Rachel S Kelly1, Haley Bayne2, Avron Spiro3, Pantel Vokonas4, David Sparrow4, Scott T Weiss2, Joel Schwartz5, Feiby L Nassan5, Kathleen Lee-Sarwar6, Mengna Huang2, Priyadarshini Kachroo2, Su H Chu2, Augusto A Litonjua7, Jessica A Lasky-Su2. 1. Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02129, USA. Electronic address: hprke@channing.harvard.edu. 2. Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02129, USA. 3. Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA; Department of Psychiatry, Boston University School of Medicine, Boston, MA, 02118, USA. 4. VA Normative Aging Study, VA Boston Healthcare System, School of Medicine and School of Public Health, Boston University, USA. 5. Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA. 6. Channing Division of Network Medicine; Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02129, USA; Division of Allergy and Clinical Immunology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA. 7. Division of Pediatric Pulmonary Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA.
Abstract
BACKGROUND: Lead (Pb) is widespread and exposure to this non-essential heavy metal can cause multiple negative health effects; however the mechanisms underlying these effects remain incompletely understood. OBJECTIVES: To identify plasma metabolomic signatures of Pb exposure, as measured in blood and toenails. METHODS: In a subset of men from the VA Normative Aging Study, mass-spectrometry based plasma metabolomic profiling was performed. Pb levels were measured in blood samples and toenail clippings collected concurrently. Multivariable linear regression models, smoothing splines and Pathway analyses were employed to identify metabolites associated with Pb exposure. RESULTS: In 399 men, 858 metabolites were measured and passed QC, of which 154 (17.9%) were significantly associated with blood Pb (p < 0.05). Eleven of these passed stringent correction for multiple testing, including pro-hydroxy-pro (β(95%CI): 1.52 (0.93,2.12), p = 7.18x10-7), N-acetylglycine (β(95%CI): 1.44 (0.85,2.02), p = 1.12x10-6), tartarate (β(95%CI): 0.68 (0.35,1.00), p = 4.84x10-5), vanillylmandelate (β(95%CI): 1.05 (0.47,1.63), p = 4.44x10-7), and lysine (β(95%CI): 1.88 (-2.8,-0.95), p = 9.10x10-5). A subset of 48 men had a second blood sample collected a mean of 6.1 years after their first. Three of the top eleven metabolites were also significant in this second blood sample. Furthermore, we identified 70 plasma metabolites associated with Pb as measured in toenails. Twenty-three plasma metabolites were significantly associated with both blood and toenail measures, while others appeared to be specific to the biosample in which Pb was measured. For example, benzanoate metabolism appeared to be of importance with the longer-term exposure assessed by toenails. DISCUSSION: Pb exposure is responsible for 0.6% of the global burden of disease and metabolomics is particularly well-suited to explore its pathogenic mechanisms. In this study, we identified metabolites and metabolomic pathways associated with Pb exposure that suggest that Pb exposure acts through oxidative stress and immune dysfunction. These findings help us to better understand the biology of this important public health burden.
BACKGROUND: Lead (Pb) is widespread and exposure to this non-essential heavy metal can cause multiple negative health effects; however the mechanisms underlying these effects remain incompletely understood. OBJECTIVES: To identify plasma metabolomic signatures of Pb exposure, as measured in blood and toenails. METHODS: In a subset of men from the VA Normative Aging Study, mass-spectrometry based plasma metabolomic profiling was performed. Pb levels were measured in blood samples and toenail clippings collected concurrently. Multivariable linear regression models, smoothing splines and Pathway analyses were employed to identify metabolites associated with Pb exposure. RESULTS: In 399 men, 858 metabolites were measured and passed QC, of which 154 (17.9%) were significantly associated with blood Pb (p < 0.05). Eleven of these passed stringent correction for multiple testing, including pro-hydroxy-pro (β(95%CI): 1.52 (0.93,2.12), p = 7.18x10-7), N-acetylglycine (β(95%CI): 1.44 (0.85,2.02), p = 1.12x10-6), tartarate (β(95%CI): 0.68 (0.35,1.00), p = 4.84x10-5), vanillylmandelate (β(95%CI): 1.05 (0.47,1.63), p = 4.44x10-7), and lysine (β(95%CI): 1.88 (-2.8,-0.95), p = 9.10x10-5). A subset of 48 men had a second blood sample collected a mean of 6.1 years after their first. Three of the top eleven metabolites were also significant in this second blood sample. Furthermore, we identified 70 plasma metabolites associated with Pb as measured in toenails. Twenty-three plasma metabolites were significantly associated with both blood and toenail measures, while others appeared to be specific to the biosample in which Pb was measured. For example, benzanoate metabolism appeared to be of importance with the longer-term exposure assessed by toenails. DISCUSSION: Pb exposure is responsible for 0.6% of the global burden of disease and metabolomics is particularly well-suited to explore its pathogenic mechanisms. In this study, we identified metabolites and metabolomic pathways associated with Pb exposure that suggest that Pb exposure acts through oxidative stress and immune dysfunction. These findings help us to better understand the biology of this important public health burden.
Authors: Mia M Gaudet; Emily L Deubler; Rachel S Kelly; W Ryan Diver; Lauren R Teras; James M Hodge; Keith E Levine; Laura G Haines; Thomas Lundh; Per Lenner; Domenico Palli; Paolo Vineis; Ingvar A Bergdahl; Susan M Gapstur; Soterios A Kyrtopoulos Journal: Int J Cancer Date: 2018-11-07 Impact factor: 7.396
Authors: Rachel S Kelly; Thomas Lundh; Miquel Porta; Ingvar A Bergdahl; Domenico Palli; Ann-Sofie Johansson; Maria Botsivali; Paolo Vineis; Roel Vermeulen; Soterios A Kyrtopoulos; Marc Chadeau-Hyam Journal: PLoS One Date: 2013-11-28 Impact factor: 3.240
Authors: Rachel S Kelly; Bo L Chawes; Kevin Blighe; Yamini V Virkud; Damien C Croteau-Chonka; Michael J McGeachie; Clary B Clish; Kevin Bullock; Juan C Celedón; Scott T Weiss; Jessica A Lasky-Su Journal: Chest Date: 2018-06-13 Impact factor: 9.410
Authors: Feiby L Nassan; Rachel S Kelly; Anna Kosheleva; Petros Koutrakis; Pantel S Vokonas; Jessica A Lasky-Su; Joel D Schwartz Journal: Environ Health Date: 2021-01-07 Impact factor: 5.984
Authors: Priyadarshini Kachroo; Joanne E Sordillo; Sharon M Lutz; Scott T Weiss; Rachel S Kelly; Michael J McGeachie; Ann Chen Wu; Jessica A Lasky-Su Journal: J Pers Med Date: 2021-11-04
Authors: Megan M Niedzwiecki; Shoshannah Eggers; Anu Joshi; Georgia Dolios; Alejandra Cantoral; Héctor Lamadrid-Figueroa; Chitra Amarasiriwardena; Martha M Téllez-Rojo; Robert O Wright; Lauren Petrick Journal: Environ Health Date: 2021-12-10 Impact factor: 7.123