» Articles » PMID: 36459652

Age-related Brain Atrophy is Not a Homogenous Process: Different Functional Brain Networks Associate Differentially with Aging and Blood Factors

Overview
Specialty Science
Date 2022 Dec 2
PMID 36459652
Authors
Affiliations
Soon will be listed here.
Abstract

Aging is characterized by a progressive loss of brain volume at an estimated rate of 5% per decade after age 40. While these morphometric changes, especially those affecting gray matter and atrophy of the temporal lobe, are predictors of cognitive performance, the strong association with aging obscures the potential parallel, but more specific role, of individual subject physiology. Here, we studied a cohort of 554 human subjects who were monitored using structural MRI scans and blood immune protein concentrations. Using machine learning, we derived a cytokine clock (CyClo), which predicted age with good accuracy (Mean Absolute Error = 6 y) based on the expression of a subset of immune proteins. These proteins included, among others, Placenta Growth Factor (PLGF) and Vascular Endothelial Growth Factor (VEGF), both involved in angiogenesis, the chemoattractant vascular cell adhesion molecule 1 (VCAM-1), the canonical inflammatory proteins interleukin-6 (IL-6) and tumor necrosis factor alpha (TNFα), the chemoattractant IP-10 (CXCL10), and eotaxin-1 (CCL11), previously involved in brain disorders. Age, sex, and the CyClo were independently associated with different functionally defined cortical networks in the brain. While age was mostly correlated with changes in the somatomotor system, sex was associated with variability in the frontoparietal, ventral attention, and visual networks. Significant canonical correlation was observed for the CyClo and the default mode, limbic, and dorsal attention networks, indicating that immune circulating proteins preferentially affect brain processes such as focused attention, emotion, memory, response to social stress, internal evaluation, and access to consciousness. Thus, we identified immune biomarkers of brain aging which could be potential therapeutic targets for the prevention of age-related cognitive decline.

Citing Articles

Analysis of functional connectivity changes from childhood to old age: A study using HCP-D, HCP-YA, and HCP-A datasets.

Wang Y, Li S, He J, Peng L, Wang Q, Zou X Imaging Neurosci (Camb). 2025; 3.

PMID: 40078534 PMC: 11894817. DOI: 10.1162/imag_a_00503.


Optimal trajectory of the neuroendoscope for third ventricle pavement access.

Sousa J, Silva S, Alves H, Carvalho B, Sousa J, Ferreira-Pinto M Front Neuroanat. 2025; 19:1431128.

PMID: 39911564 PMC: 11794814. DOI: 10.3389/fnana.2025.1431128.


Inflammaging Markers in the Extremely Cold Climate: A Case Study of Yakutian Population.

Kalyakulina A, Yusipov I, Kondakova E, Sivtseva T, Zakharova R, Semenov S Int J Mol Sci. 2025; 25(24.

PMID: 39769502 PMC: 11679676. DOI: 10.3390/ijms252413741.


The Impact of HIV on Early Brain Aging-A Pathophysiological (Re)View.

Lazar M, Moroti R, Barbu E, Chitu-Tisu C, Tiliscan C, Erculescu T J Clin Med. 2024; 13(23).

PMID: 39685490 PMC: 11642420. DOI: 10.3390/jcm13237031.


Perivascular space enlargement accelerates in ageing and Alzheimer's disease pathology: evidence from a three-year longitudinal multicentre study.

Menze I, Bernal J, Kaya P, Aki C, Pfister M, Geisendorfer J Alzheimers Res Ther. 2024; 16(1):242.

PMID: 39482759 PMC: 11526621. DOI: 10.1186/s13195-024-01603-8.


References
1.
Fjell A, McEvoy L, Holland D, Dale A, Walhovd K . What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus. Prog Neurobiol. 2014; 117:20-40. PMC: 4343307. DOI: 10.1016/j.pneurobio.2014.02.004. View

2.
Krubitzer L . In search of a unifying theory of complex brain evolution. Ann N Y Acad Sci. 2009; 1156:44-67. PMC: 2666944. DOI: 10.1111/j.1749-6632.2009.04421.x. View

3.
Casaletto K, Lindbergh C, Memel M, Staffaroni A, Elahi F, Weiner-Light S . Sexual dimorphism of physical activity on cognitive aging: Role of immune functioning. Brain Behav Immun. 2020; 88:699-710. PMC: 7416443. DOI: 10.1016/j.bbi.2020.05.014. View

4.
Ashburner J . A fast diffeomorphic image registration algorithm. Neuroimage. 2007; 38(1):95-113. DOI: 10.1016/j.neuroimage.2007.07.007. View

5.
Satizabal C, Zhu Y, Mazoyer B, Dufouil C, Tzourio C . Circulating IL-6 and CRP are associated with MRI findings in the elderly: the 3C-Dijon Study. Neurology. 2012; 78(10):720-7. DOI: 10.1212/WNL.0b013e318248e50f. View