Weak correlations between body height and several brain metrics in healthy elderly subjects.

body height cerebellar white matter cerebellum cortex cortical surface area cortical thickness cortical volume intracranial volume normal-appearing cerebral white matter subcortical grey matter total brain volume white matter hyperintensity

Journal

The European journal of neuroscience
ISSN: 1460-9568
Titre abrégé: Eur J Neurosci
Pays: France
ID NLM: 8918110

Informations de publication

Date de publication:
11 2019
Historique:
received: 13 01 2019
revised: 18 06 2019
accepted: 27 06 2019
pubmed: 7 7 2019
medline: 1 9 2020
entrez: 7 7 2019
Statut: ppublish

Résumé

The question whether body height is related to different brain size measures has recently gained renewed interest as some studies have reported that body height correlates with intelligence and several brain size measures. In this study, we re-evaluated this question by examining the relationship between body height and different brain size measures including intracranial volume, total brain volume, total cortical surface area, total cortical volume, volume of normal-appearing white matter, white matter hyperintensity, cortical surface area, cortical thickness, subcortical grey matter volume, cerebellar cortex and cerebellar white matter in a relatively large sample (n = 216) of physically and cognitively healthy elderly subjects (mean age 71 years, age range 65-85 years). We identified small correlations (r = .11-.19) between body height and seven out of 10 brain metrics (total brain volume, cortical surface area, cortical volume, subcortical volume, normal-appearing white matter volume and cerebellar grey as well as white matter volumes) when controlling for sex and age. Based on these small relationships between body height and various brain size measures, we discuss the possible reasons and theoretical problems for these small relationships.

Identifiants

pubmed: 31278790
doi: 10.1111/ejn.14501
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3578-3589

Informations de copyright

© 2019 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Références

Adams, H. H. H., Hibar, D. P., Chouraki, V., Stein, J. L., Nyquist, P. A., Rentería, M. E., … Thompson, P. M. (2016). Novel genetic loci underlying human intracranial volume identified through genome-wide association. Nature Neuroscience, 19, 1569-1582. https://doi.org/10.1038/nn.4398
Annett, M. (1970). A classification of hand preference by association analysis. British Journal of Psychology, 61, 303-321. https://doi.org/10.1111/j.2044-8295.1970.tb01248.x
Bhatt, R. R., Gupta, A., Labus, J. S., Zeltzer, L. K., Tsao, J. C., Shulman, R. J., & Tillisch, K. (2018). Altered brain structure and functional connectivity and its relation to pain perception in girls with irritable bowel syndrome. Psychosomatic Medicine, 81, 146-154.
Chirachariyavej, T., Ouyswat, K., Sanggarnjanavanich, S., Tiensuwan, M., Peonim, V., & Sirikulchayanonta, V. (2006). Normal internal organ weight of Thai adults correlated to body length and body weight. Journal of the Medical Association of Thailand, 89, 1702-1712.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159. https://doi.org/10.1037/0033-2909.112.1.155
Costafreda, S. G., Dinov, I. D., Tu, Z., Shi, Y., Liu, C.-Y., Kloszewska, I., … Simmons, A. (2011). Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment. NeuroImage, 56, 212-219. https://doi.org/10.1016/j.neuroimage.2011.01.050
Destrieux, C., Fischl, B., Dale, A., & Halgren, E. (2010). Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. NeuroImage, 53, 1-15. https://doi.org/10.1016/j.neuroimage.2010.06.010
Erickson, K. I., Voss, M. W., Prakash, R. S., Basak, C., Szabo, A., Chaddock, L., … Kramer, A. F. (2011). Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences of the United States of America, 108, 3017-3022. https://doi.org/10.1073/pnas.1015950108
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., … Dale, A. M. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33, 341-355. https://doi.org/10.1016/S0896-6273(02)00569-X
Fischl, B., Salat, D. H., van der Kouwe, A. J., Makris, N., Segonne, F., Quinn, B. T., & Dale, A. M. (2004). Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23(Suppl 1), S69-S84. https://doi.org/10.1016/j.neuroimage.2004.07.016
Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Segonne, F., Salat, D. H., … Dale, A. M. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14, 11-22. https://doi.org/10.1093/cercor/bhg087
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. ‎Journal of Psychiatric Research, 12, 189-198.
Garby, L., Lammert, O., Kock, K. F., & Thobo-Carlsen, B. (1993). Weights of brain, heart, liver, kidneys, and spleen in healthy and apparently healthy adult Danish subjects. American Journal of Human Biology, 5, 291-296. https://doi.org/10.1002/(ISSN)1520-6300
Gaser, C., Franke, K., Klöppel, S., Koutsouleris, N., Sauer, H., & Alzheimer's, Disease Neuroimaging Initiative (2013). BrainAGE in mild cognitive impaired patients: Predicting the conversion to Alzheimer's disease. PLoS One, 8, e67346. https://doi.org/10.1371/journal.pone.0067346
Grömping, U. (2006). Relative importance for linear regression in R: The package relaimpo. Journal of Statistical Software, 17, 1-27.
Hänggi, J., Fövenyi, L., Liem, F., Meyer, M., & Jäncke, L. (2014). The hypothesis of neuronal interconnectivity as a function of brain size-a general organization principle of the human connectome. Frontiers in Human Neuroscience, 8, 915.
Hartmann, P., Ramseier, A., Gudat, F., Mihatsch, M. J., & Polasek, W. (1994). [Normal weight of the brain in adults in relation to age, sex, body height and weight]. Der Pathologe, 15, 165-170. https://doi.org/10.1007/s002920050040
Haug, H. (1984). Der Einfluß der säkularen Akzeleration auf das Hirngewicht des Menschen und dessen Änderung während der Alterung. Gegenbaurs Morphologisches Jahrbuch, 130, 481-500.
Hedman, A. M., van Haren, N. E. M., Schnack, H. G., Kahn, R. S., & Hulshoff Pol, H. E. (2012). Human brain changes across the life span: A review of 56 longitudinal magnetic resonance imaging studies. Human Brain Mapping, 33, 1987-2002. https://doi.org/10.1002/hbm.21334
Heymsfield, S. B., Chirachariyavej, T., Rhyu, I. J., Roongpisuthipong, C., Heo, M., & Pietrobelli, A. (2009). Differences between brain mass and body weight scaling to height: Potential mechanism of reduced mass-specific resting energy expenditure of taller adults. Journal of Applied Physiology, 106, 40-48. https://doi.org/10.1152/japplphysiol.91123.2008
Heymsfield, S. B., Gallagher, D., Mayer, L., Beetsch, J., & Pietrobelli, A. (2007). Scaling of human body composition to stature: New insights into body mass index. American Journal of Clinical Nutrition, 86, 82-91. https://doi.org/10.1093/ajcn/86.1.82
Hirsiger, S., Koppelmans, V., Mérillat, S., Liem, F., Erdeniz, B., Seidler, R. D., & Jäncke, L. (2015). Structural and functional connectivity in healthy aging: Associations for cognition and motor behavior. Human Brain Mapping, 37, 855-867.
Ho, K. C., Roessmann, U., Straumfjord, J. V., & Monroe, G. (1980). Analysis of brain weight. II. Adult brain weight in relation to body height, weight, and surface area. Archives of Pathology and Laboratory Medicine, 104, 640-645.
Holloway, R. L. (1980). Within-species brain-body weight variability: A reexamination of the Danish data and other primate species. American Journal of Physical Anthropology, 53, 109-121. https://doi.org/10.1002/(ISSN)1096-8644
Jäncke, L. (2009). The plastic human brain. Restorative Neurology and Neuroscience, 27, 521-538.
Jäncke, L., Liem, F., & Merillat, S. (2019). Scaling of brain compartments to brain size. NeuroReport, 30, 573-579. https://doi.org/10.1097/WNR.0000000000001249
Jäncke, L., Mérillat, S., Liem, F., & Hänggi, J. (2015). Brain size, sex, and the aging brain. Human Brain Mapping, 36, 150-169. https://doi.org/10.1002/hbm.22619
Jäncke, L., Staiger, J. F., Schlaug, G., Huang, Y., & Steinmetz, H. (1997). The relationship between corpus callosum size and forebrain volume. Cerebral Cortex, 7, 48-56. https://doi.org/10.1093/cercor/7.1.48
Jäncke, L., & Steinmetz, H. (1998). Brain size: A possible source of interindividual variability in corpus callosum morphology [WWW Document]. The role of the human corpus callosum in sensory motor integration: Anatomy, physiology, and behavior; individual differences and clinical applications. Retrieved from http://cogprints.org/86/2/nato-cc.pdf
Jerison, H. J. (1979). The evolution of diversity in brain size. In M. E. Hahn, C. Jensen, & B. C. Dudek (Eds.), Development and evolution in brain size (pp. 29-57). New York, NY: Academic Press. https://doi.org/10.1016/B978-0-12-314650-2.50009-4
Jurgens, H. W., Aune, I. A., & Pieper, U. (1990). International data on anthropometry. Geneva, Switzerland: International Labour Office.
Keller, M. C., Garver-Apgar, C. E., Wright, M. J., Martin, N. G., Corley, R. P., Stallings, M. C., … Zietsch, B. P. (2013). The genetic correlation between height and IQ: Shared genes or assortative mating? PLoS Genetics, 9, e1003451. https://doi.org/10.1371/journal.pgen.1003451
Koh, I., Lee, M. S., Lee, N. J., Park, K. W., Kim, K. H., Kim, H., & Rhyu, I. J. (2005). Body size effect on brain volume in Korean youth. NeuroReport, 16, 2029-2032. https://doi.org/10.1097/00001756-200512190-00012
Krauth, J. (1988). Distribution-free statistics: An application-oriented approach. New York, NY: Elsevier Science Ltd.
Kurth, F., Jancke, L., & Luders, E. (2017). Sexual dimorphism of Broca's region: More gray matter in female brains in Brodmann areas 44 and 45. Journal of Neuroscience Research, 95, 626-632. https://doi.org/10.1002/jnr.23898
Lai, C.-Q. (2006). How much of human height is genetic and how much is due to nutrition [WWW Document]. Retrieved from https://www.scientificamerican.com/article/how-much-of-human-height/
Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Jancke, L., Steinmetz, H., & Toga, A. W. (2004). Gender differences in cortical complexity. Nature Neuroscience, 7, 799-800. https://doi.org/10.1038/nn1277
Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Woods, R. P., Deluca, H., … Toga, A. W. (2006). Gender effects on cortical thickness and the influence of scaling. Human Brain Mapping, 27, 314-324. https://doi.org/10.1002/(ISSN)1097-0193
Luders, E., Narr, K. L., Thompson, P. M., & Toga, A. W. (2009). Neuroanatomical correlates of Intelligence. Intelligence, 37, 156-163. https://doi.org/10.1016/j.intell.2008.07.002
Luders, E., Narr, K. L., Thompson, P. M., Woods, R. P., Rex, D. E., Jancke, L., … Toga, A. W. (2005). Mapping cortical gray matter in the young adult brain: Effects of gender. NeuroImage, 26, 493-501. https://doi.org/10.1016/j.neuroimage.2005.02.010
Lüders, E., Steinmetz, H., & Jäncke, L. (2002). Brain size and grey matter volume in the healthy human brain. NeuroReport, 13, 2371-2374. https://doi.org/10.1097/00001756-200212030-00040
Lukies, M. W., Watanabe, Y., Tanaka, H., Takahashi, H., Ogata, S., Omura, K., … Osaka University Twin Research Group (2017). Heritability of brain volume on MRI in middle to advanced age: A twin study of Japanese adults. PLoS One, 12, e0175800.
Madhyastha, T., Mérillat, S., Hirsiger, S., Bezzola, L., Liem, F., Grabowski, T., & Jäncke, L. (2014). Longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging. Human Brain Mapping, 35, 4544-4555. https://doi.org/10.1002/hbm.22493
Marioni, R. E., Batty, G. D., Hayward, C., Kerr, S. M., Campbell, A., Hocking, L. J., … Deary, I. J. (2014). Common genetic variants explain the majority of the correlation between height and intelligence: The generation Scotland study. Behavior Genetics, 44, 91-96. https://doi.org/10.1007/s10519-014-9644-z
Mattson, M. P., Chan, S. L., & Duan, W. (2002). Modification of brain aging and neurodegenerative disorders by genes, diet, and behavior. Physiological Reviews, 82, 637-672. https://doi.org/10.1152/physrev.00004.2002
Miskolczi, C., Halász, J., & Mikics, É. (2018). Changes in neuroplasticity following early-life social adversities: The possible role of brain-derived neurotrophic factor. Pediatric Research, 85, 225-233.
Münte, T. F., Altenmüller, E., & Jäncke, L. (2002). The musician's brain as a model of neuroplasticity. Nature Reviews Neuroscience, 3, 473-478. https://doi.org/10.1038/nrn843
NASA Reference Publication (1978) Anthropometric source book. Volume I: Anthropometry for designers. Anthropology Research Project, Yellow Springs, OH: NASA Reference Publication.
NCD Risk Factor Collaboration (NCD-RisC) (2016). A century of trends in adult human height. Elife, 5, e13410.
Nopoulos, P., Flaum, M., O'Leary, D., & Andreasen, N. C. (2000). Sexual dimorphism in the human brain: Evaluation of tissue volume, tissue composition and surface anatomy using magnetic resonance imaging. Psychiatry Research, 98, 1-13. https://doi.org/10.1016/S0925-4927(99)00044-X
Oltmanns, J., Godde, B., Winneke, A. H., Richter, G., Niemann, C., Voelcker-Rehage, C., … Staudinger, U. M. (2017). Don't lose your brain at work - The role of recurrent novelty at work in cognitive and brain aging. Frontiers in Psychology, 8, 117.
Paigen, B., Goldman, L. R., Magnant, M. M., Highland, J. H., & Steegmann, A. T. Jr (1987). Growth of children living near the hazardous waste site, Love Canal. Human Biology, 59, 489-508.
Pakkenberg, H., & Voigt, J. (1964). Brain weight of the Danes: Forensic material. Acta Anatomica, 56, 297-307. https://doi.org/10.1159/000142510
Pascual-Leone, A., Amedi, A., Fregni, F., & Merabet, L. B. (2005). The plastic human brain cortex. Annual Review of Neuroscience, 28, 377-401. https://doi.org/10.1146/annurev.neuro.27.070203.144216
Passingham, R. E. (1979). Brain size and intelligence in man. Brain, Behavior and Evolution, 16, 253-270. https://doi.org/10.1159/000121868
Peters, M., Jäncke, L., Staiger, J. F., Schlaug, G., Huang, Y., & Steinmetz, H. (1998). Unsolved problems in comparing brain sizes in Homo sapiens. Brain and Cognition, 37, 254-285. https://doi.org/10.1006/brcg.1998.0983
Posthuma, D., de Geus, E. J., Neale, M. C., Hulshoff Pol, H. E., Baaré, W. E. C., Kahn, R. S., & Boomsma, D. (2000). Multivariate genetic analysis of brain structure in an extended twin design. Behavior Genetics, 30, 311-319. https://doi.org/10.1023/A:1026501501434
R Core Team (2013). R: A language and environment for statistical computing.
Raz, N., Gunning, F. M., Head, D., Dupuis, J. H., McQuain, J., Briggs, S. D., … Acker, J. D. (1997). Selective aging of the human cerebral cortex observed in vivo: Differential vulnerability of the prefrontal gray matter. Cerebral Cortex, 7, 268-282. https://doi.org/10.1093/cercor/7.3.268
Reardon, P. K., Seidlitz, J., Vandekar, S., Liu, S., Patel, R., Park, M. T. M., … Raznahan, A. (2018). Normative brain size variation and brain shape diversity in humans. Science, 360, 1222-1227. https://doi.org/10.1126/science.aar2578
Ringo, J. L., Doty, R. W., Demeter, S., & Simard, P. Y. (1994). Time is of the essence: A conjecture that hemispheric specialization arises from interhemispheric conduction delay. Cerebral Cortex, 4, 331-343. https://doi.org/10.1093/cercor/4.4.331
Roth, G., & Dicke, U. (2005). Evolution of the brain and intelligence. Trends in Cognitive Sciences, 9, 250-257. https://doi.org/10.1016/j.tics.2005.03.005
Russ, T. C., Kivimäki, M., Starr, J. M., Stamatakis, E., & Batty, G. D. (2014). Height in relation to dementia death: Individual participant meta-analysis of 18 UK prospective cohort studies. British Journal of Psychiatry, 205, 348-354. https://doi.org/10.1192/bjp.bp.113.142984
Sammallahti, S., Pyhälä, R., Lahti, M., Lahti, J., Pesonen, A.-K., Heinonen, K., … Räikkönen, K. (2014). Infant growth after preterm birth and neurocognitive abilities in young adulthood. Journal of Pediatrics, 165, 1109-1115.e3. https://doi.org/10.1016/j.jpeds.2014.08.028
Silventoinen, K., Iacono, W. G., Krueger, R., & McGue, M. (2012). Genetic and environmental contributions to the association between anthropometric measures and IQ: A study of Minnesota twins at age 11 and 17. Behavior Genetics, 42, 393-401. https://doi.org/10.1007/s10519-011-9521-y
Skullerud, K. (1985). Variations in the size of the human brain. Influence of age, sex, body length, body mass index, alcoholism, Alzheimer changes, and cerebral atherosclerosis. Acta Neurologica Scandinavica. Supplementum, 102, 1-94.
Spann, W., & Dustmann, H. O. (1965). Weight of the human brain and its dependence on age, body length, cause of death and occupation. Deutsche Gesellschaft für Gerichtliche und Soziale Medizin, 56, 299-317.
Sturm, W., Horn, W., & Willmes, K. (1993). Leistungsprüfsystem Für 50-90jährige: (LPS 50+); Handanweisung. Göttingen, Germany: Hogrefe, Verlag für Psychologie.
Sudfeld, C. R., McCoy, D. C., Danaei, G., Fink, G., Ezzati, M., Andrews, K. G., & Fawzi, W. W. (2015). Linear growth and child development in low- and middle-income countries: A meta-analysis. Pediatrics, 135, e1266-e1275. https://doi.org/10.1542/peds.2014-3111
Sudfeld, C. R., McCoy, D. C., Fink, G., Muhihi, A., Bellinger, D. C., Masanja, H., … Fawzi, W. W. (2015). Malnutrition and its determinants are associated with suboptimal cognitive, communication, and motor development in Tanzanian children. Journal of Nutrition, 145, 2705-2714. https://doi.org/10.3945/jn.115.215996
Taki, Y., Hashizume, H., Sassa, Y., Takeuchi, H., Asano, M., Asano, K., … Kawashima, R. (2012). Correlation among body height, intelligence, and brain gray matter volume in healthy children. NeuroImage, 59, 1023-1027. https://doi.org/10.1016/j.neuroimage.2011.08.092
Valizadeh, S. A., Hänggi, J., Mérillat, S., & Jäncke, L. (2017). Age prediction on the basis of brain anatomical measures. Human Brain Mapping, 38, 997-1008. https://doi.org/10.1002/hbm.23434
Valizadeh, S. A., Liem, F., Mérillat, S., Hänggi, J., & Jäncke, L. (2018). Identification of individual subjects on the basis of their brain anatomical features. Scientific Reports, 8, 5611. https://doi.org/10.1038/s41598-018-23696-6
Voelcker-Rehage, C., Godde, B., & Staudinger, U. M. (2010). Physical and motor fitness are both related to cognition in old age. European Journal of Neuroscience, 31, 167-176. https://doi.org/10.1111/j.1460-9568.2009.07014.x
Voss, M. W., Heo, S., Prakash, R. S., Erickson, K. I., Alves, H., Chaddock, L., … Kramer, A. F. (2013). The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: Results of a one-year exercise intervention. Human Brain Mapping, 34, 2972-2985. https://doi.org/10.1002/hbm.22119
Vuoksimaa, E., Panizzon, M. S., Franz, C. E., Fennema-Notestine, C., Hagler Jr, D. J., Lyons, M. J., … Kremen, W. S. (2018). Brain structure mediates the association between height and cognitive ability. Brain Structure and Function, 223, 3487-3494. https://doi.org/10.1007/s00429-018-1675-4
Wickett, J. C., Vernon, P. A., & Lee, D. H. (1994). In vivo brain size, head perimeter, and intelligence in a sample of healthy adult females. Personality and Individual Differences, 16, 831-838. https://doi.org/10.1016/0191-8869(94)90227-5
Widdowson, E. M. (1951). Mental contentment and physical growth. Lancet, 1, 1316-1318. https://doi.org/10.1016/S0140-6736(51)91795-3
Willerman, L., Schultz, R., Neal Rutledge, J., & Bigler, E. D. (1991). In vivo brain size and intelligence. Intelligence, 15, 223-228. https://doi.org/10.1016/0160-2896(91)90031-8
Witelson, S. F., Beresh, H., & Kigar, D. L. (2006). Intelligence and brain size in 100 postmortem brains: Sex, lateralization and age factors. Brain, 129, 386-398. https://doi.org/10.1093/brain/awh696
Zatorre, R. J., Fields, R. D., & Johansen-Berg, H. (2012). Plasticity in gray and white: Neuroimaging changes in brain structure during learning. Nature Neuroscience, 15, 528-536. https://doi.org/10.1038/nn.3045
Ziegler, G., Dahnke, R., Jäncke, L., Yotter, R. A., May, A., & Gaser, C. (2012). Brain structural trajectories over the adult lifespan. Human Brain Mapping, 33, 2377-2389. https://doi.org/10.1002/hbm.21374
Zöllig, J., Mérillat, S., Eschen, A., Röcke, C., Martin, M., & Jäncke, L. (2011). Plasticity and imaging research in healthy aging: Core ideas and profile of the International Normal Aging and Plasticity Imaging Center (INAPIC). Gerontology, 57, 190-192.

Auteurs

Lutz Jäncke (L)

Division Neuropsychology, Institute of Psychology, University of Zurich, Zurich, Switzerland.
University Research Priority Program (URPP) "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.

Franz Liem (F)

Division Neuropsychology, Institute of Psychology, University of Zurich, Zurich, Switzerland.
University Research Priority Program (URPP) "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.

Susan Merillat (S)

Division Neuropsychology, Institute of Psychology, University of Zurich, Zurich, Switzerland.
University Research Priority Program (URPP) "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.

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