Skip to main content
SpringerLink
Log in

Association of copper levels in the hair with gray matter volume, mean diffusivity, and cognitive functions

  • Original Article
  • Published:
Brain Structure and Function Aims and scope Submit manuscript

Abstract

Although copper plays a critical role in normal brain functions and development, it is known that excess copper causes toxicity. Here we investigated the associations of copper levels in the hair with regional gray matter volume (rGMV), mean diffusivity (MD), and cognitive differences in a study cohort of 924 healthy young adults. Our findings showed that high copper levels were associated mostly with low cognitive abilities (low scores on the intelligence test consisting of complex speed tasks, involving reasoning task, a complex arithmetic task, and a reading comprehension task) as well as lower reverse Stroop interference, high rGMV over widespread areas of the brain [mainly including the bilateral lateral and medial parietal cortices, medial temporal structures (amygdala, hippocampus, and parahippocampal gyrus), middle cingulate cortex, orbitofrontal cortex, insula, perisylvian areas, inferior temporal lobe, temporal pole, occipital lobes, and supplementary motor area], as well as high MD of the right substantia nigra and bilateral hippocampus, which are indicative of low density in brain tissues. These results suggest that copper levels are associated with mostly aberrant cognitive functions, greater rGMV in extensive areas, greater MD (which are indicative of low density in brain tissues) in subcortical structures in the healthy young adults, possibly reflecting copper’s complex roles in neural mechanisms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ashburner J, Friston KJ (2000) Voxel-based morphometry-the methods. Neuroimage 11:805–821

    Article  CAS  PubMed  Google Scholar 

  • Ayodele J, Bayero A (2009) Lead and zinc concentrations in hair and nail of some Kano inhabitants. African J Env Sci Tech 3:164–170

    CAS  Google Scholar 

  • Bai X, Wang G, Wu L, Liu Y, Cui L, Shi H, Guo L (2013) Deep-gray nuclei susceptibility-weighted imaging filtered phase shift in patients with Wilson’s disease. Pediatr Res 75:436–442

    Article  PubMed  Google Scholar 

  • Bass DA, Hickok D, Quig D, Urek K (2001) Trace element analysis in hair: factors determining accuracy, precision, and reliability. Altern Med Rev 6:472–481

    CAS  PubMed  Google Scholar 

  • Benjamini Y, Hochberg Y (2000) On the adaptive control of the false discovery rate in multiple testing with independent statistics. J Educ Behav Stat 25:60–83

    Article  Google Scholar 

  • Brewer GJ (2009) Risks of copper and iron toxicity during aging in humans. Chem Res Toxicol 23:319–326

    Article  CAS  Google Scholar 

  • Brewer GJ (2012) Copper toxicity in Alzheimer’s disease: cognitive loss from ingestion of inorganic copper. J Trace Elem Med Biol 26:89–92

    Article  CAS  PubMed  Google Scholar 

  • Castell A, Bowland J (1968) Supplemental copper for swine: Effects upon hemoglobin, serum proteins and tissue copper levels. Can J Anim Sci 48:415–424

    Article  CAS  Google Scholar 

  • Cecil KM, Brubaker CJ, Adler CM, Dietrich KN, Altaye M, Egelhoff JC, Wessel S, Elangovan I, Hornung R, Jarvis K (2008) Decreased brain volume in adults with childhood lead exposure. PLoS Med 5:e112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chandarana H, Do RK, Mussi TC, Jensen JH, Hajdu CH, Babb JS, Taouli B (2012) The effect of liver iron deposition on hepatic apparent diffusion coefficient values in cirrhosis. Am J Roentgenol 199:803–808

    Article  Google Scholar 

  • Chang CS, Choi JB, Kim HJ, Park SB (2011) Correlation between serum testosterone level and concentrations of copper and zinc in hair tissue. Biol Trace Elem Res 144:264–271

    Article  CAS  PubMed  Google Scholar 

  • Chłopicka J, Zachwieja Z, Zagrodzki P, Frydrych J, Słota P, Krośniak M (1998) Lead and cadmium in the hair and blood of children from a highly industrial area in Poland. Biol Trace Elem Res 62:229–234

    Article  PubMed  Google Scholar 

  • Cloninger CR, Svrakic DM, Przybeck TR (1993) A psychobiological model of temperament and character. Arch Gen Psychiatry 50:975–990

    Article  CAS  PubMed  Google Scholar 

  • Costa PT, McCrae RR (1992) Professional manual: revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI). Psychological Assessment Resources, Odessa

    Google Scholar 

  • Desai V, Kaler SG (2008) Role of copper in human neurological disorders. Am J Clin Nutr 88:855S–858S

    Article  CAS  PubMed  Google Scholar 

  • Everson G, Tsai H, Wang T (1967) Copper deficiency in the guinea pig. J Nutr 93:533–540

    Article  CAS  PubMed  Google Scholar 

  • Fox PL (2003) The copper-iron chronicles: the story of an intimate relationship. Biometals 16:9–40

    Article  CAS  PubMed  Google Scholar 

  • Frieden E (1980) Caeruloplasmin: a multi-functional metalloprotein of vertebrate plasma. In: Biological roles of copper, pp 93–124: Excerpta Medica Amsterdam

  • Friedman S, Kaufman S (1965) 3, 4-dihydroxyphenylethylamine beta-hydroxylase. Physical properties, copper content, and role of copper in the catalytic acttivity. J Biol Chem 240:4763–4773

    CAS  PubMed  Google Scholar 

  • Gaetke LM, Chow CK (2003) Copper toxicity, oxidative stress, and antioxidant nutrients. Toxicology 189:147–163

    Article  CAS  PubMed  Google Scholar 

  • Ha J-H, Doguer C, Flores SR, Wang T, Collins JF (2018) Progressive increases in dietary iron are associated with the emergence of pathologic disturbances of copper homeostasis in growing rats. J Nutr 148:373–378

    Article  PubMed  PubMed Central  Google Scholar 

  • Hakoda Y, Sasaki M (1990) Group version of the Stroop and reverse-Stroop test: the effects of reaction mode, order and practice. Kyoikushinrigakukenkyu (Educational Psychology Research) 38:389–394

    Google Scholar 

  • Hashimoto M (2008) Alzheimer’s disease and nutrition, especially copper, zinc and docosahexaenoic acid. Trace Nutr Res 25:8–18

    Google Scholar 

  • Hashimoto T, Takeuchi H, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R (2015) Neuroanatomical correlates of the sense of control: Gray and white matter volumes associated with an internal locus of control. Neuroimage 119:146–151

    Article  PubMed  Google Scholar 

  • Hunt D (1980) Copper and neurological function. Biol Roles Copper 7:247–266

    Google Scholar 

  • Hunt CD, Idso JP (1995) Moderate copper deprivation during gestation and lactation affects dentate gyrus and hippocampal maturation in immature male rats. J Nutr 125:2700–2710

    CAS  PubMed  Google Scholar 

  • Jacob RA, Klevay L, Logan G Jr (1978) Hair as a biopsy material V. Hair metal as an index of hepatic metal in rats: copper and zinc. Am J Clin Nutr 31:477–480

    Article  CAS  PubMed  Google Scholar 

  • Johansen-Berg H, Baptista CS, Thomas AG (2012) Human structural plasticity at record speed. Neuron 73:1058–1060

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jung RE, Segall JM, Jeremy Bockholt H, Flores RA, Smith SM, Chavez RS, Haier RJ (2010) Neuroanatomy of creativity. Hum Brain Mapp 31:398–409

    PubMed  PubMed Central  Google Scholar 

  • Kedzierska E (2003) Concentrations of selected bioelements and toxic metals and their influence on health status of children and youth residing in Szczecin]. Ann Acad Med Stetin 49:131–143

    CAS  PubMed  Google Scholar 

  • Kijima N, Saito R, Takeuchi M, Yoshino A, Ono Y, Kato M, Kitamura T (1996) Cloninger-no-kishitsu-to-seikaku-no-7inshimodel-oyobi-nihongoban [Cloninger’s seven-factor model of temperament and character and Japanese version of Temperament and Character Inventory (TCI)]. Seishinka-shindangaku [Archives of Psychiatric. Diagn Clin Evaluat 7:379–399

    Google Scholar 

  • Koc ER, Ilhan A, Aytürk Z, Acar B, GÜRLER M, Karapirli ALTUNTAŞA, Bodur M AS (2015) A comparison of hair and serum trace elements in patients with Alzheimer disease and healthy participants. Turkish J Med Sci 45:1034–1039

    Article  CAS  Google Scholar 

  • Kondo H, Morishita M, Ashida K, Osaka N (2003) Reading comprehension and working memory–structural equation modeling approach. Jpn J Psychol 73:480–487

    Article  Google Scholar 

  • Krejpcio Z, Olejnik D, Wójciak R, Kielczewska K, Gawęcki J (1997) Assessment of the content of calcium, magnesium, zinc and copper in hair and serum of children with hyperactivity. Polish J Environ Stud 6:89–92

    Google Scholar 

  • Kriegeskorte N, Simmons WK, Bellgowan PS, Baker CI (2009) Circular analysis in systems neuroscience: the dangers of double dipping. Nat Neurosci 12:535–540

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lech T (2002) Lead, copper, zinc, and magnesium content in hair of children and young people with some neurological diseases. Biol Trace Elem Res 85:111–126

    Article  CAS  PubMed  Google Scholar 

  • Loef M, Walach H (2012) Copper and iron in Alzheimer’s disease: a systematic review and its dietary implications. Br J Nutr 107:7–19

    Article  CAS  PubMed  Google Scholar 

  • Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH (2003) An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19:1233–1239

    Article  PubMed  Google Scholar 

  • Maldjian JA, Laurienti PJ, Burdette JH (2004) Precentral gyrus discrepancy in electronic versions of the Talairach atlas. Neuroimage 21:450–455

    Article  PubMed  Google Scholar 

  • Manto M (2014) Abnormal copper homeostasis: mechanisms and roles in neurodegeneration. Toxics 2:327–345

    Article  CAS  Google Scholar 

  • McNair DM, Lorr M, Droppleman LF (1992) Profile of mood states. Educational and Industrial Testing Service, San Diego

    Google Scholar 

  • Mikulewicz M, Chojnacka K, Gedrange T, Górecki H (2013) Reference values of elements in human hair: a systematic review. Environ Toxicol Pharmacol 36:1077–1086

    Article  CAS  PubMed  Google Scholar 

  • Morris MC, Evans DA, Tangney CC, Bienias JL, Schneider JA, Wilson RS, Scherr PA (2006) Dietary copper and high saturated and trans fat intakes associated with cognitive decline. Arch Neurol 63:1085–1088

    Article  PubMed  Google Scholar 

  • Nolan KR (1983) Copper toxicity syndrome. J Orthomol Psychiatry 12:270–282

    Google Scholar 

  • Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:97–113

    Article  CAS  PubMed  Google Scholar 

  • Pal A, Siotto M, Prasad R, Squitti R (2015) Towards a unified vision of copper involvement in Alzheimer’s disease: a review connecting basic, experimental, and clinical research. J Alzheimer’s Dis 44:343–354

    Article  CAS  Google Scholar 

  • Paris I, Dagnino-Subiabre A, Marcelain K, Bennett LB, Caviedes P, Caviedes R, Azar CO, Segura-Aguilar J (2001) Copper neurotoxicity is dependent on dopamine-mediated copper uptake and one-electron reduction of aminochrome in a rat substantia nigra neuronal cell line. J Neurochem 77:519–529

    Article  CAS  PubMed  Google Scholar 

  • Péran P, Cherubini A, Assogna F, Piras F, Quattrocchi C, Peppe A, Celsis P, Rascol O, Démonet J-F, Stefani A (2010) Magnetic resonance imaging markers of Parkinson’s disease nigrostriatal signature. Brain 133:3423–3433

    Article  PubMed  Google Scholar 

  • Pfeiffer CC, Mailloux R (1987) Excess copper as a factor in human diseases. J Orthomol Med 2:171–182

    Google Scholar 

  • Priya MDL, Geetha A (2011) Level of trace elements (copper, zinc, magnesium and selenium) and toxic elements (lead and mercury) in the hair and nail of children with autism. Biol Trace Elem Res 142:148–158

    Article  CAS  Google Scholar 

  • Rahman MA, Azad MAK, Hossain MI, Qusar MS, Bari W, Begum F, Huq SI, Hasnat A (2009) Zinc, manganese, calcium, copper, and cadmium level in scalp hair samples of schizophrenic patients. Biol Trace Elem Res 127:102–108

    Article  CAS  PubMed  Google Scholar 

  • Raven J (1998) Manual for Raven’s progressive matrices and vocabulary scales. Oxford Psychologists Press, Oxford

    Google Scholar 

  • Razek AA, Elmongy A, Hazem M, Zakareyia S, Gabr W (2011) Idiopathic Parkinson disease effect of levodopa on apparent diffusion coefficient value of the brain. Acad Radiol 18:70–73

    Article  PubMed  Google Scholar 

  • Rimland B, Larson GE (1983) Hair mineral analysis and behavior an analysis of 51 studies. J Learn Disabil 16:279–285

    Article  CAS  PubMed  Google Scholar 

  • Sagi Y, Tavor I, Hofstetter S, Tzur-Moryosef S, Blumenfeld-Katzir T, Assaf Y (2012) Learning in the fast lane: new insights into neuroplasticity. Neuron 73:1195–1203

    Article  CAS  PubMed  Google Scholar 

  • Sakai A (1970) Iron, copper, and zinc content of human hair. Nippon Eiseigaku Zasshi 25:420–437

    Article  CAS  PubMed  Google Scholar 

  • Salustri C, Barbati G, Ghidoni R, Quintiliani L, Ciappina S, Binetti G, Squitti R (2010) Is cognitive function linked to serum free copper levels? A cohort study in a normal population. Clin Neurophysiol 121:502–507

    Article  CAS  PubMed  Google Scholar 

  • Sasaki M, Hakoda Y (1985) The group version of the Stroop and reverse-Stroop test (1). In: Proceedings of Japan Educational Psyhological 27th annual meeting, p 208

  • Sasaki M, Hakoda Y, Yamagami R (1993) Schizophrenia and reverse-Stroop interference in the group version of the Stroop and reverse-Stroop test. Jpn J Psychol 64:43–50

    Article  CAS  Google Scholar 

  • Segura-Aguilar J, Metodiewa D, Baez S (2001) The possible role of one-electron reduction of aminochrome in the neurodegenerative process of the dopaminergic system. Neurotox Res 3:157–165

    Article  CAS  PubMed  Google Scholar 

  • Seppi K, Schocke MF, Donnemiller E, Esterhammer R, Kremser C, Scherfler C, Diem A, Jaschke W, Wenning GK, Poewe W (2004) Comparison of diffusion-weighted imaging and [123I] IBZM-SPECT for the differentiation of patients with the Parkinson variant of multiple system atrophy from those with Parkinson’s disease. Mov Disord 19:1438–1445

    Article  PubMed  Google Scholar 

  • Shaw P, Greenstein D, Lerch J, Clasen L, Lenroot R, Gogtay N, Evans A, Rapoport J, Giedd J (2006) Intellectual ability and cortical development in children and adolescents. Nature 440:676–679

    Article  CAS  PubMed  Google Scholar 

  • Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage 44:83–98

    Article  PubMed  Google Scholar 

  • Society_For_Creative_Minds (1969) Manual of S-A creativity test. Tokyo shinri Corporation, Tokyo

    Google Scholar 

  • Squitti R, Rossini P, Cassetta E-p, Moffa F, Pasqualetti P, Cortesi M, Colloca A, Rossi L (2002) d-penicillamine reduces serum oxidative stress in Alzheimer’s disease patients. Eur J Clin Invest 32:51–59

    Article  CAS  PubMed  Google Scholar 

  • Squitti R, Bressi F, Pasqualetti P, Bonomini C, Ghidoni R, Binetti G, Cassetta E, Moffa F, Ventriglia M, Vernieri F (2009) Longitudinal prognostic value of serum “free” copper in patients with Alzheimer disease. Neurology 72:50–55

    Article  CAS  PubMed  Google Scholar 

  • Squitti R, Siotto M, Polimanti R (2014a) Low-copper diet as a preventive strategy for Alzheimer’s disease. Neurobiol Aging 35:S40–S50

    Article  CAS  PubMed  Google Scholar 

  • Squitti R, Simonelli I, Ventriglia M, Siotto M, Pasqualetti P, Rembach A, Doecke J, Bush AI (2014b) Meta-analysis of serum non-ceruloplasmin copper in Alzheimer’s disease. J Alzheimer’s Dis 38:809–822

    Article  CAS  Google Scholar 

  • Takeuchi H, Kawashima R (2016) Neural mechanisms and children’s intellectual development: multiple impacts of environmental factors. Neuroscientist 22:618–631

    Article  PubMed  Google Scholar 

  • Takeuchi H, Kawashima R (2018) Mean diffusivity in the dopaminergic system and neural differences related to dopaminergic system. Curr Neuropharmacol 16:460–474

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Takeuchi H, Taki Y, Sassa Y, Hashizume H, Sekiguchi A, Fukushima A, Kawashima R (2010) Regional gray matter volume of dopaminergic system associate with creativity: evidence from voxel-based morphometry. Neuroimage 51:578–585

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Sassa Y, Hashizume H, Sekiguchi A, Fukushima A, Kawashima R (2011a) Working memory training using mental calculation impacts regional gray matter of the frontal and parietal regions. PLoS One 6:e23175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Takeuchi H, Taki Y, Hashizume H, Sassa Y, Nagase T, Nouchi R, Kawashima R (2011b) Failing to deactivate: the association between brain activity during a working memory task and creativity. Neuroimage 55:681–687

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Hashizume H, Sassa Y, Nagase T, Nouchi R, Kawashima R (2012) The association between resting functional connectivity and creativity. Cereb Cortex 22:2921–2929

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Hashizume H, Sekiguchi A, Kotozaki Y, Nakagawa S, Miyauchi CM, Sassa Y, Kawashima R (2013a) Effects of working memory-training on functional connectivity and cerebral blood flow during rest. Cortex 49:2106–2125

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Thyreau B, Sassa Y, Hashizume H, Sekiguchi A, Nagase T, Nouchi R, Fukushima A, Kawashima R (2013b) White matter structures associated with empathizing and systemizing in young adults. Neuroimage 77:222–236

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T, Yamamoto Y, Hanawa S, Araki T, Hashizume H, Sassa Y, Kawashima R (2013c) Association of hair iron levels with creativity and psychological variables related to creativity. Front Hum Neurosci 7:1–9

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Hashizume H, Sekiguchi A, Kotozaki Y, Nakagawa S, Miyauchi CM, Sassa Y, Kawashima R (2015a) Working memory training impacts the mean diffusivity in the dopaminergic system. Brain Struct Funct 220:3101–3111

    Article  CAS  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Sekuguchi A, Hashizume H, Nouchi R, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K, Nakagawa S, Nagase T, Kunitoki K, Kawashima R (2015b) Mean diffusivity of globus pallidus associated with verbal creativity measured by divergent thinking and creativity-related temperaments in young healthy adults. Hum Brain Mapp 36:1808–1827

    Article  PubMed  PubMed Central  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Hashizume H, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K, Seishu N, Tomomi N, Kunitoki K, Kawashima R (2015c) Degree centrality and fractional amplitude of low-frequency oscillations associated with Stroop interference. Neuroimage 119:197–209

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T, Yamamoto Y, Hanawa S, Araki T, Hashizume H, Sassa Y, Kawashima R (2015d) Brain structures in the sciences and humanities. Brain Struct Funct 220:3295–3305

    Article  PubMed  Google Scholar 

  • Takeuchi H, Taki Y, Hashizume H, Asano K, Asano M, Sassa Y, Yokota S, Kotozaki Y, Nouchi R, Kawashima R (2016a) Impact of videogame play on the brain’s microstructural properties: cross-sectional and longitudinal analyses. Mol Psychiatry 21:1781–1789

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Takeuchi H, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T (2016b) Mean diffusivity of basal ganglia and thalamus specifically associated with motivational states among mood states. Brain Struct Funct:1–11

  • Takeuchi H, Taki Y, Nouchi R, Yokoyama R, Kotozaki Y, Nakagawa S, Sekiguchi A, Iizuka K, Yamamoto Y, Hanawa S, Araki T, Miyauchi CM, Shinada T, Sakaki K, Sassa Y, Nozawa T, Ikeda S, Yokota S, Daniele M, Kawashima R (2017) Creative females have larger white matter structures: evidence from a large sample study. Hum Brain Mapp 38:414–430

    Article  PubMed  Google Scholar 

  • Taki Y, Hashizume H, Sassa Y, Takeuchi H, Wu K, Asano M, Asano K, Fukuda H, Kawashima R (2011) Correlation between gray matter density-adjusted brain perfusion and age using brain MR images of 202 healthy children. Hum Brain Mapp 32:1973–1985

    Article  PubMed  Google Scholar 

  • Tanaka K, Okamoto K, Tanaka H (2003) Manual of new tanaka B type intelligence test. Kaneko Syobo, Tokyo

    Google Scholar 

  • Tobi EW, Goeman JJ, Monajemi R, Gu H, Putter H, Zhang Y, Slieker RC, Stok AP, Thijssen PE, Müller F (2014) DNA methylation signatures link prenatal famine exposure to growth and metabolism. Nat Commun 5:5592

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Turnlund JR, Jacob RA, Keen CL, Strain J, Kelley DS, Domek JM, Keyes WR, Ensunsa JL, Lykkesfeldt J, Coulter J (2004) Long-term high copper intake: effects on indexes of copper status, antioxidant status, and immune function in young men. Am J Clin Nutr 79:1037–1044

    Article  CAS  PubMed  Google Scholar 

  • Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289

    Article  CAS  PubMed  Google Scholar 

  • Vir SC, Love A (1981) Zinc and copper nutriture of women taking oral contraceptive agents. Am J Clin Nutr 34:1479–1483

    Article  CAS  PubMed  Google Scholar 

  • Wilson L (2003) Nutritional balancing and hair tissue mineral analysis. Explore-Mount Vernon 12:42–53

    Google Scholar 

  • Yokoyama K (2005) POMS Shortened Version (in Japanese). Kanekoshobo, Tokyo

    Google Scholar 

  • Zecca L, Zucca F, Toscani M, Adorni F, Giaveri G, Rizzio E, Gallorini M (2005) Iron, copper and their proteins in substantia nigra of human brain during aging. J Radioanal Nuclear Chem 263:733–737

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We respectfully thank Yuki Yamada for operating the MRI scanner, and Haruka Nouchi for being an examiner of psychological tests. We also thank study participants, the other examiners of psychological tests, and all of our colleagues in Institute of Development, Aging and Cancer and in Tohoku University for their support. This study was supported by a Grant-in-Aid for Young Scientists (B) (KAKENHI 23700306) and a Grant-in-Aid for Young Scientists (A) (KAKENHI 25700012) from the Ministry of Education, Culture, Sports, Science, and Technology. The authors would like to thank Enago (http://www.enago.jp) for the English language review. We would like to thank La Belle Vie Inc. and its employees for the hair mineral level analyses as well as Dr. Yasuda and Dr. Sonobe for their technical advice regarding the analyses.

Author information

Authors and Affiliations

  1. Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, 4-1 Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan

    Hikaru Takeuchi, Yasuyuki Taki, Susumu Yokota, Yuko Sassa & Ryuta Kawashima

  2. Division of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan

    Yasuyuki Taki & Atsushi Sekiguchi

  3. Department of Radiology and Nuclear Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Yasuyuki Taki

  4. Creative Interdisciplinary Research Division, Frontier Research Institute for Interdisciplinary Science, Tohoku University, Sendai, Japan

    Rui Nouchi

  5. Human and Social Response Research Division, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan

    Rui Nouchi

  6. Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Rui Nouchi, Kohei Sakaki & Ryuta Kawashima

  7. School of Medicine, Kobe University, Kobe, Japan

    Ryoichi Yokoyama

  8. Division of Clinical research, Medical-Industry Translational Research Center, Fukushima Medical University School of Medicine, Fukushima, Japan

    Yuka Kotozaki

  9. Department of Human Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Seishu Nakagawa, Yuki Yamamoto, Sugiko Hanawa & Ryuta Kawashima

  10. Division of Psychiatry, Tohoku Medical and Pharmaceutical University, Sendai, Japan

    Seishu Nakagawa

  11. Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan

    Atsushi Sekiguchi

  12. Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan

    Kunio Iizuka

  13. ADVANTAGE Risk Management Co., Ltd, Tokyo, Japan

    Tsuyoshi Araki

  14. Department of Language Sciences, Graduate School of Humanities, Tokyo Metropolitan University, Tokyo, Japan

    Carlos Makoto Miyauchi

  15. Collaborative Research Center for Happiness Co-Creation Society through Intelligent Communications, Tokyo Institute of Technology, Tokyo, Japan

    Takayuki Nozawa

  16. Department of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Shigeyuki Ikeda

  17. Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, UK

    Magistro Daniele

Authors
  1. Hikaru Takeuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yasuyuki Taki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui Nouchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ryoichi Yokoyama
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuka Kotozaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Seishu Nakagawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Atsushi Sekiguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Kunio Iizuka
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yuki Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Sugiko Hanawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Tsuyoshi Araki
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Carlos Makoto Miyauchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Kohei Sakaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Takayuki Nozawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Shigeyuki Ikeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Susumu Yokota
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Magistro Daniele
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Yuko Sassa
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Ryuta Kawashima
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hikaru Takeuchi.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 196 KB)

Supplementary material 2 (TIF 112 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Takeuchi, H., Taki, Y., Nouchi, R. et al. Association of copper levels in the hair with gray matter volume, mean diffusivity, and cognitive functions. Brain Struct Funct 224, 1203–1217 (2019). https://doi.org/10.1007/s00429-019-01830-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00429-019-01830-y

Keywords

Search

Navigation