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Do Post-breast Cancer Diagnosis Toenail Trace Element Concentrations Reflect Prediagnostic Concentrations?

O’Brien, Katie M.a,b; White, Alexandra J.b; Sandler, Dale P.b; Jackson, Brian P.c; Karagas, Margaret R.d; Weinberg, Clarice R.a

doi: 10.1097/EDE.0000000000000927

Background: Exposure to trace elements may affect health, including breast cancer risk. Trace element levels in toenails are potentially useful biomarkers of exposure, but their reliability is not established. We assessed the reproducibility of toenail element concentrations over time and whether concentrations change following a breast cancer diagnosis.

Methods: We assessed trace element levels in toenails collected at two time points from 221 women (111 with and 110 without an intervening breast cancer diagnosis). We measured levels of arsenic, cadmium, chromium, cobalt, copper, iron, mercury, manganese, molybdenum, nickel, lead, antimony, selenium, tin, vanadium, and zinc using inductively coupled plasma mass spectrometry in samples collected at baseline and 4–10 years later. We compared trace element concentrations over time using Spearman’s rank correlation coefficient (R). We used linear models to examine the magnitude and direction of changes and the influence of a breast cancer diagnosis.

Results: Overall, we observed positive correlations (R = 0.18–0.71) between paired samples for all trace elements. However, nickel (R = −0.02) and antimony (R = 0.12) were not correlated among cases. We observed decreases in cadmium, chromium, mercury, manganese, molybdenum, nickel, and lead between baseline and follow-up, but case status was unrelated to these changes. The declines are consistent with decreases over calendar time rather than age time.

Conclusions: Toenail trace element concentrations were correlated over time, but many elements showed systematic decreases by calendar year. Aside from nickel and antimony, postdiagnostic toenail levels correlated with prediagnostic levels, providing support for using postdiagnostic toenail samples in retrospective studies.

From the aBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC

bEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC

cDepartment of Earth Sciences, Dartmouth College, Hanover, NH

dDepartment of Epidemiology and Children’s Environmental Health and Disease Prevention Research Center at Dartmouth, Geisel School of Medicine at Dartmouth, Lebanon, NH.

Submitted March 31, 2018; accepted September 21, 2018.

This work was supported by the Intramural Research Program of the National Institutes of Health, National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S. and Z01-ES102245 to C.R.W.) and Superfund (P42ES007373 to M.R.K., B.P.J.) and National Cancer Center Support (5P30CA023108 to M.R.K., B.P.J.) grants.

The authors report no conflicts of interest.

Data requests: Requests for deidentified Sister Study data, including the data used in this manuscript, can be requested through the study website ( The Sister Study is an ongoing prospective study, and the data sharing policy was developed to protect the privacy of study participants. It is consistent with study informed consent documents as approved by the National Institute of Environmental Health Sciences (NIEHS) Institutional Review Board.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (

Correspondence: Katie M. O’Brien, 111 TW Alexander Dr, Research Triangle Park, NC 27709. E-mail:

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