Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum.

Alzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .

A plasma proteomic signature links secretome of senescent monocytes to aging- and obesity-related clinical outcomes in humans.

Cellular senescence increases with age and contributes to age-related declines and pathologies. We identified circulating biomarkers of senescence associated with diverse clinical traits in humans to facilitate future non-invasive assessment of individual senescence burden and efficacy testing of novel senotherapeutics. Using a novel nanoparticle-based proteomic workflow, we profiled the senescence-associated secretory phenotype (SASP) in monocytes and examined these proteins in plasma samples (N = 1060) from the Baltimore Longitudinal Study of Aging (BLSA). Machine learning models trained on monocyte SASP associated with several age-related phenotypes in a test cohort, including body fat composition, blood lipids, inflammation, and mobility-related traits, among others. Notably, a subset of SASP-based predictions, including a 'high impact' SASP panel that predicts age- and obesity-related clinical traits, were validated in InCHIANTI, an independent aging cohort. These results demonstrate the clinical relevance of the circulating SASP and identify relevant biomarkers of senescence that could inform future clinical studies.

The ankle-brachial index, gastrocnemius mitochondrial respirometry, and walking performance in people with and without peripheral artery disease.

Background: Mitochondrial abnormalities exist in lower-extremity peripheral artery disease (PAD), yet the association of the ankle-brachial index (ABI) with mitochondrial respiration in gastrocnemius muscle is unknown. The association of gastrocnemius mitochondrial respiration with 6-minute walk distance in PAD is unknown. Objective: To describe associations of the ABI with mitochondrial respiratory function in gastrocnemius muscle biopsies and associations of gastrocnemius mitochondrial respirometry with 6-minute walk distance in people with and without PAD. Methods: People with (ABI ⩽ 0.90) and without (ABI 1.00-1.40) PAD were enrolled. ABI and 6-minute walk distance were measured. Mitochondrial function of permeabilized myofibers from gastrocnemius biopsies was measured with high-resolution respirometry. Results: A total of 30 people with PAD (71.7 years, mean ABI: 0.64) and 68 without PAD (71.8 years, ABI: 1.17) participated. In non-PAD participants, higher ABI values were associated significantly with better mitochondrial respiration (Pearson correlation for maximal oxidative phosphorylation PCI+II: +0.29, p = 0.016). In PAD, the ABI correlated negatively and not significantly with mitochondrial respiration (Pearson correlation for PCI+II: -0.17, p = 0.38). In people without PAD, better mitochondrial respiration was associated with better 6-minute walk distance (Pearson correlation: +0.51, p < 0.001), but this association was not present in PAD (Pearson correlation: +0.10, p = 0.59). Conclusions: Major differences exist between people with and without PAD in the association of gastrocnemius mitochondrial respiration with ABI and 6-minute walk distance. Among people without PAD, ABI and walking performance were positively associated with mitochondrial respiratory function. These associations were not observed in PAD.

Deep network and multi-atlas segmentation fusion for delineation of thigh muscle groups in three-dimensional water-fat separated MRI.

Purpose: Segmentation is essential for tissue quantification and characterization in studies of aging and age-related and metabolic diseases and the development of imaging biomarkers. We propose a multi-method and multi-atlas methodology for automated segmentation of functional muscle groups in three-dimensional (3D) thigh magnetic resonance images. These groups lie anatomically adjacent to each other, rendering their manual delineation a challenging and time-consuming task. Approach: We introduce a framework for automated segmentation of the four main functional muscle groups of the thigh, gracilis, hamstring, quadriceps femoris, and sartorius, using chemical shift encoded water-fat magnetic resonance imaging (CSE-MRI). We propose fusing anatomical mappings from multiple deformable models with 3D deep learning model-based segmentation. This approach leverages the generalizability of multi-atlas segmentation (MAS) and accuracy of deep networks, hence enabling accurate assessment of volume and fat content of muscle groups. Results: For segmentation performance evaluation, we calculated the Dice similarity coefficient (DSC) and Hausdorff distance 95th percentile (HD-95). We evaluated the proposed framework, its variants, and baseline methods on 15 healthy subjects by threefold cross-validation and tested on four patients. Fusion of multiple atlases, deformable registration models, and deep learning segmentation produced the top performance with an average DSC of 0.859 and HD-95 of 8.34 over all muscles. Conclusions: Fusion of multiple anatomical mappings from multiple MAS techniques enriches the template set and improves the segmentation accuracy. Additional fusion with deep network decisions applied to the subject space offers complementary information. The proposed approach can produce accurate segmentation of individual muscle groups in 3D thigh MRI scans.

Cardiovascular health, measured using Life's Essential 8, is associated with reduced dementia risk among older men and women.

BACKGROUND: Dementia poses considerable challenges to healthy aging. Prevention and management of dementia are essential given the lack of effective treatments for this condition. METHODS: A secondary data analysis was conducted using data from 928 InCHIANTI study participants (55% female) aged 65 years and older without dementia at baseline. Cardiovascular health (CVH) was assessed by the "Life's Essential 8" (LE8) metric that included health behaviors (diet, physical activity, smoking status, sleep duration) and health factors (body mass index, blood lipid, blood glucose, blood pressure). This new LE8 metric scores from 0 to 100, with categorization including "low LE8" (0-49), indicating low CVH, "moderate LE8 (50-79)", indicating moderate CVH, and "high LE8 (80-100)", indicating high CVH. Dementia was ascertained by a combination of neuropsychological testing and clinical assessment at each follow-up visit. Cox proportional hazards models were used to examine associations between CVH at baseline and risk of incident dementia after a median follow-up of 14 years. RESULTS: Better CVH (moderate/high LE8 vs. low LE8) was inversely associated with the risk of incident dementia (hazard ratio [HR]: 0.61, 95% confidence interval [CI]: 0.46-0.83, p = 0.001). Compared with health factors, higher scores of the health behaviors (per 1 standard deviation [SD]), specifically weekly moderate-to-vigorous physical activity time (per 1 SD), were significantly associated with a lower risk of incident dementia (health behaviors: HR:0.84, CI:0.73-0.96, p = 0.01; physical activity: HR: 0.62, CI: 0.53-0.72, p < 0.001). CONCLUSION: While longitudinal studies with repeated measures of CVH are needed to confirm these findings, improving CVH, measured by the LE8 metric, may be a promising dementia prevention strategy.

Clinical-transcriptional prioritization of the circulating proteome in human heart failure.

Given expanding studies in epidemiology and disease-oriented human studies offering hundreds of associations between the human "ome" and disease, prioritizing molecules relevant to disease mechanisms among this growing breadth is important. Here, we link the circulating proteome to human heart failure (HF) propensity (via echocardiographic phenotyping and clinical outcomes) across the lifespan, demonstrating key pathways of fibrosis, inflammation, metabolism, and hypertrophy. We observe a broad array of genes encoding proteins linked to HF phenotypes and outcomes in clinical populations dynamically expressed at a transcriptional level in human myocardium during HF and cardiac recovery (several in a cell-specific fashion). Many identified targets do not have wide precedent in large-scale genomic discovery or human studies, highlighting the complementary roles for proteomic and tissue transcriptomic discovery to focus epidemiological targets to those relevant in human myocardium for further interrogation.

Challenges and recommendations for the translation of biomarkers of aging.

Biomarkers of aging (BOA) are quantitative parameters that predict biological age and ideally its changes in response to interventions. In recent years, many promising molecular and omic BOA have emerged with an enormous potential for translational geroscience and improving healthspan. However, clinical translation remains limited, in part due to the gap between preclinical research and the application of BOA in clinical research and other translational settings. We surveyed experts in these areas to better understand current challenges for the translation of aging biomarkers. We identified six key barriers to clinical translation and developed guidance for the field to overcome them. Core recommendations include linking BOA to clinically actionable insights, improving affordability and availability to broad populations and validation of biomarkers that are robust and responsive at the level of individuals. Our work provides key insights and practical recommendations to overcome barriers impeding clinical translation of BOA.

Mitochondrial DNA copy number associated dementia risk by somatic mutations and frailty.

Mitochondrial dysfunction is linked to physical impairment and dementia. Mitochondrial DNA copy number (mtDNAcn) from blood may predict cognitive decline and dementia risk, but the effect of somatic mutations or frailty is unknown. We estimated mtDNAcn using fastMitoCalc and microheteroplasmies using mitoCaller, from Whole Genome Sequencing (WGS) data. In 189,566 participants free of dementia at study entry (mean age = 56 ± 8), we examined the association between mtDNAcn and subsequent dementia diagnosis using Cox regression. Cognition was assessed in a subset on average 8.9 years later. We examined the associations between mtDNAcn and cognitive measures using multivariable linear regression, adjusted for demographic factors, mtDNAcn-related parameters, and apolipoprotein E ε4 status. We further stratified by frailty and microheteroplasmies. Over an average follow-up of 13.2 years, 3533 participants developed dementia. Each SD higher mtDNAcn (16) was associated with 4.2% lower all-cause dementia hazard (HR = 0.958, p = 0.030), 6% lower non-AD dementia hazard (HR = 0.933, p = 0.022), and not-AD dementia hazard. The associations between mtDNAcn and all-cause dementia and non-AD dementia were stronger among those who were pre-frail or frail or with higher microheteroplasmies. Higher mtDNAcn was associated with higher DSST scores (p = 0.036) and significant only among those with higher microheteroplasmies or frailty (p = 0.029 and 0.048, respectively). mtDNAcn was also associated with delta TMT and paired associate learning only in pre-frail/frail participants (p = 0.007 and 0.045, respectively). Higher WGS-based mtDNAcn in human blood is associated with lower dementia risk, specifically non-AD dementia, and specific cognitive function. The relationships appear stronger in high somatic mutations or frailty. Future studies are warranted to investigate biological underpinnings.

The repeated bout effect evokes the training-induced skeletal muscle cellular memory.

Physical exercise is well-established as beneficial for health. With the 20th-century epidemiological transition, promoting healthy habits like exercise has become crucial for preventing chronic diseases. Stress can yield adaptive long-term benefits, potentially transmitted trans-generationally. Physical training exposes individuals to metabolic, thermal, mechanical, and oxidative stressors, activating cell signaling pathways that regulate gene expression and adaptive responses, thereby enhancing stress tolerance-a phenomenon known as hormesis. Muscle memory is the capacity of skeletal muscle to respond differently to environmental stimuli in an adaptive (positive) or maladaptive (negative) manner if the stimuli have been encountered previously. The Repeated Bout Effect encompasses our skeletal muscle capacity to activate an intrinsic protective mechanism that reacts to eccentric exercise-induced damage by activating an adaptive response that resists subsequent damage stimuli. Deciphering the molecular mechanism of this phenomenon would allow the incorporation of muscle memory in training programs for professional athletes, active individuals looking for the health benefits of exercise training, and patients with "exercise intolerance." Moreover, enhancing the adaptive response of muscle memory could promote healing in individuals who traditionally do not recover after immobilization. The improvement could be part of an exercise program but could also be targeted pharmacologically. This review explores Repeated Bout Effect mechanisms: neural adaptations, tendon and muscle fiber property changes, extracellular matrix remodeling, and improved inflammatory responses.

Evidence of association between higher cardiorespiratory fitness and higher cerebral myelination in aging.

Emerging evidence suggests that altered myelination is an important pathophysiologic correlate of several neurodegenerative diseases, including Alzheimer and Parkinson's diseases. Thus, improving myelin integrity may be an effective intervention to prevent and treat age-associated neurodegenerative pathologies. It has been suggested that cardiorespiratory fitness (CRF) may preserve and enhance cerebral myelination throughout the adult lifespan, but this hypothesis has not been fully tested. Among cognitively normal participants from two well-characterized studies spanning a wide age range, we assessed CRF operationalized as the maximum rate of oxygen consumption (VO2max) and myelin content defined by myelin water fraction (MWF) estimated through our advanced multicomponent relaxometry MRI method. We found significant positive correlations between VO2max and MWF across several white matter regions. Interestingly, the effect size of this association was higher in brain regions susceptible to early degeneration, including the frontal lobes and major white matter fiber tracts. Further, the interaction between age and VO2max exhibited i) a steeper positive slope in the older age group, suggesting that the association of VO2max with MWF is stronger at middle and older ages and ii) a steeper negative slope in the lower VO2max group, indicating that lower VO2max levels are associated with lower myelination with increasing age. Finally, the nonlinear pattern of myelin maturation and decline is VO2max-dependent with the higher VO2max group reaching the MWF peak at later ages. This study provides evidence of an interconnection between CRF and cerebral myelination and suggests therapeutic strategies for promoting brain health and attenuating white matter degeneration.

Proteomics identifies potential immunological drivers of postinfection brain atrophy and cognitive decline.

Infections have been associated with the incidence of Alzheimer disease and related dementias, but the mechanisms responsible for these associations remain unclear. Using a multicohort approach, we found that influenza, viral, respiratory, and skin and subcutaneous infections were associated with increased long-term dementia risk. These infections were also associated with region-specific brain volume loss, most commonly in the temporal lobe. We identified 260 out of 942 immunologically relevant proteins in plasma that were differentially expressed in individuals with an infection history. Of the infection-related proteins, 35 predicted volumetric changes in brain regions vulnerable to infection-specific atrophy. Several of these proteins, including PIK3CG, PACSIN2, and PRKCB, were related to cognitive decline and plasma biomarkers of dementia (Aß42/40, GFAP, NfL, pTau-181). Genetic variants that influenced expression of immunologically relevant infection-related proteins, including ITGB6 and TLR5, predicted brain volume loss. Our findings support the role of infections in dementia risk and identify molecular mediators by which infections may contribute to neurodegeneration.

Brain aging patterns in a large and diverse cohort of 49,482 individuals.

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Can geroscience be translated into healthcare?

As an introduction to this special issue on geroscience, the present work focuses on the complexity of disentangling biomolecular mechanisms of aging from biopsychosocial causes of accelerated aging. Due to this complexity, the biomolecular aging hallmarks of frailty and multimorbidity as predominant aging phenotypes in geriatrics reflect single aspects of the aging process. A possible approach to facilitate the integration of geroscience into healthcare might be to consider aging as the dynamic ratio between damage accumulation at the molecular and cellular level and resilience as strategies that prevent or repair such damage. There is a large body of evidence to show that geroscience has the potential to change healthcare; however, reaching a consensus and translating the best tool to measure aging needs more research on 1) the sensitivity of biomarkers to interventions and 2) the relationship between changes in biomarkers and changes in health trajectories.

Age and objectively measured sleep: investigating associations and interactions by sex and race in middle-aged and older adults.

Study Objectives: Few studies of middle-aged and older adults have examined the association between age and sleep using objective sleep measures. We examined these associations in adults aged ≥40 years using wrist actigraphy, and investigated whether these associations differed by sex and race. Methods: Participants were 468 cognitively normal adults aged ≥40 years enrolled in the Baltimore Longitudinal Study of Aging who completed wrist actigraphy. We used Generalized Least Squares Models to examine the associations of age with actigraphic sleep parameters, including total sleep time (TST), sleep efficiency, sleep onset latency, and wake after sleep onset (WASO). We conducted interaction and stratification analyses to test whether cross-sectional age-sleep associations were modified by sex and race. Results: In analyses adjusting for sex, body mass index, and individual medical conditions, older age was associated with longer TST from ages 40-70 that plateaued after age 70. Older age also was associated with lower sleep efficiency, longer sleep onset latency, and greater WASO. In men only, after age 70, older age was associated with shorter TST, lower sleep efficiency, longer onset latency, and greater WASO. However, we did not observe any significant interactions of race with age. Conclusions: Older age was associated with longer TST from ages 40 to 70 and with poorer sleep quality after age 40, and these relationships might vary by sex. Future studies with larger sample sizes are needed to investigate mechanisms that may account for sex differences in the observed age-sleep associations.

Proteome-wide analysis identifies plasma immune regulators of amyloid-beta progression.

While immune function is known to play a mechanistic role in Alzheimer's disease (AD), whether immune proteins in peripheral circulation influence the rate of amyloid-ß (Aß) progression - a central feature of AD - remains unknown. In the Baltimore Longitudinal Study of Aging, we quantified 942 immunological proteins in plasma and identified 32 (including CAT [catalase], CD36 [CD36 antigen], and KRT19 [keratin 19]) associated with rates of cortical Aß accumulation measured with positron emission tomography (PET). Longitudinal changes in a subset of candidate proteins also predicted Aß progression, and the mid- to late-life (20-year) trajectory of one protein, CAT, was associated with late-life Aß-positive status in the Atherosclerosis Risk in Communities (ARIC) study. Genetic variation that influenced plasma levels of CAT, CD36 and KRT19 predicted rates of Aß accumulation, including causal relationships with Aß PET levels identified with two-sample Mendelian randomization. In addition to associations with tau PET and plasma AD biomarker changes, as well as expression patterns in human microglia subtypes and neurovascular cells in AD brain tissue, we showed that 31 % of candidate proteins were related to mid-life (20-year) or late-life (8-year) dementia risk in ARIC. Our findings reveal plasma proteins associated with longitudinal Aß accumulation, and identify specific peripheral immune mediators that may contribute to the progression of AD pathophysiology.

A unified metric of human immune health.

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine.