Effects of race and socioeconomic status on the epigenetic aging clock

种族和社会经济地位对表观遗传衰老时钟的影响

• 批准号: 10473355
• 负责人: michele k evans
• 金额: $ 47.81万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10473355
• 关键词: Acceleration; Address; Adult; Affect; African American; Age; Aging; Animal Model; Area; Behavioral; Biological; Blood; Cardiovascular Diseases; Chronology; Cognition; Cognitive; CpG dinucleotide; Cytosine; DNA; DNA Methylation; Data; Data Analyses; Demographic Factors; Development; Discrimination; Disease; Education; Elderly; Environmental Exposure; Epigenetic Process; European; Female; Future; GSTT1 gene; Gene Expression Regulation; Genes; Genetic; Genomics; Glutathione S-Transferase; Growth and Development function; Guidelines; Health; Human; Individual; Lead; Linear Regressions; Liver; Longevity; Longitudinal Studies; Malignant Neoplasms; Measurement; Measures; Metabolic syndrome; Methods; Methylation; Mitochondria; Modeling; Neighborhoods; Obesity; Outcome; Participant; Pathway interactions; Peptide Hydrolases; Peripheral Blood Mononuclear Cell; Phenotype; Play; Population; Positioning Attribute; Poverty; Process; Protein phosphatase; Psychosocial Stress; Publications; Quality Control; Race; Residual state; Risk; Risk Factors; Role; Sample Size; Sampling; Site; Socioeconomic Status; Specific qualifier value; Stearoyl-CoA Desaturase; TXNIP gene; Time; Tissues; Whole Blood; Woman; age related; base; bead chip; bisulfite; cardiometabolic risk; caucasian American; cell type; cohort; depressive symptoms; design; differential expression; epidemiology study; epigenome-wide association studies; epigenomics; fitness; genome wide methylation; genome-wide; health care availability; health disparity; healthy aging; human model; insight; lifestyle factors; male; men; methylation pattern; middle age; mortality; novel; peripheral blood; premature; sex; social health determinants

We designed a sub-cohort of individuals from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study that would enable us to address the effects of race and SES on DNAm age. Based on power and sample size calculations, and extensive discussions with our collaborative team, we have selected 508 participants from Wave 1 of HANDLS. We chose these individuals with peripheral blood DNA samples from both Wave 1 and Wave 3, which will allow us to perform longitudinal study of accelerated DNAm age. These individuals were comprised of above and below poverty, AA and white, male and female across the age-span of the HANDLS study (30-64 yrs.). We measured genome-wide DNA methylation (866,836 CpGs) using the Illumina MethylationEPIC BeadChip in blood DNA extracted from 487 middle-aged AA (N=244) and white (N=243), men (N=248) and women (N=239). The mean (sd) age was 48.4 (8.8) in AA and 49.0 (8.7) in whites (p=0.48). We identified 4,930 significantly associated aDMPs in AAs and 469 in whites. Of these, 75.6% and 53.1% were novel, largely driven by the increased number of measured CpGs in the EPIC array, in AA and whites, respectively. AAs had more age-associated DNAm changes than whites in genes implicated in age-related diseases and cellular pathways involved in growth and development. We assessed three epigenetic age acceleration measures (universal, intrinsic and extrinsic). AAs had a significantly slower extrinsic aging compared to whites. Furthermore, compared to AA women, both AA and white men had faster aging in the universal age acceleration measure (+2.04 and +1.24 years, respectively, p<0.05). AAs have more wide-spread methylation changes than whites. Race and sex interact to underlie biological age acceleration suggesting altered DNA methylation patterns may be important in age-associated health disparities. In future, we will also analyze genome-wide DNA methylation longitudinally using DNA samples from wave 3. Once the wave 3 methylation measurement is complete, we will follow similar quality control standards, and perform longitudinal data analysis using linear mixed-effects regression models (i) to assess the effect of sex, race, SES, and their interaction on the longitudinal changes of epigenetic age acceleration; and (ii) to identify age-associated differentially methylated CpG sites and differentially methylated regions that change longitudinally. We will also perform genome-wide methylation analysis on the longitudinal data to identify differentially methylated CpG positions and regions associated with age to identify genes that could play role in the aging processes and pathways. Data generated will help to understand factors affecting the longitudinal changes in epigenetic age acceleration as well as in genome-wide CpG methylation. We also have examined an important area of health disparities, metabolic syndrome. Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors for all-cause mortality, cardiovascular disease, and cancer. Identifying epigenetic alterations associated with MetS in African Americans (AAs) and Whites may provide insight into genes that influence its differential health outcomes. We examined DNA methylation (DNAm) and performed an epigenome-wide association study (EWAS) of MetS among AAs and Whites with and without MetS. We assessed age, race and poverty status associated DNAm among AAs (n = 225) and White (n = 233) adults using NCEP-ATP III guidelines. Genome-wide DNAm measurement was assessed using Illumina Infinium Methylation EPIC BeadChip. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) were identified using dmpFinder and bumphunter. EWAS was performed using CpGassoc. We found significant DMPs associated with age, poverty status and MetS in each race. GSTT1(Glutathione S-Transferase Theta 1) was one of the top-hypermethylated genes and MIPEP (Mitochondrial Intermediate Peptidase) was one of the most hypomethylated genes when comparing AAs with and without MetS. PPP1R13L (Protein Phosphatase 1 Regulatory Subunit 13 Like) was the top hypermethylated and SCD (stearoyl-CoA desaturase-1) was one of the most hypomethylated genes for Whites with and without MetS. EWAS results showed that DNAm differences might contribute to MetS risk among Whites and AAs since different genes were identified in AAs and Whites. We replicated previously identified MetS associated genes and found that Thioredoxin-interacting protein (TXN1P) was statistically significantly differentially expressed only in Whites. Our results may be useful in further studies of genes underlying differences in MetS among AAs and Whites. We have also begun to examine the relationships between epigenetic age acceleration and important behavioral conditions relevant to health disparities and aging; these include depressive symptoms, perceived discrimination and cognition.

我们设计了整个生命周期多样性（Handls）研究中健康衰老的个人的子果园，这将使我们能够解决种族和SES对DNAM时代的影响。基于功率和样本量计算以及与我们的协作团队的广泛讨论，我们从Handls的第一波中选择了508名参与者。我们选择了波浪1和3波第3的外周血DNA样品的这些个体，这将使我们能够对加速的DNAM年龄进行纵向研究。这些人由贫困，AA和白人，男性和女性组成，跨越了Handls研究的年龄跨度（30 - 64年）。 我们使用487个中年AA（n = 244）和白色（n = 243），男性（n = 248）和女性（n = 239）中提取的血液DNA中测量了全基因组DNA甲基化（866,836 CPG），并使用487个中年AA（n = 243）提取的血液DNA中的Illumina甲基化表皮珠。在AA中的平均年龄为48.4（8.8），白人为49.0（8.7）（p = 0.48）。我们在AAS中确定了4,930个显着相关的ADMP和469名白人。其中75.6％和53.1％是新颖的，在很大程度上是由于史诗阵列中测得的CpG数量增加，分别是AA和白人。与与年龄有关的疾病和与生长与发育有关的年龄相关疾病和细胞途径涉及的基因中，AA的年龄相关的DNAM变化比白人更大。我们评估了三项表观遗传年龄的加速度度量（通用，内在和外在）。与白人相比，AAS的外在衰老明显较慢。此外，与AA女性相比，AA和白人男性在通用年龄加速度措施中的老化速度更快（分别为+2.04和+1.24岁，P <0.05）。与白人相比，AA具有更广泛的甲基化变化。种族和性别与生物年龄加速的基础相互作用表明改变DNA甲基化模式可能在与年龄相关的健康差异中很重要。 将来，我们还将使用第3浪中的DNA样品纵向分析全基因组DNA甲基化。 （ii）确定与年龄相关的差异甲基化的CpG位点以及纵向改变的差异甲基化区域。我们还将对纵向数据进行全基因组甲基化分析，以鉴定与年龄相关的差异甲基化的CpG位置和区域，以鉴定可以在衰老过程和途径中起作用的基因。产生的数据将有助于理解影响表观遗传年龄加速度以及全基因组CpG甲基化纵向变化的因素。 我们还研究了健康差异的重要领域，代谢综合征。 代谢综合征（METS）是全因死亡率，心血管疾病和癌症的心脏代谢风险因素的一群。确定与非洲裔美国人（AAS）和白人相关的表观遗传变化可能会提供对影响其差异健康结果的基因的见解。我们检查了DNA甲基化（DNAM），并在具有和没有MetS的AAS和白人中对MetS进行了表观基因组的关联研究（EWA）。我们使用NCEP-ATP III指南评估了AAS（n = 225）和白人（n = 233）成年人的年龄，种族和贫困状况相关的DNAM。使用Illumina Infinium甲基化Epic Beadchip评估全基因组DNAM的测量。使用DMPFinder和Bumphunter鉴定出差异甲基化位置（DMP）和差异甲基化区域（DMR）。使用CPGASSOC进行EWAS。我们发现每个种族中与年龄，贫困状况和大都会大都会的重要DMP相关。 GSTT1（谷胱甘肽S-转移酶Theta 1）是顶级甲基化基因之一，MIPEP（线粒体中间肽酶）是与具有MetS的AAS进行比较时，是最低甲基化的基因之一。 PPP1R13L（蛋白质磷酸酶1调节亚基13）是顶部的高甲基化，SCD（stearoyl-COA去饱和酶-1）是具有和没有Mets的白色的最低氧基因之一。 EWAS的结果表明，DNAM的差异可能会导致白人和AAS之间的METS风险，因为在AAS和Whites中发现了不同的基因。我们复制了先前鉴定的MetS相关基因，发现硫氧还蛋白相互作用蛋白（TXN1P）在统计学上仅在白人中显着差异表达。我们的结果可能对AAS和白人之间MetS的基因的进一步研究可能有用。 我们还开始研究表观遗传年龄加速与与健康差异和衰老有关的重要行为条件之间的关系；这些包括抑郁症状，感知的歧视和认知。