Fetal influence on the human brain through the lifespan.

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Brain aging differs with cognitive ability regardless of education.

Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal cognitively healthy brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up for up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.

Associations of circulating C-reactive proteins, APOE ε4, and brain markers for Alzheimer's disease in healthy samples across the lifespan.

The apolipoprotein E gene ε4 allele (APOE ε4) and higher circulating level of C-reactive protein (CRP) have been extensively investigated as risk factors for Alzheimer's disease (AD). Paradoxically, APOE ε4 has been associated with lower levels of blood CRP in middle-aged and older populations. However, few studies have investigated this intriguing relation and its impact on neurological markers for AD in younger ages, nor across the whole lifespan. Here, we examine associations of blood CRP levels, APOE ε4, and biomarkers for AD in a cognitively healthy lifespan cohort (N up to 749; 20-81 years of age) and replicate the findings in UK Biobank (N = 304 322; 37-72 years of age), the developmental ABCD study (N = 10 283; 9-11 years of age), and a middle-aged sample (N = 339; 40-65 years of age). Hippocampal volume, brain amyloid-ß (Aß) plaque levels, cerebrospinal fluid (CSF) levels of Aß and tau species, and neurofilament protein light protein (NFL) were used as AD biomarkers in subsamples. In addition, we examined the genetic contribution to the variation of CRP levels over different CRP ranges using polygenic scores for CRP (PGS-CRP). Our results show APOE ε4 consistently associates with low blood CRP levels across all age groups (p < 0.05). Strikingly, both ε4 and PGS-CRP associated mainly with blood CRP levels within the low range (<5mg/L). We then show both APOE ε4 and high CRP levels associate with smaller hippocampus volumes across the lifespan (p < 0.025). APOE ε4 was associated with high Aß plaque levels in the brain (FDR-corrected p = 8.69x10-4), low levels of CSF Aß42 (FDR-corrected p = 6.9x10-2), and lower ratios of Aß42 to Aß40 (FDR-corrected p = 5.08x10-5). Blood CRP levels were weakly correlated with higher ratio of CSF Aß42 to Aß40 (p = 0.03, FDR-corrected p = 0.4). APOE ε4 did not correlate with blood concentrations of another 9 inflammatory cytokines, and none of these cytokines correlated with AD biomarkers. CONCLUSION: The inverse correlation between APOEε 4 and blood CRP levels existed before any pathological AD biomarker was observed, and only in the low CRP level range. Thus, we suggest to investigate whether APOEε 4 can confer risk by being associated with a lower inflammatory response to daily exposures, possibly leading to greater accumulation of low-grade inflammatory stress throughout life. A lifespan perspective is needed to understand this relationship concerning risk of developing AD.

Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change.

Brain age is a widely used index for quantifying individuals' brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.

Scientists who study the brain and aging are keen to find an effective way to measure brain health, which could help identify people at risk for dementia or memory problems. One popular marker is 'brain age'. This measurement uses a brain scan to estimate a person's chronological age, then compares the estimated brain age to the person's actual age to determine whether their brain is aging faster or slower than expected for their age. However, since brain age relies on one brain scan taken at one point in time, it is not clear whether it really measures brain aging or if it might capture brain differences that have been present throughout the individual's life. Studies comparing individual brain scans over several years would be necessary to know for sure. Now, Vidal-Piñeiro et al. show that the brain-age measurement does not reflect faster brain aging. In the experiments, the researchers compared repeated brain scans of thousands of individuals over 40 years of age. The experiments showed that deviations from normative brain age detected in a single scan reflected early life differences more than changes in the brain over time. For example, people with older-looking brains were more likely to have had a low birth weight or to have a combination of genes associated with having an older looking brain. Vidal-Piñeiro et al. show that brain age mostly reflects a pre-existing brain condition rather than brain aging. The experiments also suggest that genetics and early brain development likely have a strong impact on brain health throughout life. Future studies trying to test or develop brain-aging measurements should use serial measurements to track brain changes over time.

Educational attainment does not influence brain aging.

Education has been related to various advantageous lifetime outcomes. Here, using longitudinal structural MRI data (4,422 observations), we tested the influential hypothesis that higher education translates into slower rates of brain aging. Cross-sectionally, education was modestly associated with regional cortical volume. However, despite marked mean atrophy in the cortex and hippocampus, education did not influence rates of change. The results were replicated across two independent samples. Our findings challenge the view that higher education slows brain aging.

Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium.

We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.