Clonal Hematopoiesis Analyses in Clinical, Epidemiologic, and Genetic Aging Studies to Unravel Underlying Mechanisms of Age-Related Dysfunction in Humans.

Aging is characterized by increased mortality, functional decline, and exponential increases in the incidence of diseases such as cancer, stroke, cardiovascular disease, neurological disease, respiratory disease, etc. Though the role of aging in these diseases is widely accepted and considered to be a common denominator, the underlying mechanisms are largely unknown. A significant age-related feature observed in many population cohorts is somatic mosaicism, the detectable accumulation of somatic mutations in multiple cell types and tissues, particularly those with high rates of cell turnover (e.g., skin, liver, and hematopoietic cells). Somatic mosaicism can lead to the development of cellular clones that expand with age in otherwise normal tissues. In the hematopoietic system, this phenomenon has generally been referred to as "clonal hematopoiesis of indeterminate potential" (CHIP) when it applies to a subset of clones in which mutations in driver genes of hematologic malignancies are found. Other mechanisms of clonal hematopoiesis, including large chromosomal alterations, can also give rise to clonal expansion in the absence of conventional CHIP driver gene mutations. Both types of clonal hematopoiesis (CH) have been observed in studies of animal models and humans in association with altered immune responses, increased mortality, and disease risk. Studies in murine models have found that some of these clonal events are involved in abnormal inflammatory and metabolic changes, altered DNA damage repair and epigenetic changes. Studies in long-lived individuals also show the accumulation of somatic mutations, yet at this advanced age, carriership of somatic mutations is no longer associated with an increased risk of mortality. While it remains to be elucidated what factors modify this genotype-phenotype association, i.e., compensatory germline genetics, cellular context of the mutations, protective effects to diseases at exceptional age, it points out that the exceptionally long-lived are key to understand the phenotypic consequences of CHIP mutations. Assessment of the clinical significance of somatic mutations occurring in blood cell types for age-related outcomes in human populations of varied life and health span, environmental exposures, and germline genetic risk factors will be valuable in the development of personalized strategies tailored to specific somatic mutations for healthy aging.

Optimizing Translational Research for Exceptional Health and Life Span: A Systematic Narrative of Studies to Identify Translatable Therapeutic Target(s) for Exceptional Health Span in Humans.

BACKGROUND: Exceptional longevity as manifested by the lower incidence and delayed onset of age-related disabilities/diseases that include cardiovascular disease, Alzheimer's disease, cancer is believed to be influenced by inherent protective molecular factors in exceptionally long-lived individuals. Unraveling these protective factors could lead to the discovery of therapeutic target(s) and interventions to promote healthy aging. METHODS: In this context, the National Institute on Aging has established a collection of translational longevity research projects (ie, the Long-Life Family Study, the Longevity Consortium, Longevity Genomics, and the Integrative Longevity Omics) which are generating large omics data sets spanning the human genome to phenome and have embarked on cross-species multiomic data analyses integrating human and nonhuman species that display wide variation in their life spans. RESULTS: It is expected that these studies will discover key signaling pathways that influence exceptional health span and identify therapeutic targets for translation to enhance health and life span. Other efforts related to translational longevity research include the "Comprehensive Evaluation of Aging-Related Clinical Outcomes and Geroproteins study," which focuses on potential effects in humans of polypeptides/proteins whose circulating levels change with age, and for which experimental evidence indicates reversal or acceleration of aging changes. The "Predictive Human Mechanistic Markers Network" is devoted to the development of predictive markers of aging, for target engagement when testing novel interventions for healthy aging. CONCLUSION: We describe here the significance, the unique study design, categories of data sets, analytical strategies, and a data portal to facilitate open science and sharing of resources from these longevity studies to identify and validate potential therapeutic targets for healthy aging.

Artificial Intelligence Based Approaches to Identify Molecular Determinants of Exceptional Health and Life Span-An Interdisciplinary Workshop at the National Institute on Aging.

Artificial intelligence (AI) has emerged as a powerful approach for integrated analysis of the rapidly growing volume of multi-omics data, including many research and clinical tasks such as prediction of disease risk and identification of potential therapeutic targets. However, the potential for AI to facilitate the identification of factors contributing to human exceptional health and life span and their translation into novel interventions for enhancing health and life span has not yet been realized. As researchers on aging acquire large scale data both in human cohorts and model organisms, emerging opportunities exist for the application of AI approaches to untangle the complex physiologic process(es) that modulate health and life span. It is expected that efficient and novel data mining tools that could unravel molecular mechanisms and causal pathways associated with exceptional health and life span could accelerate the discovery of novel therapeutics for healthy aging. Keeping this in mind, the National Institute on Aging (NIA) convened an interdisciplinary workshop titled "Contributions of Artificial Intelligence to Research on Determinants and Modulation of Health Span and Life Span" in August 2018. The workshop involved experts in the fields of aging, comparative biology, cardiology, cancer, and computational science/AI who brainstormed ideas on how AI can be leveraged for the analyses of large-scale data sets from human epidemiological studies and animal/model organisms to close the current knowledge gaps in processes that drive exceptional life and health span. This report summarizes the discussions and recommendations from the workshop on future application of AI approaches to advance our understanding of human health and life span.

The APOE ε4 allele is associated with a reduction in FEV1/FVC in women: A cross-sectional analysis of the Long Life Family Study.

INTRODUCTION: Murine studies have shown that apolipoprotein E modulates pulmonary function during development, aging, and allergen-induced airway disease. It is not known whether the polymorphic human APOE gene influences pulmonary function. OBJECTIVES: We assessed whether an association exists between the polymorphic human APOE ε2, ε3, and ε4 alleles and pulmonary function among participants in the Long Life Family Study. METHODS: Data from 4,468 Caucasian subjects who had genotyping performed for the APOE ε2, ε3, and ε4 alleles were analyzed, with and without stratification by sex. Statistical models were fitted considering the effects of the ε2 allele, defined as ε2/2 or ε2/3 genotypes, and the ε4 allele, defined as ε3/4 or ε4/4 genotypes, which were compared to the ε3/3 genotype. RESULTS: The mean FEV1/FVC ratio (the forced expiratory volume in one second divided by the forced vital capacity) was lower among women with the ε4 allele as compared to women with the ε3/3 genotype or the ε2 allele. Carriage of the APOE ε4 allele was associated with FEV1/FVC, which implied lower values. Further analysis showed that the association primarily reflected women without lung disease who were older than 70 years. The association was not mediated by lipid levels, smoking status, body mass index, or cardiovascular disease. CONCLUSIONS: This study for the first time identifies that the APOE gene is associated with modified lung physiology in women. This suggests that a link may exist between the APOE ε4 allele, female sex, and a reduction in the FEV1/FVC ratio in older individuals.

Report: NIA workshop on translating genetic variants associated with longevity into drug targets.

To date, candidate gene and genome-wide association studies (GWAS) have led to the discovery of longevity-associated variants (LAVs) in genes such as FOXO3A and APOE. Unfortunately, translating variants into drug targets is challenging for any trait, and longevity is no exception. Interdisciplinary and integrative multi-omics approaches are needed to understand how LAVs affect longevity-related phenotypes at the molecular physiologic level in order to leverage their discovery to identify new drug targets. The NIA convened a workshop in August 2017 on emerging and novel in silico (i.e., bioinformatics and computational) approaches to the translation of LAVs into drug targets. The goal of the workshop was to identify ways of enabling, enhancing, and facilitating interactions among researchers from different disciplines whose research considers either the identification of LAVs or the mechanistic or causal pathway(s) and protective factors they influence for discovering drug targets. Discussions among the workshop participants resulted in the identification of critical needs for enabling the translation of LAVs into drug targets in several areas. These included (1) the initiation and better use of cohorts with multi-omics profiling on the participants; (2) the generation of longitudinal information on multiple individuals; (3) the collection of data from non-human species (both long and short-lived) for comparative biology studies; (4) the refinement of computational tools for integrative analyses; (5) the development of novel computational and statistical inference techniques for assessing the potential of a drug target; (6) the identification of available drugs that could modulate a target in a way that could potentially provide protection against age-related diseases and/or enhance longevity; and (7) the development or enhancement of databases and repositories of relevant information, such as the Longevity Genomics website ( https://www.longevitygenomics.org ), to enhance and help motivate future interdisciplinary studies. Integrative approaches that examine the influence of LAVs on molecular physiologic phenotypes that might be amenable to pharmacological modulation are necessary for translating LAVs into drugs to enhance health and life span.

Overview of Gene Expression Analysis: Transcriptomics.

Currently, the study of the transcriptome is widely used to interpret the functional elements of the genome and molecular constituents of cells and tissues in an effort to unravel biological pathways associated with development and disease. The advent of technologies is now enabling the study of such comprehensive transcriptional characterization of mRNA, miRNA, lncRNA, and small RNA in a robust and successful manner. Transcriptomic strategies are gaining momentum across diverse areas of biological, plant sciences, medical, clinical, and pharmaceutical research for biomarker discovery, and disease diagnosis and prognosis.

Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies.

BACKGROUND: Identification of single nucleotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative trait loci (eQTLs), may improve understanding of the functional role of phenotype-associated SNPs in genome-wide association studies (GWAS). The small sample sizes of some previous eQTL studies have limited their statistical power. We conducted an eQTL investigation of microarray-based gene and exon expression levels in whole blood in a cohort of 5257 individuals, exceeding the single cohort size of previous studies by more than a factor of 2. RESULTS: We detected over 19,000 independent lead cis-eQTLs and over 6000 independent lead trans-eQTLs, targeting over 10,000 gene targets (eGenes), with a false discovery rate (FDR) < 5%. Of previously published significant GWAS SNPs, 48% are identified to be significant eQTLs in our study. Some trans-eQTLs point toward novel mechanistic explanations for the association of the SNP with the GWAS-related phenotype. We also identify 59 distinct blocks or clusters of trans-eQTLs, each targeting the expression of sets of six to 229 distinct trans-eGenes. Ten of these sets of target genes are significantly enriched for microRNA targets (FDR < 5%). Many of these clusters are associated in GWAS with multiple phenotypes. CONCLUSIONS: These findings provide insights into the molecular regulatory patterns involved in human physiology and pathophysiology. We illustrate the value of our eQTL database in the context of a recent GWAS meta-analysis of coronary artery disease and provide a list of targeted eGenes for 21 of 58 GWAS loci.

Protective role of the apolipoprotein E2 allele in age-related disease traits and survival: evidence from the Long Life Family Study.

The apolipoprotein E (apoE) is a classic example of a gene exhibiting pleiotropism. We examine potential pleiotropic associations of the apoE2 allele in three biodemographic cohorts of long-living individuals, offspring, and spouses from the Long Life Family Study, and intermediate mechanisms, which can link this allele with age-related phenotypes. We focused on age-related macular degeneration, bronchitis, asthma, pneumonia, stroke, creatinine, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, diseases of heart (HD), cancer, and survival. Our analysis detected favorable associations of the ε2 allele with lower LDL-C levels, lower risks of HD, and better survival. The ε2 allele was associated with LDL-C in each gender and biodemographic cohort, including long-living individuals, offspring, and spouses, resulting in highly significant association in the entire sample (ß = -7.1, p = 6.6 × 10-44). This allele was significantly associated with HD in long-living individuals and offspring (relative risk [RR] = 0.60, p = 3.1 × 10-6) but this association was not mediated by LDL-C. The protective effect on survival was specific for long-living women but it was not explained by LDL-C and HD in the adjusted model (RR = 0.70, p = 2.1 × 10-2). These results show that ε2 allele may favorably influence LDL-C, HD, and survival through three mechanisms. Two of them (HD- and survival-related) are pronounced in the long-living parents and their offspring; the survival-related mechanism is also sensitive to gender. The LDL-C-related mechanism appears to be independent of these factors. Insights into mechanisms linking ε2 allele with age-related phenotypes given biodemographic structure of the population studied may benefit translation of genetic discoveries to health care and personalized medicine.

Genetic landscape of APOE in human longevity revealed by high-throughput sequencing.

Apolipoprotein E (APOE) gene has been the most replicated longevity-associated gene in humans. Two common APOE alleles are either significantly depleted (ε4 allele) or enriched (ε2 allele) in long-lived individuals as compared to controls. We performed high-throughput sequencing analysis of exons and 2kb proximal promoter of APOE in 450 centenarians and 500 controls of Ashkenazi Jewish decent. We found two common regulatory variants, rs405509 (p=0.006) and rs769449 (p=0.036), that were significantly depleted in centenarians. Genotyping analysis of rs7412 and rs429358 showed significant enrichment of ε2 allele (p=0.003) and ε2/ε3 genotype (p=0.005), and significant depletion of ε3/ε4 genotype (p=0.005) in centenarians. Our findings support the hypothesis that variants in both coding and regulatory regions of APOE may contribute to longevity in humans.