Biomarkers of aging for the identification and evaluation of longevity interventions.

With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

The association between hepatic steatosis and incident cardiovascular disease, cancer, and all-cause mortality in a US multicohort study.

BACKGROUND AND AIMS: NAFLD strongly associates with cardiovascular disease (CVD) risk factors; however, the association between NAFLD and incident CVD, CVD-related mortality, incident cancer, and all-cause mortality is unclear. APPROACH AND RESULTS: We included 10,040 participants from the Framingham Heart Study, the Coronary Artery Risk Development in Young Adults Study, and the Multi-ethnic Study of Atherosclerosis to assess the longitudinal association between liver fat (defined on CT) and incident CVD, CVD-related mortality, incident cancer, and all-cause mortality. We performed multivariable-adjusted Cox regression models including age, sex, diabetes, systolic blood pressure, alcohol use, smoking, HDL, triglycerides, and body mass index at baseline or time-varying covariates. The average age was 51.3±3.3 years and 50.6% were women. Hepatic steatosis was associated with all-cause mortality after 12.7 years of mean follow-up when adjusting for baseline CVD risk factors, including body mass index (HR: 1.21, 1.04-1.40); however, the results were attenuated when utilizing time-varying covariates. The association between hepatic steatosis and incident CVD was not statistically significant after we accounted for body mass index in models considering baseline covariates or time-varying covariates. We observed no association between hepatic steatosis and CVD-related mortality or incident cancer. CONCLUSIONS: In this large, multicohort study of participants with CT-defined hepatic steatosis, accounting for change in CVD risk factors over time attenuated associations between liver fat and overall mortality or incident CVD. Our work highlights the need to consider concurrent cardiometabolic disease when determining associations between NAFLD and CVD and mortality outcomes.

A mechanism by which gut microbiota elevates permeability and inflammation in obese/diabetic mice and human gut.

OBJECTIVE: Ample evidence exists for the role of abnormal gut microbiota composition and increased gut permeability ('leaky gut') in chronic inflammation that commonly co-occurs in the gut in both obesity and diabetes, yet the detailed mechanisms involved in this process have remained elusive. DESIGN: In this study, we substantiate the causal role of the gut microbiota by use of faecal conditioned media along with faecal microbiota transplantation. Using untargeted and comprehensive approaches, we discovered the mechanism by which the obese microbiota instigates gut permeability, inflammation and abnormalities in glucose metabolism. RESULTS: We demonstrated that the reduced capacity of the microbiota from both obese mice and humans to metabolise ethanolamine results in ethanolamine accumulation in the gut, accounting for induction of intestinal permeability. Elevated ethanolamine increased the expression of microRNA-miR-101a-3p by enhancing ARID3a binding on the miR promoter. Increased miR-101a-3p decreased the stability of zona occludens-1 (Zo1) mRNA, which in turn, weakened intestinal barriers and induced gut permeability, inflammation and abnormalities in glucose metabolism. Importantly, restoring ethanolamine-metabolising activity in gut microbiota using a novel probiotic therapy reduced elevated gut permeability, inflammation and abnormalities in glucose metabolism by correcting the ARID3a/miR-101a/Zo1 axis. CONCLUSION: Overall, we discovered that the reduced capacity of obese microbiota to metabolise ethanolamine instigates gut permeability, inflammation and glucose metabolic dysfunctions, and restoring ethanolamine-metabolising capacity by a novel probiotic therapy reverses these abnormalities. TRIAL REGISTRATION NUMBER: NCT02869659 and NCT03269032.

Associations of Early-Life Adversity With Later-Life Epigenetic Aging Profiles in the Multi-Ethnic Study of Atherosclerosis.

Epigenetic biomarkers of accelerated aging have been widely used to predict disease risk and may enhance our understanding of biological mechanisms between early-life adversity and disparities in aging. With respect to childhood adversity, most studies have used parental education or childhood disadvantage and/or have not examined the role played by socioemotional or physical abuse and trauma in epigenetic profiles at older ages. This study leveraged data from the Multi-Ethnic Study of Atherosclerosis (MESA) on experiences of threat and deprivation in participants' early lives (i.e., before the age of 18 years) to examine whether exposure to specific dimensions of early-life adversity is associated with epigenetic profiles at older ages that are indicative of accelerated biological aging. The sample included 842 MESA respondents with DNA methylation data collected between 2010 and 2012 who answered questions on early-life adversities in a 2018-2019 telephone follow-up. We found that experiences of deprivation, but not threat, were associated with later-life GrimAge epigenetic aging signatures that were developed to predict mortality risk. Results indicated that smoking behavior partially mediates this association, which suggests that lifestyle behaviors may act as downstream mechanisms between parental deprivation in early life and accelerated epigenetic aging in later life.

Gene expression associations with body mass index in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND/OBJECTIVES: Obesity, defined as excessive fat accumulation that represents a health risk, is increasing in adults and children, reaching global epidemic proportions. Body mass index (BMI) correlates with body fat and future health risk, yet differs in prediction by fat distribution, across populations and by age. Nonetheless, few genetic studies of BMI have been conducted in ancestrally diverse populations. Gene expression association with BMI was assessed in the Multi-Ethnic Study of Atherosclerosis (MESA) in four self-identified race and ethnicity (SIRE) groups to identify genes associated with obesity. SUBJECTS/METHODS: RNA-sequencing was performed on 1096 MESA participants (37.8% white, 24.3% Hispanic, 28.4% African American, and 9.5% Chinese American) and linear models were used to assess the association of expression from each gene for its effect on BMI, adjusting for age, sex, sequencing center, study site, five expression and four genetic principal components in each self-identified race group. Sample-size-weighted meta-analysis was performed to identify genes with BMI-associated expression across ancestry groups. RESULTS: Within individual SIRE groups, there were zero to three genes whose expression is significantly (p < 1.97 × 10-6) associated with BMI. Across all groups, 45 genes were identified by meta-analysis whose expression was significantly associated with BMI, explaining 29.7% of BMI variation. The 45 genes are expressed in a variety of tissues and cell types and are enriched for obesity-related processes including erythrocyte function, oxygen binding and transport, and JAK-STAT signaling. CONCLUSIONS: We have identified genes whose expression is significantly associated with obesity in a multi-ethnic cohort. We have identified novel genes associated with BMI as well as confirmed previously identified genes from earlier genetic analyses. These novel genes and their biological pathways represent new targets for understanding the biology of obesity as well as new therapeutic intervention to reduce obesity and improve global public health.

Role of DNA methylation on the association between physical activity and cardiovascular diseases: results from the longitudinal multi-ethnic study of atherosclerosis (MESA) cohort.

BACKGROUND: The complexity of physical activity (PA) and DNA methylation interaction in the development of cardiovascular disease (CVD) is rarely simultaneously investigated in one study. We examined the role of DNA methylation on the association between PA and CVD. RESULTS: The Multi-Ethnic Study of Atherosclerosis (MESA) cohort Exam 5 data with 1065 participants free of CVD were used for final analysis. The quartile categorical total PA variable was created by activity intensity (METs/week). During a median follow-up of 4.0 years, 69 participants developed CVD. Illumina HumanMethylation450 BeadChip was used to provide genome-wide DNA methylation profiles in purified human monocytes (CD14+). We identified 23 candidate DNA methylation loci to be associated with both PA and CVD. We used the structural equation modeling (SEM) approach to test the complex relationships among multiple variables and the roles of mediators. Three of the 23 identified loci (corresponding to genes VPS13D, PIK3CD and VPS45) remained as significant mediators in the final SEM model along with other covariates. Bridged by the three genes, the 2nd PA quartile (ß = - 0.959; 95%CI: - 1.554 to - 0.449) and the 3rd PA quartile (ß = - 0.944; 95%CI: - 1.628 to - 0.413) showed the greatest inverse associations with CVD development, while the 4th PA quartile had a relatively weaker inverse association (ß = - 0.355; 95%CI: - 0.713 to - 0.124). CONCLUSIONS: The current study is among the first to simultaneously examine the relationships among PA, DNA methylation, and CVD in a large cohort with long-term exposure. We identified three DNA methylation loci bridged the association between PA and CVD. The function of the identified genes warrants further investigation in the pathogenesis of CVD.

Predicting Non-Alcoholic Fatty Liver Disease for Adults Using Practical Clinical Measures: Evidence from the Multi-ethnic Study of Atherosclerosis.

BACKGROUND: Many adults have risk factors for non-alcoholic fatty liver disease (NAFLD). Screening all adults with risk factors for NAFLD using imaging is not feasible. OBJECTIVE: To develop a practical scoring tool for predicting NAFLD using participant demographics, medical history, anthropometrics, and lab values. DESIGN: Cross-sectional. PARTICIPANTS: Data came from 6194 white, African American, Hispanic, and Chinese American participants from the Multi-Ethnic Study of Atherosclerosis cohort, ages 45-85 years. MAIN MEASURES: NAFLD was identified by liver computed tomography (≤ 40 Hounsfield units indicating > 30% hepatic steatosis) and data on 14 predictors was assessed for predicting NAFLD. Random forest variable importance was used to identify the minimum subset of variables required to achieve the highest predictive power. This subset was used to derive (n = 4132) and validate (n = 2063) a logistic regression-based score (NAFLD-MESA Index). A second NAFLD-Clinical Index excluding laboratory predictors was also developed. KEY RESULTS: NAFLD prevalence was 6.2%. The model included eight predictors: age, sex, race/ethnicity, type 2 diabetes, smoking history, body mass index, gamma-glutamyltransferase (GGT), and triglycerides (TG). The NAFLD-Clinical Index model excluded GGT and TG. In the NAFLD-MESA model, the derivation set achieved an AUCNAFLD-MESA = 0.83 (95% CI, 0.81 to 0.86), and the validation set an AUCNAFLD-MESA = 0.80 (0.77 to 0.84). The NAFLD-Clinical Index model was AUCClinical = 0.78 [0.75 to 0.81] in the derivation set and AUCClinical = 0.76 [0.72 to 0.80] in the validation set (pBonferroni-adjusted < 0.01). CONCLUSIONS: The two models are simple but highly predictive tools that can aid clinicians to identify individuals at high NAFLD risk who could benefit from imaging.

Bivariate Genome-Wide Association Study of Depressive Symptoms With Type 2 Diabetes and Quantitative Glycemic Traits.

OBJECTIVE: Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. METHODS: We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of ß-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 × 10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. RESULTS: The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes). CONCLUSIONS: We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.