, but mainly examined individual factors, overlooking complex mixture effects., Methods: This study applies an exposomic approach encompassing the totality of responders' experience, defined as the WTC exposome. We analyzed data from 34,096 members of the WTC Health Program General Responder, including mental and physical health, occupational history, traumatic and environmental exposures using generalized weighted quantile sum regression., Results: We find a statistically significant association between the exposure mixture index and all investigated health outcomes. Factors identified as risk factors include working in an enclosed heavily contaminated area, construction occupation, and exposure to blood and body fluids. Conversely, full-time employment emerged as a protective factor., Conclusions: This exposomics study emphasizes the importance of considering combined exposures for the identification of harmful and protective factors within the WTC exposome, providing valuable insights for targeted interventions and preventive measures. In an era marked by more frequent and severe natural disasters due to the evolving climate crisis, the exposomic framework is a promising tool for disaster preparedness., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Published
2024
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48. Source-Specific PM 2.5 and Atherosclerotic Cardiovascular Disease Mortality.

Author

Ma T, Knobel P, Hadley M, Colicino E, Amini H, Federman A, Schwartz J, Steenland K, and Sade MY

Subjects
Humans, United States epidemiology, Female, Aged, Male, Air Pollution adverse effects, Air Pollution analysis, Air Pollutants adverse effects, Air Pollutants analysis, Environmental Exposure adverse effects, Cardiovascular Diseases mortality, Aged, 80 and over, Particulate Matter adverse effects, Particulate Matter analysis, Atherosclerosis mortality
Abstract

Background: Fine particulate matter (PM 2.5 ) exposure is adversely linked to atherosclerotic cardiovascular disease (ASCVD). However, most studies focused on PM 2.5 mass rather than its chemical composition and specific sources. Particulate pollution sources can have distinct, cumulative, and potentially synergistic health impacts. We investigated the associations of source-specific PM 2.5 exposure with ASCVD mortality in the United States, considering the combined associations and regional variations., Methods: We used data from the Centers for Medicare & Medicaid Services (including data from 65,838,403 participants) from 2000 to 2016. We estimated PM 2.5 exposure using machine-learning models and attributed components to five source categories. We used Poisson survival models to assess the associations with the source categories., Results: Higher ASCVD mortality rate (rate ratio [95% confidence interval (CI)] per interquartile range increase) was associated with oil combustion (1.051 [1.049 to 1.052]), industrial pollution (1.054 [1.052 to 1.056]), coal and biomass burning (1.065 [1.062 to 1.067]), and motor vehicle pollution (1.044 [1.042 to 1.046]). These associations persisted even after limiting our sample to ZIP code-years with PM 2.5 <9 μg/m 3 - the current National Ambient Air Quality Standard. In these areas the observed rate ratio for a one-unit increase in PM 2.5 mass was 1.028 (95% CI, 1.026 to 1.029)., Conclusions: We found higher ASCVD mortality rate associated with PM 2.5 , with differential effects across sources. These data highlight the importance of considering local population characteristics and exposure patterns when assessing health risks associated with PM 2.5 .

Published
2024
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49. Prenatal exposure to phthalates and childhood wheeze and asthma in the PROGRESS cohort.

Author

Alcala CS, Lamadrid-Figueroa H, Tamayo-Ortiz M, Mercado-Garcia A, Midya V, Just AC, Foppa-Pedretti N, Colicino E, Téllez-Rojo MM, Wright RO, Wright RJ, Carroll KN, and Rosa MJ

Subjects
Humans, Female, Pregnancy, Child, Preschool, Male, Child, Mexico epidemiology, Cohort Studies, Adult, Phthalic Acids, Asthma epidemiology, Prenatal Exposure Delayed Effects epidemiology, Respiratory Sounds, Environmental Pollutants, Maternal Exposure statistics & numerical data
Abstract

Introduction: Prenatal phthalate exposure may influence lung development and lead to wheezing and asthma in childhood, and these associations may vary by sex. Despite ubiquity of exposure, there is limited epidemiologic data on these associations in Latin America., Methods: We assessed 593 mother-child dyads enrolled in the Programming Research in Obesity, Growth, Environment, and Social Stressors birth cohort in Mexico City. We quantified 15 phthalate metabolites in 2nd and 3rd trimester maternal urine. Report of ever wheeze, wheeze in the past 12 months (current wheeze) and ever asthma were obtained using a validated survey when children were 4 and 6 years of age. We examined individual associations with modified Poisson models. Mixture effects were assessed using Bayesian Weighted Quantile Sum (BWQS) regression. All models were adjusted for child's sex, maternal age and education at enrollment, and parity., Results: In Poisson models, a doubling of mono (carboxy-isononyl) phthalate (MCNP) during the 2nd trimester was associated with higher risk of wheeze (RR: 1.14, 95 % CI: 1.01, 1.29), and asthma (RR: 1.44, 95 % CI: 1.05, 1.97) at 4 years of age. Higher concentrations of the sum of di-isononyl phthalate metabolites (∑DiNP) during the 2nd trimester were also associated with asthma at 4 years of age (RR: 1.30, 95 % CI: 1.04, 1.61). Mixture associations of phthalate metabolite concentrations during the 2nd trimester and asthma at 4 years of age were stronger in males (BWQS, OR: 1.94, 95 % CI: 0.90, 4.60; 90 % CrI: 1.04, 3.73) compared to females (BWQS, OR: 1.23, 95 % CI: 0.56, 2.88; 90 % CrI: 0.61, 2.55). Additionally, we observed stronger inverse associations between prenatal phthalate mixtures during the 3rd trimester and current wheeze at 4 and 6 years of age in females (BWQS, OR: 0.54, 90 % CrI: 0.35, 0.82; OR: 0.45, 90 % CrI: 0.22, 0.84) compared to males (BWQS, OR: 0.95, 90 % Cri: 0.68, 1.35; OR: 0.97, 90 % CrI: 0.59, 1.54)., Conclusions: Prenatal phthalate metabolite concentrations were associated with respiratory outcomes in childhood, with some evidence of sex specific effects. Future work investigating phthalate exposure and wheeze trajectories/lung function will be important for understanding how these may predict later disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Published
2024
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50. Cross-Cohort Mixture Analysis: A Data Integration Approach With Applications on Gestational Age and DNA-Methylation-Derived Gestational Age Acceleration Metrics.

Author

Colicino E, Ascari R, Saddiki H, Merced-Nieves F, Foppa Pedretti N, Huddleston K, Wright RO, and Wright RJ

Subjects
Humans, Female, Cohort Studies, Pregnancy, Environmental Exposure, Bayes Theorem, DNA Methylation, Biometry methods, Gestational Age
Abstract

Data integration of multiple studies can provide enhanced exposure contrast and statistical power to examine associations between environmental exposure mixtures and health outcomes. Extant research has combined populations and identified an overall mixture-outcome association, without accounting for differences across studies. We extended the Bayesian Weighted Quantile Sum (BWQS) regression to a hierarchical framework to analyze mixtures across cohorts. The hierarchical BWQS (HBWQS) approach aggregates sample size of multiple cohorts to calculate an overall mixture index, thereby identifying the most harmful exposure(s) across cohorts; and provides cohort-specific associations between the overall mixture index and the outcome. We showed results from 10 simulated scenarios including four mixture components in three, eight, and ten populations, and two real-case examples on the association between prenatal metal mixture exposure-comprising arsenic, cadmium, and lead-and both gestational age and epigenetic-derived gestational age acceleration metrics. Simulated scenarios showed good empirical coverage and little bias for all HBWQS-estimated parameters. The Watanabe-Akaike information criterion showed a better average performance for the HBWQS regression than the BWQS across scenarios. HBWQS results incorporating cohorts within the national Environmental influences on Child Health Outcomes (ECHO) program from three different sites showed that the environmental mixture was negatively associated with gestational age in a single site. The HBWQS approach facilitates the combination of multiple cohorts and accounts for individual cohort differences in mixture analyses. HBWQS findings can be used to develop regulations, policies, and interventions regarding multiple co-occurring environmental exposures and it will maximize the use of extant publicly available data., (© 2024 Wiley‐VCH GmbH.)

Published
2024
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