Age-associated Gene Expression Research Articles

Unveiling the molecular landscape of cognitive aging: insights from polygenic risk scores, DNA methylation, and gene expression

BackgroundAging represents a significant risk factor for the occurrence of cerebral small vessel disease, associated with white matter (WM) lesions, and to age-related cognitive alterations, though the precise mechanisms remain largely unknown. This study aimed to investigate the impact of polygenic risk scores (PRS) for WM integrity, together with age-related DNA methylation, and gene expression alterations, on cognitive aging in a cross-sectional healthy aging cohort. The PRSs were calculated using genome-wide association study (GWAS) summary statistics for magnetic resonance imaging (MRI) markers of WM integrity, including WM hyperintensities, fractional anisotropy (FA), and mean diffusivity (MD). These scores were utilized to predict age-related cognitive changes and evaluate their correlation with structural brain changes, which distinguish individuals with higher and lower cognitive scores. To reduce the dimensionality of the data and identify age-related DNA methylation and transcriptomic alterations, Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) was used. Subsequently, a canonical correlation algorithm was used to integrate the three types of omics data (PRS, DNA methylation, and gene expression data) and identify an individual “omics” signature that distinguishes subjects with varying cognitive profiles.ResultsWe found a positive association between MD-PRS and long-term memory, as well as a correlation between MD-PRS and structural brain changes, effectively discriminating between individuals with lower and higher memory scores. Furthermore, we observed an enrichment of polygenic signals in genes related to both vascular and non-vascular factors. Age-related alterations in DNA methylation and gene expression indicated dysregulation of critical molecular features and signaling pathways involved in aging and lifespan regulation. The integration of multi-omics data underscored the involvement of synaptic dysfunction, axonal degeneration, microtubule organization, and glycosylation in the process of cognitive aging.ConclusionsThese findings provide valuable insights into the biological mechanisms underlying the association between WM coherence and cognitive aging. Additionally, they highlight how age-associated DNA methylation and gene expression changes contribute to cognitive aging.

Characterization of age-associated gene expression changes in mouse sweat glands.

Evaporation of sweat on the skin surface is the major mechanism for dissipating heat in humans. The secretory capacity of sweat glands (SWGs) declines during aging, leading to heat intolerance in the elderly, but the mechanisms responsible for this decline are poorly understood. We investigated the molecular changes accompanying SWG aging in mice, where sweat tests confirmed a significant reduction of active SWGs in old mice relative to young mice. We first identified SWG-enriched mRNAs by comparing the skin transcriptome of Eda mutant Tabby male mice, which lack SWGs, with that of wild-type control mice by RNA-sequencing analysis. This comparison revealed 171 mRNAs enriched in SWGs, including 47 mRNAs encoding 'core secretory' proteins such as transcription factors, ion channels, ion transporters, and trans-synaptic signaling proteins. Among these, 28 SWG-enriched mRNAs showed significantly altered abundance in the aged male footpad skin, and 11 of them, including Foxa1, Best2, Chrm3, and Foxc1 mRNAs, were found in the 'core secretory' category. Consistent with the changes in mRNA expression levels, immunohistology revealed that higher numbers of secretory cells from old SWGs express the transcription factor FOXC1, the protein product of Foxc1 mRNA. In sum, our study identified mRNAs enriched in SWGs, including those that encode core secretory proteins, and altered abundance of these mRNAs and proteins with aging in mouse SWGs.

A comprehensive AI-driven analysis of large-scale omic datasets reveals novel dual-purpose targets for the treatment of cancer and aging.

As aging and tumorigenesis are tightly interconnected biological processes, targeting their common underlying driving pathways may induce dual-purpose anti-aging and anti-cancer effects. Our transcriptomic analyses of 16,740 healthy samples demonstrated tissue-specific age-associated gene expression, with most tumor suppressor genes downregulated during aging. Furthermore, a large-scale pan-cancer analysis of 11 solid tumor types (11,303 cases and 4431 control samples) revealed that many cellular processes, such as protein localization, DNA replication, DNA repair, cell cycle, and RNA metabolism, were upregulated in cancer but downregulated in healthy aging tissues, whereas pathways regulating cellular senescence were upregulated in both aging and cancer. Common cancer targets were identified by the AI-driven target discovery platform-PandaOmics. Age-associated cancer targets were selected and further classified into four groups based on their reported roles in lifespan. Among the 51 identified age-associated cancer targets with anti-aging experimental evidence, 22 were proposed as dual-purpose targets for anti-aging and anti-cancer treatment with the same therapeutic direction. Among age-associated cancer targets without known lifespan-regulating activity, 23 genes were selected based on predicted dual-purpose properties. Knockdown of histone demethylase KDM1A, one of these unexplored candidates, significantly extended lifespan in Caenorhabditis elegans. Given KDM1A's anti-cancer activities reported in both preclinical and clinical studies, our findings propose KDM1A as a promising dual-purpose target. This is the first study utilizing an innovative AI-driven approach to identify dual-purpose target candidates for anti-aging and anti-cancer treatment, supporting the value of AI-assisted target identification for drug discovery.

Age-associated differences in the human lung extracellular matrix.

Extracellular matrix (ECM) remodeling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study, we aimed to identify and localize age-associated ECM differences in human lungs using comprehensive transcriptomic, proteomic, and immunohistochemical analyses. Our previously identified age-associated gene expression signature of the lung was re-analyzed limiting it to an aging signature based on 270 control patients (37-80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (false discovery rate, FDR < 0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from nine control patients (49-76 years) (FDR < 0.05). Extensive immunohistochemical analysis was used to localize and semi-quantify the age-associated ECM differences in lung tissues from 62 control patients (18-82 years). Comparative analysis of transcriptomic and proteomic data identified seven ECM proteins with higher expression with age at both gene and protein levels: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4, and LUM. With immunohistochemistry, we demonstrated higher protein levels with age for COL6A2 in whole tissue, parenchyma, airway wall, and blood vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in lung parenchyma. Our study revealed that higher age is associated with lung ECM remodeling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility to developing chronic lung diseases.NEW & NOTEWORTHY We identified seven age-associated extracellular matrix (ECM) proteins, i.e., COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4, and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for COL6A2 in whole tissue, parenchyma, airway wall, and vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in parenchyma. Our findings lay a new foundation for the investigation of ECM differences in age-associated chronic lung diseases.

Effects of RAGE Deletion on the Cardiac Transcriptome during Aging.

Cardiac aging is characterized by increased cardiomyocyte hypertrophy, myocardial stiffness, and fibrosis, which enhance cardiovascular risk. The receptor for advanced glycation end-products (RAGE) is involved in several age-related diseases. RAGE knockout (Rage−/−) mice show an acceleration of cardiac dimension changes and interstitial fibrosis with aging. This study identifies the age-associated cardiac gene expression signature induced by RAGE deletion. We analyzed the left ventricle transcriptome of 2.5-(Young), 12-(Middle age, MA), and 21-(Old) months-old female Rage−/− and C57BL/6N (WT) mice. By comparing Young, MA, and Old Rage−/− versus age-matched WT mice, we identified 122, 192, and 12 differently expressed genes, respectively. Functional inference analysis showed that RAGE deletion is associated with: (i) down-regulation of genes involved in antigen processing and presentation of exogenous antigen, adaptive immune response, and cellular responses to interferon beta and gamma in Young animals; (ii) up-regulation of genes related to fatty acid oxidation, cardiac structure remodeling and cellular response to hypoxia in MA mice; (iii) up-regulation of few genes belonging to complement activation and triglyceride biosynthetic process in Old animals. Our findings show that the age-dependent cardiac phenotype of Rage−/− mice is associated with alterations of genes related to adaptive immunity and cardiac stress pathways.

RETRACTED: Parallel bimodal single-cell sequencing of transcriptome and methylome provides molecular and translational insights on oocyte maturation and maternal aging

Advanced maternal aging has become a worldwide public health issue contributing to female fertility decline. To provide a complete landscape of transcriptome and epigenetic changes during oocyte aging and maturation, we applied a parallel bimodal genomics approach to parallel transcriptome and methylome profiles of mouse oocytes at single-cell and single-base resolution. Age-associated gene expression changes were associated with defective spindle assembly and mitochondrial dysfunction. Parallel sequencing data suggested aged-related defects in mRNA degradation and methylome remodelling during oocyte maturation. Differentially methylated region in aged mature oocyte was associated with trimethylation of Histone H3 at Lysine 4. More importantly, RNA expression-based prediction model for assessing maturation and oocytes age. Taken together, our work provides a better understanding of molecular mechanisms during mouse oocyte aging, points a new direction of oocyte quality assessment and paves the way for developing novel treatments to improve oocyte quality.

RNA-sequencing Reveals a Gene Expression Signature in Skeletal Muscle of a Mouse Model of Age-associated Postoperative Functional Decline.

This study aimed to characterize the effects of laparotomy on postoperative physical function and skeletal muscle gene expression in male C57BL/6N mice at 3, 20, and 24 months of age to investigate late-life vulnerability and resiliency to acute surgical stress. Pre and postoperative physical functioning was assessed by forelimb grip strength on postoperative day (POD) 1 and 3 and motor coordination on POD 2 and 4. Laparotomy-induced an age-associated postoperative decline in forelimb grip strength that was the greatest in the oldest mice. While motor coordination declined with increasing age at baseline, it was unaffected by laparotomy. Baseline physical function as stratified by motor coordination performance (low functioning vs high functioning) in 24-month-old mice did not differentially affect postlaparotomy reduction in grip strength. RNA sequencing of soleus muscles showed that laparotomy-induced age-associated differential gene expression and canonical pathway activation with the greatest effects in the youngest mice. Examples of such age-associated, metabolically important pathways that were only activated in the youngest mice after laparotomy included oxidative phosphorylation and NRF2-mediated oxidative stress response. Analysis of lipid mediators in serum and gastrocnemius muscle showed alterations in profiles during aging and confirmed an association between such changes and functional status in gastrocnemius muscle. These findings demonstrate a mouse model of laparotomy which recapitulated some features of postoperative skeletal muscle decline in older adults, and identified age-associated, laparotomy-induced molecular signatures in skeletal muscles. Future research can build upon this model to study molecular mechanisms of late-life vulnerability and resiliency to acute surgical stress.

Aging and Light Stress Result in Overlapping and Unique Gene Expression Changes in Photoreceptors.

Advanced age is one of the leading risk factors for vision loss and eye disease. Photoreceptors are the primary sensory neurons of the eye. The extended photoreceptor cell lifespan, in addition to its high metabolic needs due to phototransduction, makes it critical for these neurons to continually respond to the stresses associated with aging by mounting an appropriate gene expression response. Here, we sought to untangle the more general neuronal age-dependent transcriptional signature of photoreceptors with that induced by light stress. To do this, we aged flies or exposed them to various durations of blue light, followed by photoreceptor nuclei-specific transcriptome profiling. Using this approach, we identified genes that are both common and uniquely regulated by aging and light induced stress. Whereas both age and blue light induce expression of DNA repair genes and a neuronal-specific signature of death, both conditions result in downregulation of phototransduction. Interestingly, blue light uniquely induced genes that directly counteract the overactivation of the phototransduction signaling cascade. Lastly, unique gene expression changes in aging photoreceptors included the downregulation of genes involved in membrane potential homeostasis and mitochondrial function, as well as the upregulation of immune response genes. We propose that light stress contributes to the aging transcriptome of photoreceptors, but that there are also other environmental or intrinsic factors involved in age-associated photoreceptor gene expression signatures.

In silico identification of anti-aging pharmaceutics from community knowledge

In this era of Big Data, the volume of biological data is growing exponentially. Systematic profiling and analysis of these data will provide a new insight into biology and human health. Among diverse types of biological data, gene expression data closely mirror both the static phenotypes and the dynamic changes in biological systems. Drug-to-drug or drug-to-disease comparison of gene expression signature allows repurposing/repositioning of existing pharmaceutics to treat additional diseases that, in turn, provides a rapid and cost-effective approach for drug discovery. Thanks to technological advances, gene expression profiling by mRNA-seq became a routine tool to address all aspects of the problem in modern biological research. Here, we present how drug repositioning using published mRNA-seq data can provide unbiased and applicable pharmaco-chemical intervention strategies to human diseases and aging. In specifics, we profiled over a half-million gene expression profiling data generated from various contexts, and using this, we screened conditions that can suppress age-associated gene expression changes. As a result, our analysis identified various previously validated aging intervention strategies as positive hits. Furthermore, our analysis also predicted a novel group of chemicals that has not been studied from an aging context, and this indeed significantly extended the life span in model animals. Taken together, our data demonstrate that our community knowledge-guided in silico drug-discovery pipeline provides a useful and effective tool to identify the novel aging intervention strategy.

The Protective Effects of Apigenin on Cognitive Function and The Brain Transcriptome in Old Mice

CCG-1423 is a Rho A pathway inhibitor which has been reported to inhibit Rho/SRF-mediated transcriptional regulation. SRF and SRF cofactors, which include ternary complex factors (TCFs) and myocardin-related transcription factor (MRTF), regulate various cellular functions. The Rho/SRF signaling pathway also regulates the sirtuin 2 (SIRT2) gene that contains a classic serum response element (SRE) sequence. Current research on CCG-1423 focuses on gene expression levels of SRF in response to CCG-1423 and how SRF levels affect the cells; the studies are focused on cell morphology, migration, viability/reproduction, and overall function. The pathways of this inhibitor have yet to be fully elucidated, but several have been suggested with good evidence. Our goal is to study the effect of CCG-1423 on mitochondrial function and gene expression of cells. In this work C2C12 myoblast cells have been used as an in-vitro model to study cellular bioenergetics and variations in gene expressions induced by CCG-1423. The effect of CCG-1423 on mitochondrial function was determined by measuring the mitochondrial oxygen consumption rate and glycolysis rate after treating C2C12 cells with varying concentrations of CCG-1423 overnight. In C2C12 myoblast cells, CCG-1423 treatment significantly reduced mitochondrial oxygen consumption rate (OCR) in a dose-dependent manner. However, treatment of C2C12 cells with CCG-1423 overnight increased the extracellular acidification rate (ECAR) in a dose-dependent manner. By indicating that CCG-1423 represses mitochondrial respiration via the Rho-SRF signaling pathway, the results of this study may enable a better understanding of the bioenergetics of the cell in the aging body.

Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression.

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.

Abstract P646: The Aging Immune Transcriptome is Linked to Ischemic Stroke Outcome

Background: Advancing age is associated with changes to the immune system, which affect stroke outcome. We previously demonstrated an age-associated alteration in leukocyte gene expression in patients with ischemic stroke. The aim of this study is to validate these findings in an independent stroke cohort and assess the relationship to stroke outcome. Methods: Genes associated with age were identified in a cohort of 57 patients with acute ischemic stroke. Peripheral blood RNA was measured using whole genome microarrays and genes associated with advancing age identified (FDR-corrected p &lt; 0.05, partial correlation coefficient r &gt; |0.3|); age-associated gene expression differences in patients with poor 90-day outcome (mRS &lt; 2) were also compared. Genes were functionally characterized by pathway and enrichment analysis and verified against age-associated genes from two additional stroke cohorts containing a total of 173 patients. Results: There were 536 genes associated with age in the new stroke cohort, of which 286 decreased and 253 increased with age. Thirty-nine (39) of the age-associated genes were present in previous stroke cohorts analyzed, including a decrease in CCR6, CXCR5, BLNK and NT5E. A decrease in CXCR5 and CD79B was also identified in patients with poor outcome. Pathways and enriched terms relating to the humoral adaptive system immune system, including B-cell and lymphocyte activation, were among those represented in age-associated genes. Conclusions: Age-related changes in leukocyte gene expression were validated in an independent cohort of patients with ischemic stroke. Verified changes include alterations to the humoral immune system and a relationship to stroke outcome. Further investigation of the aging immune system in stroke is warranted.

Age and Tumor Differentiation-Associated Gene Expression Based Analysis of Non-Familial Prostate Cancers.

Prostate cancer incidence in young men has increased. Patients diagnosed at an earlier age are likely to have aggressive prostate cancer and treatment decisions are continuing to be weighted by patient age and life expectancy. Identification of age-associated gene-expression signatures hold great potential to augment current and future treatment modalities. To investigate age-specific tumor associated gene signatures and their potential biomarkers for disease aggressiveness, this study was designed and stratified into well and poorly differentiated tumor types of young (42–58 years) and old (66–73 years) prostate cancer patients. The differentially expressed genes related to tumor-normal differences between non-familial prostate cancer patients were identified and several genes uniquely associated with the age and tumor differentiation are markedly polarized. Overexpressed genes known to be associated with somatic genomic alterations was predominantly found in young men, such as TMPRESS2-ERG and c-MYC. On the other hand, old men have mostly down-regulated gene expressions indicating the loss of protective genes and reduced cell mediated immunity indicated by decreased HLA-A and HLA-B expression. The normalization for the benign signatures between the age groups indicates a significant age and tumor dependent heterogeneity exists among the patients with a great potential for age-specific and tumor differentiation-based therapeutic stratification of prostate cancer.

Age-associated changes in the transcriptomes of non-cultured adipose-derived stem cells from young and old mice assessed via single-cell transcriptome analysis.

Adipose-derived stem cells (ASCs) exhibit self-renewal and pluripotency. The differentiation potency of ASCs has been reported to deteriorate with aging; however, relevant studies used ASCs that were isolated and subcultured several times. It is still unclear whether subcultured ASCs accurately reflect the in vivo state. To address this question, we used freshly isolated stromal vascular fractions (SVFs) and performed comprehensive single-cell transcriptome analysis. In this study, we identified three cell populations as putative ASC candidates in SVFs and three novel ASC-related genes: Adamts7, Snai2, and Tgfbr1, that are reported to be negative regulators of cell differentiation. Moreover, we identified age-associated high gene expression levels of Adamts7, Egfr, and Igfbp4 in the earliest differentiation stage of ASCs. These results suggest that aging may make it impossible to maintain the stringency of the regulation of the expression of some genes related to ASC differentiation.

Age-related gene expression alterations by SARS-CoV-2 infection contribute to poor prognosis in elderly

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people worldwide and with notable heterogeneity in its clinical presentation. Probability of contracting this highly contagious infection is similar across age groups but disease severity and fatality among aged patients with or without comorbidities are reportedly higher. Previous studies suggest that age associated transcriptional changes in lung and immune system results in a proinflammatory state and increased susceptibility to infectious lung diseases. Similarly, SARS-CoV-2 infection could augment ageing-related gene expression alterations resulting in severe outcomes in elderly patients. To identify genes that can potentially increase covid-19 disease severity in ageing people, we compared age associated gene expression changes with disease-associated expression changes in lung/BALF and whole blood obtained from publicly available data. We observed (i) a significant overlap of gene expression profiles of patients’ BALF and blood with lung and blood of the healthy group, respectively; (ii) a more pronounced overlap in blood compared to lung; and (iii) a similar overlap between host genes interacting with SARS-CoV-2 and ageing blood transcriptome. Pathway enrichment analysis of overlapping gene sets suggest that infection alters expression of genes already dysregulated in the elderly, which together may lead to poor prognosis. eQTLs in these genes may also confer poor outcome in young patients worsening with age and comorbidities. Further, the pronounced overlap observed in blood may explain clinical symptoms including blood clots, strokes, heart attack, multi-organ failure etc. in severe cases. This model based on a limited patient dataset seems robust and holds promise for testing larger tissue specific datasets from patients with varied severity and across populations.Electronic supplementary materialThe online version of this article (10.1007/s12041-020-01233-7) contains supplementary material, which is available to authorized users.

Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders

Many psychiatric disorders can be conceptualized as disorders of brain maturation during childhood and adolescence. Discovering the neurobiological underpinnings of brain maturation may elucidate molecular pathways of vulnerability and resilience to such disorders. To investigate the underlying neurobiological mechanisms of age-associated cortical thinning during maturation and their implications for psychiatric disorders. This multicohort analysis used data from 3 community-based studies. The Saguenay Youth Study provided data from 1024 adolescents who were recruited at a single site in Quebec, Canada. The IMAGEN cohort provided data from 1823 participants who were recruited in 8 European cities. The Brazil High Risk Cohort Study for the Development of Childhood Psychiatric Disorders provided data from 815 participants who were recruited in 2 Brazilian cities. Cortical thickness was estimated from the results of magnetic resonance imaging (MRI) scans, and age-associated cortical thinning was estimated in 34 cortical regions. Gene expression from the Allen Human Brain Atlas was aligned with the same regions. Similarities in the interregional profiles of gene expression and the profiles of age-associated cortical thinning were measured. The involvement of dendrites, dendritic spines, and myelin was tested using 3 gene panels. Enrichment for genes associated with psychiatric disorders was tested among the genes associated with thinning and their coexpression networks. Data analysis was conducted between March and October 2019. MRI-derived estimates of age-associated cortical thinning and gene expression in 34 cortical regions. A total of 3596 individuals aged 9 to 21 years were included in this study. Of those, 1803 participants (50.1%) were female, and the mean (SD) age was 15.2 (2.6) years. Interregional profiles of age-associated cortical thinning were associated with interregional gradients in the expression of genes associated with dendrites, dendritic spines, and myelin; the variance in thinning explained by the gene panels across different points ranged from 0.45% to 10.55% for the dendrite panel, 0.00% to 9.98% for the spine panel, and 0.19% to 26.39% for the myelin panel. These genes and their coexpression networks were enriched for genes associated with several psychiatric disorders. In this study, genetic similarity between interregional variation in cortical thinning during maturation and multiple psychiatric disorders suggests overlapping molecular underpinnings. This finding adds to the understanding of the neurodevelopmental mechanisms of psychiatric disorders.

Age-dependent dysregulation of redox genes may contribute to fibrotic pulmonary disease susceptibility

Aging is associated with enhanced oxidative stress and increased susceptibility to numerous diseases. This relationship is particularly striking with respect to the incidence of fibrotic lung disease. To identify potential mechanisms underlying the association between aging and susceptibility to fibrotic lung disease we analyzed transcriptome data from 342 disease-free human lung samples as a function of donor age. Our analysis reveals that aging in lung is accompanied by modest yet progressive changes in genes modulating redox homeostasis, the TGF-beta 1 signaling axis, and the extracellular matrix (ECM), pointing to an aging lung functional network (ALFN). Further, the transcriptional changes we document are tissue-specific, with age-dependent gene expression patterns differing across organ systems. Our findings suggest that the age-associated increased incidence of fibrotic pulmonary disease occurs in the context of tissue-specific, age-dependent transcriptional changes. Understanding the relationship between age-associated gene expression and susceptibility to fibrotic pulmonary disease may allow for more accurate risk stratification and effective therapeutic interventions within this challenging clinical space.

DNA methylation in the human frontal cortex reveals a putative mechanism for age-by-disease interactions

A consistent gene set undergoes age-associated expression changes in the human cerebral cortex, and our Age-by-Disease Model posits that these changes contribute to psychiatric diseases by “pushing” the expression of disease-associated genes in disease-promoting directions. DNA methylation (DNAm) is an attractive candidate mechanism for age-associated gene expression changes. We used the Illumina HumanMethylation450 array to characterize genome-wide DNAm in the postmortem orbital frontal cortex from 20 younger (<42 years) and 19 older (>60 years) subjects. DNAm data were integrated with existing normal brain aging expression data and sets of psychiatric disease risk genes to test the hypothesis that age-associated DNAm changes contribute to age-associated gene expression changes and, by extension, susceptibility to psychiatric diseases. We found that age-associated differentially methylated regions (aDMRs) are common, robust, bidirectional, concentrated in CpG island shelves and sea, depleted in CpG islands, and enriched among genes undergoing age-associated expression changes (OR = 2.30, p = 1.69 × 10−27). We found the aDMRs are enriched among genetic association-based risk genes for schizophrenia, Alzheimer’s disease (AD), and major depressive disorder (MDD) (OR = 2.51, p = 0.00015; OR = 2.38, p = 0.036; and OR = 3.08, p = 0.018, respectively) as well as expression-based MDD-associated genes (OR = 1.48, p = 0.00012). Similar patterns of enrichment were found for aDMRs that correlate with local gene expression. These results were replicated in a large publically-available dataset, and confirmed by meta-analysis of the two datasets. Our findings suggest DNAm is a molecular mechanism for age-associated gene expression changes and support a role for DNAm in age-by-disease interactions through preferential targeting of disease-associated genes.

The poly-omics of ageing through individual-based metabolic modelling

BackgroundAgeing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype.ResultsWe propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor.ConclusionsWe show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells.

Transcriptional Profiling of Age-Associated Gene Expression Changes in Human Circulatory CD1c+ Myeloid Dendritic Cell Subset.

Immune dysfunction is a hallmark of aging and is thought to be responsible for the age-associated diseases. Dendritic cells (DCs) of the immune system function as initiators and regulators of the immune responses. Recent studies have highlighted the division of labor between various DC subsets. CD1c+ DC subset has emerged as a major inducer of CD4 T cell response. There is a scarcity of information regarding the age-associated changes in the functions of DC subsets in the elderly. Here, we investigated the changes in transcriptional profile of CD1c+ DC subset from healthy aged and young individuals using RNA sequencing. Our results suggest that majority of the genes in DCs are upregulated with age. Glucose transport, GPCR, and potassium channel genes are all upregulated in DCs from aged as compared to young indicating an enhanced activation state of DCs from aged individuals. The expression of histones, small nucleolar RNA H/ACA box (SNORA) and small nucleolar RNA C/D/box (SNORD), and long non-coding RNA (lncRNA) is also substantially upregulated in the DCs from aged. In contrast, the antigen-presenting and energy generating pathways are downregulated. In summary, DCs from aged subjects display an activated state coupled with reduced antigen presentation which may be responsible for age-associate immune dysfunction.