Skip to main content

Advertisement

Log in

Mobility decline in the elderly relates to lesion accrual in the splenium of the corpus callosum

  • Published:
AGE Aims and scope Submit manuscript

Abstract

In a previous cross-sectional study on baseline data, we demonstrated that the volume of brain white matter hyperintensities (WMH) in the splenium of corpus callosum (SCC) predicted the current mobility function of older persons. The primary aim of this follow-up study was to determine the relation of WMH volume change in SCC (SCC-∆WMH) with change in mobility measures. A secondary aim was to characterize the global and regional progression of WMH. Mobility function and WMH burden were evaluated at baseline and at 2 years in 77 community-dwelling individuals (baseline age, 82 ± 4). Regional WMH in SCC, as well as genu and body of corpus callosum, subregions of corona radiata, and superior longitudinal fasciculus were determined using a white matter parcellation atlas. The total WMH volume increased 3.3 ± 3.5 ml/year, mainly through enlargement. Significant WMH increases were observed in all selected regions, particularly within the corona radiata. While at baseline and follow-up we observed correlations between WMH burden and several measures of mobility, longitudinal change correlated only with change in chair rise (CR). SCC-∆WMH showed the highest correlation (r = −0.413, p = 0.0002) and was the best regional predictor of CR decline (OR = 1.5, r 2 = 0.3). The SCC-∆WMH was more than five times larger in the CR-decline group compared to the no-decline group (p = 0.0003). The SCC-∆WMH (top quartile) showed a higher sensitivity/specificity for CR decline compared to change in total WMH, 63/88% versus 52/84%, respectively. The findings suggest that accrual of WMHs in posterior areas of the brain supporting inter-hemispheric integration and processing of visual–spatial information is a mechanism contributing to age-related mobility deterioration.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Baezner H, Blahak C, Poggesi A, Pantoni L, Inzitari D, Chabriat H, Erkinjuntti T, Fazekas F, Ferro JM, Langhorne P, O'Brien J, Scheltens P, Visser MC, Wahlund LO, Waldemar G, Wallin A, Hennerici MG (2008) Association of gait and balance disorders with age-related white matter changes: the LADIS Study. Neurology 70(12):935–942

    Article  PubMed  CAS  Google Scholar 

  • Baloh RW, Vinters HV (1995) White matter lesions and disequilibrium in older people. II. Clinicopathologic correlation. Arch Neurol 52(10):975–981

    Article  PubMed  CAS  Google Scholar 

  • Baloh RW, Yue Q, Socotch TM, Jacobson KM (1995) White matter lesions and disequilibrium in older people. I. Case–control comparison. Arch Neurol 52(10):970–974

    Article  PubMed  CAS  Google Scholar 

  • Baloh RW, Ying SH, Jacobson KM (2003) A longitudinal study of gait and balance dysfunction in normal older people. Arch Neurol 60(6):835–839

    Article  PubMed  Google Scholar 

  • Benson RR, Guttmann CR, Wei X, Warfield SK, Hall C, Schmidt JA, Kikinis R, Wolfson LI (2002) Older people with impaired mobility have specific loci of periventricular abnormality on MRI. Neurology 58(1):48–55

    PubMed  CAS  Google Scholar 

  • Borger LL, Whitney SL, Redfern MS, Furman JM (1999) The influence of dynamic visual environments on postural sway in the elderly. J Vestib Res 9(3):197–205

    PubMed  CAS  Google Scholar 

  • Camicioli R, Moore MM, Sexton G, Howieson DB, Kaye JA (1999) Age-related brain changes associated with motor function in healthy older people. J Am Geriatr Soc 47(3):330–334

    PubMed  CAS  Google Scholar 

  • DeCarli C, Fletcher E, Ramey V, Harvey D, Jagust WJ (2005) Anatomical mapping of white matter hyperintensities (WMH): exploring the relationships between periventricular WMH, deep WMH, and total WMH burden. Stroke 36(1):50–55

    Article  PubMed  Google Scholar 

  • Fazekas F, Kleinert R, Offenbacher H, Schmidt R, Kleinert G, Payer F, Radner H, Lechner H (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43(9):1683–1689

    PubMed  CAS  Google Scholar 

  • Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3):341–355

    Article  PubMed  CAS  Google Scholar 

  • Franch O, Calandre L, Alvarez-Linera J, Louis ED, Bermejo-Pareja F, Benito-Leon J (2009) Gait disorders of unknown cause in the elderly: clinical and MRI findings. J Neurol Sci 280(1–2):84–86

    Article  PubMed  Google Scholar 

  • Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49(2):M85–94

    PubMed  CAS  Google Scholar 

  • Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB (1995) Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med 332(9):556–561

    Article  PubMed  CAS  Google Scholar 

  • Guttmann CR, Benson R, Warfield SK, Wei X, Anderson MC, Hall CB, Abu-Hasaballah K, Mugler JP 3rd, Wolfson L (2000) White matter abnormalities in mobility-impaired older persons. Neurology 54(6):1277–1283

    PubMed  CAS  Google Scholar 

  • Jenkinson M, Smith S (2001) A global optimisation method for robust affine registration of brain images. Med Image Anal 5(2):143–156

    Article  PubMed  CAS  Google Scholar 

  • Kuo HK, Lipsitz LA (2004) Cerebral white matter changes and geriatric syndromes: is there a link? J Gerontol A Biol Sci Med Sci 59(8):818–826

    Article  PubMed  Google Scholar 

  • Masdeu JC, Wolfson L, Lantos G, Tobin JN, Grober E, Whipple R, Amerman P (1989) Brain white-matter changes in the elderly prone to falling. Arch Neurol 46(12):1292–1296

    Article  PubMed  CAS  Google Scholar 

  • Mori S, Oishi K, Jiang H, Jiang L, Li X, Akhter K, Hua K, Faria AV, Mahmood A, Woods R, Toga AW, Pike GB, Neto PR, Evans A, Zhang J, Huang H, Miller MI, van Zijl P, Mazziotta J (2008) Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. Neuroimage 40(2):570–582

    Article  PubMed  Google Scholar 

  • Moscufo N, Guttmann CRG, Meier D, Csapo I, Hildenbrand PG, Healy BC, Schmidt JA, Wolfson L (2011) Brain regional lesion burden and impaired mobility in the elderly. Neurobiol Aging 32(4):646–654

    Google Scholar 

  • Pantoni L, Garcia JH (1997) Pathogenesis of leukoaraiosis: a review. Stroke 28(3):652–659

    Article  PubMed  CAS  Google Scholar 

  • Pohl KM, Bouix S, Kikinis R, Grimson WEL (2004) Anatomical guided segmentation with non-stationary tissue class distributions in an expectation–maximization framework. IEEE International Symposium on Biomedical Imaging: From Nano to Macro., Arlington, VA, USA, pp 81–84

  • Pyykko I, Jantti P, Aalto H (1990) Postural control in elderly subjects. Age Ageing 19(3):215–221

    Article  PubMed  CAS  Google Scholar 

  • Rosano C, Sigurdsson S, Siggeirsdottir K, Phillips CL, Garcia M, Jonsson PV, Eiriksdottir G, Newman AB, Harris TB, van Buchem MA, Gudnason V, Launer LJ (2008) Magnetization transfer imaging, white matter hyperintensities, brain atrophy and slower gait in older men and women. Neurobiol Aging 31(7):1197–1204

    Article  PubMed  Google Scholar 

  • Sachdev PS, Wen W, Christensen H, Jorm AF (2005) White matter hyperintensities are related to physical disability and poor motor function. J Neurol Neurosurg Psychiatry 76(3):362–367

    Article  PubMed  CAS  Google Scholar 

  • Sachdev P, Wen W, Chen X, Brodaty H (2007) Progression of white matter hyperintensities in elderly individuals over 3 years. Neurology 68(3):214–222

    Article  PubMed  Google Scholar 

  • Schmidt R, Enzinger C, Ropele S, Schmidt H, Fazekas F (2003) Progression of cerebral white matter lesions: 6-year results of the Austrian Stroke Prevention Study. Lancet 361(9374):2046–2048

    Article  PubMed  Google Scholar 

  • Schmidt R, Scheltens P, Erkinjuntti T, Pantoni L, Markus HS, Wallin A, Barkhof F, Fazekas F (2004) White matter lesion progression: a surrogate endpoint for trials in cerebral small-vessel disease. Neurology 63(1):139–144

    PubMed  CAS  Google Scholar 

  • Silbert LC, Nelson C, Howieson DB, Moore MM, Kaye JA (2008) Impact of white matter hyperintensity volume progression on rate of cognitive and motor decline. Neurology 71(2):108–113

    Article  PubMed  CAS  Google Scholar 

  • Sled JG, Zijdenbos AP, Evans AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17(1):87–97

    Article  PubMed  CAS  Google Scholar 

  • Srikanth V, Beare R, Blizzard L, Phan T, Stapleton J, Chen J, Callisaya M, Martin K, Reutens D (2009) Cerebral white matter lesions, gait, and the risk of incident falls: a prospective population-based study. Stroke 40(1):175–180

    Article  PubMed  Google Scholar 

  • Srikanth V, Phan TG, Chen J, Beare R, Stapleton JM, Reutens DC (2010) The location of white matter lesions and gait—a voxel-based study. Ann Neurol 67(2):265–269

    Article  PubMed  Google Scholar 

  • Taylor WD, MacFall JR, Provenzale JM, Payne ME, McQuoid DR, Steffens DC, Krishnan KR (2003) Serial MR imaging of volumes of hyperintense white matter lesions in elderly patients: correlation with vascular risk factors. AJR Am J Roentgenol 181(2):571–576

    PubMed  Google Scholar 

  • ten Dam VH, van den Heuvel DM, de Craen AJ, Bollen EL, Murray HM, Westendorp RG, Blauw GJ, van Buchem MA (2007) Decline in total cerebral blood flow is linked with increase in periventricular but not deep white matter hyperintensities. Radiology 243(1):198–203

    Article  PubMed  Google Scholar 

  • Tinetti M (1986) Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc 34(2):119–126

    PubMed  CAS  Google Scholar 

  • Tinetti ME, Kumar C (2010) The patient who falls: "It's always a trade-off". Jama 303(3):258–266

    Article  PubMed  CAS  Google Scholar 

  • Wakefield DB, Moscufo N, Guttmann CR, Kuchel GA, Kaplan RF, Pearlson G, Wolfson L (2010) White matter hyperintensities predict functional decline in voiding, mobility, and cognition in older adults. J Am Geriatr Soc 58(2):275–281

    Article  PubMed  Google Scholar 

  • Wardlaw JM, Sandercock PA, Dennis MS, Starr J (2003) Is breakdown of the blood–brain barrier responsible for lacunar stroke, leukoaraiosis, and dementia? Stroke 34(3):806–812

    Article  PubMed  CAS  Google Scholar 

  • Wen W, Sachdev P (2004) The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals. Neuroimage 22(1):144–154

    Article  PubMed  Google Scholar 

  • Whitman GT, Tang Y, Lin A, Baloh RW (2001) A prospective study of cerebral white matter abnormalities in older people with gait dysfunction. Neurology 57(6):990–994

    PubMed  CAS  Google Scholar 

  • Wolfson L, Wei X, Hall CB, Panzer V, Wakefield D, Benson RR, Schmidt JA, Warfield SK, Guttmann CR (2005) Accrual of MRI white matter abnormalities in elderly with normal and impaired mobility. J Neurol Sci 232(1–2):23–27

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Study supported by the National Institute on Aging—AG022092 (LW) and AG022092-01A1S1 (NM)—University of Connecticut Health Center General Clinical Research Center Grant M01 RR06192; NIH 5 P41 RR13218. We wish to thank Istvan Csapo for his expert advice on image analysis and method validation, Yang Duang for expert neuroradiological assistance, Antal Kucsai for assistance with computer network and archiving of digital MR images, Brian Healy for advice on statistical analyses, and Julie Raulukaitis, Greg Book, and Russell Starankewicz for assistance with MR image acquisition and transfer.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nicola Moscufo.

Electronic supplementary materials

Below is the link to the electronic supplementary material.

Fig. 1

Boxplots show the distribution of WMH volume changes (y-axis) in the two chair rise mobility groups (decline and no-decline, x-axis). The WMH variables shown are those that, in addition to the splenium of corpus callosum, showed significant correlation with decline in the chair rise test (see Table 3). Change was calculated as: [WMH burden at follow-up] − [WMH burden at baseline] (see also “Methods”). Thick horizontal line in the boxes indicates the group median. Circles, outliers; star, extreme outliers. The statistical significance of the group difference (Mann–Whitney group comparison test) is shown on top (JPEG 9 kb)

High resolution image file. (TIFF 1427 kb)

Tables 1–2

(DOC 89 kb)

About this article

Cite this article

Moscufo, N., Wolfson, L., Meier, D. et al. Mobility decline in the elderly relates to lesion accrual in the splenium of the corpus callosum. AGE 34, 405–414 (2012). https://doi.org/10.1007/s11357-011-9242-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11357-011-9242-4

Keywords

Navigation