chromosome 8 for Se, at the p-terminal end of chromosome 18 for Cd, around 15–30 cM on chromosome 20 for Cd, and on the X chro- mosome at 95 cM also for Cd. Given these results, we can investigate whether genes likely to affect element trans- port or binding to proteins are located under any of these novel peaks. This excludes the chromosome 3 peak for Pb, which we dis- cussed previously (Whitfield et al. 2007). Each peak is broad, as is common with genetic linkage analysis, and covers a large number of genes. Starting with candidate genes expected to affect the processes of uptake, distribution, or binding of these elements, we checked their location against the regions showing sugges- tive linkage on chromosomes 2, 4, 5, 8, 18, 20, or X. The candidates include the hemo- chromatosis gene (chromosome 6), the met- allothioneins (all chromosome 16), divalent metal transporters {SLC11A1 [solute carrier family 11 (proton-coupled divalent metal ion transporters), member 1], chromosome 2; and SLC11A2 [solute carrier family 11 (pro- ton-coupled divalent metal ion transporters), member 2], chromosome 12}, hepcidin (chro- mosome 19), and iron regulatory proteins [ACO1 (soluble aconitase 1), chromosome 9; IREB2 (iron-responsive element binding pro- tein 2), chromosome 15]. The only overlap between a linkage peak and one of these can- didate genes is for SLC11A1 (at 218.9 Mb on chromosome 2), which is within the region of linkage for Zn on chromosome 2. The peak LOD score for Zn we found in the present study is 2.73 at 220 cM, or approximately 219 Mb. This gene codes for a divalent metal transporter that has been studied mainly in relation to iron, but the initial report on its characterization (Gunshin et al. 1997) clearly showed transport activity for Zn, Cd, Mn, Cu, and cobalt at rates similar to those for iron, and some transport of nickel and Pb. It is particularly interesting that the linkage region around 220 cM on chromosome 2 showed minor peaks for Cd and Se as well as the suggestive one for Zn, perhaps reflecting the broad specificity of this transporter. Working in the other direction, starting with the locations of the suggestive linkage peaks and checking them against known genes in these regions, we could identify no other obvious candidates within the linkage regions. Strengths and limitations. Our data are derived from twin subjects. First, this is a major strength, because it allows the investi- gation of genetic and environmental sources of variation in individual elements and cova- riation between concentrations of two or more elements. Clearly, more can be inferred about the causes of covariation between ele- ments when it is possible to ascribe it to either genetic or environmental effects on both. Second, use of related subjects (siblings; in this case, pairs of DZ twins) allows use of genetic linkage techniques to localize genes contributing to overall heritability. Twin studies have been questioned because of pos- sibly greater similarity of environments in MZ than DZ pairs, but this is unlikely for our subjects, who were adults with a mean age of 46 years. Other limitations include restriction of the measurements to erythro- cytes and lack of clinical data on our study participants. Given that the consequences of variation in toxic element concentrations in the general population are subtle, a focus on genetic effects on outcomes without prior consideration of intermediate phenotypes would require a prohibitively large study. Conclusions The hypothesis underlying our studies of gene effects on toxic element concentrations is that although exposure is a precondition for harm, some people may be more vulner- able than others by reason of their greater tendency to absorb and retain one or several toxic elements. We have previously shown such variation for erythrocyte Pb concentra- tion (Whitfield et al. 2007) and have now extended our analyses to conclude that the same applies for As, Hg, and probably for Cd. We have also identified genetic effects on Cu, Se, and Zn, which are not among the toxic elements but are essential and may modulate the toxic effects of the other elements. We now have one significant and several sugges- tive regions of linkage and have identified two strong candidate genes (SLC4A7 and SLC11A1) for future association studies on single nucleotide polymorphisms. Identification and confirmation of the genes and variants responsible depends on further research, but if such variants can be identified, then such data can be incorpo- rated into models of the relationship between exposure and disease. Part of the difficulty in unraveling the health consequences of low-level exposure to toxic substances may be due to variation in vulnerability, and if a subgroup of the population can be defined as high risk, then exposure– disease associations may be found that are obscured in the general population. It may also be possible to protect people identified as being at high risk by reducing their occu- pational or environmental exposure to poten- tially hazardous situations. This concept of personalized medicine—basing treatment, advice, or lifestyle modification on genetic data—has been much discussed and may have major effects on individual and population health, but its application to occupational or population health would require both evi- dence of benefit and discussion of the social or ethical issues. Environmental Health Perspectives • volume 118 | number 6 | June 2010 Genetic effects on trace elements Ref Rencs Abecasis GR, Burt RA, Hall D, Bochum S, Doheny KF, Lundy SL, et al. 2004. Genomewide scan in families with schizophre- nia from the founder population of Afrikaners reveals evidence for linkage and uniparental disomy on chromo- some 1. Am J Hum Genet 74(3):403–417. Alfven T, Elinder CG, Carlsson MD, Grubb A, Hellstrom L, Persson B, et al. 2000. Low-level cadmium exposure and osteoporosis. J Bone Miner Res 15:1579–1586. Alfven T, Elinder CG, Hellstrom L, Lagarde F, Jarup L. 2004. Cadmium exposure and distal forearm fractures. J Bone Miner Res 19:900–905. Axelrad DA, Bellinger DC, Ryan LM, Woodruff TJ. 2007. Dose– response relationship of prenatal mercury exposure and IQ: an integrative analysis of epidemiologic data. Environ Health Perspect 115:609–615. Balshaw S, Edwards J, Daughtry B, Ross K. 2007. Mercury in seafood: mechanisms of accumulation and consequences for consumer health. Rev Environ Health 22:91–113. Beekman M, Heijmans BT, Martin NG, Whitfield JB, Pedersen NL, DeFaire U, et al. 2003. Evidence for a QTL on chromosome 19 influencing LDL cholesterol levels in the general population. Eur J Hum Genet 11(11):845–850. Bellinger DC. 2008. Late neurodevelopmental effects of early exposures to chemical contaminants: reducing uncertainty in epidemiological studies. Basic Clin Pharmacol Toxicol 102:237–244. Bjorkman L, Vahter M, Pedersen NL. 2000. Both the environment and genes are important for concentrations of cadmium and lead in blood. Environ Health Perspect 108:719–722. Borak J, Hosgood HD. 2007. Seafood arsenic: implications for human risk assessment. Regul Toxicol Pharmacol 47:204–212. Canfield RL, Henderson CR Jr, Cory-Slechta DA, Cox C, Jusko TA, Lanphear BP. 2003. Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter. N Engl J Med 348:1517–1526. Coronado-Gonzalez JA, Del Razo LM, Garcia-Vargas G, Sanmiguel-Salazar F, Escobedo-de la Pena J. 2007. Inorganic arsenic exposure and type 2 diabetes mellitus in Mexico. Environ Res 104:383–389. Davidson PW, Myers GJ, Weiss B. 2004. Mercury exposure and child development outcomes. Pediatrics 113(suppl 4):1023–1029. Ekino S, Susa M, Ninomiya T, Imamura K, Kitamura T. 2007. Minamata disease revisited: an update on the acute and chronic manifestations of methyl mercury poisoning. J Neurol Sci 262:131–144. Friberg L, Piscator M, Nordberg GF, Kjellstrom T. 1974. Cadmium in the Environment. 2nd ed. Cleveland, OH:CRC Press. Grandjean P, Olsen NB, Hollnagel H. 1981. Influence of smoking and alcohol consumption on blood lead levels. Int Arch Occup Environ Health 48:391–397. Grasmick C, Huel G, Moreau T, Sarmini H. 1985. The combined effect of tobacco and alcohol consumption on the level of lead and cadmium in blood. Sci Total Environ 41:207–217. Gunshin H, Mackenzie B, Berger UV, Gunshin Y, Romero MF, Boron WF, et al. 1997. Cloning and characterization of a mammalian proton-coupled metal-ion transporter. Nature 388:482–488. Hasselbalch AL, Heitmann BL, Kyvik KO, Sorensen TI. 2008. Studies of twins indicate that genetics influence dietary intake. J Nutr 138:2406–2412. Hense HW, Filipiak B, Novak L, Stoeppler M. 1992. Nonoccupa- tional determinants of blood lead concentrations in a gen- eral population. Int J Epidemiol 21:753–762. Hodgson S, Nieuwenhuijsen MJ, Elliott P, Jarup L. 2007. Kidney disease mortality and environmental exposure to mercury. Am J Epidemiol 165:72–77. Hopper JL, Balderas A, Mathews JD. 1982. Analysis of variation in blood lead levels in Melbourne families. Med J Aust 2:573–576. Hopper JL, Mathews JD. 1983. Extensions to multivariate normal models for pedigree analysis. II. Modeling the effect of shared environment in the analysis of variation in blood lead levels. Am J Epidemiol 117:344–355. Jemal A, Graubard BI, Devesa SS, Flegal KM. 2002. The associa- tion of blood lead level and cancer mortality among whites in the United States. Environ Health Perspect 110:325–329. Lloyd B, Lloyd RS, Clayton BE. 1983. Effect of smoking, alcohol, and other factors on the selenium status of a healthy population. J Epidemiol Community Health 37:213–217. Lugon-Moulin N, Martin F, Krauss MR, Ramey PB, Rossi L. 2006. Cadmium concentration in tobacco (Nicotiana tabacum L.) 781