Accelerated Brain Aging Research Articles

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the ‘last in, first out’ mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Population clustering of structural brain aging and its association with brain development.

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the 'last in, first out' mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Brain predicted age in chronic pelvic pain: a study by the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network.

The effect of chronic pain on brain-predicted age is unclear. We performed secondary analyses of a large cross-sectional and 3-year longitudinal data set from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network to test the hypothesis that chronic pelvic pain accelerates brain aging and brain aging rate. Brain-predicted ages of 492 chronic pelvic pain patients and 72 controls were determined from T1-weighted MRI scans and used to calculate the brain-predicted age gap estimation (brainAGE; brain-predicted - chronological age). Separate regression models determined whether the presence of chronic pelvic pain could explain brainAGE and brain aging rate when accounting for covariates. We performed secondary analyses to understand whether brainAGE was associated with factors that subtype chronic pelvic pain patients (inflammation, widespread pain, and psychological comorbidities). We found a significant association between chronic pelvic pain and brainAGE that differed by sex. Women with chronic pelvic pain had higher brainAGE than female controls, whereas men with chronic pelvic pain exhibited lower brainAGE than male controls on average-however, the effect was not statistically significant in men or women when considered independently. Secondary analyses demonstrated preliminary evidence of an association between inflammatory load and brainAGE. Further studies of brainAGE and inflammatory load are warranted.

Association between allostatic load and accelerated white matter brain aging: findings from the UK biobank.

White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29years in association analysis and by 0.33years in Mendelian analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64years old, with no significant sex difference. This study demonstrated that higher chronic stress was significantly associated with accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.

Diabetes, Prediabetes, and Brain Aging: The Role of Healthy Lifestyle.

Diabetes is a well-known risk factor for dementia. We investigated the association between (pre)diabetes and older brain age and whether this can be attenuated by modifiable lifestyle behaviors. The study included 31,229 dementia-free adults from the UK Biobank between the ages of 40 and 70 years. Glycemic status (normoglycemia, prediabetes, or diabetes) was ascertained based on medical history, medication use, and HbA1c measured at baseline. Information on cardiometabolic risk factors (obesity, hypertension, low HDL, and high triglycerides) and lifestyle behaviors (smoking, drinking, and physical activity) was also collected at baseline. Participants underwent up to two brain MRI scans over 11 years of follow-up. Brain age was estimated using a machine learning model based on 1,079 brain MRI phenotypes and used to calculate brain age gap (BAG; i.e., brain age minus chronological age). At baseline, 13,518 participants (43.3%) had prediabetes and 1,149 (3.7%) had diabetes. Prediabetes (β = 0.22 [95% CI 0.10, 0.34]) and diabetes (2.01 [1.70, 2.32]) were both associated with significantly higher BAG, and diabetes was further associated with significant increase in BAG over time (0.27 [0.01, 0.53]). The association between (pre)diabetes and higher BAG was more pronounced in men and in people with two or more cardiometabolic risk factors. In joint exposure analysis, having a healthy lifestyle (i.e., no smoking, no heavy drinking, and high physical activity) significantly attenuated the diabetes-BAG association. Diabetes and even prediabetes are associated with accelerated brain aging, especially among men and people with poor cardiometabolic health. However, a healthy lifestyle may counteract this.

Quantification of white matter hyperintensities in type 1 diabetes and its relation to neuropathy and clinical characteristics

AimsThe aims were to quantify periventricular and deep white matter hyperintensities (WMHs) in adults with type 1 diabetes with different neuropathic phenotypes and to correlate WMH measurements to explanatory factors in diabetes. MethodsWMH measurements were obtained from brain magnetic resonance imaging of 56 adults with type 1 diabetes in subgroups including painful diabetic peripheral neuropathy (DPN), painless DPN, without DPN and 20 healthy controls using Fazekas scale and automatic segmentation analysis. ResultsNo differences in Fazekas assessed WMHs were found (individuals with periventricular lesions: diabetes 66 % vs. controls 40 %,p = 0.063, deep lesions: diabetes 52 % vs. controls 50 %,p = 1.0). Using automatic detection, there were no significant differences in count of periventricular (p = 0.30) or deep (p = 0.31) WMHs. Higher periventricular lesion burden was present in diabetes compared with controls (0.21 % vs. 0.06 %,p = 0.048), which was associated with more severe DPN, increased age, decreased cognitive function, and reduced volumetric and metabolic brain measures (all p < 0.05). ConclusionsOur findings indicate increased burden of periventricular WMHs in diabetes which were associated to DPN severity and measures reflecting neurodegeneration. Deep WMHs, often considered as chronic ischemic, were not significantly different. Mechanisms reflecting neurodegeneration and accelerated brain aging could be an overlooked aspect of peripheral and central neuropathy.

Extract of Angelica keiskei Leaves Attenuates Spatial Memory Impairment on the D-galactose Model of Brain Aging in Mice

Aging is a complex and inexorable phenomenon, entailing several physiological changes. Impaired memory skills are associated with cell death in the hippocampus as a result of the age-related buildup of free radicals. D-galactose can artificially accelerate brain aging, causing memory impairment in mice due to neuroinflammation and oxidative stress. Numerous phytoconstituents found in Angelica keiskei possess anti-oxidant, anti-inflammatory, and memory-enhancing properties. In this study, we sought to determine the effects of an ethanol extract from the leaves of A. keiskei (EELAK) on spatial memory in mice with impaired memory functions due to D-gal. Here, we showed that administering 300 mg/kg BW/day of D-gal orally for a duration of 28 days significantly decreased spatial memory as quantified by the Morris Water Maze, and this was linked to a marked increase in hippocampal acetylcholinesterase (AChE), inflammation, and oxidative stress. The spatial memory of D-gal-induced mice was markedly enhanced by 20 mg/kg BW/day of EELAK, demonstrating its potent memory-boosting properties. The mice treated with EELAK also showed a notable decrease in hippocampal neuroinflammation (p65 NF-kB, NO, and TNF-α protein) and an increase in antioxidant activity (elevated SOD activity and reduced MDA levels), suggesting its potent neuroprotective activity. In conclusion, our results establish for the first time that by reducing oxidative stress and neuroinflammation, EELAK enhances spatial memory. Hence, for the prevention and treatment of age-related neurodegenerative illnesses like Alzheimer's disease, EELAK may be a useful therapeutic approach.

Sex-dependent temporal changes in astrocyte-vessel interactions following diffuse traumatic brain injury in rats.

Traumatic brain injury (TBI) is associated with diffuse axonal injury (DAI), a primary pathology linked to progressive neurodegeneration and neuroinflammation, including chronic astrogliosis, which influences long-term post-TBI recovery and morbidity. Sex-based differences in blood-brain barrier (BBB) permeability increases the risk of accelerated brain aging and early-onset neurodegeneration. However, few studies have evaluated chronic time course of astrocytic responses around cerebrovascular in the context of aging after TBI and sex dependence. We observed increased glial fibrillary acidic protein (GFAP)-labeled accessory processes branching near and connecting with GFAP-ensheathed cortical vessels, suggesting a critical nuance in astrocyte-vessel interactions after TBI. To quantify this observation, male and female Sprague Dawley rats (∼3months old, n = 5-6/group) underwent either sham surgery or midline fluid percussion injury. Using immunohistochemical analysis, we quantified GFAP-labeled astrocyte primary and accessory processes that contacted GFAP-ensheathed vessels in the somatosensory barrel cortex at 7, 56, and 168days post-injury (DPI). TBI significantly increased GFAP-positive primary processes at 7 DPI (P < 0.01) in both sexes. At 56 DPI, these vessel-process interactions remained significantly increased exclusively in males (P < 0.05). At 168 DPI, both sexes showed a significant reduction in vessel-process interactions compared to 7 DPI (P < 0.05); however, a modest but significant injury effect reemerged in females (P < 0.05). A similar sex-dependent pattern in the number of accessory processes provides novel evidence of long-term temporal changes in astrocyte-vessel interactions. TBI-induced changes in astrocyte-vessel interactions may indicate chronic BBB vulnerability and processes responsible for early onset vascular and neurodegenerative pathology.

Acceleration of brain aging after small-volume infarcts.

Previous studies have shown that stroke patients exhibit greater neuroimaging-derived biological "brain age" than control subjects. This difference, known as the brain age gap (BAG), is calculated by comparing the chronological age with predicted brain age and is used as an indicator of brain health and aging. However, whether stroke accelerates the process of brain aging in patients with small-volume infarcts has not been established. By utilizing longitudinal data, we aimed to investigate whether small-volume infarctions can significantly increase the BAG, indicating accelerated brain aging. A total of 123 stroke patients presenting with small-volume infarcts were included in this retrospective study. The brain age model was trained via established protocols within the field of machine learning and the structural features of the brain from our previous study. We used t-tests and regression analyses to assess longitudinal brain age changes after stroke and the associations between brain age, acute stroke severity, and poststroke outcome factors. Significant brain aging occurred between the initial and 6-month follow-ups, with a mean increase in brain age of 1.04 years (t = 3.066, p < 0.05). Patients under 50 years of age experienced less aging after stroke than those over 50 years of age (p = 0.245). Additionally, patients with a National Institute of Health Stroke Scale score >3 at admission presented more pronounced adverse effects on brain aging, even after adjusting for confounders such as chronological age, sex, and total intracranial volume (F 1,117 = 7.339, p = 0.008, η 2 = 0.059). There were significant differences in the proportional brain age difference at 6 months among the different functional outcome groups defined by the Barthel Index (F 2,118 = 4.637, p = 0.012, η 2 = 0.073). Stroke accelerates the brain aging process, even in patients with relatively small-volume infarcts. This phenomenon is particularly accentuated in elderly patients, and both stroke severity and poststroke functional outcomes are closely associated with accelerated brain aging. Further studies are needed to explore the mechanisms underlying the accelerated brain aging observed in stroke patients, with a particular focus on the structural alterations and plasticity of the brain following minor strokes.

Anabolic-androgenic steroids in sport

Introduction and objective Anabolic-androgenic steroids (AAS) are a group of doping substances. They cause muscle hypertrophy and an increase in strength. Moreover, they may lead to dangerous side effects. Knowledge of the side effects of AAS use is necessary because in clinical practice we often encounter patients who decide to supplement with steroids. The aim of the study is to present information on the epidemiology, mechanism of action, methods of detecting AAS, the impact of the substance on the male and female body, and a description of organ side effects, highlighting: the cardiovascular system, the nervous system and the psyche. Review methods Literature search was conducted in the PubMed database with inclusion criteria ‘free full texts’ and publications date between 2015 – 2024. A total of 7272 results were found; 30 publications were ultimately included in the review. Abbreviated description of the state of knowledge Overusing AAS is very popular among people training at the gym. They have an anabolic effect on muscle tissue. They contribute to infertility in men and masculinization in women. Stimulation of androgen receptors above physiological doses of AAS leads to vascular changes that, in extreme cases, may lead to sudden cardiac death. Moreover, they accelerate brain aging. An increase in aggression and risky sexual behavior has been observed among people using doping. The diagnostic material used in anti-doping tests is urine and blood serum. Summary AAS abuse is a serious public health problem. Men who want to improve their figure and decide to use doping are particularly at risk. Due to the easy availability of steroids, society should be made aware of the negative effects of steroid use.

Brain Age Is Not a Significant Predictor of Relapse Risk in Late-Life Depression

BackgroundLate-life depression (LLD) has been associated cross-sectionally with lower brain structural volumes and accelerated brain aging compared with healthy control participants (HCs). There are few longitudinal studies on the neurobiological predictors of recurrence in LLD. We tested a machine learning brain age model and its prospective association with LLD recurrence risk. MethodsWe recruited individuals with LLD (n = 102) and HCs (n = 43) into a multisite, 2-year longitudinal study. Individuals with LLD were enrolled within 4 months of remission. Remitted participants with LLD underwent baseline neuroimaging and longitudinal clinical follow-up. Over 2 years, 43 participants with LLD relapsed and 59 stayed in remission. We used a previously developed machine learning brain age algorithm to compute brain age at baseline, and we evaluated brain age group differences (HC vs. LLD and HC vs. remitted LLD vs. relapsed LLD). We conducted a Cox proportional hazards model to evaluate whether baseline brain age predicted time to relapse. ResultsWe found that brain age did not significantly differ between the HC and LLD groups or between the HC, remitted LLD, and relapsed LLD groups. Brain age did not significantly predict time to relapse. ConclusionsIn contrast to our hypothesis, we found that brain age did not differ between control participants without depression and individuals with remitted LLD, and brain age was not associated with subsequent recurrence. This is in contrast to existing literature which has identified baseline brain age differences in late life but consistent with work that has shown no differences between people who do and do not relapse on gross structural measures.

Effects and Thresholds of Young to Midlife Vascular Risks on Brain Health.

Vascular risk factors, particularly hypertension, are important contributors to accelerated brain aging. We sought to quantify vascular risk factor risks over adulthood and assess the empirical evidence for risk thresholds. We used SBP (systolic blood pressure) and diastolic blood pressure, total cholesterol, fasting blood glucose, and body mass index measurements collected from participants in the CARDIA study (Coronary Artery Risk Development in Young Adults) at 2- to 5-year intervals through year 30. The Montreal Cognitive Assessment and domain-specific cognitive tests were performed at year 30. White matter hyperintensity volume was measured by magnetic resonance imaging. We used a 2-step method to fit longitudinal vascular risk factor exposures to optimized spline functions with mixed-effects models, then used the participant-specific random effects that characterized individual exposures over time in cross-sectional models adjusted for sex, race, age, and education to study effects on midlife brain health. Change in SBP up to 33 years of age was negatively associated with Montreal Cognitive Assessment scores (-0.29 Montreal Cognitive Assessment Z score per mm Hg/y change [95% CI, -0.49 to -0.09]; P=0.005), with similar effects for SBP changes from 33 to 49 years of age (-0.08 [95% CI, -0.16 to 0.01]; P=0.08). We observed comparable, significant associations between SBP exposure during those ages, midlife performance on specific cognitive domains, and volume of white matter hyperintensity (all P<0.05). SBP ≤111 mm Hg was the estimated threshold below which no harmful association with midlife cognitive performance was identified. SBP in early adulthood is the vascular risk factor most strongly associated with midlife cognitive performance and white matter hyperintensity burden, with SBP 111 mm Hg suggested as a harm threshold.

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.

White matter brain-age in diverse forms of epilepsy and interictal psychosis

Abnormal brain aging is suggested in epilepsy. Given the brain network dysfunction in epilepsy, the white matter tracts, which primarily interconnect brain regions, could be of special importance. We focused on white matter brain aging in diverse forms of epilepsy and comorbid psychosis. We obtained brain diffusion tensor imaging (DTI) data at 3 T-MRI in 257 patients with epilepsy and 429 healthy subjects. The tract-based fractional anisotropy values of the healthy subjects were used to build a brain-age prediction model, and we calculated the brain-predicted age difference (brain-PAD: predicted age—chronological age) of all subjects. As a result, almost all epilepsy categories showed significantly increased brain-PAD (p < 0.001), including temporal lobe epilepsy (TLE) with no MRI-lesion (+ 4.2 yr), TLE with hippocampal sclerosis (+ 9.1 yr), extratemporal focal epilepsy (+ 5.1 yr), epileptic encephalopathy or progressive myoclonus epilepsy (+ 18.4 yr), except for idiopathic generalized epilepsy (IGE). Patients with psychogenic non-epileptic seizures also presented increased brain-PAD. In TLE, interictal psychosis significantly raised brain-PAD by 8.7 years. In conclusion, we observed increased brain aging in most types of epilepsy, which was generally consistent with brain morphological aging results in previous studies. Psychosis may accelerate brain aging in TLE. These findings may suggest abnormal aging mechanisms in epilepsy and comorbid psychotic symptoms.

Redundancy protects processing speed in healthy individuals with accelerated brain aging.

Recent advancements in computational learning techniques have enabled the estimation of brain age (BA) from neuroimaging data. The difference between chronological age (CA) and BA, known as the BA gap, can potentially serve as a biomarker of brain health. Studies, however, have documented low correlations between BA gap and cognition in healthy aging. This suggests that protective mechanisms in the brain may help counter the effect of accelerated brain aging. Here, we investigated whether redundancy in brain networks may protect cognitive function in individuals with accelerated brain aging. First, we employed deep learning to estimate individual brain ages from structural magnetic resonance imaging (MRI). Next, we associated CA, BA, and BA gap, with cognitive measures and network topology derived from diffusion MRI and tractography. We found that CA and BA were both similarly related to cognitive measures and network topology, while BA gap did not show strong relationships in either domain. Despite observing no strong relationships between brain-age gap (BA gap) and demographic variables, cognitive measures, or topological features in healthy aging, individuals with accelerated aging (BA gap+) exhibited lower average degree and redundancy within the dorsal attention network compared to those with delayed aging (BA gap-). Furthermore, redundancy in the dorsal attention network was positively associated with processing speed in BA gap+ individuals. These results indicate a potential neuroprotective role of redundancy in structural brain networks for mitigating the impact of accelerated brain atrophy on cognitive performance in healthy aging.

Compromised cell competition exhausts neural stem cells pool.

Blood vessels play a crucial role in maintaining the stem cell niche in both tumours and developing organs. Cell competition is critical for tumour progression. We hypothesise that blood vessels may act as a regulator of this process. As a pioneer, the secretions of blood vessels regulate the intensity of cell competition, which is essential for tumour invasion and developmental organ extension. Brd4 expresses highly in endothelial cells within various tumours and is positively correlated with numerous invasive genes, making it an ideal focal point for further research on the relationship between blood vessels and cell competition. Our results indicated that the absence of endothelial Brd4 led to a reduction in neural stem cell mortality and compromised cell competition. Endothelial Brd4 regulated cell competition was dependent on Testican2. Testican2 was capable of depositing Sparc and acted as a suppressor of Sparc. Compromised cell competition resulted in the depletion of neural stem cells and accelerated brain ageing. Testican2 could rescue the run-off of neural stem cells and accelerate the turnover rate of neurons. AD patients show compromised cell competition. Through the cloning of a point mutant of Brd4 identified in a subset of AD patients, it was demonstrated that the mutant lacked the ability to promote cell competition. This study suggests a novel approach for treating age-related diseases by enhancing the intensity of cell competition.

Frequent Alzheimer's disease neuropathological change in patients with glioblastoma.

The incidence of brain cancer and neurodegenerative diseases is increasing with a demographic shift towards aging populations. Biological parallels have been observed between glioblastoma and Alzheimer's disease (AD), which converge on accelerated brain aging. Here, we aimed to map the cooccurrence of AD neuropathological change (ADNC) in the tumor-adjacent cortex of patients with glioblastoma. Immunohistochemical screening of AD markers amyloid beta (Abeta), amyloid precursor protein (APP), and hyperphosphorylated tau (pTau) was conducted in 420 tumor samples of 205 patients. For each cortex area, we quantified ADNC, neurons, tumor cells, and microglia. Fifty-two percent of patients (N = 106/205) showed ADNC (Abeta and pTau, Abeta or pTau) in the tumor-adjacent cortex, with histological patterns widely consistent with AD. ADNC was positively correlated with patient age and varied spatially according to Thal phases and Braak stages. It decreased with increasing tumor cell infiltration (P < .0001) and was independent of frequent expression of APP in neuronal cell bodies (N = 182/205) and in tumor necrosis-related axonal spheroids (N = 195/205; P = .46). Microglia response was most present in tumor cell infiltration plus ADNC, being further modulated by patient age and sex. ADNC did not impact patient survival in the present cohort. Our findings highlight the frequent presence of ADNC in the glioblastoma vicinity, which was linked to patient age and tumor location. The cooccurrence of AD and glioblastoma seemed stochastic without clear spatial relation. ADNC did not impact patient survival in our cohort.

Plasma neurofilament light protein is differentially associated with age in individuals with treatment-resistant schizophrenia and bipolar affective disorder compared to controls

Accelerated brain ageing has been observed in multiple psychiatric disorders. This study examined whether relationships between age and plasma neurofilament light (NfL) protein differed in individuals with psychiatric disorders (major depressive disorder (n = 42), bipolar affective disorder (n = 121), treatment-resistant schizophrenia (TRS, n = 82)) compared to two healthy control (HC) groups (n = 1,926 and n = 59). Compared to two independent HC samples, individuals with TRS demonstrated a stronger positive relationship between age and NfL levels. Individuals with BPAD had a stronger negative relationship between age and NfL levels compared to the large normative HC cohort, but not locally-acquired HCs. These findings show that plasma NfL levels are differentially associated with age in individuals with TRS and BPAD compared to healthy individuals.

Ethnic differences in the effects of apolipoprotein E ɛ4 and vascular risk factors on accelerated brain aging.

The frequency of the apolipoprotein E ɛ4 allele and vascular risk factors differs among ethnic groups. We aimed to assess the combined effects of apolipoprotein E ɛ4 and vascular risk factors on brain age in Korean and UK cognitively unimpaired populations. We also aimed to determine the differences in the combined effects between the two populations. We enrolled 2314 cognitively unimpaired individuals aged ≥45 years from Korea and 6942 cognitively unimpaired individuals from the UK, who were matched using propensity scores. Brain age was defined using the brain age index. The apolipoprotein E genotype (ɛ4 carriers, ɛ2 carriers and ɛ3/ɛ3 homozygotes) and vascular risk factors (age, hypertension and diabetes) were considered predictors. Apolipoprotein E ɛ4 carriers in the Korean (β = 0.511, P = 0.012) and UK (β = 0.302, P = 0.006) groups had higher brain age index values. The adverse effects of the apolipoprotein E genotype on brain age index values increased with age in the Korean group alone (ɛ2 carriers × age, β = 0.085, P = 0.009; ɛ4 carriers × age, β = 0.100, P < 0.001). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ2 carriers × age × ethnicity, β = 0.091, P = 0.022; ɛ4 carriers × age × ethnicity, β = 0.093, P = 0.003). The effects of apolipoprotein E on the brain age index values were more pronounced in individuals with hypertension in the Korean group alone (ɛ4 carriers × hypertension, β = 0.777, P = 0.038). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ4 carriers × hypertension × ethnicity, β=1.091, P = 0.014). We highlight the ethnic differences in the combined effects of the apolipoprotein E ɛ4 genotype and vascular risk factors on accelerated brain age. These findings emphasize the need for ethnicity-specific strategies to mitigate apolipoprotein E ɛ4-related brain aging in cognitively unimpaired individuals.

Population clustering of structural brain aging and its association with brain development.

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.