Proteomic analysis of APOEε4 carriers implicates lipid metabolism, complement and lymphocyte signaling in cognitive resilience.

BACKGROUND: Apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer's disease (AD). This case-cohort study used targeted plasma biomarkers and large-scale proteomics to examine the biological mechanisms that allow some APOEε4 carriers to maintain normal cognitive functioning in older adulthood. METHODS: APOEε4 carriers and APOEε3 homozygotes enrolled in the Women's Health Initiative Memory Study (WHIMS) from 1996 to 1999 were classified as resilient if they remained cognitively unimpaired beyond age 80, and as non-resilient if they developed cognitive impairment before or at age 80. AD pathology (Aß42/40) and neurodegeneration (NfL, tau) biomarkers, as well as 1007 proteins (Olink) were quantified in blood collected at study enrollment (on average 14 years prior) when participants were cognitively normal. We identified plasma proteins that distinguished between resilient and non-resilient APOEε4 carriers, examined whether these associations generalized to APOEε3 homozygotes, and replicated these findings in the UK Biobank. RESULTS: A total of 1610 participants were included (baseline age: 71.3 [3.8 SD] years; all White; 42% APOEε4 carriers). Compared to resilient APOEε4 carriers, non-resilient APOEε4 carriers had lower Aß42/40/tau ratio and greater NfL at baseline. Proteomic analyses identified four proteins differentially expressed between resilient and non-resilient APOEε4 carriers at an FDR-corrected P < 0.05. While one of the candidate proteins, a marker of neuronal injury (NfL), also distinguished resilient from non-resilient APOEε3 homozygotes, the other three proteins, known to be involved in lipid metabolism (ANGPTL4) and immune signaling (PTX3, NCR1), only predicted resilient vs. non-resilient status among APOEε4 carriers (protein*genotype interaction-P < 0.05). Three of these four proteins also predicted 14-year dementia risk among APOEε4 carriers in the UK Biobank validation sample (N = 9420). While the candidate proteins showed little to no association with targeted biomarkers of AD pathology, protein network and enrichment analyses suggested that natural killer (NK) cell and T lymphocyte signaling (via PKC-θ) distinguished resilient from non-resilient APOEε4 carriers. CONCLUSIONS: We identified and replicated a plasma proteomic signature associated with cognitive resilience among APOEε4 carriers. These proteins implicate specific immune processes in the preservation of cognitive status despite elevated genetic risk for AD. Future studies in diverse cohorts will be needed to assess the generalizability of these results.

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer's disease neuropathology.

BACKGROUND: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aß) profiles, and to predicted progression to Alzheimer's disease (AD). METHODS: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). FINDINGS: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. INTERPRETATION: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. FUNDING: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

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.

A hematology-based clock derived from the Study of Longitudinal Aging in Mice to estimate biological age.

Biological clocks and other molecular biomarkers of aging are difficult to implement widely in a clinical setting. In this study, we used routinely collected hematological markers to develop an aging clock to predict blood age and determine whether the difference between predicted age and chronologic age (aging gap) is associated with advanced aging in mice. Data from 2,562 mice of both sexes and three strains were drawn from two longitudinal studies of aging. Eight hematological variables and two metabolic indices were collected longitudinally (12,010 observations). Blood age was predicted using a deep neural network. Blood age was significantly correlated with chronological age, and aging gap was positively associated with mortality risk and frailty. Platelets were identified as the strongest age predictor by the deep neural network. An aging clock based on routinely collected blood measures has the potential to provide a practical clinical tool to better understand individual variability in the aging process.

Body Mass Index and Diabetes Incidence Across the Adult Lifespan: The Baltimore Longitudinal Study of Aging.

Context: Body composition and glucose metabolism change with aging. Whether different levels of body-mass-index (BMI) are needed to define diabetes risk across the adult lifespan is unknown. Objective: This work aimed to investigate whether BMI similarly reflects relative fat mass (FM) and diabetes risk across age groups. Methods: Participants without diabetes from the Baltimore Longitudinal Study of Aging (973 men, 1073 women), stratified by age (<50, 50-59, 60-69, ≥70 years) and categorized by either World Health Organization (WHO)-defined BMI categories (for normal weight, overweight or obesity) or BMI quartiles. The primary exposure was BMI. The primary outcome was diabetes incidence. The relationship of BMI to dual-energy x-ray absorptiometry-derived FM was also investigated in older vs younger participants. Results: The median (range) follow-up time was 7.1 years (range, 0-29.0 years). Within WHO-defined BMI categories, different age groups demonstrated significantly different FM percentage, FM/lean mass, and waist circumference (P < .05). WHO-defined BMI categories for overweight and obesity were generally related to higher diabetes risk compared to normal weight in all ages except 50 to 59 years. When BMI was categorized by quartiles, diabetes incidence increased dramatically beginning in quartile 2 (23-25 kg/m2) in older groups. BMI cutoffs with equivalent diabetes incidence rate as BMI 25 kg/m2 and 30.0 kg/m2 in individuals younger than 50 years were 22.7 kg/m2 and 25.2 kg/m2 for ages 50 to 59 years; 22.8 kg/m2 and 25.0 kg/m2 for ages 60 to 69 years; and 23.2 kg/m2 and 25.8 kg/m2 for ages 70 years and older, respectively. Conclusion: WHO-defined BMI categories do not reflect similar diabetes risk across the lifespan. Diabetes incidence is greater at lower levels of BMI in older adults and may lead to underestimation of diabetes risk with aging, particularly among those traditionally classified as normal-weight individuals.

Mitochondria break free: Mitochondria-derived vesicles in aging and associated conditions.

Mitophagy is the intracellular recycling system that disposes damaged/inefficient mitochondria and allows biogenesis of new organelles to ensure mitochondrial quality is optimized. Dysfunctional mitophagy has been implicated in human aging and diseases. Multiple evolutionarily selected, redundant mechanisms of mitophagy have been identified, but their specific roles in human health and their potential exploitation as therapeutic targets are unclear. Recently, the characterization of the endosomal-lysosomal system has revealed additional mechanisms of mitophagy and mitochondrial quality control that operate via the production of mitochondria-derived vesicles (MDVs). Circulating MDVs can be isolated and characterized to provide an unprecedented opportunity to study this type of mitochondrial recycling in vivo and to relate it to human physiology and pathology. Defining the role of MDVs in human physiology, pathology, and aging is hampered by the lack of standardized methods to isolate, validate, and characterize these vesicles. Hence, some basic questions about MDVs remain unanswered. While MDVs are generated directly through the extrusion of mitochondrial membranes within the cell, a set of circulating extracellular vesicles leaking from the endosomal-lysosomal system and containing mitochondrial portions have also been identified and warrant investigation. Preliminary research indicates that MDV generation serves multiple biological roles and contributes to restoring cell homeostasis. However, studies have shown that MDVs may also be involved in pathological conditions. Therefore, further research is warranted to establish when/whether MDVs are supporting disease progression and/or are extracting damaged mitochondrial components to alleviate cellular oxidative burden and restore redox homeoastasis. This information will be relevant for exploiting these vesicles for therapeutic purpose. Herein, we provide an overview of preclinical and clinical studies on MDVs in aging and associated conditions and discuss the interplay between MDVs and some of the hallmarks of aging (mitophagy, inflammation, and proteostasis). We also outline open questions on MDV research that should be prioritized by future investigations.

The role of genetically predicted serum iron levels on neurodegenerative and cardiovascular traits.

Iron is an essential mineral that supports numerous biological functions. Studies have reported associations between iron dysregulation and certain cardiovascular and neurodegenerative diseases, but the direction of influence is not clear. Our goal was to use computational approaches to better understand the role of genetically predicted iron levels on disease risk. We meta-analyzed genome-wide association study summary statistics for serum iron levels from two cohorts and two previous meta-analyses. We then obtained summary statistics from 11 neurodegenerative, cerebrovascular, cardiovascular or lipid traits to assess global and regional genetic correlation between iron levels and these traits. We used two-sample Mendelian randomization (MR) to estimate causal effects. Sex-stratified analyses were also carried out to identify effects potentially differing by sex. Overall, we identified three significant global correlations between iron levels and (i) coronary heart disease, (ii) triglycerides, and (iii) high-density lipoprotein (HDL) cholesterol levels. A total of 194 genomic regions had significant (after correction for multiple testing) local correlations between iron levels and the 11 tested traits. MR analysis revealed two potential causal relationships, between genetically predicted iron levels and (i) total cholesterol or (ii) non-HDL cholesterol. Sex-stratified analyses suggested a potential protective effect of iron levels on Parkinson's disease risk in females, but not in males. Our results will contribute to a better understanding of the genetic basis underlying iron in cardiovascular and neurological health in aging, and to the eventual identification of new preventive interventions or therapeutic avenues for diseases which affect women and men worldwide.

Critical assessment of anti-amyloid-ß monoclonal antibodies effects in Alzheimer's disease: a systematic review and meta-analysis highlighting target engagement and clinical meaningfulness.

Despite most monoclonal antibodies against Aß in Alzheimer's failed to demonstrate efficacy, the newest antibodies showed statistically significant clinical effects. We conducted a systematic review and meta-analysis to assess the efficacy, target engagement, and safety of anti-Aß antibodies in sporadic AD including phase III RCTs published up to November 28, 2023. Antibodies as a drug class, attenuated worsening on the clinical scales CDR-SB and ADAS-Cog by very small effect sizes and reduced amyloid on PET by a very large effect size. Reduction of amyloid on PET was moderately correlated with CDR-SB and ADAS-Cog reductions. However, antibodies increased risk of ARIA-E and ARIA-H by a very large and moderate effect size, respectively. In subgroup analyses by individual drug, Donanemab and Lecanemab induced the largest benefits. In subgroup analyses by binding affinity, antibodies without binding to monomers were associated with the most favorable effects. Despite statistical significance for improvement on clinical measures, antibody effects were below the threshold of clinically meaningful change during the period they were studied. However, the newest antibodies demonstrably interfere with the underlying ΑD pathophysiology and therefore their benefit could be cumulative over time leading to larger clinical effects in subsequent years. PROSPERO registration no. CRD42022381334.

Variability of 7K and 11K SomaScan Plasma Proteomics Assays.

SomaScan is an aptamer-based proteomics assay designed for the simultaneous measurement of thousands of human proteins with a broad range of endogenous concentrations. The 7K SomaScan assay has recently been expanded into the new 11K version. Following up on our previous assessment of the 7K assay, here, we expand our work on technical replicates from donors enrolled in the Baltimore Longitudinal Study of Aging. By generating SomaScan data from a second batch of technical replicates in the 7K version as well as additional intra- and interplate replicate measurements in the new 11K version using the same donor samples, this work provides useful precision benchmarks for the SomaScan user community. Beyond updating our previous technical assessment of the 7K assay with increased statistics, here, we estimate interbatch variability, assess inter- and intraplate variability in the new 11K assay, compare the observed variability between the 7K and 11K assays (leveraging the use of overlapping pairs of technical replicates), and explore the potential effects of sample storage time (ranging from 2 to 30 years) in the assays' precision.

White matter integrity and motor function: a link between cerebral myelination and longitudinal changes in gait speed in aging.

Gait speed is a robust health biomarker in older adults, correlating with the risk of physical and cognitive impairments, including dementia. Myelination plays a crucial role in neurotransmission and consequently affects various functions, yet the connection between myelination and motor functions such as gait speed is not well understood. Understanding this link could offer insights into diagnosing and treating neurodegenerative diseases that impair mobility. This study analyzed 437 longitudinal observations from 138 cognitively unimpaired adults, aged 22 to 94 years, to investigate the relationship between myelin content and changes in gait speed over an average of 6.42 years. Myelin content was quantified using a novel multicomponent magnetic resonance relaxometry method, and both usual and rapid gait speeds (UGS, RGS) were measured following standard protocols. Adjusting for covariates, we found a significant fixed effect of myelin content on UGS and RGS. Longitudinally, lower myelin content was linked to a greater decline in UGS, particularly in brain regions associated with motor planning. These results suggest that changes in UGS may serve as a reliable marker of neurodegeneration, particularly in cognitively unimpaired adults. Interestingly, the relationship between myelin content and changes in RGS was only observed in a limited number of brain regions, although the reason for such local susceptibility remains unknown. These findings enhance our understanding of the critical role of myelination in gait performance in unimpaired adults and provide evidence of the interconnection between myelin content and motor function impairment.

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/ .

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.

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.

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.

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.

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.

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.

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.

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.

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.