title: Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships.
abstract: Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.
authors: Consulting in Health Sciences and Risk Assessment, BR Stern Associates, Annandale, Virginia 22003, USA. brstern1@aol.com
authors: Bonnie Ransom
authors: BR
authors: Stern
authors: Marc
authors: M
authors: Solioz
authors: Daniel
authors: D
authors: Krewski
authors: Peter
authors: P
authors: Aggett
authors: Tar-Ching
authors: TC
authors: Aw
authors: Scott
authors: S
authors: Baker
authors: Kenny
authors: K
authors: Crump
authors: Michael
authors: M
authors: Dourson
authors: Lynne
authors: L
authors: Haber
authors: Rick
authors: R
authors: Hertzberg
authors: Carl
authors: C
authors: Keen
authors: Bette
authors: B
authors: Meek
authors: Larisa
authors: L
authors: Rudenko
authors: Rita
authors: R
authors: Schoeny
authors: Wout
authors: W
authors: Slob
authors: Tom
authors: T
authors: Starr
mesh_terms: D000818:Animals; D003300:Copper / Q000172:deficiency / Q000378:metabolism* / Q000633:toxicity*; D003677:Deficiency Diseases / Q000473:pathology; D004305:Dose-Response Relationship, Drug; D004781:Environmental Exposure / Q000009:adverse effects; D006801:Humans; D008661:Metabolism, Inborn Errors / Q000473:pathology
chemical_list: D003300:Copper