Sleep Duration Polygenic Risk and Phenotype: Associations with Biomarkers of Accelerated Aging in the Baltimore Longitudinal Study of Aging.

We sought to explore whether genetic risk for, and self-reported, short sleep are associated with biological aging and whether age and sex moderate these associations. Participants were a subset of individuals from the Baltimore Longitudinal Study of Aging who had complete data on self-reported sleep (n = 567) or genotype (n = 367). Outcomes included: Intrinsic Horvath age, Hannum age, PhenoAge, GrimAge, and DNAm-based estimates of plasminogen activator inhibitor-1 (PAI-1) and granulocyte count. Results demonstrated that polygenic risk for short sleep was positively associated with granulocyte count; compared to those reporting <6 hr sleep, those reporting >7 hr demonstrated faster PhenoAge and GrimAge acceleration and higher estimated PAI-1. Polygenic risk for short sleep and self-reported sleep duration interacted with age and sex in their associations with some of the outcomes. Findings highlight that polygenic risk for short sleep and self-reported long sleep is associated with variation in the epigenetic landscape and subsequently aging.

A Gentle Introduction to Bayesian Network Meta-Analysis Using an Automated R Package.

Network meta-analysis is an extension of standard meta-analysis. It allows researchers to build a network of evidence to compare multiple interventions that may have not been compared directly in existing publications. With a Bayesian approach, network meta-analysis can be used to obtain a posterior probability distribution of all the relative treatment effects, which allows for the estimation of relative treatment effects to quantify the uncertainty of parameter estimates, and to rank all the treatments in the network. Ranking treatments using both direct and indirect evidence can provide guidance to policy makers and clinicians for making decisions. The purpose of this paper is to introduce fundamental concepts of Bayesian network meta-analysis (BNMA) to researchers in psychology and social sciences. We discuss several essential concepts of BNMA, including the assumptions of homogeneity and consistency, the fixed and random effects models, prior specification, and model fit evaluation strategies, while pointing out some issues and areas where researchers should use caution in the application of BNMA. Additionally, using an automated R package, we provide a step-by-step demonstration on how to conduct and report the findings of BNMA with a real dataset of psychological interventions extracted from PubMed.

Association between walking energy utilisation and longitudinal cognitive performance in older adults.

BACKGROUND: Human motor function is optimised for energetic efficiency, however, age-related neurodegenerative changes affects neuromotor control of walking. Energy utilisation has been associated with motor performance, but its association with cognitive performance is unknown. METHODS: The study population included 979 Baltimore Longitudinal Study of Aging participants aged $\ge$50 years (52% female, mean age: 70$\pm$10.2 years) with a median follow-up time of 4.7 years. Energy utilisation for walking was operationalised as a ratio of the energy cost of slow walking to peak walking energy expenditure during standardised tasks ('cost-ratio'). Cognitive functioning was measured using the Trail Making Tests, California Verbal Learning Test, Wechsler Adult Intelligence Scale (WAIS), letter and category fluency and card rotation tests. Linear mixed models adjusted for demographics, education and co-morbidities assessed the association between baseline cost-ratio and cognitive functioning, cross-sectionally and longitudinally. To investigate the relationship among those with less efficient energy utilisation, subgroup analyses were performed. RESULTS: In fully adjusted models, a higher cost-ratio was cross-sectionally associated with poorer performance on all cognitive tests except WAIS (P < 0.05 for all). Among those with compromised energy utilisation, the baseline cost-ratio was also associated with a faster decline in memory (long-delay free recall: ß = -0.4, 95% confidence interval [CI] = [-0.8, -0.02]; immediate word recall: ß = -1.3, 95% CI = [-2.7, 0.1]). CONCLUSIONS: These findings suggest cross-sectional and longitudinal links between energy utilisation and cognitive performance, highlighting an intriguing link between brain function and the energy needed for ambulation. Future research should examine this association earlier in the life course to gauge the potential for interventive mechanisms.

Prior psychosocial profile and perceived impact of the COVID-19 pandemic: insights from the Baltimore Longitudinal Study of Aging.

Stress, social isolation, and changes in health behaviors during the COVID-19 pandemic period may have a lasting influence on health. Here, the correlation between current or prior demographic, social and health related characteristics, including psychosocial factors with perceived impact of the COVID-19 pandemic assessed by questionnaire during the early pandemic period is evaluated among 770 participants of the Baltimore Longitudinal Study of Aging. In multinomial logistic regression models participants with higher pre-pandemic personal mastery, a construct related to self-efficacy, were more likely to report "both positive and negative" impact of the pandemic than a solely "negative" impact (OR: 2.17, 95% CI: 1.29-3.65). Higher perceived stress and frequent contact with family prior to the pandemic were also associated with pandemic impact. These observations highlight the relevance of psychosocial factors in the COVID-19 pandemic experience and identify characteristics that may inform interventions in future public health crises.

Functional stability of CFTR depends on tight binding of ATP at its degenerate ATP-binding site.

Opening of the cystic fibrosis transmembrane conductance regulator (CFTR) channel is coupled to the motion of its two nucleotide-binding domains: they form a heterodimer sandwiching two functionally distinct ATP-binding sites (sites 1 and 2). While active ATP hydrolysis in site 2 triggers rapid channel closure, the functional role of stable ATP binding in the catalysis-incompetent (or degenerate) site 1, a feature conserved in many other ATP-binding cassette (ABC) transporter proteins, remains elusive. Here, we found that CFTR loses its prompt responsiveness to ATP after the channel is devoid of ATP for tens to hundreds of seconds. Mutants with weakened ATP binding in site 1 and the most prevalent disease-causing mutation, F508del, are more vulnerable to ATP depletion. In contrast, strengthening ligand binding in site 1 with N6 -(2-phenylethyl)-ATP, a high-affinity ATP analogue, or abolishing ATP hydrolysis in site 2 by the mutation D1370N, helps sustain a durable function of the otherwise unstable mutant channels. Thus, tight binding of ATP in the degenerate ATP-binding site is crucial to the functional stability of CFTR. Small molecules targeting site 1 may bear therapeutic potential to overcome the membrane instability of F508del-CFTR. KEY POINTS: During evolution, many ATP-binding cassette transporters - including the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel, whose dysfunction causes cystic fibrosis (CF) - lose the ability to hydrolyse ATP in one of the two ATP-binding sites. Here we show that tight ATP binding at this degenerate site in CFTR is central for maintaining the stable, robust function of normal CFTR. We also demonstrate that membrane instability of the most common CF-causing mutant, F508del-CFTR, can be rescued by strengthening ATP binding at CFTR's degenerate site. Our data thus explain an evolutionary puzzle and offer a potential therapeutic strategy for CF.

Frailty as a predictor of outcomes for patients undergoing carotid artery stenting.

OBJECTIVE: The concept of frailty has been proposed to capture the vulnerability resulting from aging and has been implemented for the prediction of perioperative outcomes. Carotid artery stenting (CAS) is considered an appropriate minimally invasive procedure for patients considered to high risk to undergo carotid endarterectomy. Recently, the predictive accuracy for perioperative outcomes using the five-item modified frailty index (5mFI) has been reported to be relatively poor for cardiovascular surgery compared with other surgeries. The effects of functional status and the 5mFI on the outcomes after CAS remain unknown. Thus, in the present study, we investigated the relationship between 5mFI, functional status, and perioperative outcomes. METHODS: All the patients who had undergone CAS in the Vascular Quality Initiative from November 15, 2016 to December 31, 2018 were included. Good functional status was defined as the ability to perform all predisease activities without restriction using a new variable added to the Vascular Quality Initiative from November 15, 2016 onward. The 5mFI was calculated using functional status and a history of diabetes, chronic obstructive pulmonary disease, congestive heart failure, and hypertension. The perioperative outcomes included in-hospital stroke or death within 30 days after CAS, a prolonged postoperative stay (≥2 days), and nonhome discharge. The associations between functional status, 5mFI, and perioperative outcomes were examined using univariate and multivariable logistic regression, adjusting for sex, age, race, degree of stenosis, symptomatic status, and the usage of preoperative medications. An analysis stratified by functional status was also performed. RESULTS: Of the 7836 patients, 188 (2.4%) had experienced perioperative stroke or death, 765 (9.8%) had required a nonhome discharge, and 2584 (33.0%) had required a prolonged postoperative stay. A higher (≥0.6 vs <0.6) 5mFI score was associated with greater odds of perioperative stroke or death (adjusted odds ratio [aOR], 2.75; 95% confidence interval [CI], 1.42-5.28; P = .003), non-home discharge (aOR, 2.70; 95% CI, 1.89-3.85; P < .001), and a prolonged postoperative length of stay (aOR, 1.96; 95% CI, 1.56-2.46; P < .001). For the predictive accuracy of the perioperative outcomes, the 5mFI model had an area under the curve for in-hospital stroke or death, nonhome discharge, and prolonged postoperative length of stay of 0.714, 0.767, and 0.668, respectively. The functional status model was not inferior to the 5mFI model for any of these outcomes. In the subgroup analysis, of the asymptomatic patients, a higher 5mFI score was associated with greater odds of perioperative stroke or death (aOR, 7.08; 95% CI, 2.02-24.48; P = .002), nonhome discharge (aOR, 5.87; 95% CI, 2.45-13.90; P < .001), and a prolonged postoperative stay (aOR, 2.60; 95% CI, 1.82-3.71; P < .001). CONCLUSIONS: Frailty, as measured using the 5mFI, and functional status were independent predictors of perioperative stroke or death, nonhome discharge, and an increased length of stay for patients undergoing CAS. These results were greatly pronounced in asymptomatic patients. The results from the present study, thus, caution against the use of CAS for asymptomatic frail patients.

The Vascular Quality Initiative 30-day stroke/death risk score calculator after transfemoral carotid artery stenting.

OBJECTIVE: Carotid artery stenting (CAS) was introduced as an alternative carotid revascularization procedure in patients deemed to be at high risk for carotid endarterectomy. Although techniques and selection criteria for patients have dramatically improved, CAS continues to have higher risk of stroke and death in comparison to carotid endarterectomy. Several risk factors are known to be associated with worse outcomes. Whereas knowledge of these independent factors is helpful, clinical decision-making is further refined when these are considered in aggregate. This study aimed to develop a score to predict the risk of stroke/death after transfemoral CAS (TFCAS). METHODS: We analyzed the Vascular Quality Initiative CAS data set from 2010 to 2018. Lesions due to trauma, dissection, or transcarotid artery stenting and cases performed without an embolic protection device were excluded. Univariable and multivariable logistic regression methods with bootstrapping (1000 repetitions) were used to identify predictors associated with 30-day stroke/death. Stepwise backward selection for variables was used to achieve model parsimony. A risk score was made by converting regression coefficients for each predictor to integers from which probability was calculated. Scores were grouped into simplified categories. RESULTS: We identified 10,753 patients undergoing TFCAS during the study period with a combined 30-day stroke/death rate of 4.1%. On multivariable adjustment, independent predictors of 30-day stroke/death included age (odds ratio [OR], 1.05; 95% confidence interval [CI], 1.03-1.06; P < .001), nonwhite race (OR, 1.42; 95% CI, 1.16-1.74; P = .001), diabetes (OR,1.34; 95% CI, 1.08-1.67; P = .01), coronary artery disease (OR, 1.40; 95% CI, 1.13-1.73; P = .001), congestive heart failure (OR, 1.41; 95% CI, 1.07-1.85; P = .02), symptomatic status (OR, 2.11; 95% CI, 1.64-2.72; P < .001), and contralateral occlusion (OR, 1.64; 95% CI, 1.22-2.19; P = .001). On the other hand, preoperative use of statins (OR, 0.074; 95% CI, 0.59-0.93; P = .02) and dual antiplatelet therapy (P2Y12 inhibitors and aspirin; OR, 0.46; 95% CI, 0.32-0.66; P < .001) were associated with a significant reduction in stroke/death after TFCAS. The model had a C statistic of 69.0%. The coefficients of these predictors were used to develop a risk score calculator that estimates the probability of 30-day stroke/death after TFCAS. CONCLUSIONS: In an analysis of 10,753 patients undergoing TFCAS between 2010 and 2018, significant predictors of perioperative stroke or death included old age, nonwhite race, symptomatic status, diabetes, coronary artery disease, congestive heart failure, and contralateral occlusion in addition to perioperative dual antiplatelet therapy and statin use. These variables were used to develop a risk score calculator that estimates the probability of 30-day stroke/death after TFCAS. External validation of this tool in different populations of patients and data sets is warranted to evaluate its predictive performance.

Correction: A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study.

[This corrects the article DOI: 10.1371/journal.pmed.1002718.].

Risk of emergent carotid endarterectomy varies by type of presenting symptoms.

BACKGROUND: The timing of carotid revascularization in symptomatic patients is a matter of ongoing debate. Current evidence indicates that carotid endarterectomy (CEA) within 2 weeks of symptoms is superior to delayed treatment. However, there is little evidence on the outcomes of emergent CEA (eCEA). The purpose of this study was to compare outcomes of emergency eCEA vs nonemergent CEA (non-eCEA), stratified by type of presenting symptoms. METHODS: We analyzed the Vascular Targeted-National Surgical Quality Improvement Program dataset from 2011 to 2016. Symptomatic patients were divided into two groups: eCEA and non-eCEA. Univariable and multivariable methods were used to compare patient characteristics and to evaluate stroke, death, myocardial infarction (MI), stroke/death, and stroke/death/MI within 30 days of surgery adjusting for all potential confounders. A further subgroup analysis was done to compare the outcomes of eCEA vs non-eCEA stratified by the type of presenting symptoms (amaurosis, transient ischemic attack [TIA], and stroke). RESULTS: A total of 9271 patients were identified, of which 10.7% were eCEA vs 89.3% non-eCEA. Comparing eCEA vs non-eCEA, the two groups were similar in age (70.8 vs 70.5), female gender (36.3% vs 36.9%), diabetes (26.2% vs 28.9%), and smoking status (31.9% vs 28.7%; all P > .05). Patients undergoing eCEA were less likely to be hypertensive (76.2% vs 80.2%; P = .025), but more likely to belong to non-white race (51.5% vs 20.5%; P < .001). The eCEA patients were less likely to be on preprocedural medication vs non-eCEA (antiplatelets, 76.8% vs 89.2%; statins, 74.2% vs 79.9%; beta-blockers, 44.6% vs 50.4%; all P < .05). The 30-day outcomes comparing eCEA vs non-eCEA were: stroke, 6.2% vs 3.1%; death, 2% vs 1%; and stroke/death, 6.9% vs 3.7% (all P < .05). After risk adjustment, perioperative stroke (odds ratio [OR], 2.04; 95% confidence interval [CI], 1.36-3.0), stroke/death (OR, 1.66; 95% CI, 1.13-2.45), and stroke/death/MI (OR, 1.58; 95% CI, 1.18-2.23) were higher after eCEA (all P < .01). When stratified by the type of presenting symptom, eCEA vs non-eCEA stroke outcomes were similar in patients who presented with stroke or amaurosis fugax. However, in the subset of patients presenting with TIA, eCEA had much worse outcomes compared with non-eCEA (stroke, 8.3% vs 2.5%; stroke/death, 8.3% vs 3.2%) and had significantly higher odds of stroke (OR, 3.12; 95% CI, 1.71-5.68) and stroke/death (OR, 2.24; 95% CI, 1.25-4.03) in the adjusted analysis (all P < .05). CONCLUSIONS: In patients presenting with stroke, eCEA does not seem to add significant risk compared with non-eCEA. However, patients presenting with TIA might be better served with non-emergent surgery as their risk of stroke is tripled when CEA is performed emergently.

A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study.

BACKGROUND: A person's rate of aging has important implications for his/her risk of death and disease; thus, quantifying aging using observable characteristics has important applications for clinical, basic, and observational research. Based on routine clinical chemistry biomarkers, we previously developed a novel aging measure, Phenotypic Age, representing the expected age within the population that corresponds to a person's estimated mortality risk. The aim of this study was to assess its applicability for differentiating risk for a variety of health outcomes within diverse subpopulations that include healthy and unhealthy groups, distinct age groups, and persons with various race/ethnic, socioeconomic, and health behavior characteristics. METHODS AND FINDINGS: Phenotypic Age was calculated based on a linear combination of chronological age and 9 multi-system clinical chemistry biomarkers in accordance with our previously established method. We also estimated Phenotypic Age Acceleration (PhenoAgeAccel), which represents Phenotypic Age after accounting for chronological age (i.e., whether a person appears older [positive value] or younger [negative value] than expected, physiologically). All analyses were conducted using NHANES IV (1999-2010, an independent sample from that originally used to develop the measure). Our analytic sample consisted of 11,432 adults aged 20-84 years and 185 oldest-old adults top-coded at age 85 years. We observed a total of 1,012 deaths, ascertained over 12.6 years of follow-up (based on National Death Index data through December 31, 2011). Proportional hazard models and receiver operating characteristic curves were used to evaluate all-cause and cause-specific mortality predictions. Overall, participants with more diseases had older Phenotypic Age. For instance, among young adults, those with 1 disease were 0.2 years older phenotypically than disease-free persons, and those with 2 or 3 diseases were about 0.6 years older phenotypically. After adjusting for chronological age and sex, Phenotypic Age was significantly associated with all-cause mortality and cause-specific mortality (with the exception of cerebrovascular disease mortality). Results for all-cause mortality were robust to stratifications by age, race/ethnicity, education, disease count, and health behaviors. Further, Phenotypic Age was associated with mortality among seemingly healthy participants-defined as those who reported being disease-free and who had normal BMI-as well as among oldest-old adults, even after adjustment for disease prevalence. The main limitation of this study was the lack of longitudinal data on Phenotypic Age and disease incidence. CONCLUSIONS: In a nationally representative US adult population, Phenotypic Age was associated with mortality even after adjusting for chronological age. Overall, this association was robust across different stratifications, particularly by age, disease count, health behaviors, and cause of death. We also observed a strong association between Phenotypic Age and the disease count an individual had. These findings suggest that this new aging measure may serve as a useful tool to facilitate identification of at-risk individuals and evaluation of the efficacy of interventions, and may also facilitate investigation into potential biological mechanisms of aging. Nevertheless, further evaluation in other cohorts is needed.

Contrasting characteristics of daily physical activity in older adults by cancer history.

BACKGROUND: Using objectively collected physical activity (PA) data from the Baltimore Longitudinal Study of Aging, the authors tested whether patterns of daily activity and sedentary time differed by cancer survivorship in older adults. METHODS: In total, 659 participants (mean age ± standard deviation, 71 ± 10 years; 51% women) who had self-reported information on cancer history were instructed to wear an accelerometer for 7 consecutive days. Accelerometer data were summarized into: 1) PA volume and 2) activity fragmentation (interrupted activity), expressed as both continuous and as dichotomized (low and high) variables. Participants were categorized into 4 groups by cross-classification of dichotomous PA volume and fragmentation. Multiple regression models were used to estimate differences in PA patterns by cancer history. RESULTS: Cancer survivors averaged 0.12 fewer log-transformed activity counts per day (standard error, 0.05; P = .02) than individuals who reported no history of cancer after adjusting for demographics, behavioral factors, and comorbidities. Although fragmentation did not differ by cancer survivorship in the continuous model (P = .13), cancer survivorship was associated with 77% greater odds (odds ratio, 1.77; 95% confidence interval, 1.11-2.82) of having high (vs low) fragmentation and 94% greater odds (odds ratio, 1.94; 95% confidence interval, 1.13-3.33) of having combined low PA/high fragmentation (vs high PA/low fragmentation) relative to those with no cancer history. CONCLUSIONS: The current findings suggest that cancer survivors engage in lower total daily PA and that they perform this activity in a more fragmented manner compared with adults without a history of cancer. These results may reflect the onset and progression of a low-activity phenotype that is more vulnerable to heightened levels of fatigue and functional decline with aging.

Differential impacts of cardiac and abdominal ectopic fat deposits on cardiometabolic risk stratification.

BACKGROUND: Previous studies have shown that excessive abdominal visceral adipose tissue (AVAT) and epicardial adipose tissue (EAT) are risk factors of cardiometabolic disease; we hypothesized there is differential contribution of abdominal and cardiac fat deposits to the cardiometabolic profiles. METHODS: Two hundred eight consecutive subjects with clinical suspicion of coronary artery disease (CAD) who underwent cardiac and abdominal CT for Agatston score and abdominal visceral fat measurement were retrospectively analyzed. Regional thickness of EAT (EATth), total volume of EAT, total volume of paracardial adipose tissue (PAT) and total volume of AVAT from L2 to L5 level were measured. The relationships between abdominal and cardiac adipose tissue measurements, the number of components of metabolic syndrome, and the severity of Agatston score on a four ranking scale (0, 1-10,11-100, 101-400, >400) were investigated. RESULTS: The amounts of AVAT, EAT, PAT and EATth-LAVG showed a significant linear trend with increasing number (0-5) of components in metabolic syndrome (AVAT, EAT and PAT P for trend <0.0001; EATth-LVAG P for trend <0.001). EATth at left atrioventricular groove (EATth-LAVG) showed significant linear trend with the severity of Agatston score on a four ranking scale (P for trend <0.0001). In multivariate binary regression analysis, total volume of AVAT was the sole adiposity predictor for metabolic syndrome independent to age, gender, and waist circumference (odds ratio of 1.20, 95 % CI 1.08-1.32, p < 0.001) while total volume of EAT, PAT, and EATth-LAVG were not. In contrary, EATth-LAVG was the sole adiposity predictor for Agatston score >400 (odds ratio of 1.11, 95% CI 1.034-1.184, p = 0.004). CONCLUSIONS: Excessive total volume of AVAT appears to be preferentially associated with metabolic syndrome; while EAT, esp. EATth-LAVG is preferentially associated with coronary artery disease. This differential effect of the two adiposities deserves a large-scale cohort study for further investigation.

Plasma metabolomic signatures of dual decline in memory and gait in older adults.

Older adults experiencing dual decline in memory and gait have greater dementia risk than those with memory or gait decline only, but mechanisms are unknown. Dual decline may indicate specific pathophysiological pathways to dementia which can be reflected by circulating metabolites. We compared longitudinal changes in plasma metabolite biomarkers of older adults with and without dual decline in the Baltimore Longitudinal Study of Aging (BLSA). Participants were grouped into 4 phenotypes based on annual rates of decline in verbal memory and gait speed: no decline in memory or gait, memory decline only, gait decline only, and dual decline. Repeated measures of plasma metabolomics were measured by biocrates p500 kit during the same time of memory and gait assessments. In BLSA, 18 metabolites differed across groups (q-value < 0.05). Metabolites differentially abundant were enriched for lysophosphatidylcholines (lysoPC C18:0,C16:0,C17:0,C18:1,C18:2), ceramides (d18:2/24:0,d16:1/24:0,d16:1/23:0), and amino acids (glycine) classes. Compared to no decline, the dual decline group showed greater declines in lysoPC C18:0, homoarginine synthesis, and the metabolite module containing mostly triglycerides, and showed a greater increase in indoleamine 2,3-dioxygenase (IDO) activity. Metabolites distinguishing dual decline and no decline groups were implicated in metabolic pathways of the aminoacyl-tRNA biosynthesis, valine, leucine and isoleucine biosynthesis, histidine metabolism, and sphingolipid metabolism. Older adults with dual decline exhibit the most extensive alterations in metabolic profiling of lysoPCs, ceramides, IDO activity, and homoarginine synthesis. Alterations in these metabolites may indicate mitochondrial dysfunction, compromised immunity, and elevated burden of cardiovascular and kidney pathology.

Epigenetic signature of human immune aging in the GESTALT study.

Age-associated DNA methylation in blood cells convey information on health status. However, the mechanisms that drive these changes in circulating cells and their relationships to gene regulation are unknown. We identified age-associated DNA methylation sites in six purified blood-borne immune cell types (naive B, naive CD4+ and CD8+ T cells, granulocytes, monocytes, and NK cells) collected from healthy individuals interspersed over a wide age range. Of the thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Genes close to age-associated hypomethylated sites were enriched for collagen biosynthesis and complement cascade pathways, while genes close to hypermethylated sites mapped to neuronal pathways. In silico analyses showed that in most cell types, the age-associated hypo- and hypermethylated sites were enriched for ARNT (HIF1ß) and REST transcription factor (TF) motifs, respectively, which are both master regulators of hypoxia response. To conclude, despite spatial heterogeneity, there is a commonality in the putative regulatory role with respect to TF motifs and histone modifications at and around these sites. These features suggest that DNA methylation changes in healthy aging may be adaptive responses to fluctuations of oxygen availability.

Understanding the Human Aging Proteome Using Epidemiological Models.

Human aging is a complex multifactorial process associated with a decline of physical and cognitive function and high susceptibility to chronic diseases, influenced by genetic, epigenetic, environmental, and demographic factors. This chapter will provide an overview on the use of epidemiological models with proteomics data as a method that can be used to identify factors that modulate the aging process in humans. This is demonstrated with proteomics data from human plasma and skeletal muscle, where the combination with epidemiological models identified a set of mitochondrial, spliceosome, and senescence proteins as well as the role of energetic pathways such as glycolysis, and electron transport pathways that regulate the aging process.

Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging.

To define metrics of phenotypic aging, it is essential to identify biological and environmental factors that influence the pace of aging. Previous attempts to develop aging metrics were hampered by cross-sectional designs and/or focused on younger populations. In the Baltimore Longitudinal Study of Aging (BLSA), we collected longitudinally across the adult age range a comprehensive list of phenotypes within four domains (body composition, energetics, homeostatic mechanisms and neurodegeneration/neuroplasticity) and functional outcomes. We integrated individual deviations from population trajectories into a global longitudinal phenotypic metric of aging and demonstrate that accelerated longitudinal phenotypic aging is associated with faster physical and cognitive decline, faster accumulation of multimorbidity and shorter survival. These associations are more robust compared with the use of phenotypic and epigenetic measurements at a single time point. Estimation of these metrics required repeated measures of multiple phenotypes over time but may uniquely facilitate the identification of mechanisms driving phenotypic aging and subsequent age-related functional decline.

DNA methylation GrimAge version 2.

We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10-167 versus P=2.6x10-144) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10-136), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10-54). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10-155). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10-267) and visceral fat (cor=0.41, P=4.7x10-41). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk.

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking.

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.