Myocardial TGF-β expression is upregulated in experimental models of myocardial infarction and cardiac hypertrophy, and in patients with dilated or hypertrophic cardiomyopathy. Through its effects on cardiomyocytes, mesenchymal and immune cells, TGF-β plays an important role in the pathogenesis of cardiac remodeling and fibrosis. TGF-β overexpression in the mouse heart is associated with fibrosis and hypertrophy. Endogenous TGF-β plays an important role in the pathogenesis of cardiac fibrotic and hypertrophic remodeling, and modulates matrix metabolism in the pressure-overloaded heart. In the infarcted heart, TGF-β deactivates inflammatory macrophages, while promoting myofibroblast transdifferentiation and matrix synthesis through Smad3-dependent pathways. Thus, TGF-β may serve as the "master switch" for the transition of the infarct from the inflammatory phase to formation of the scar. Because of its crucial role in cardiac remodeling, the TGF-β system may be a promising therapeutic target for patients with heart failure. However, efforts to translate these concepts into therapeutic strategies, in order to prevent cardiac hypertrophy and fibrosis, are hampered by the complex, pleiotropic and diverse effects of TGF-β signaling, by concerns regarding deleterious actions of TGF-β inhibition and by the possibility of limited benefit in patients receiving optimal treatment with ACE inhibitors and β-adrenergic blockers. Dissection of the pathways responsible for specific TGF-β-mediated actions and understanding of cell-specific actions of TGF-β are needed to design optimal therapeutic strategies.

BackgroundEpigenetic biomarkers of aging (the “epigenetic clock”) have the potential to address puzzling findings surrounding mortality rates and incidence of cardio-metabolic disease such as: (1) women consistently exhibiting lower mortality than men despite having higher levels of morbidity; (2) racial/ethnic groups having different mortality rates even after adjusting for socioeconomic differences; (3) the black/white mortality cross-over effect in late adulthood; and (4) Hispanics in the United States having a longer life expectancy than Caucasians despite having a higher burden of traditional cardio-metabolic risk factors.ResultsWe analyzed blood, saliva, and brain samples from seven different racial/ethnic groups. We assessed the intrinsic epigenetic age acceleration of blood (independent of blood cell counts) and the extrinsic epigenetic aging rates of blood (dependent on blood cell counts and tracks the age of the immune system). In blood, Hispanics and Tsimane Amerindians have lower intrinsic but higher extrinsic epigenetic aging rates than Caucasians. African-Americans have lower extrinsic epigenetic aging rates than Caucasians and Hispanics but no differences were found for the intrinsic measure. Men have higher epigenetic aging rates than women in blood, saliva, and brain tissue.ConclusionsEpigenetic aging rates are significantly associated with sex, race/ethnicity, and to a lesser extent with CHD risk factors, but not with incident CHD outcomes. These results may help elucidate lower than expected mortality rates observed in Hispanics, older African-Americans, and women.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1030-0) contains supplementary material, which is available to authorized users.

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM's constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs.

Telomere length (TL) is associated with several aging-related diseases. Here, we present a DNA methylation estimator of TL (DNAmTL) based on 140 CpGs. Leukocyte DNAmTL is applicable across the entire age spectrum and is more strongly associated with age than measured leukocyte TL (LTL) (r ~-0.75 for DNAmTL versus r ~ -0.35 for LTL). Leukocyte DNAmTL outperforms LTL in predicting: i) time-to-death (p=2.5E-20), ii) time-to-coronary heart disease (p=6.6E-5), iii) time-to-congestive heart failure (p=3.5E-6), and iv) association with smoking history (p=1.21E-17). These associations are further validated in large scale methylation data (n=10k samples) from the Framingham Heart Study, Women's Health Initiative, Jackson Heart Study, InChianti, Lothian Birth Cohorts, Twins UK, and Bogalusa Heart Study. Leukocyte DNAmTL is also associated with measures of physical fitness/functioning (p=0.029), age-at-menopause (p=0.039), dietary variables (omega 3, fish, vegetable intake), educational attainment (p=3.3E-8) and income (p=3.1E-5). Experiments in cultured somatic cells show that DNAmTL dynamics reflect in part cell replication rather than TL per se. DNAmTL is not only an epigenetic biomarker of replicative history of cells, but a useful marker of age-related pathologies that are associated with it.