Klinische Neurophysiologie 2024; 55(01): 16-22
DOI: 10.1055/a-2252-2148
Originalarbeit

Alter und Neurodegeneration in der Bildgebung

Insights into Aging and Neurodegeneration with Imaging Modalities
Gérard Bischof
1   Nuklearmedizin, Uniklinik Köln, Köln, Germany
2   INM-2, Forschungszentrum Juelich, Juelich, Germany
,
Merle Hoenig
1   Nuklearmedizin, Uniklinik Köln, Köln, Germany
2   INM-2, Forschungszentrum Juelich, Juelich, Germany
› Author Affiliations

Zusammenfassung

Das Wort „Altern“ nutzen wir in unserem alltäglichen Leben als einfachen Begriff zur Beschreibung von Veränderungen, die mit der Zeit auftreten. Das Wort stammt von den germanischen Ableitungen „ala“ - „wachsen, nähren“ und *aldra - „Lebensalter“. Somit umfasst der Begriff des Alterns einen multifaktoriellen Prozess, der im frühen und mittleren Lebensalter durch das „Wachsen und Nährens“ des Gehirns geprägt ist, und im späteren Lebensalter durch degenerative Prozesse, welche wiederrum durch die Ansammlung von altersbedingten Proteinen und dem Absterben von Neuronen bedingt sind. Zwar unterliegt jeder Mensch solchen Alterungsprozessen, jedoch resultieren sie dennoch in einer hohen interindividuellen Varianz des Gehirnalterns und der kognitiven Fähigkeiten. Eine extreme Abweichung vom normalen Gehirnalterungsprozess stellt dabei das pathologische Altern dar, wie zum Beispiel bei der Alzheimer Erkrankung. Im Gegenzug gibt es Individuen, bei denen der Gehirnalterungsprozess scheinbar verlangsamt ist und welche trotz eines sehr hohen Alters weiterhin die kognitiven Fähigkeiten von jüngeren Personen aufweisen, sogenannte „Super-Ager“. Im Folgenden werden wir dieses Kontinuum des Gehirnalterungsprozesses beschreiben sowie die Bildgebungsmethoden, die bereits verwendet werden, um die zugrundeliegenden Mechanismen zu untersuchen.

Abstract

We use the word “aging” in our everyday lives as a simple term to describe changes that occur over time. Yet, the concept of aging encompasses a multifactorial process that is characterized by the “growing and nourishing” of the brain in early and middle age, and in later life by degenerative processes, which in turn are caused by the accumulation of age-related proteins and subsequent neuronal death. Although every person is subject to such aging processes, there are high inter-individual variances in brain aging and cognitive abilities. Pathological aging, such as Alzheimer’s disease, is an extreme deviation from the normal brain aging process. On the other hand, there are individuals, in whom the brain aging process appears to be slowed and who, despite their advanced age, continue to exhibit cognitive abilities similar to younger people, the so-called “super-agers”. Here, we will describe this continuum of brain aging and the imaging methods that are used to investigate the underlying mechanisms.



Publication History

Article published online:
04 April 2024

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  • Literatur

  • 1 Raz N, Lindenberger U, Rodrigue KM. et al. Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cerebral cortex 2005; 15: 1676-1689
  • 2 Raz N, Rodrigue KM, Kennedy KM. et al. Differential aging of the human striatum: longitudinal evidence. American Journal of Neuroradiology 2003; 24: 1849-1856
  • 3 Fjell AM, Westlye LT, Grydeland H. et al. Accelerating cortical thinning: unique to dementia or universal in aging?. Cerebral cortex 2014; 24: 919-934
  • 4 Smith ET, Hennessee JP, Wig GS. et al. Longitudinal changes in gray matter correspond to changes in cognition across the lifespan: implications for theories of cognition. Neurobiology of Aging 2023; 129: 1-14
  • 5 Vonk JM, Ghaznawi R, Zwartbol MH. et al. The role of cognitive and brain reserve in memory decline and atrophy rate in mid and late-life: The SMART-MR study. Cortex 2022; 148: 204-214
  • 6 Park DC, Bischof GN. Neuroplasticity, aging, and cognitive function. In: Handbook of the psychology of aging. Elsevier; 2011: 109-119
  • 7 Cabeza R. Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychology and aging 2002; 17: 85
  • 8 Greenwood P. Functional plasticity in cognitive aging: review and hypothesis. Neuropsychology 2007; 21: 657
  • 9 Greenwood PM, Parasuraman R. Neuronal and cognitive plasticity: a neurocognitive framework for ameliorating cognitive aging. Frontiers in aging neuroscience 2010; 2: 150
  • 10 Park DC, Reuter-Lorenz P. The adaptive brain: aging and neurocognitive scaffolding. Annual review of psychology 2009; 60: 173-196
  • 11 Tucker-Drob EM, De la Fuente J, Köhncke Y. et al. A strong dependency between changes in fluid and crystallized abilities in human cognitive aging. Science Advances 2022; 8: eabj2422
  • 12 Kennedy KM, Raz N. Aging white matter and cognition: differential effects of regional variations in diffusion properties on memory, executive functions, and speed. Neuropsychologia 2009; 47: 916-927
  • 13 Garnier-Crussard A, Bougacha S, Wirth M. et al. White matter hyperintensities across the adult lifespan: relation to age, Aβ load, and cognition. Alzheimer’s research & therapy 2020; 12: 1-11
  • 14 Pauley C, Kobelt M, Werkle-Bergner M. et al Age differences in neural distinctiveness during memory retrieval versus reinstatement. bioRxiv. 2023 2023.2003. 2021.533591
  • 15 Park DC, Polk TA, Park R. et al. Aging reduces neural specialization in ventral visual cortex. Proceedings of the National Academy of Sciences 2004; 101: 13091-13095
  • 16 Lynch G, Rex CS, Gall CM. Synaptic plasticity in early aging. Ageing Res Rev 2006; 5: 255-280 DOI: 10.1016/j.arr.2006.03.008.
  • 17 Burke SN, Barnes CA. Neural plasticity in the ageing brain. Nat Rev Neurosci 2006; 7: 30-40 DOI: 10.1038/nrn1809.
  • 18 Shivarama Shetty M, Sajikumar S. ‘Tagging’ along memories in aging: Synaptic tagging and capture mechanisms in the aged hippocampus. Ageing Res Rev 2017; 35: 22-35 DOI: 10.1016/j.arr.2016.12.008.
  • 19 Ryan MM, Guevremont D, Luxmanan C. et al. Aging alters long-term potentiation--related gene networks and impairs synaptic protein synthesis in the rat hippocampus. Neurobiol Aging 2015; 36: 1868-1880 DOI: 10.1016/j.neurobiolaging.2015.01.012.
  • 20 Mitchell SJ, Scheibye-Knudsen M, Longo DL. et al. Animal models of aging research: implications for human aging and age-related diseases. Annu Rev Anim Biosci 2015; 3: 283-303 DOI: 10.1146/annurev-animal-022114-110829.
  • 21 Hedden T, Schultz AP, Rieckmann A. et al. Multiple brain markers are linked to age-related variation in cognition. Cerebral cortex 2016; 26: 1388-1400
  • 22 Hampel H. Amyloid-β and cognition in aging and Alzheimer’s disease: molecular and neurophysiological mechanisms. Journal of Alzheimer’s Disease 2013; 33: S79-S86
  • 23 Bischof GN. Alzheimer’s disease risk: amyloid versus neurodegeneration. The Lancet Neurology 2016; 15: 1000-1001
  • 24 Jack CR, Wiste HJ, Knopman DS. et al. Rates of β-amyloid accumulation are independent of hippocampal neurodegeneration. Neurology 2014; 82: 1605-1612
  • 25 Rodrigue K, Kennedy K, Devous M. et al. β-Amyloid burden in healthy aging: regional distribution and cognitive consequences. Neurology 2012; 78: 387-395
  • 26 Villemagne VL, Burnham S, Bourgeat P. et al. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. The Lancet Neurology 2013; 12: 357-367
  • 27 Rowe CC, Ellis KA, Rimajova M. et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiology of aging 2010; 31: 1275-1283
  • 28 Aizenstein HJ, Nebes RD, Saxton JA. et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Archives of neurology 2008; 65: 1509-1517
  • 29 Pike KE, Ellis KA, Villemagne VL. et al. Cognition and beta-amyloid in preclinical Alzheimer’s disease: data from the AIBL study. Neuropsychologia 2011; 49: 2384-2390
  • 30 Mormino E, Kluth J, Madison C. et al. Episodic memory loss is related to hippocampal-mediated β-amyloid deposition in elderly subjects. Brain 2009; 132: 1310-1323
  • 31 Johnson KA, Schultz A, Betensky RA. et al. Tau positron emission tomographic imaging in aging and early A lzheimer disease. Annals of neurology 2016; 79: 110-119
  • 32 Schöll M, Lockhart SN, Schonhaut DR. et al. PET imaging of tau deposition in the aging human brain. Neuron 2016; 89: 971-982
  • 33 Hanseeuw BJ, Betensky RA, Jacobs HI. et al. Association of amyloid and tau with cognition in preclinical Alzheimer disease: a longitudinal study. JAMA neurology 2019; 76: 915-924
  • 34 Jack CR, Wiste HJ, Weigand SD. et al. Predicting future rates of tau accumulation on PET. Brain 2020; 143: 3136-3150
  • 35 Kwan AT, Arfaie S, Therriault J. et al. Medial temporal tau predicts memory decline in cognitively unimpaired elderly. Brain Communications 2023; 5: fcac325
  • 36 Tosun D, Demir Z, Veitch DP. et al. Contribution of Alzheimer’s biomarkers and risk factors to cognitive impairment and decline across the Alzheimer’s disease continuum. Alzheimer’s & Dementia 2022; 18: 1370-1382
  • 37 Alafuzoff I, Libard S. Mixed brain pathology is the most common cause of cognitive impairment in the elderly. Journal of Alzheimer’s Disease 2020; 78: 453-465
  • 38 Rahimi J, Kovacs GG. Prevalence of mixed pathologies in the aging brain. Alzheimer’s research & therapy 2014; 6: 1-11
  • 39 Jellinger KA. Recent update on the heterogeneity of the Alzheimer’s disease spectrum. Journal of Neural Transmission 2022; 129: 1-24
  • 40 Jellinger KA, Attems J. Prevalence and impact of vascular and Alzheimer pathologies in Lewy body disease. Acta neuropathologica 2008; 115: 427-436
  • 41 Johnson KA, Minoshima S, Bohnen NI. et al. Update on appropriate use criteria for amyloid PET imaging: dementia experts, mild cognitive impairment, and education. Alzheimer’s & Dementia 2013; 9: e106-e109
  • 42 Groot C, Villeneuve S, Smith R. et al. Tau PET imaging in neurodegenerative disorders. Journal of Nuclear Medicine 2022; 63: 20S-26S
  • 43 Livingston G, Huntley J, Sommerlad A. et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 2020; 396: 413-446 DOI: 10.1016/s0140-6736(20)30367-6.
  • 44 Buettner D, Skemp S. Blue zones: lessons from the world’s longest lived. American journal of lifestyle medicine 2016; 10: 318-321
  • 45 Arenaza-Urquijo EM, Vemuri P. Improving the resistance and resilience framework for aging and dementia studies. Alzheimer’s research & therapy 2020; 12: 1-4
  • 46 Garo-Pascual M, Gaser C, Zhang L. et al. Brain structure and phenotypic profile of superagers compared with age-matched older adults: a longitudinal analysis from the Vallecas Project. The Lancet Healthy Longevity 2023; 4: e374-e385
  • 47 Rogalski EJ, Gefen T, Shi J. et al. Youthful memory capacity in old brains: anatomic and genetic clues from the Northwestern SuperAging Project. Journal of cognitive neuroscience 2013; 25: 29-36
  • 48 Stern Y, Arenaza-Urquijo EM, Bartrés-Faz D. et al. Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimer’s & Dementia 2020; 16: 1305-1311
  • 49 Hoenig MC, van Eimeren T, Dzialas V. et al. The Concept of Motor Reserve in Parkinson’s Disease: New Wine in Old Bottles?. Movement disorders 2023; 38: 16-20
  • 50 Hoenig MC, Bischof GN, Hammes J. et al. Tau pathology and cognitive reserve in Alzheimer’s disease. Neurobiology of aging 2017; 57: 1-7
  • 51 Kemppainen NM, Aalto S, Karrasch M. et al. Cognitive reserve hypothesis: Pittsburgh Compound B and fluorodeoxyglucose positron emission tomography in relation to education in mild Alzheimer’s disease. Annals of Neurology: Official Journal of the American Neurological Association and the Child Neurology Society 2008; 63: 112-118
  • 52 Neitzel J, Franzmeier N, Rubinski A. et al. Left frontal connectivity attenuates the adverse effect of entorhinal tau pathology on memory. Neurology 2019; 93: e347-e357
  • 53 Groot C, Doré V, Robertson J. et al. Mesial temporal tau is related to worse cognitive performance and greater neocortical tau load in amyloid-β–negative cognitively normal individuals. Neurobiology of aging 2021; 97: 41-48
  • 54 Hoenig MC, Bischof GN, Onur ÖA. et al. Level of education mitigates the impact of tau pathology on neuronal function. European journal of nuclear medicine and molecular imaging 2019; 46: 1787-1795
  • 55 Naganawa M, Li S, Nabulsi N. et al. First-in-Human Evaluation of (18)F-SynVesT-1, a Radioligand for PET Imaging of Synaptic Vesicle Glycoprotein 2A. J Nucl Med 2021; 62: 561-567 DOI: 10.2967/jnumed.120.249144.
  • 56 Mecca AP, O'Dell RS, Sharp ES. et al. Synaptic density and cognitive performance in Alzheimer’s disease: A PET imaging study with [(11) C]UCB-J. Alzheimers Dement 2022; 18: 2527-2536 DOI: 10.1002/alz.12582.
  • 57 van Loenhoud AC, van der Flier WM, Wink AM. et al. Cognitive reserve and clinical progression in Alzheimer disease: A paradoxical relationship. Neurology 2019; 93: e334-e346 DOI: 10.1212/wnl.0000000000007821.
  • 58 Zhang J, Andreano JM, Dickerson BC. et al. Stronger functional connectivity in the default mode and salience networks is associated with youthful memory in superaging. Cerebral Cortex 2020; 30: 72-84
  • 59 Arenaza-Urquijo EM, Przybelski SA, Lesnick TL. et al. The metabolic brain signature of cognitive resilience in the 80+: beyond Alzheimer pathologies. Brain 2019; 142: 1134-1147
  • 60 Rogalski E, Gefen T, Mao Q. et al. Cognitive trajectories and spectrum of neuropathology in S uper A gers: The first 10 cases. Hippocampus 2019; 29: 458-467
  • 61 Gefen T, Peterson M, Papastefan ST. et al. Morphometric and histologic substrates of cingulate integrity in elders with exceptional memory capacity. Journal of Neuroscience 2015; 35: 1781-1791
  • 62 Hoenig MC, Willscheid N, Bischof GN. et al. Assessment of tau tangles and amyloid-β plaques among super agers using PET imaging. JAMA Network Open 2020; 3: e2028337-e2028337
  • 63 Huentelman MJ, Piras IS, Siniard AL. et al. Associations of MAP2K3 gene variants with superior memory in SuperAgers. Frontiers in Aging Neuroscience 2018; 10: 155
  • 64 Neitzel J, Franzmeier N, Rubinski A. et al. KL-VS heterozygosity is associated with lower amyloid-dependent tau accumulation and memory impairment in Alzheimer’s disease. Nature communications 2021; 12: 3825
  • 65 Snitz BE, Chang Y, Tudorascu DL. et al. Predicting resistance to amyloid-beta deposition and cognitive resilience in the oldest-old. Neurology 2020; 95: e984-e994
  • 66 Winer JR, Morehouse A, Fenton L. et al. Tau and β-Amyloid Burden Predict Actigraphy-Measured and Self-Reported Impairment and Misperception of Human Sleep. J Neurosci 2021; 41: 7687-7696 DOI: 10.1523/jneurosci.0353-21.2021.
  • 67 Nedergaard M. Garbage truck of the brain. Science 2013; 340: 1529-1530
  • 68 Harrison IF, Siow B, Akilo AB. et al. Non-invasive imaging of CSF-mediated brain clearance pathways via assessment of perivascular fluid movement with diffusion tensor MRI. Elife 2018; 7 DOI: 10.7554/eLife.34028.
  • 69 Borelli WV, Schilling LP, Radaelli G. et al. Neurobiological findings associated with high cognitive performance in older adults: a systematic review. International Psychogeriatrics 2018; 30: 1813-1825