Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms.

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT.

Contextual modifiers of healthspan, lifespan, and epigenome in mice under chronic social stress.

Sustained life stress and low socioeconomic status are among the major causes of aging-related diseases and decreased life expectancy. Experimental rodent models can help to identify the underlying mechanisms, yet very few studies address the long-term consequences of social stress on aging. We conducted a randomized study involving more than 300 male mice of commonly used laboratory strains (C57BL/6J, CD1, and Sv129Ev) chosen for the spontaneous aggression gradient and stress-vulnerability. Mice were exposed to a lifelong chronic psychosocial stress protocol to model social gradients in aging and disease vulnerability. Low social rank, inferred based on a discretized aggression index, was found to negatively impact lifespan in our study population. However, social rank interacted with genetic background in that low-ranking C57BL/6J, high-ranking Sv129Ev, and middle-ranking CD1 mice had lower survival, respectively, implying a cost of maintaining a given social rank that varies across strains. Machine learning linear discriminant analysis identified baseline fat-free mass as the most important predictor of mouse genetic background and social rank in the present dataset. Finally, strain and social rank differences were significantly associated with epigenetic changes, most significantly in Sv129Ev mice and in high-ranking compared to lower ranking subjects. Overall, we identified genetic background and social rank as critical contextual modifiers of aging and lifespan in an ethologically relevant rodent model of social stress, thereby providing a preclinical experimental paradigm to study the impact of social determinants of health disparities and accelerated aging.

mLiftOver: harmonizing data across infinium DNA methylation platforms.

MOTIVATION: Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip. RESULTS: We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells. AVAILABILITY: mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenetic moderators of naltrexone efficacy in reducing heavy drinking in Alcohol Use Disorder: a randomized trial.

Polymorphisms in genes associated with opioid signaling and dopamine reuptake and inactivation may moderate naltrexone efficacy in Alcohol Use Disorder (AUD), but the effects of epigenetic modification of these genes on naltrexone response are largely unexplored. This study tested interactions between methylation in the µ-opioid receptor (OPRM1), dopamine transporter (SLC6A3), and catechol-O-methyltransferase (COMT) genes as predictors of naltrexone effects on heavy drinking in a 16-week randomized, placebo-controlled trial among 145 treatment-seeking AUD patients. OPRM1 methylation interacted with both SLC6A3 and COMT methylation to moderate naltrexone efficacy, such that naltrexone-treated individuals with lower methylation of the OPRM1 promoter and the SLC6A3 promoter (p = 0.006), COMT promoter (p = 0.005), or SLC6A3 3' untranslated region (p = 0.004), relative to placebo and to those with higher OPRM1 and SLC6A3 or COMT methylation, had significantly fewer heavy drinking days. Epigenetic modification of opioid- and dopamine-related genes may represent a novel pharmacoepigenetic predictor of naltrexone efficacy in AUD.

Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

Menopause accelerates biological aging.

Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the "epigenetic clock"), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

A meta-analysis of gene expression signatures of blood pressure and hypertension.

Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.

Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes.

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)

Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes.

BACKGROUND: Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown. METHODS AND RESULTS: We built a CVD network using 1512 SNPs associated with 21 CVD traits in genome-wide association studies (at P≤5×10(-8)) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-expression quantitative trait loci (eQTLs; SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples in which the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in genome-wide association studies may exert their function by altering expression of eQTL genes (eg, LDLR and PCSK7), which in turn may promote interindividual variation in phenotypes. CONCLUSIONS: Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD.

Integrative network analysis reveals molecular mechanisms of blood pressure regulation.

Genome-wide association studies (GWAS) have identified numerous loci associated with blood pressure (BP). The molecular mechanisms underlying BP regulation, however, remain unclear. We investigated BP-associated molecular mechanisms by integrating BP GWAS with whole blood mRNA expression profiles in 3,679 individuals, using network approaches. BP transcriptomic signatures at the single-gene and the coexpression network module levels were identified. Four coexpression modules were identified as potentially causal based on genetic inference because expression-related SNPs for their corresponding genes demonstrated enrichment for BP GWAS signals. Genes from the four modules were further projected onto predefined molecular interaction networks, revealing key drivers. Gene subnetworks entailing molecular interactions between key drivers and BP-related genes were uncovered. As proof-of-concept, we validated SH2B3, one of the top key drivers, using Sh2b3(-/-) mice. We found that a significant number of genes predicted to be regulated by SH2B3 in gene networks are perturbed in Sh2b3(-/-) mice, which demonstrate an exaggerated pressor response to angiotensin II infusion. Our findings may help to identify novel targets for the prevention or treatment of hypertension.

Epigenome-wide association study of fasting blood lipids in the Genetics of Lipid-lowering Drugs and Diet Network study.

BACKGROUND: Genetic research regarding blood lipids has largely focused on DNA sequence variation; few studies have explored epigenetic effects. Genome-wide surveys of DNA methylation may uncover epigenetic factors influencing lipid metabolism. METHODS AND RESULTS: To identify whether differential methylation of cytosine-(phosphate)-guanine dinucleotides (CpGs) correlated with lipid phenotypes, we isolated DNA from CD4+ T cells and quantified the proportion of sample methylation at >450 000 CpGs by using the Illumina Infinium HumanMethylation450 Beadchip in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network. We modeled the percentage of methylation at individual CpGs as a function of fasting very-low-density lipoprotein cholesterol and triglycerides (TGs) by using mixed linear regression adjusted for age, sex, study site, cell purity, and family structure. Four CpGs (cg00574958, cg17058475, cg01082498, and cg09737197) in intron 1 of carnitine palmitoyltransferase 1A (CPT1A) were strongly associated with very-low low-density lipoprotein cholesterol (P=1.8×10(-21) to 1.6×10(-8)) and TG (P=1.6×10(-26) to 1.5×10(-9)). Array findings were validated by bisulfite sequencing. We performed quantitative polymerase chain reaction experiments demonstrating that methylation of the top CpG (cg00574958) was correlated with CPT1A expression. The association of cg00574958 with TG and CPT1A expression were replicated in the Framingham Heart Study (P=4.1×10(-14) and 3.1×10(-13), respectively). DNA methylation at CPT1A cg00574958 explained 11.6% and 5.5% of the variation in TG in the discovery and replication cohorts, respectively. CONCLUSIONS: This genome-wide epigenomic study identified CPT1A methylation as strongly and robustly associated with fasting very-low low-density lipoprotein cholesterol and TG. Identifying novel epigenetic contributions to lipid traits may inform future efforts to identify new treatment targets and biomarkers of disease risk.

A systematic heritability analysis of the human whole blood transcriptome.

Genome-wide expression quantitative trait locus (eQTL) mapping may reveal common genetic variants regulating gene expression. In addition to mapping eQTLs, we systematically evaluated the heritability of the whole blood transcriptome in 5,626 participants from the Framingham Heart Study. Of all gene expression measurements, about 40 % exhibit evidence of being heritable [hgeneExp(2) > 0, (p < 0.05)], the average heritability was estimated to be 0.13, and 10 % display hgeneExp(2) > 0.2. To identify the role of eQTLs in promoting phenotype differences and disease susceptibility, we investigated the proportion of cis/trans eQTLs in different heritability categories and discovered that genes with higher heritability are more likely to have cis eQTLs that explain large proportions of variance in the expression of the corresponding genes. Single cis eQTLs explain 0.33-0.53 of variance in transcripts on average, whereas single trans eQTLs only explain 0.02-0.07. The top cis eQTLs tend to explain more variance in the corresponding gene when its hgeneExp(2) is greater. Taking body mass index (BMI) as a case study, we cross-linked cis/trans eQTLs with both GWAS SNPs and differentially expressed genes for BMI. We discovered that BMI GWAS SNPs in 16p11.2 (e.g., rs7359397) are associated with several BMI differentially expressed genes in a cis manner (e.g. SULT1A1, SPNS1, and TUFM). These BMI signature genes explain a much larger proportion of variance in BMI than do the GWAS SNPs. Our results shed light on the impact of eQTLs on the heritability of the human whole blood transcriptome and its relations to phenotype differences.

Age, body mass, usage of exogenous estrogen, and lifestyle factors in relation to circulating sex hormone-binding globulin concentrations in postmenopausal women.

BACKGROUND: Circulating concentrations of sex hormone-binding globulin (SHBG) have been associated with cardiovascular diseases, type 2 diabetes, metabolic syndrome, and hormone-dependent cancers; however, correlates of SHBG concentrations are not well understood. METHODS: We comprehensively investigated correlates of SHBG concentrations among 13 547 women who participated in the Women's Health Initiative and who had SHBG measurements. We estimated study- and ethnicity-specific associations of age, reproductive history, usage of exogenous estrogen, body mass index (BMI), and lifestyle factors such as physical activity, smoking, alcohol consumption, coffee intake, and dietary factors with SHBG concentrations. These estimates were pooled using random-effects models. We also examined potential nonlinear associations using spline analyses. RESULTS: There was no significant ethnic difference in the age-adjusted mean concentrations of SHBG. Age, exogenous estrogen use, physical activity, and regular coffee intake were positively associated with SHBG concentrations, whereas BMI was inversely associated with SHBG concentrations after adjustment for potential confounding factors. Similar patterns were observed among both ever users and never users of exogenous estrogen. The spline analysis indicated nonlinear relations of regular intake of coffee, age, and BMI with SHBG concentrations. Two or more cups/day of regular coffee consumption and age of 60 years or older were associated with higher SHBG concentrations; the inverse BMI-SHBG relation was especially strong among women whose BMI was below 30. CONCLUSIONS: In this large sample of postmenopausal women, age, exogenous estrogen use, physical activity, regular coffee intake, and BMI were significant correlates of SHBG concentrations, presenting potential targets for interventions.

Effects of varying doses of testosterone on atherogenic markers in healthy younger and older men.

Whether exogenous testosterone is proatherogenic remains controversial. We assessed the effects of graded doses of testosterone on serum markers of oxidative stress, chemotaxis, adhesion, and inflammation in healthy younger and older men. In a double-blind, randomized trial, 121 eugonadal men (n = 61, 18-35 years of age and n = 60, 60-75 years of age) were randomized to one of five groups to receive weekly injections of 25, 50, 125, 300, or 600 mg of testosterone enanthate for 20 wk, respectively, along with a long-acting gonadotropin-releasing hormone (GnRH) agonist. Energy and protein intakes were standardized and no resistance training was allowed. We measured plasma levels of the atherogenic biomarkers monocyte chemotactic protein-1 (MCP-1), soluble intracellular adhesion molecule-1 (sICAM-1), 8-isoprostane-PGF(2α) (8-iso-PGF(2α)), and high-sensitivity C-reactive protein (hs-CRP) before and after the intervention. Administration of increasing doses of testosterone led to reduction in total 8-iso-PGF(2α) in the younger (p-trend(Younger) = 0.01), but not older (p-trend(Older) = 0.79) men. No significant linear associations were observed between testosterone dose and MCP-1, sICAM-1, or hs-CRP (all p-trend >0.20). In apparently healthy men, over a wide dose range, testosterone did not adversely affect atherogenic biomarkers. Long-term studies with larger sample sizes are warranted to determine whether testosterone supplementation affects atherosclerosis progression and cardiovascular risk.

Validation of biomarkers of aging.

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Sex hormone-binding globulin and risk of clinical diabetes in American black, Hispanic, and Asian/Pacific Islander postmenopausal women.

BACKGROUND: Recent prospective studies have shown a strong inverse association between sex hormone-binding globulin (SHBG) concentrations and risk of clinical diabetes in white individuals. However, it remains unclear whether this relationship extends to other racial/ethnic populations. METHODS: We evaluated the association between baseline concentrations of SHBG and clinical diabetes risk in the Women's Health Initiative Observational Study. Over a median follow-up of 5.9 years, we identified 642 postmenopausal women who developed clinical diabetes (380 blacks, 157 Hispanics, 105 Asians) and 1286 matched controls (777 blacks, 307 Hispanics, 202 Asians). RESULTS: Higher concentrations of SHBG at baseline were associated with a significantly lower risk of clinical diabetes [relative risk (RR), 0.15; 95% CI, 0.09-0.26 for highest vs lowest quartile of SHBG, adjusted for BMI and known diabetes risk factors]. The associations remained consistent within ethnic groups [RR, 0.19 (95% CI, 0.10-0.38) for blacks; RR, 0.17 (95% CI, 0.05-0.57) for Hispanics; and 0.13 (95% CI, 0.03-0.48) for Asians]. Adjustment for potential confounders, such as total testosterone (RR, 0.11; 95% CI, 0.07-0.19) or HOMA-IR (RR, 0.26; 95% CI, 0.14-0.48) did not alter the RR substantially. In addition, SHBG concentrations were significantly associated with risk of clinical diabetes across categories of hormone therapy use (never users: RR(per SD) = 0.42, 95% CI, 0.34-0.51; past users: RR(per SD) = 0.53;, 95% CI, 0.37-0.77; current users: RR(per SD) = 0.57; 95% CI, 0.46-0.69; P-interaction = 0.10). CONCLUSIONS: In this prospective study of postmenopausal women, we observed a robust, inverse relationship between serum concentrations of SHBG and risk of clinical diabetes in American blacks, Hispanics, and Asians/Pacific Islanders. These associations appeared to be independent of sex hormone concentrations, adiposity, or insulin resistance.

Minimum standards for evaluating machine-learned models of high-dimensional data.

The maturation of machine learning and technologies that generate high dimensional data have led to the growth in the number of predictive models, such as the "epigenetic clock". While powerful, machine learning algorithms run a high risk of overfitting, particularly when training data is limited, as is often the case with high-dimensional data ("large p, small n"). Making independent validation a requirement of "algorithmic biomarker" development would bring greater clarity to the field by more efficiently identifying prediction or classification models to prioritize for further validation and characterization. Reproducibility has been a mainstay in science, but only recently received attention in defining its various aspects and how to apply these principles to machine learning models. The goal of this paper is merely to serve as a call-to-arms for greater rigor and attention paid to newly developed models for prediction or classification.

Association of Epigenetic Age Acceleration With Incident Mild Cognitive Impairment and Dementia Among Older Women.

BACKGROUND: Epigenetic age acceleration (AgeAccel), which indicates faster biological aging relative to chronological age, has been associated with lower cognitive function. However, the association of AgeAccel with mild cognitive impairment (MCI) or dementia is not well-understood. We examined associations of 4 AgeAccel measures with incident MCI and dementia. METHODS: This prospective analysis included 578 older women from the Women's Health Initiative Memory Study selected for a case-cohort study of coronary heart disease (CHD). Women were free of CHD and cognitive impairment at baseline. Associations of AgeAccel measures (intrinsic AgeAccel [IEAA], extrinsic AgeAccel [EEAA], AgeAccelPheno, and AgeAccelGrim) with risks for incident adjudicated diagnoses of MCI and dementia overall and stratified by incident CHD status were evaluated. RESULTS: IEAA was not significantly associated with MCI (HR, 1.23; 95% CI, 0.99-1.53), dementia (HR, 1.10; 95% CI, 0.88-1.38), or cognitive impairment (HR, 1.18; 95% CI, 0.99-1.40). In stratified analysis by incident CHD status, there was a 39% (HR, 1.39; 95% CI, 1.07-1.81) significantly higher risk of MCI for every 5-year increase in IEAA among women who developed CHD during follow-up. Other AgeAccel measures were not significantly associated with MCI or dementia. CONCLUSIONS: IEAA was not significantly associated with cognitive impairment overall but was associated with impairment among women who developed CHD. Larger studies designed to examine associations of AgeAccel with cognitive impairment are needed, including exploration of whether associations are stronger in the setting of underlying vascular pathologies.

DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse.

We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.