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Age-related structural and functional variations in 5,967 individuals across the adult lifespan.

ABSTRACT: Exploring brain changes across the human lifespan is becoming an important topic in neuroscience. Though there are multiple studies which investigated the relationship between age and brain imaging, the results are heterogeneous due to small sample sizes and relatively narrow age ranges. Here, based on year-wise estimation of 5,967 subjects from 13 to 72 years old, we aimed to provide a more precise description of adult lifespan variation trajectories of gray matter volume (GMV), structural network correlation (SNC), and functional network connectivity (FNC) using independent component analysis and multivariate linear regression model. Our results revealed the following relationships: (a) GMV linearly declined with age in most regions, while parahippocampus showed an inverted U-shape quadratic relationship with age; SNC presented a U-shape quadratic relationship with age within cerebellum, and inverted U-shape relationship primarily in the default mode network (DMN) and frontoparietal (FP) related correlation. (b) FNC tended to linearly decrease within resting-state networks (RSNs), especially in the visual network and DMN. Early increase was revealed between RSNs, primarily in FP and DMN, which experienced a decrease at older ages. U-shape relationship was also revealed to compensate for the cognition deficit in attention and subcortical related connectivity at late years. (c) The link between middle occipital gyrus and insula, as well as precuneus and cerebellum, exhibited similar changing trends between SNC and FNC across the adult lifespan. Collectively, these results highlight the benefit of lifespan study and provide a precise description of age-related regional variation and SNC/FNC changes based on a large dataset.

SUBMITTER: Luo N

PROVIDER: S-EPMC7267948 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The brain atrophy and lesion index (BALI) has been developed to assess whole-brain structural deficits that are commonly seen on magnetic resonance imaging (MRI) in aging. It is unclear whether such changes can be detected at younger ages and how they might relate to other exposures. Here, we investigate how BALI scores, and the subcategories that make the total score, compare across adulthood and whether they are related to the level of cardiovascular risks, in both young and old adulthood. Methods: Data were from 229 subjects (72% men; 24-80 years of age) whose annual health evaluation included a routine anatomical MRI examination. A BALI score was generated for each subject from T2-weighted MRI. Differences in the BALI total score and categorical subscores were examined by age and by the level of cardiovascular risk factors (CVRFs). Regression analysis was used to evaluate relationships between continuous variables. Relative risk ratios (RRRs) of CVRF on BALI were examined using a multinomial logistic regression. The area under the receiver operating characteristic (ROC) curve was used to estimate the classification accuracy. Results: Nearly 90% of the participants had at least one CVRF. Mean CVRF scores increased with age (slope = 0.03; r = 0.36, 95% confidence intervals: 0.23-0.48; p < 0.001). The BALI total score was closely related to age (slope = 0.18; r = 0.69, 95% confidence intervals: 0.59-0.78; p < 0.001), as so were the categorical subscores (r's = 0.41-0.61, p < 0.001); each differed by the number of CVRF (t-test: 4.16-14.83, χ 2: 6.9-43.9, p's < 0.050). Multivariate analyses adjusted for age and sex suggested an independent impact of age and the CVRF on the BALI score (for each year of advanced age, RRR = 1.20, 95% CI = 1.11-1.29; for each additional CVRF, RRR = 3.63, 95% CI = 2.12-6.23). The CVRF and BALI association remained significant even in younger adults. Conclusion: The accumulation of MRI-detectable structural brain deficits can be evident from young adulthood. Age and the number of CVFR are independently associated with BALI score. Further research is needed to understand the extent to which other age-related health deficits can increase the risk of abnormalities in brain structure and function, and how these, with BALI scores, relate to cognition.

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Age-related structural and functional variations in 5,967 individuals across the adult lifespan.

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