RNAAgeCalc: A multi-tissue transcriptional age calculator

EDA2R-NIK signaling in cancer cachexia

PURPOSE OF REVIEW

Cachexia is a debilitating condition causing weight loss and skeletal muscle wasting that negatively influences treatment and survival of cancer patients. The objective of this review is to describe recent discoveries on the role of a novel signaling pathway involving ectodysplasin A2 receptor (EDA2R) and nuclear factor κB (NFκB)-inducing kinase (NIK) in muscle atrophy.

RECENT FINDINGS

Studies identified tumor-induced upregulation of EDA2R expression in muscle tissues in pre-clinical cachexia models and patients with various cancers. Activation of EDA2R by its ligand promoted atrophy in cultured myotubes and muscle tissue, which depended on NIK activity. The non-canonical NFκB pathway via NIK also stimulated muscle atrophy. Mice lacking EDA2R or NIK were protected from muscle loss due to tumors. Tumor-induced cytokine oncostatin M (OSM) upregulated EDA2R expression in muscles whereas OSM receptor-deficient mice were resistant to muscle wasting.

SUMMARY

Recent discoveries revealed a mechanism involving EDA2R-NIK signaling and OSM that drives cancer-associated muscle loss, opening up new directions for designing anti-cachexia treatments. The therapeutic potential of targeting this mechanism to prevent muscle loss should be further investigated. Future research should also explore broader implications of the EDA2R-NIK pathway in other muscle wasting diseases and overall muscle health.

Aging promotes accumulation of senescent and multiciliated cells in human endometrial epithelium

STUDY QUESTION

What changes occur in the endometrium during aging, and do they impact fertility?

SUMMARY ANSWER

Both the transcriptome and cellular composition of endometrial samples from women of advanced maternal age (AMA) are significantly different from that of samples from young women, suggesting specific changes in epithelial cells that may affect endometrial receptivity.

WHAT IS KNOWN ALREADY

Aging is associated with the accumulation of senescent cells in aging tissues. Reproductive aging is mostly attributed to the decline in ovarian reserve and oocyte quality, whereas the endometrium is a unique complex tissue that is monthly renewed under hormonal regulation. Several clinical studies have reported lower implantation and pregnancy rates in oocyte recipients of AMA during IVF. Molecular studies have indicated the presence of specific mutations within the epithelial cells of AMA endometrium, along with altered gene expression of bulk endometrial tissue.

STUDY DESIGN SIZE DURATION

Endometrial transcriptome profiling was performed for 44 women undergoing HRT during the assessment of endometrial receptivity before IVF. Patients younger than 28 years were considered as the young maternal age (YMA) group (age 23-27 years) and women older than 45 years were considered as the AMA group (age 47-50 years). Endometrial biopsies were obtained on Day 5 of progesterone treatment and RNA was extracted. All endometrial samples were evaluated as being receptive based on the expression of 68 common endometrial receptivity markers. Endometrial samples from another 24 women classified into four age groups (YMA, intermediate age group 1 (IMA1, age 29-35), intermediate age group 2 (IMA2, age 36-44), and AMA) were obtained in the mid-secretory stage of a natural cycle (NC) and used for validation studies across the reproductive lifespan.

PARTICIPANTS/MATERIALS SETTING METHODS

A total of 24 HRT samples (12 YMA and 12 AMA) were subject to RNA sequencing (RNA-seq) and differential gene expression analysis, 20 samples (10 YMA and 10 AMA) were used for qPCR validation, and 24 NC samples (6 YMA, 6 IMA1, 6 IMA2 and 6AMA) were used for RNA-seq validation of AMA genes across the woman's reproductive lifespan. Immunohistochemistry (IHC) was used to confirm some expression changes at the protein level. Computational deconvolution using six endometrial cell type-specific transcriptomic profiles was conducted to compare the cellular composition between the groups.

MAIN RESULTS AND THE ROLE OF CHANCE

Comparisons between YMA and AMA samples identified a lower proportion of receptive endometria in the AMA group (P = 0.007). Gene expression profiling identified 491 differentially expressed age-sensitive genes (P adj < 0.05) that revealed the effects of age on endometrial epithelial growth and receptivity, likely contributing to decreased reproductive performance. Our results indicate that changes in the expression of the cellular senescence marker p16INK4a and genes associated with metabolism, inflammation, and hormone response are involved in endometrial aging. Importantly, we demonstrate that the proportion of multi-ciliated cells, as discovered based on RNA-seq data deconvolution and tissue IHC results, is affected by endometrial aging, and propose a putative onset of age-related changes. Furthermore, we propose that aging has an impact on the transcriptomic profile of endometrial tissue in the context of endometrial receptivity.

LARGE SCALE DATA

The raw sequencing data reported in this article are deposited at the Gene Expression Omnibus under accession code GSE236128.

LIMITATIONS REASONS FOR CAUTION

This retrospective study identified changes in the endometrium of patients undergoing hormonal replacement and validated these changes using samples obtained during a NC. However, future studies must clarify the importance of these findings on the clinical outcomes of assisted reproduction.

WIDER IMPLICATIONS OF THE FINDINGS

The findings reported in this study have important implications for devising future strategies aimed at improving fertility management in women of advanced reproductive age.

STUDY FUNDING/COMPETING INTERESTS

This research was funded by the Estonian Research Council (grant no. PRG1076), Horizon 2020 innovation grant (ERIN, grant no. EU952516), Enterprise Estonia (grant no. EU48695), MSCA-RISE-2020 project TRENDO (grant no. 101008193), EU 874867 project HUTER, the Horizon Europe NESTOR grant (grant no. 101120075) of the European Commission, the EVA specialty program (grant no. KP111513) of the Maastricht University Medical Center (MUMC+), MICIU/AEI/10.13039/501100011033 and FEDER, EU projects Endo-Map (grant no. PID2021-12728OB-100), ROSY (grant no. CNS2022-135999), and the National Science Fund of Bulgaria (grant no. KII-06 H31/2). The authors declare no competing interests.

Accelerated Aging and Microsatellite Instability in Recessive Dystrophic Epidermolysis Bullosa-Associated Cutaneous Squamous Cell Carcinoma

Recessive dystrophic epidermolysis bullosa (RDEB) is a severely debilitating disorder caused by pathogenic variants in COL7A1 and is characterized by extreme skin fragility, chronic inflammation, and fibrosis. A majority of patients with RDEB develop squamous cell carcinoma, a highly aggressive skin cancer with limited treatment options currently available. In this study, we utilized an approach leveraging whole-genome sequencing and RNA sequencing across 3 different tissues in a single patient with RDEB to gain insight into possible mechanisms of RDEB-associated squamous cell carcinoma progression and to identify potential therapeutic options. As a result, we identified PLK-1 as a possible candidate for targeted therapy and discovered microsatellite instability and accelerated aging as factors potentially contributing to the aggressive nature and early onset of RDEB squamous cell carcinoma. By integrating multitissue genomic and transcriptomic analyses in a single patient, we demonstrate the promise of bridging the gap between genomic research and clinical applications for developing tailored therapies for patients with rare genetic disorders such as RDEB.

Ectodysplasin A2 receptor signaling in skeletal muscle pathophysiology

Skeletal muscle is essential in generating mechanical force and regulating energy metabolism and body temperature. Pathologies associated with muscle tissue often lead to impaired physical activity and imbalanced metabolism. Recently, ectodysplasin A2 receptor (EDA2R) signaling has been shown to promote muscle loss and glucose intolerance. Upregulated EDA2R expression in muscle tissue was associated with aging, denervation, cancer cachexia, and muscular dystrophies. Here, we describe the roles of EDA2R signaling in muscle pathophysiology, including muscle atrophy, insulin resistance, and aging-related sarcopenia. We also discuss the EDA2R pathway, which involves EDA-A2 as the ligand and nuclear factor (NF)κB-inducing kinase (NIK) as a downstream mediator, and the therapeutic potential of targeting these proteins in the treatment of muscle wasting and metabolic dysfunction.

Geroprotective interventions converge on gene expression programs of reduced inflammation and restored fatty acid metabolism

Understanding the mechanisms of geroprotective interventions is central to aging research. We compare four prominent interventions: senolysis, caloric restriction, in vivo partial reprogramming, and heterochronic parabiosis. Using published mice transcriptomic data, we juxtapose these interventions against normal aging. We find a gene expression program common to all four interventions, in which inflammation is reduced and several metabolic processes, especially fatty acid metabolism, are increased. Normal aging exhibits the inverse of this signature across multiple organs and tissues. A similar inverse signature arises in three chronic inflammation disease models in a non-aging context, suggesting that the shift in metabolism occurs downstream of inflammation. Chronic inflammation is also shown to accelerate transcriptomic age. We conclude that a core mechanism of geroprotective interventions acts through the reduction of inflammation with downstream effects that restore fatty acid metabolism. This supports the notion of directly targeting genes associated with these pathways to mitigate age-related deterioration.

ATAC-clock: An aging clock based on chromatin accessibility

The establishment of aging clocks highlighted the strong link between changes in DNA methylation and aging. Yet, it is not known if other epigenetic features could be used to predict age accurately. Furthermore, previous studies have observed a lack of effect of age-related changes in DNA methylation on gene expression, putting the interpretability of DNA methylation-based aging clocks into question. In this study, we explore the use of chromatin accessibility to construct aging clocks. We collected blood from 159 human donors and generated chromatin accessibility, transcriptomic, and cell composition data. We investigated how chromatin accessibility changes during aging and constructed a novel aging clock with a median absolute error of 5.27 years. The changes in chromatin accessibility used by the clock were strongly related to transcriptomic alterations, aiding clock interpretation. We additionally show that our chromatin accessibility clock performs significantly better than a transcriptomic clock trained on matched samples. In conclusion, we demonstrate that the clock relies on cell-intrinsic chromatin accessibility alterations rather than changes in cell composition. Further, we present a new approach to construct epigenetic aging clocks based on chromatin accessibility, which bear a direct link to age-related transcriptional alterations, but which allow for more accurate age predictions than transcriptomic clocks.

Molecular hallmarks of ageing in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, severely debilitating and rapidly progressing disorder affecting motor neurons in the brain, brainstem, and spinal cord. Unfortunately, there are few effective treatments, thus there remains a critical need to find novel interventions that can mitigate against its effects. Whilst the aetiology of ALS remains unclear, ageing is the major risk factor. Ageing is a slowly progressive process marked by functional decline of an organism over its lifespan. However, it remains unclear how ageing promotes the risk of ALS. At the molecular and cellular level there are specific hallmarks characteristic of normal ageing. These hallmarks are highly inter-related and overlap significantly with each other. Moreover, whilst ageing is a normal process, there are striking similarities at the molecular level between these factors and neurodegeneration in ALS. Nine ageing hallmarks were originally proposed: genomic instability, loss of telomeres, senescence, epigenetic modifications, dysregulated nutrient sensing, loss of proteostasis, mitochondrial dysfunction, stem cell exhaustion, and altered inter-cellular communication. However, these were recently (2023) expanded to include dysregulation of autophagy, inflammation and dysbiosis. Hence, given the latest updates to these hallmarks, and their close association to disease processes in ALS, a new examination of their relationship to pathophysiology is warranted. In this review, we describe possible mechanisms by which normal ageing impacts on neurodegenerative mechanisms implicated in ALS, and new therapeutic interventions that may arise from this.

Transcriptome-wide analysis reveals GYG2 as a mitochondria-related aging biomarker in human subcutaneous adipose tissue

Subcutaneous adipose tissue (SAT), a vital energy reservoir and endocrine organ for maintaining systemic glucose, lipid, and energy homeostasis, undergoes significant changes with age. However, among the existing aging-related markers, only few genes are associated with SAT aging. In this study, weighted gene co-expression network analysis was used on a transcriptome of SAT obtained from the Genotype-Tissue Expression portal to identify biologically relevant, SAT-specific, and age-related marker genes. We found modules that exhibited significant changes with age and identified GYG2 as a novel key aging associated gene. The link between GYG2 and mitochondrial function as well as brown/beige adipocytes was supported using additional bioinformatics and experimental analyses. Additionally, we identified PPARG as the transcription factor of GYG2 expression. The newly discovered GYG2 marker can be used to not only determine the age of SAT but also uncover new mechanisms underlying SAT aging.

Quantifying Healthy Aging in Older Veterans Using Computational Audio Analysis

BACKGROUND

Researchers are increasingly interested in better methods for assessing the pace of aging in older adults, including vocal analysis. The present study sought to determine whether paralinguistic vocal attributes improve estimates of the age and risk of mortality in older adults.

METHODS

To measure vocal age, we curated interviews provided by male U.S. World War II Veterans in the Library of Congress collection. We used diarization to identify speakers and measure vocal features and matched recording data to mortality information. Veterans (N = 2 447) were randomly split into testing (n = 1 467) and validation (n = 980) subsets to generate estimations of vocal age and years of life remaining. Results were replicated to examine out-of-sample utility using Korean War Veterans (N = 352).

RESULTS

World War II Veterans' average age was 86.08 at the time of recording and 91.28 at the time of death. Overall, 7.4% were prisoners of war, 43.3% were Army Veterans, and 29.3% were drafted. Vocal age estimates (mean absolute error = 3.255) were within 5 years of chronological age, 78.5% of the time. With chronological age held constant, older vocal age estimation was correlated with shorter life expectancy (aHR = 1.10; 95% confidence interval: 1.06-1.15; p < .001), even when adjusting for age at vocal assessment.

CONCLUSIONS

Computational analyses reduced estimation error by 71.94% (approximately 8 years) and produced vocal age estimates that were correlated with both age and predicted time until death when age was held constant. Paralinguistic analyses augment other assessments for individuals when oral patient histories are recorded.

Glutathione amino acid precursors protect skin from UVB-induced damage and improve skin tone

BACKGROUND

UV radiation exposure causes skin irritation, erythema, darkening and barrier disruption by inducing oxidative stress and inflammation. Glutathione, a master antioxidant, plays an important role in the antioxidant defence network of the skin.

OBJECTIVE

This study aimed to assess the in vitro protective effects of the glutathione amino acid precursors blend (GAP) on transcriptomic and phenotypic endpoints against UVB-induced challenges.

METHODS

Normal human epidermal melanocytes (NHEMs) were exposed to GAP, ascorbic acid (AA) and its derivatives. Viability was assessed using the CCK8 method. Melakutis®, a pigmented living skin equivalent (pLSE) model, underwent repeated 50 mJ/cm2 UVB irradiation with or without GAP treatment. Images of the model were captured with consistent camera parameters, and the model's light intensity was measured using a spectrophotometer. Melanin content was determined by measuring absorbance at 405 nm. Confirmation of melanin deposition and distribution was achieved through Fontana-Masson staining. Transcriptomic analysis was conducted using RNA sequencing (RNA-Seq), and a machine learning approach was employed for transcriptomic aging clock analysis.

RESULTS

In NHEMs, all tested compounds exhibited over 85% viability compared to the vehicle control, indicating no heightened risk of cytotoxicity. Notably, GAP demonstrated greater efficacy in inhibiting melanin production than AA derivatives at equivalent concentrations. In pLSE models, GAP notably enhanced model lightness, and reduced melanin content and deposition following the UVB challenge, whereas AA showed minimal impact. GAP effectively counteracted UVB-induced alterations in gene expression linked to pigmentation, inflammation and aging. Moreover, recurrent UVB exposure substantially elevated the biological age of pLSE models, a phenomenon mitigated by GAP treatment.

CONCLUSIONS

In NHEMs, GAP exhibited enhanced effectiveness in inhibiting melanin production at identical tested doses in comparison to AA derivatives. Noteworthy protective effects of GAP against UVB irradiation were observed in the pLSE models, as evidenced by skin pigmentation measurements and transcriptomic changes.

Selecting mRNA markers in blood for age estimation of the donor of a biological stain

RNA has gained a substantial amount of attention within the forensic field over the last decade. There is evidence that RNAs are differentially expressed with biological age. Since RNA can be co-extracted with DNA from the same piece of evidence, RNA-based analysis appears as a promising molecular alternative for predicting the biological age and hence inferring the chronological age of a person. Using RNA-Seq data we searched for markers in blood potentially associated with age. We used our own RNA-Seq data from dried blood stains as well as publicly available RNA-Seq data from whole blood, and compared two different approaches to select candidate markers. The first approach focused on individual gene analysis with DESeq2 to select the genes most correlated with age, while the second approach employed lasso regression to select a set of genes for optimal prediction of age. We present two lists with 270 candidate markers, one for each approach.

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease landscapes. However, lack of independent validation in different populations and tissue samples have greatly limited their use in clinical and research settings. We overcame these issues by performing hierarchical clustering on the 5000 most variably expressed autosomal genes from motor cortex expression data of people with sporadic ALS from the KCL BrainBank (N = 112). Three molecular phenotypes linked to ALS pathogenesis were identified: synaptic and neuropeptide signalling, oxidative stress and apoptosis, and neuroinflammation. Cluster validation was achieved by applying linear discriminant analysis models to cases from TargetALS US motor cortex (N = 93), as well as Italian (N = 15) and Dutch (N = 397) blood expression datasets, for which there was a high assignment probability (80-90%) for each molecular subtype. The ALS and motor cortex specificity of the expression signatures were tested by mapping KCL BrainBank controls (N = 59), and occipital cortex (N = 45) and cerebellum (N = 123) samples from TargetALS to each cluster, before constructing case-control and motor cortex-region logistic regression classifiers. We found that the signatures were not only able to distinguish people with ALS from controls (AUC 0.88 ± 0.10), but also reflect the motor cortex-based disease process, as there was perfect discrimination between motor cortex and the other brain regions. Cell types known to be involved in the biological processes of each molecular phenotype were found in higher proportions, reinforcing their biological interpretation. Phenotype analysis revealed distinct cluster-related outcomes in both motor cortex datasets, relating to disease onset and progression-related measures. Our results support the hypothesis that different mechanisms underpin ALS pathogenesis in subgroups of patients and demonstrate potential for the development of personalised treatment approaches. Our method is available for the scientific and clinical community at https://alsgeclustering.er.kcl.ac.uk .

Smoking affects epigenetic ageing of lung bronchoalveolar lavage cells in Multiple Sclerosis

BACKGROUND

A compelling body of evidence implicates cigarette smoking and lung inflammation in Multiple Sclerosis (MS) susceptibility and progression. Previous studies have reported epigenetic age (DNAm age) acceleration in blood immune cells and in glial cells of people with MS (pwMS) compared to healthy controls (HC).

OBJECTIVES

We aimed to examine biological ageing in lung immune cells in the context of MS and smoking.

METHODS

We analyzed age acceleration residuals in lung bronchoalveolar lavage (BAL) cells, constituted of mainly alveolar macrophages, from 17 pwMS and 22 HC in relation to smoking using eight DNA methylation-based clocks, namely AltumAge, Horvath, GrimAge, PhenoAge, Zhang, SkinBlood, Hannum, Monocyte clock as well as two RNA-based clocks, which capture different aspects of biological ageing.

RESULTS

After adjustment for covariates, five epigenetic clocks showed significant differences between the groups. Four of them, Horvath (Padj = 0.028), GrimAge (Padj = 4.28 × 10-7), SkinBlood (Padj = 0.001) and Zhang (Padj = 0.02), uncovered the sole effect of smoking on ageing estimates, irrespective of the clinical group. The Horvath, SkinBlood and Zhang clocks showed a negative impact of smoking while GrimAge detected smoking-associated age acceleration in BAL cells. On the contrary, the AltumAge clock revealed differences between pwMS and HC and indicated that, in the absence of smoking, BAL cells of pwMS were epigenetically 5.4 years older compared to HC (Padj = 0.028). Smoking further affected epigenetic ageing in BAL cells of pwMS specifically as non-smoking pwMS exhibited a 10.2-year AltumAge acceleration compared to pwMS smokers (Padj = 0.0049). Of note, blood-derived monocytes did not show any MS-specific or smoking-related AltumAge differences. The difference between BAL cells of pwMS smokers and non-smokers was attributable to the differential methylation of 114 AltumAge-CpGs (Padj < 0.05) affecting genes involved in innate immune processes such as cytokine production, defense response and cell motility. These changes functionally translated into transcriptional differences in BAL cells between pwMS smokers and non-smokers.

CONCLUSIONS

BAL cells of pwMS display inflammation-related and smoking-dependent changes associated to epigenetic ageing captured by the AltumAge clock. Future studies examining potential confounders, such as the distribution of distinct BAL myeloid cell types in pwMS compared to control individuals in relation to smoking may clarify the varying performance and DNAm age estimations among epigenetic clocks.

Transcriptomics age acceleration in prolonged treated HIV infection

Biological aging in people with HIV (PWH) with prolonged successful antiretroviral therapy (ART) is convoluted and poorly defined. Here, we aimed to investigate the transcriptomics age estimator (TAE) in a cohort of 178 PWH on prolonged successful ART with immune reconstitution and viral suppression from the Copenhagen Comorbidity (COCOMO) cohort. We also used 143 clinical, demographical, and lifestyle factors to identify the confounders potentially responsible or associated with age acceleration. Among the PWH, 43% had an accelerated aging process (AAP), and 21% had decelerated aging process (DAP). DAP is linked with older age, European ancestry, and higher use of tenofovir disoproxil/alafenamide fumarate. A directionally class-based gene set enrichment analysis identified the upregulation of inflammatory pathways (e.g., cytokine and Retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathways) and immune response like T-cell receptor signaling, antigen processing, and presentation in AAP and the downregulation of metabolic processes like oxidative phosphorylation, pyruvate metabolism.

Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications

BACKGROUND

DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals.

OBJECTIVE

This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application.

METHODS

The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics.

CONCLUSION

The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.

Deconvolution of whole blood transcriptomics identifies changes in immune cell composition in patients with systemic lupus erythematosus (SLE) treated with mycophenolate mofetil

BACKGROUND

Systemic lupus erythematosus (SLE) is a clinically and biologically heterogeneous autoimmune disease. We explored whether the deconvolution of whole blood transcriptomic data could identify differences in predicted immune cell frequency between active SLE patients, and whether these differences are associated with clinical features and/or medication use.

METHODS

Patients with active SLE (BILAG-2004 Index) enrolled in the BILAG-Biologics Registry (BILAG-BR), prior to change in therapy, were studied as part of the MASTERPLANS Stratified Medicine consortium. Whole blood RNA-sequencing (RNA-seq) was conducted at enrolment into the registry. Data were deconvoluted using CIBERSORTx. Predicted immune cell frequencies were compared between active and inactive disease in the nine BILAG-2004 domains and according to immunosuppressant use (current and past).

RESULTS

Predicted cell frequency varied between 109 patients. Patients currently, or previously, exposed to mycophenolate mofetil (MMF) had fewer inactivated macrophages (0.435% vs 1.391%, p = 0.001), naïve CD4 T cells (0.961% vs 2.251%, p = 0.002), and regulatory T cells (1.858% vs 3.574%, p = 0.007), as well as a higher proportion of memory activated CD4 T cells (1.826% vs 1.113%, p = 0.015), compared to patients never exposed to MMF. These differences remained statistically significant after adjusting for age, gender, ethnicity, disease duration, renal disease, and corticosteroid use. There were 2607 differentially expressed genes (DEGs) in patients exposed to MMF with over-representation of pathways relating to eosinophil function and erythrocyte development and function. Within CD4 + T cells, there were fewer predicted DEGs related to MMF exposure. No significant differences were observed for the other conventional immunosuppressants nor between patients according disease activity in any of the nine organ domains.

CONCLUSION

MMF has a significant and persisting effect on the whole blood transcriptomic signature in patients with SLE. This highlights the need to adequately adjust for background medication use in future studies using whole blood transcriptomics.

Histone modification analysis reveals common regulators of gene expression in liver and blood stage merozoites of Plasmodium parasites

Gene expression in malaria parasites is subject to various layers of regulation, including histone post-translational modifications (PTMs). Gene regulatory mechanisms have been extensively studied during the main developmental stages of Plasmodium parasites inside erythrocytes, from the ring stage following invasion to the schizont stage leading up to egress. However, gene regulation in merozoites that mediate the transition from one host cell to the next is an understudied area of parasite biology. Here, we sought to characterize gene expression and the corresponding histone PTM landscape during this stage of the parasite lifecycle through RNA-seq and ChIP-seq on P. falciparum blood stage schizonts, merozoites, and rings, as well as P. berghei liver stage merozoites. In both hepatic and erythrocytic merozoites, we identified a subset of genes with a unique histone PTM profile characterized by a region of H3K4me3 depletion in their promoter. These genes were upregulated in hepatic and erythrocytic merozoites and rings, had roles in protein export, translation, and host cell remodeling, and shared a DNA motif. These results indicate that similar regulatory mechanisms may underlie merozoite formation in the liver and blood stages. We also observed that H3K4me2 was deposited in gene bodies of gene families encoding variant surface antigens in erythrocytic merozoites, which may facilitate switching of gene expression between different members of these families. Finally, H3K18me and H2K27me were uncoupled from gene expression and were enriched around the centromeres in erythrocytic schizonts and merozoites, suggesting potential roles in the maintenance of chromosomal organization during schizogony. Together, our results demonstrate that extensive changes in gene expression and histone landscape occur during the schizont-to-ring transition to facilitate productive erythrocyte infection. The dynamic remodeling of the transcriptional program in hepatic and erythrocytic merozoites makes this stage attractive as a target for novel anti-malarial drugs that may have activity against both the liver and blood stages.

High-Intensity interval training reduces transcriptomic age: A randomized controlled trial

While the relationship between exercise and life span is well-documented, little is known about the effects of specific exercise protocols on modern measures of biological age. Transcriptomic age (TA) predictors provide an opportunity to test the effects of high-intensity interval training (HIIT) on biological age utilizing whole-genome expression data. A single-site, single-blinded, randomized controlled clinical trial design was utilized. Thirty sedentary participants (aged 40-65) were assigned to either a HIIT group or a no-exercise control group. After collecting baseline measures, HIIT participants performed three 10 × 1 HIIT sessions per week for 4 weeks. Each session lasted 23 min, and total exercise duration was 276 min over the course of the 1-month exercise protocol. TA, PSS-10 score, PSQI score, PHQ-9 score, and various measures of body composition were all measured at baseline and again following the conclusion of exercise/control protocols. Transcriptomic age reduction of 3.59 years was observed in the exercise group while a 3.29-years increase was observed in the control group. Also, PHQ-9, PSQI, BMI, body fat mass, and visceral fat measures were all improved in the exercise group. A hypothesis-generation gene expression analysis suggested exercise may modify autophagy, mTOR, AMPK, PI3K, neurotrophin signaling, insulin signaling, and other age-related pathways. A low dose of HIIT can reduce an mRNA-based measure of biological age in sedentary adults between the ages of 40 and 65 years old. Other changes in gene expression were relatively modest, which may indicate a focal effect of exercise on age-related biological processes.

Decoding the role of transcriptomic clocks in the human prefrontal cortex

Aging is a complex process with interindividual variability, which can be measured by aging biological clocks. Aging clocks are machine-learning algorithms guided by biological information and associated with mortality risk and a wide range of health outcomes. One of these aging clocks are transcriptomic clocks, which uses gene expression data to predict biological age; however, their functional role is unknown. Here, we profiled two transcriptomic clocks (RNAAgeCalc and knowledge-based deep neural network clock) in a large dataset of human postmortem prefrontal cortex (PFC) samples. We identified that deep-learning transcriptomic clock outperforms RNAAgeCalc to predict transcriptomic age in the human PFC. We identified associations of transcriptomic clocks with psychiatric-related traits. Further, we applied system biology algorithms to identify common gene networks among both clocks and performed pathways enrichment analyses to assess its functionality and prioritize genes involved in the aging processes. Identified gene networks showed enrichment for diseases of signal transduction by growth factor receptors and second messenger pathways. We also observed enrichment of genome-wide signals of mental and physical health outcomes and identified genes previously associated with human brain aging. Our findings suggest a link between transcriptomic aging and health disorders, including psychiatric traits. Further, it reveals functional genes within the human PFC that may play an important role in aging and health risk.

Measuring biological age using a functionally interpretable multi-tissue RNA clock

The quantification of the biological age of cells yields great promises for accelerating the discovery of novel rejuvenation strategies. Here, we present MultiTIMER, the first multi-tissue aging clock that measures the biological, rather than chronological, age of cells from their transcriptional profiles by evaluating key cellular processes. We applied MultiTIMER to more than 70,000 transcriptional profiles and demonstrate that it accurately responds to cellular stressors and known interventions while informing about dysregulated cellular functions.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

PTSD, major depression, and advanced transcriptomic age in brain tissue

BACKGROUND

Psychiatric disorders have been associated with advanced epigenetic age in DNA methylation, yet this relationship has not been studied in the brain transcriptome. We examined transcriptomic age using an RNA-based algorithm recently developed by Ren and Kuan ("RNAAgeCalc") and the associations between posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and alcohol use disorder with age-adjusted RNA age ("RNA age residuals") in three brain regions: dorsolateral prefrontal cortex, ventromedial prefrontal cortex (vmPFC), and motor cortex.

METHODS

RNA sequencing was used to measure gene expression in postmortem brain tissue from the VA National PTSD Brain Bank (n = 94; 59% male).

RESULTS

Linear models revealed that diagnoses of PTSD and/or MDD were positively associated with RNA age residuals in vmPFC only (p-adj = 0.012). Three genes in the RNAAgeCalc algorithm (KCNJ16, HYAL2, and CEBPB) were also differentially expressed in association with PTSD/MDD in vmPFC (p-adj = 6.45E-05 to 0.02). Enrichment analysis revealed that inflammatory and immune-related pathways were overrepresented (p-adj < 0.05) among the 43 genes in RNAAgeCalc that were also at least nominally associated with PTSD/MDD in vmPFC relative to the 448 RNAAgeCalc genes. Endothelial and mural cells were negatively associated with RNA age residuals in vmPFC (both p-adj = 0.028) and with PTSD/MDD (both p-adj = 0.017).

CONCLUSIONS

Results highlight the importance of inflammation and immune system dysregulation in the link between psychopathology and accelerated cellular aging and raise the possibility that blood-brain barrier degradation may play an important role in stress-related accelerated brain aging.

Biological Age Predictors: The Status Quo and Future Trends

There is no single universal biomarker yet to estimate overall health status and longevity prospects. Moreover, a consensual approach to the very concept of aging and the means of its assessment are yet to be developed. Markers of aging could facilitate effective health control, more accurate life expectancy estimates, and improved health and quality of life. Clinicians routinely use several indicators that could be biomarkers of aging. Duly validated in a large cohort, models based on a combination of these markers could provide a highly accurate assessment of biological age and the pace of aging. Biological aging is a complex characteristic of chronological age (usually), health-to-age concordance, and medically estimated life expectancy. This study is a review of the most promising techniques that could soon be used in routine clinical practice. Two main selection criteria were applied: a sufficient sample size and reliability based on validation. The selected biological age calculators were grouped according to the type of biomarker used: (1) standard clinical and laboratory markers; (2) molecular markers; and (3) epigenetic markers. The most accurate were the calculators, which factored in a variety of biomarkers. Despite their demonstrated effectiveness, most of them require further improvement and cannot yet be considered for use in standard clinical practice. To illustrate their clinical application, we reviewed their use during the COVID-19 pandemic.

NSD1 mutations deregulate transcription and DNA methylation of bivalent developmental genes in Sotos syndrome

Sotos syndrome (SS), the most common overgrowth with intellectual disability (OGID) disorder, is caused by inactivating germline mutations of NSD1, which encodes a histone H3 lysine 36 methyltransferase. To understand how NSD1 inactivation deregulates transcription and DNA methylation (DNAm), and to explore how these abnormalities affect human development, we profiled transcription and DNAm in SS patients and healthy control individuals. We identified a transcriptional signature that distinguishes individuals with SS from controls and was also deregulated in NSD1-mutated cancers. Most abnormally expressed genes displayed reduced expression in SS; these downregulated genes consisted mostly of bivalent genes and were enriched for regulators of development and neural synapse function. DNA hypomethylation was strongly enriched within promoters of transcriptionally deregulated genes: overexpressed genes displayed hypomethylation at their transcription start sites while underexpressed genes featured hypomethylation at polycomb binding sites within their promoter CpG island shores. SS patients featured accelerated molecular aging at the levels of both transcription and DNAm. Overall, these findings indicate that NSD1-deposited H3K36 methylation regulates transcription by directing promoter DNA methylation, partially by repressing polycomb repressive complex 2 (PRC2) activity. These findings could explain the phenotypic similarity of SS to OGID disorders that are caused by mutations in PRC2 complex-encoding genes.

Increased DNA methylation, cellular senescence and premature epigenetic aging in guinea pigs and humans with tuberculosis

BACKGROUND

Tuberculosis (TB) is the archetypical chronic infection, with patients having months of symptoms before diagnosis. In the two years after successful therapy, survivors of TB have a three-fold increased risk of death.

METHODS

Guinea pigs were infected with Mycobacterium tuberculosis (Mtb) for 45 days, followed by RRBS DNA methylation analysis. In humans, network analysis of differentially expressed genes across three TB cohorts were visualized at the pathway-level. Serum levels of inflammation were measured by ELISA. Horvath (DNA methylation) and RNA-seq biological clocks were used to investigate shifts in chronological age among humans with TB.

RESULTS

Guinea pigs with TB demonstrated DNA hypermethylation and showed system-level similarity to humans with TB (p-value = 0.002). The transcriptome in TB in multiple cohorts was enriched for DNA methylation and cellular senescence. Senescence associated proteins CXCL9, CXCL10, and TNF were elevated in TB patients compared to healthy controls. Humans with TB demonstrate 12.7 years (95% CI: 7.5, 21.9) and 14.38 years (95% CI: 10.23-18.53) of cellular aging as measured by epigenetic and gene expression based cellular clocks, respectively.

CONCLUSIONS

In both guinea pigs and humans, TB perturbs epigenetic processes, promoting premature cellular aging and inflammation, a plausible means to explain the long-term detrimental health outcomes after TB.

Pan-cancer analysis reveals molecular patterns associated with age

Older age is a strong risk factor for several diseases, including cancer. The etiology and biology of age-associated differences among cancers are poorly understood. To address this knowledge gap, we aim to delineate differences in tumor molecular characteristics between younger and older patients across a variety of tumor types from The Cancer Genome Atlas. We show that these groups exhibit widespread molecular differences in select tumor types. Our work shows that tumors in younger individuals exhibit a dysregulated molecular aging phenotype and are associated with hallmarks of premature senescence. Additionally, we find that these tumors are enriched for driver gene mutations, resulting in homologous recombination defects. Lastly, we observe a trend toward decreased immune infiltration and function in older patients and find that, immunologically, young tumor tissue resembles aged healthy tissue. Taken together, we find that tumors from young individuals possess unique characteristics that may be leveraged for therapy.

Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms

Background

COVID-19 has caused millions of deaths globally, yet the cellular mechanisms underlying the various effects of the disease remain poorly understood. Recently, a new analytical platform for comprehensive analysis of plasma protein profiles using proximity extension assays combined with next generation sequencing has been developed, which allows for multiple proteins to be analyzed simultaneously without sacrifice on accuracy or sensitivity.

Methods

We analyzed the plasma protein profiles of COVID-19 patients (n = 50) with mild and moderate symptoms by comparing the protein levels in newly diagnosed patients with the protein levels in the same individuals after 14 days.

Findings

The study has identified more than 200 proteins that are significantly elevated during infection and many of these are related to cytokine response and other immune-related functions. In addition, several other proteins are shown to be elevated, including SCARB2, a host cell receptor protein involved in virus entry. A comparison with the plasma protein response in patients with severe symptoms shows a highly similar pattern, but with some interesting differences.

Interpretation

The study presented here demonstrates the usefulness of “next generation plasma protein profiling” to identify molecular signatures of importance for disease progression and to allow monitoring of disease during recovery from the infection. The results will facilitate further studies to understand the molecular mechanism of the immune-related response of the SARS-CoV-2 virus.

Funding

This work was financially supported by Knut and Alice Wallenberg Foundation.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.

Predictors of Biological Age: The Implications for Wellness and Aging Research

As healthspan and lifespan research breakthroughs have become more commonplace, the need for valid, practical markers of biological age is becoming increasingly paramount. The accessibility and affordability of biological age predictors that can reveal information about mortality and morbidity risk, as well as remaining years of life, has profound clinical and research implications. In this review, we examine 5 groups of aging biomarkers capable of providing accurate biological age estimations. The unique capabilities of these biomarkers have far reaching implications for the testing of both pharmaceutical and non-pharmaceutical interventions designed to slow or reverse biological aging. Additionally, the enhanced validity and availability of these tools may have increasingly relevant clinical value. The authors of this review explore those implications, with an emphasis on lifestyle modification research, and provide an overview of the current evidence regarding 5 biological age predictor categories: Telomere length, composite biomarkers, DNA methylation “epigenetic clocks,” transcriptional predictors of biological age, and functional age predictors.

Cellular reprogramming and epigenetic rejuvenation

Ageing is an inevitable condition that afflicts all humans. Recent achievements, such as the generation of induced pluripotent stem cells, have delivered preliminary evidence that slowing down and reversing the ageing process might be possible. However, these techniques usually involve complete dedifferentiation, i.e. somatic cell identity is lost as cells are converted to a pluripotent state. Separating the rejuvenative properties of reprogramming from dedifferentiation is a promising prospect, termed epigenetic rejuvenation. Reprogramming-induced rejuvenation strategies currently involve using Yamanaka factors (typically transiently expressed to prevent full dedifferentiation) and are promising candidates to safely reduce biological age. Here, we review the development and potential of reprogramming-induced rejuvenation as an anti-ageing strategy.

PTSD is associated with accelerated transcriptional aging in World Trade Center responders

Posttraumatic stress disorder (PTSD) is associated with shortened lifespan and healthspan, which suggests accelerated aging. Emerging evidence suggests that methylation age may be accelerated in PTSD. It is important to examine whether transcriptional age is also accelerated because transcriptome is highly dynamic, associated with age-related outcomes, and may offer greater insight into the premature aging in PTSD. This study is the first reported investigation of the relationship between transcriptional age and PTSD. Using RNA-Seq data from our previous study on 324 World Trade Center responders (201 never had PTSD, 81 with current PTSD, and 42 with past PTSD), as well as a transcriptional age calculator (RNAAgeCalc) recently developed by our group, we found that responders with current PTSD, compared with responders without a PTSD diagnosis, showed accelerated transcriptional aging (p = 0.0077) after adjustment for chronological age and race. We compared our results to the epigenetic aging results computed from several epigenetic clock calculators on matching DNA methylation data. GrimAge methylation age acceleration was also associated with PTSD diagnosis (p = 0.0097), and the results remained significant after adjustment for the proportions of immune cell types. PhenoAge, Hannum, and Horvath methylation age acceleration were not reliably related to PTSD. Both epigenetic and transcriptional aging may provide biological insights into the mechanisms underpinning aging in PTSD.

Ranking Biomarkers of Aging by Citation Profiling and Effort Scoring

Aging affects most living organisms and includes the processes that reduce health and survival. The chronological and the biological age of individuals can differ remarkably, and there is a lack of reliable biomarkers to monitor the consequences of aging. In this review we give an overview of commonly mentioned and frequently used potential aging-related biomarkers. We were interested in biomarkers of aging in general and in biomarkers related to cellular senescence in particular. To answer the question whether a biological feature is relevant as a potential biomarker of aging or senescence in the scientific community we used the PICO strategy known from evidence-based medicine. We introduced two scoring systems, aimed at reflecting biomarker relevance and measurement effort, which can be used to support study designs in both clinical and research settings.