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In Pre-Clinical AD Small Vessel Disease is Associated With Altered Hippocampal Connectivity and Atrophy

Published:September 24, 2022DOI:https://doi.org/10.1016/j.jagp.2022.09.011

      HIGHLIGHTS

      • What is the primary question addressed by this study?We investigated whether the presence of small vessel disease (SVD) (measured as significant WMH burden) altered the associations between brain amyloid-beta (Aβ) and hippocampal functional connectivity during associative encoding in cognitively normal older adults.
      • What is the main finding of this study?In older adults with significant WMH burden (WMH+), greater Aβ burden was associated with a more localized pattern of hippocampal-medial temporal lobe (MTL) hyperconnectivity, but not in individuals with minimum WMH burden (WMH-). This local hippocampal-MTL hyperconnectivity is associated with local MTL atrophy.
      • What is the meaning of the finding?These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in pre-clinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD.

      ABSTRACT

      Objective

      Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aβ) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume.

      Methods

      This study included 61 cognitively normal older adults (age range: 65–93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aβ, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity.

      Results

      We found that, in WMH (+) older adults greater Aβ burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aβ burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy.

      Conclusion

      These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD.

      KEY WORDS

      Abbreviations:

      AD (Alzheimer's disease), AIR (automated image registration), (beta-Amyloid-beta), SVD (cerebral small vessel disease), EPI (echo-planar imaging), TE (echo time), FOV (field of view), fMRI (functional magnetic resonance imaging), gPPI (generalized psychophysiological interactions), MPRAGE (magnetization-prepared rapid gradient echo sequence), MTL (medial temporal lobe), MCI (mild cognitive impairment), MMSE (Mini–Mental State Examination), MNI (Montreal Neurological Institute), PiB (Pittsburgh Compound-B), TR (repetition time), SUVR (standardized uptake value ratio), T1w (T1-weighted), WML (white matter lesion), WMH (white matter hyperintensities)
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      REFERENCES

        • Perrin RJ
        • Fagan AM
        • Holtzman DM
        Multimodal techniques for diagnosis and prognosis of Alzheimer's disease.
        Nature. 2009; 461: 916-922
        • Jack Jr, CR
        • Knopman DS
        • Jagust WJ
        • et al.
        Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade.
        Lancet Neurol. 2010; 9: 119-128.
        • Sperling RA
        • Aisen PS
        • Beckett LA
        • et al.
        Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.
        Alzheimers Dement. 2011; 7: 280-292
        • Toledo JB
        • Arnold SE
        • Raible K
        • et al.
        Contribution of cerebrovascular disease in autopsy confirmed neurodegenerative disease cases in the National Alzheimer's Coordinating Centre.
        Brain. 2013; 136: 2697-2706
        • Snowdon DA
        • Greiner LH
        • Mortimer JA
        • et al.
        Brain infarction and the clinical expression of Alzheimer disease. The Nun Study.
        JAMA. 1997; 277: 813-817
        • Heyman A
        • Fillenbaum GG
        • Welsh-Bohmer KA
        • et al.
        Cerebral infarcts in patients with autopsy-proven Alzheimer's disease: CERAD, part XVIII. Consortium to Establish a Registry for Alzheimer's Disease.
        Neurology. 1998; 51: 159-162
        • Schneider JA
        • Wilson RS
        • Bienias JL
        • et al.
        Cerebral infarctions and the likelihood of dementia from Alzheimer disease pathology.
        Neurology. 2004; 62: 1148-1155
        • Esiri MM
        • Nagy Z
        • Smith MZ
        • et al.
        Cerebrovascular disease and threshold for dementia in the early stages of Alzheimer's disease.
        Lancet. 1999; 354: 919-920
        • Bos I
        • Verhey FR
        • Ramakers I
        • et al.
        Cerebrovascular and amyloid pathology in predementia stages: the relationship with neurodegeneration and cognitive decline.
        Alzheimers Res Ther. 2017; 9: 101
        • Vemuri P
        • Lesnick TG
        • Przybelski SA
        • et al.
        Vascular and amyloid pathologies are independent predictors of cognitive decline in normal elderly.
        Brain. 2015; 138: 761-771
        • Lerdkrai C
        • Asavapanumas N
        • Brawek B
        • et al.
        Intracellular Ca (2+) stores control in vivo neuronal hyperactivity in a mouse model of Alzheimer's disease.
        Proc Natl Acad Sci U S A. 2018; 115: E1279-E1288
        • Dong XX
        • Wang Y
        • Qin ZH
        Molecular mechanisms of excitotoxicity and their relevance to pathogenesis of neurodegenerative diseases.
        Acta Pharmacol Sin. 2009; 30: 379-387
        • Zott B
        • Simon MM
        • Hong W
        • et al.
        A vicious cycle of β amyloid–dependent neuronal hyperactivation.
        Science. 2019; 365: 559-565
        • Wu M
        • Thurston RC
        • Tudorascu DL
        • et al.
        Amyloid deposition is associated with different patterns of hippocampal connectivity in men versus women.
        Neurobiol Aging. 2019; 76: 141-150
        • Edelman K
        • Tudorascu D
        • Agudelo C
        • et al.
        Amyloid-beta deposition is associated with increased medial temporal lobe activation during memory encoding in the cognitively normal elderly.
        Am J Geriatr Psychiatry. 2017; 25: 551-560
        • Wilson AA
        • Garcia A
        • Jin L
        • et al.
        Radiotracer synthesis from [ (11)C]-iodomethane: a remarkably simple captive solvent method.
        Nucl Med Biol. 2000; 27: 529-532
        • Sperling R
        • Chua E
        • Cocchiarella A
        • et al.
        Putting names to faces: successful encoding of associative memories activates the anterior hippocampal formation.
        Neuroimage. 2003; 20: 1400-1410
        • Woods RP
        • Mazziotta JC
        • Cherry SR
        MRI-PET registration with automated algorithm.
        J Comput Assist Tomogr. 1993; 17: 536-546
        • Cohen AD
        • Price JC
        • Weissfeld LA
        • et al.
        Basal cerebral metabolism may modulate the cognitive effects of Abeta in mild cognitive impairment: an example of brain reserve.
        J Neurosci. 2009; 29: 14770-14778
        • Lopresti BJ
        • Klunk WE
        • Mathis CA
        • et al.
        Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis.
        J Nucl Med. 2005; 46: 1959-1972
        • Meltzer CC
        • Cantwell MN
        • Greer PJ
        • et al.
        Does cerebral blood flow decline in healthy aging? A PET study with partial-volume correction.
        J Nucl Med. 2000; 41: 1842-1848
        • Cohen AD
        • Mowrey W
        • Weissfeld LA
        • et al.
        Classification of amyloid-positivity in controls: comparison of visual read and quantitative approaches.
        Neuroimage. 2013; 71: 207-215
        • Ashburner J
        A fast diffeomorphic image registration algorithm.
        Neuroimage. 2007; 38: 95-113
        • Good CD
        • Ashburner J
        • Frackowiak RS
        Computational neuroanatomy: new perspectives for neuroradiology.
        Rev Neurol (Paris). 2001; 157: 797-806
        • Wu M
        • Rosano C
        • Butters M
        • et al.
        A fully automated method for quantifying and localizing white matter hyperintensities on MR images.
        Psychiatry Res. 2006; 148: 133-142
        • Friston KJ
        • Buechel C
        • Fink GR
        • et al.
        Psychophysiological and modulatory interactions in neuroimaging.
        Neuroimage. 1997; 6: 218-229
        • Tzourio-Mazoyer N
        • Landeau B
        • Papathanassiou D
        • et al.
        Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.
        Neuroimage. 2002; 15: 273-289
        • Maillard P
        • Fletcher E
        • Lockhart SN
        • et al.
        White matter hyperintensities and their penumbra lie along a continuum of injury in the aging brain.
        Stroke. 2014; 45: 1721-1726
        • Reginold W
        • Itorralba J
        • Luedke AC
        • et al.
        Tractography at 3T MRI of corpus callosum tracts crossing white matter hyperintensities.
        AJNR Am J Neuroradiol. 2016; 37: 1617-1622
        • Reginold W
        • Sam K
        • Poublanc J
        • et al.
        Impact of white matter hyperintensities on surrounding white matter tracts.
        Neuroradiology. 2018; 60: 933-944
        • He J
        • Wong VS
        • Fletcher E
        • et al.
        The contributions of MRI-based measures of gray matter, white matter hyperintensity, and white matter integrity to late-life cognition.
        AJNR Am J Neuroradiol. 2012; 33: 1797-1803
        • Yatawara C
        • Lee D
        • Ng KP
        • et al.
        Mechanisms linking white matter lesions, tract integrity, and depression in Alzheimer disease.
        Am J Geriatr Psychiatry. 2019; 27: 948-959
        • Villain N
        • Desgranges B
        • Viader F
        • et al.
        Relationships between hippocampal atrophy, white matter disruption, and gray matter hypometabolism in Alzheimer's disease.
        J Neurosci. 2008; 28: 6174-6181
        • Hillary FG
        • Roman CA
        • Venkatesan U
        • et al.
        Hyperconnectivity is a fundamental response to neurological disruption.
        Neuropsychology. 2015; 29: 59-75
        • Guzman VA
        • Carmichael OT
        • Schwarz C
        • et al.
        White matter hyperintensities and amyloid are independently associated with entorhinal cortex volume among individuals with mild cognitive impairment.
        Alzheimers Dement. 2013; 9: S124-S131
        • Fiford CM
        • Manning EN
        • Bartlett JW
        • et al.
        White matter hyperintensities are associated with disproportionate progressive hippocampal atrophy.
        Hippocampus. 2017; 27: 249-262
        • Liu Y
        • Braidy N
        • Poljak A
        • et al.
        Cerebral small vessel disease and the risk of Alzheimer's disease: a systematic review.
        Ageing Res Rev. 2018; 47: 41-48
        • Gordon BA
        • Najmi S
        • Hsu P
        • et al.
        The effects of white matter hyperintensities and amyloid deposition on Alzheimer dementia.
        Neuroimage Clin. 2015; 8: 246-252
        • Ye BS
        • Seo SW
        • Kim JH
        • et al.
        Effects of amyloid and vascular markers on cognitive decline in subcortical vascular dementia.
        Neurology. 2015; 85: 1687-1693
        • Koncz R
        • Sachdev PS
        Are the brain's vascular and Alzheimer pathologies additive or interactive?.
        Curr Opin Psychiatry. 2018; 31: 147-152
        • Nebes RD
        • Snitz BE
        • Cohen AD
        • et al.
        Cognitive aging in persons with minimal amyloid-β and white matter hyperintensities.
        Neuropsychologia. 2013; 51: 2202-2209