Socioeconomic status across the early life course predicts gene expression signatures of disease and senescence

Background: Socioeconomic status (SES) is associated with many chronic diseases, indicators of senescence and mortality. However, the changing salience of SES in the prediction of adult health is not well understood. Using mRNA-seq abundance data from wave V of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examine the extent to which SES across the early life course is related to gene expression-based signatures for chronic diseases, senescence and inflammation in the late 30s. Methods: We use Bayesian methods to identify the most likely model of life course epidemiology (critical, sensitive and accumulation models) that characterises the changing importance of parental SES and SES during young (ages 27-30) and mid-adulthood (ages 36-39) in the prediction of the signatures. Results: For most signatures, SES is an important predictor in all periods, although parental SES or SES during young adulthood are often the most predictive. For three signatures (components of diabetes, inflammation and ageing), critical period models involving the exclusive salience of SES in young adulthood (for diabetes) or parental SES (for inflammation and ageing) are most probable. The observed associations are likely mediated by body mass index. Conclusion: Models of life course patterns of SES may inform efforts to identify age-specific mechanisms by which SES is associated with health at different points in life and they also suggest an enhanced approach to prediction models that recognise the changing salience of risk factors.</p

A Bayesian functional approach to test models of life course epidemiology over continuous time

BACKGROUND: Life course epidemiology examines associations between repeated measures of risk and health outcomes across different phases of life. Empirical research, however, is often based on discrete-time models that assume that sporadic measurement occasions fully capture underlying long-term continuous processes of risk.METHODS: We propose (i) the functional relevant life course model (fRLM), which treats repeated, discrete measures of risk as unobserved continuous processes, and (ii) a testing procedure to assign probabilities that the data correspond to conceptual models of life course epidemiology (critical period, sensitive period and accumulation models). The performance of the fRLM is evaluated with simulations, and the approach is illustrated with empirical applications relating body mass index (BMI) to mRNA-seq signatures of chronic kidney disease, inflammation and breast cancer.RESULTS: Simulations reveal that fRLM identifies the correct life course model with three to five repeated assessments of risk and 400 subjects. The empirical examples reveal that chronic kidney disease reflects a critical period process and inflammation and breast cancer likely reflect sensitive period mechanisms.CONCLUSIONS: The proposed fRLM treats repeated measures of risk as continuous processes and, under realistic data scenarios, the method provides accurate probabilities that the data correspond to commonly studied models of life course epidemiology. fRLM is implemented with publicly-available software.</p

A Bayesian functional approach to test models of life course epidemiology over continuous time

BACKGROUND: Life course epidemiology examines associations between repeated measures of risk and health outcomes across different phases of life. Empirical research, however, is often based on discrete-time models that assume that sporadic measurement occasions fully capture underlying long-term continuous processes of risk.METHODS: We propose (i) the functional relevant life course model (fRLM), which treats repeated, discrete measures of risk as unobserved continuous processes, and (ii) a testing procedure to assign probabilities that the data correspond to conceptual models of life course epidemiology (critical period, sensitive period and accumulation models). The performance of the fRLM is evaluated with simulations, and the approach is illustrated with empirical applications relating body mass index (BMI) to mRNA-seq signatures of chronic kidney disease, inflammation and breast cancer.RESULTS: Simulations reveal that fRLM identifies the correct life course model with three to five repeated assessments of risk and 400 subjects. The empirical examples reveal that chronic kidney disease reflects a critical period process and inflammation and breast cancer likely reflect sensitive period mechanisms.CONCLUSIONS: The proposed fRLM treats repeated measures of risk as continuous processes and, under realistic data scenarios, the method provides accurate probabilities that the data correspond to commonly studied models of life course epidemiology. fRLM is implemented with publicly-available software.</p

A Bayesian functional approach to test models of life course epidemiology over continuous time

Background Life course epidemiology examines associations between repeated measures of risk and health outcomes across different phases of life. Empirical research, however, is often based on discrete-time models that assume that sporadic measurement occasions fully capture underlying long-term continuous processes of risk. Methods We propose (i) the functional relevant life course model (fRLM), which treats repeated, discrete measures of risk as unobserved continuous processes, and (ii) a testing procedure to assign probabilities that the data correspond to conceptual models of life course epidemiology (critical period, sensitive period and accumulation models). The performance of the fRLM is evaluated with simulations, and the approach is illustrated with empirical applications relating body mass index (BMI) to mRNA-seq signatures of chronic kidney disease, inflammation and breast cancer. Results Simulations reveal that fRLM identifies the correct life course model with three to five repeated assessments of risk and 400 subjects. The empirical examples reveal that chronic kidney disease reflects a critical period process and inflammation and breast cancer likely reflect sensitive period mechanisms. Conclusions The proposed fRLM treats repeated measures of risk as continuous processes and, under realistic data scenarios, the method provides accurate probabilities that the data correspond to commonly studied models of life course epidemiology. fRLM is implemented with publicly-available software

Socioeconomic Inequalities and Molecular Risk for Aging in Young Adulthood

Diverse manifestations of biological aging often reflect disparities in socioeconomic status (SES). In this paper, we examine associations between indicators of SES and an mRNA-based aging signature during young adulthood, before clinical indications of aging are common. We use data from wave V (2016–2018) of the National Longitudinal Study of Adolescent to Adult Health, a nationally representative study of adults aged 33–43 years, with transcriptomic data from a subset of 2,491 participants. Biological aging is measured using 1) a composite transcriptomic aging signature previously identified by Peters et al.’s out-of-sample meta-analysis (Nat Commun. 2015;6:8570) and 2) 9 subsets that represent functional pathways of coexpressed genes. SES refers to income, education, occupation, subjective social status, and a composite measure combining these 4 dimensions. We examine hypothesized mechanisms through which SES could affect aging: body mass index, smoking, health insurance status, difficulty paying bills, and psychosocial stress. We find that SES—especially the composite measure and income—is associated with transcriptomic aging and immune, mitochondrial, ribosomal, lysosomal, and proteomal pathways. Counterfactual mediational models suggest that the mediators partially account for these associations. The results thus reveal that numerous biological pathways associated with aging are already linked to SES in young adulthood

Socioeconomic inequalities in molecular risk for chronic diseases observed in young adulthood

Many common chronic diseases of aging are negatively associated with socioeconomic status (SES). This study examines whether inequalities can already be observed in the molecular underpinnings of such diseases in the 30s, before many of them become prevalent. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a large, nationally representative sample of US subjects who were followed for over two decades beginning in adolescence. We now have transcriptomic data (mRNA-seq) from a random subset of 4,543 of these young adults. SES in the household-of-origin and in young adulthood were examined as covariates of a priori -defined mRNA-based disease signatures and of specific gene transcripts identified de novo . An SES composite from young adulthood predicted many disease signatures, as did income and subjective status. Analyses highlighted SES-based inequalities in immune, inflammatory, ribosomal, and metabolic pathways, several of which play central roles in senescence. Many genes are also involved in transcription, translation, and diverse signaling mechanisms. Average causal-mediated effect models suggest that body mass index plays a key role in accounting for these relationships. Overall, the results reveal inequalities in molecular risk factors for chronic diseases often decades before diagnoses and suggest future directions for social signal transduction models that trace how social circumstances regulate the human genome

Histone deacetylase activity is essential for the expression of HoxA9 and for endothelial commitment of progenitor cells

The regulation of acetylation is central for the epigenetic control of lineage-specific gene expression and determines cell fate decisions. We provide evidence that the inhibition of histone deacetylases (HDACs) blocks the endothelial differentiation of adult progenitor cells. To define the mechanisms by which HDAC inhibition prevents endothelial differentiation, we determined the expression of homeobox transcription factors and demonstrated that HoxA9 expression is down-regulated by HDAC inhibitors. The causal involvement of HoxA9 in the endothelial differentiation of adult progenitor cells is supported by the finding that HoxA9 overexpression partially rescued the endothelial differentiation blockade induced by HDAC inhibitors. Knockdown and overexpression studies revealed that HoxA9 acts as a master switch to regulate the expression of prototypical endothelial-committed genes such as endothelial nitric oxide synthase, VEGF-R2, and VE-cadherin, and mediates the shear stress–induced maturation of endothelial cells. Consistently, HoxA9-deficient mice exhibited lower numbers of endothelial progenitor cells and showed an impaired postnatal neovascularization capacity after the induction of ischemia. Thus, HoxA9 is regulated by HDACs and is critical for postnatal neovascularization

PI3K-C2β limits mTORC1 signaling and angiogenic growth

Phosphoinositide 3-kinases (PI3Ks) phosphorylate intracellular inositol lipids to regulate signaling and intracellular vesicular trafficking. Mammals have eight PI3K isoforms, of which class I PI3Kα and class II PI3K-C2α are essential for vascular development. The class II PI3K-C2β is also abundant in endothelial cells. Using in vivo and in vitro approaches, we found that PI3K-C2β was a critical regulator of blood vessel growth by restricting endothelial mTORC1 signaling. Mice expressing a kinase-inactive form of PI3K-C2β displayed enlarged blood vessels without corresponding changes in endothelial cell proliferation or migration. Instead, inactivation of PI3K-C2β resulted in an increase in the size of endothelial cells, particularly in the sprouting zone of angiogenesis. Mechanistically, we showed that the aberrantly large size of PI3K-C2β mutant endothelial cells was caused by mTORC1 activation, which sustained growth in these cells. Consistently, pharmacological inhibition of mTORC1 with rapamycin normalized vascular morphogenesis in PI3K-C2β mutant mice. Together, these results identify PI3K-C2β as a crucial determinant of endothelial signaling and illustrate the importance of mTORC1 regulation during angiogenic growth

Control of endothelial quiescence by FOXO-regulated metabolites.

Funder: - Cancer Center Support Grant 5P30CA045508Funder: - Medical Research Council (MRC_MC_UU_12022/6)Funder: - Max Planck Society - European Research Council (ERC) Consolidator Grant EMERGE (773047) - European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie action (814316) - Deutsche Forschungsgemeinschaft (SFB 834) - Cardio-Pulmonary Institute (EXC 2026, Project ID: 390649896) - DZHK (German Center for Cardiovascular Research) - Foundation Leducq Transatlantic Network - Stiftung Charité - European Molecular BiologyOrganization (EMBO) Young Investigator ProgrammeEndothelial cells (ECs) adapt their metabolism to enable the growth of new blood vessels, but little is known how ECs regulate metabolism to adopt a quiescent state. Here, we show that the metabolite S-2-hydroxyglutarate (S-2HG) plays a crucial role in the regulation of endothelial quiescence. We find that S-2HG is produced in ECs after activation of the transcription factor forkhead box O1 (FOXO1), where it limits cell cycle progression, metabolic activity and vascular expansion. FOXO1 stimulates S-2HG production by inhibiting the mitochondrial enzyme 2-oxoglutarate dehydrogenase. This inhibition relies on branched-chain amino acid catabolites such as 3-methyl-2-oxovalerate, which increase in ECs with activated FOXO1. Treatment of ECs with 3-methyl-2-oxovalerate elicits S-2HG production and suppresses proliferation, causing vascular rarefaction in mice. Our findings identify a metabolic programme that promotes the acquisition of a quiescent endothelial state and highlight the role of metabolites as signalling molecules in the endothelium

PTEN mediates Notch-dependent stalk cell arrest in angiogenesis.

Coordinated activity of VEGF and Notch signals guides the endothelial cell (EC) specification into tip and stalk cells during angiogenesis. Notch activation in stalk cells leads to proliferation arrest via an unknown mechanism. By using gain- and loss-of-function gene-targeting approaches, here we show that PTEN is crucial for blocking stalk cell proliferation downstream of Notch, and this is critical for mouse vessel development. Endothelial deletion of PTEN results in vascular hyperplasia due to a failure to mediate Notch-induced proliferation arrest. Conversely, overexpression of PTEN reduces vascular density and abrogates the increase in EC proliferation induced by Notch blockade. PTEN is a lipid/protein phosphatase that also has nuclear phosphatase-independent functions. We show that both the catalytic and non-catalytic APC/C-Fzr1/Cdh1-mediated activities of PTEN are required for stalk cells' proliferative arrest. These findings define a Notch-PTEN signalling axis as an orchestrator of vessel density and implicate the PTEN-APC/C-Fzr1/Cdh1 hub in angiogenesis