Undulating changes in human plasma proteome profiles across the lifespan

Increased plasma levels of neuro-related proteins in patients with stress-related exhaustion: A longitudinal study

Exhaustion disorder (ED) is a stress-related disorder characterized by physical and mental symptoms of exhaustion. Recent data suggest that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED. The aims of this study were to investigate if plasma levels of neuro-related proteins differ between patients with ED and healthy controls, and, if so, to investigate if these differences persist over time. Using the Olink Neuro Exploratory panel, we quantified the plasma levels of 92 neuro-related proteins in 163 ED patients at the time of diagnosis (baseline), 149 patients at long-term follow-up (7-12 years later, median follow-up time 9 years and 5 months), and 100 healthy controls. We found that the plasma levels of 40 proteins were significantly higher in the ED group at baseline compared with the control group. Out of these, the plasma levels of 36 proteins were significantly lower in the ED group at follow-up compared with the same group at baseline and the plasma levels of four proteins did not significantly differ between the groups. At follow-up, the plasma levels of two proteins were significantly lower in the ED group compared with the control group. These data support the hypothesis that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED.

APOB and CCL17 as mediators in the protective effect of SGLT2 inhibition against myocardial infarction: Insights from proteome-wide mendelian randomization

AIMS

Sodium-glucose cotransporter 2 (SGLT2) inhibitors offer a novel therapeutic avenue for myocardial infarction (MI). However, the exact nature of this relationship and the underlying mechanisms are not fully understood.

METHODS

Utilizing a two-sample Mendelian Randomization (MR) analysis, we elucidated the causal effects stemming from the inhibition of SGLT2 on MI. Then, The pool of 4907 circulating proteins within the plasma proteome were utilized to explore the mediators of SGLT2 inhibitors on MI. Protein-protein network and enrichment analysis were conducted to clarify the potential mechanism. Finally, employing MR analysis and meta-analysis techniques, we systematically assessed the causal associations between SGLT2 inhibition and coronary heart diseases (CHD).

RESULTS

SGLT2 inhibition (per 1 SD decrement in HbA1c) was associated with reduced risk of MI (odds ratio [OR] = 0.462, [95% CI 0.222, 0.958], P = 0.038). Among 4907 circulating proteins, we identified APOB and CCL17 which were related to both SGLT2 inhibition and MI. Mediation analysis showed evidence of the indirect effect of SGLT2 inhibition on MI through APOB (β = -0.557, 95%CI [-1.098, -0.155]) with a mediated proportion of 72%, and CCL17 (β = -0.176, 95%CI [-0.332, -0.056]) with a mediated proportion of 17%. The meta-analysis result showed that SGLT2 inhibition was associated with a lower risk of CHD.

CONCLUSION

Based on proteome-wide mendelian randomization, APOB and CCL17 were seen as mediators in the protective effect of SGLT2 inhibition against myocardial infarction.

Long COVID as a disease of accelerated biological aging: An opportunity to translate geroscience interventions

It has been four years since long COVID-the protracted consequences that survivors of COVID-19 face-was first described. Yet, this entity continues to devastate the quality of life of an increasing number of COVID-19 survivors without any approved therapy and a paucity of clinical trials addressing its biological root causes. Notably, many of the symptoms of long COVID are typically seen with advancing age. Leveraging this similarity, we posit that Geroscience-which aims to target the biological drivers of aging to prevent age-associated conditions as a group-could offer promising therapeutic avenues for long COVID. Bearing this in mind, this review presents a translational framework for studying long COVID as a state of effectively accelerated biological aging, identifying research gaps and offering recommendations for future preclinical and clinical studies.

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort

Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.

DNA methylation clocks for estimating biological age in Chinese cohorts

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.

Host-derived protein profiles of human neonatal meconium across gestational ages

Meconium, a non-invasive biomaterial reflecting prenatal substance accumulation, could provide valuable insights into neonatal health. However, the comprehensive protein profile of meconium across gestational ages remains unclear. Here, we conducted an extensive proteomic analysis of first meconium from 259 newborns across varied gestational ages to delineate protein composition and elucidate its relevance to neonatal diseases. The first meconium samples were collected, with the majority obtained before feeding, and the mean time for the first meconium passage from the anus was 11.9 ± 9.47 h. Our analysis revealed 5370 host-derived meconium proteins, which varied depending on sex and gestational age. Specifically, meconium from preterm infants exhibited elevated concentrations of proteins associated with the extracellular matrix. Additionally, the protein profiles of meconium also exhibited unique variations depending on both specific diseases, including gastrointestinal diseases, congenital heart diseases, and maternal conditions. Furthermore, we developed a machine learning model to predict gestational ages using meconium proteins. Our model suggests that newborns with gastrointestinal diseases and congenital heart diseases may have immature gastrointestinal systems. These findings highlight the intricate relationship between clinical parameters and meconium protein composition, offering potential for a novel approach to assess neonatal gastrointestinal health.

qMAP enabled microanatomical mapping of human skin aging

Aging is a major driver of diseases in humans. Identifying features associated with aging is essential for designing robust intervention strategies and discovering novel biomarkers of aging. Extensive studies at both the molecular and organ/whole-body physiological scales have helped determined features associated with aging. However, the lack of meso-scale studies, particularly at the tissue level, limits the ability to translate findings made at molecular scale to impaired tissue functions associated with aging. In this work, we established a tissue image analysis workflow - quantitative micro-anatomical phenotyping (qMAP) - that leverages deep learning and machine vision to fully label tissue and cellular compartments in tissue sections. The fully mapped tissue images address the challenges of finding an interpretable feature set to quantitatively profile age-related microanatomic changes. We optimized qMAP for skin tissues and applied it to a cohort of 99 donors aged 14 to 92. We extracted 914 microanatomic features and found that a broad spectrum of these features, represented by 10 cores processes, are strongly associated with aging. Our analysis shows that microanatomical features of the skin can predict aging with a mean absolute error (MAE) of 7.7 years, comparable to state-of-the-art epigenetic clocks. Our study demonstrates that tissue-level architectural changes are strongly associated with aging and represent a novel category of aging biomarkers that complement molecular markers. Our results highlight the complex and underexplored multi-scale relationship between molecular and tissue microanatomic scales.

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

BACKGROUND

Aging 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.

RESULTS

We 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.

CONCLUSIONS

These 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.

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age

BACKGROUND

Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health.

METHODS

Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status.

FINDINGS

Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group.

INTERPRETATION

Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases.

FUNDING

The specific funding of this article is provided in the acknowledgements section.

Phenotypical and biochemical characterization of murine psoriasiform and fibrotic skin disease models in Stabilin-deficient mice

Stabilin-1 (Stab1) and Stabilin-2 (Stab2) are scavenger receptors expressed by liver sinusoidal endothelial cells (LSECs). The Stabilin-mediated scavenging function is responsible for regulating the molecular composition of circulating blood in mammals. Stab1 and Stab2 have been shown to influence fibrosis in liver and kidneys and to modulate inflammation in atherosclerosis. In this context, circulating and localized TGFBi and POSTN are differentially controlled by the Stabilins as their receptors. To assess Stab1 and Stab2 functions in inflammatory and fibrotic skin disease, topical Imiquimod (IMQ) was used to induce psoriasis-like skin lesions in mice and Bleomycin (BLM) was applied subcutaneously to induce scleroderma-like effects in the skin. The topical treatment with IMQ, as expected, led to psoriasis-like changes in the skin of mice, including increased epidermal thickness and significant weight loss. Clinical severity was reduced in Stab2-deficient compared to Stab1-deficient mice. We did not observe differential effects in the skin of Stabilin-deficient mice after bleomycin injection. Interestingly, treatment with IMQ led to a significant increase of Stabilin ligand TGFBi plasma levels in Stab2-/- mice, treatment with BLM resulted in a significant decrease in TGFBi levels in Stab1-/- mice. Overall, Stab1 and Stab2 deficiency resulted in minor alterations of the disease phenotypes accompanied by alterations of circulating ligands in the blood in response to the disease models. Stabilin-mediated clearance of TGFBi was altered in these disease processes. Taken together our results suggest that Stabilin deficiency-associated plasma alterations may interfere with preclinical disease severity and treatment responses in patients.

A proteomic signature of healthspan

The focus of aging research has shifted from increasing lifespan to enhancing healthspan to reduce the time spent living with disability. Despite significant efforts to develop biomarkers of aging, few studies have focused on biomarkers of healthspan. We developed a proteomics-based signature of healthspan (healthspan proteomic score (HPS)) using data from the UK Biobank Pharma Proteomics Project (53,018 individuals and 2920 proteins). A lower HPS was associated with higher mortality risk and several age-related conditions, such as COPD, diabetes, heart failure, cancer, myocardial infarction, dementia, and stroke. HPS showed superior predictive accuracy for these outcomes compared to chronological age and biological age measures. Proteins associated with HPS were enriched in hallmark pathways such as immune response, inflammation, cellular signaling, and metabolic regulation. Our findings demonstrate the validity of HPS, making it a valuable tool for assessing healthspan and as a potential surrogate marker in geroscience-guided studies.

The longitudinal trajectory of CSF sTREM2: the alzheimer's disease neuroimaging initiative

BACKGROUND

The soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) is considered a biomarker of microglia activity. The objective of this study was to investigate the trajectory of CSF sTREM2 levels over time and examine its association with sex.

METHODS

A total of 1,017 participants from the Alzheimer's Disease Neuroimaging Initiative Study (ADNI) with at least one CSF sTREM2 record were included. The trajectory of CSF sTREM2 was analyzed using a growth curve model. The association between CSF sTREM2 levels and sex was assessed using linear mixed-effect models.

RESULTS

CSF sTREM2 levels were increased with age over time (P < 0.0001). No significant sex difference was observed in sTREM2 levels across the entire sample; however, among the APOE ε4 allele carriers, women exhibited significantly higher sTREM2 levels than men (β = 0.146, P = 0.002).

CONCLUSION

Our findings highlight the association between CSF sTREM2 levels and age-related increments, underscoring the potential influence of aging on sTREM2 dynamics. Furthermore, our observations indicate a noteworthy association between sex and CSF sTREM2 levels, particularly in individuals carrying the APOE ε4 allele.

Heart proteomic profiling discovers MYH6 and COX5B as biomarkers for sudden unexplained death

Sudden unexplained death (SUD) is not uncommon in forensic pathology. Yet, diagnosis of SUD remains challenging due to lack of specific biomarkers. This study aimed to screen differentially expressed proteins (DEPs) and validate their usefulness as diagnostic biomarkers for SUD cases. We designed a three-phase investigation, where in the discovery phase, formalin-fixed paraffin-embedded (FFPE) heart specimens were screened through label-free proteomic analysis of cases dying from SUD, mechanical injury and carbon monoxide (CO) intoxication. A total of 26 proteins were identified to be DEPs for the SUD cases after rigorous criterion. Bioinformatics and Adaboost-recursive feature elimination (RFE) analysis further revealed that three of the 26 proteins (MYH6, COX5B and TNNT2) were potential discriminative biomarkers. In the training phase, MYH6 and COX5B were verified to be true DEPs in cardiac tissues from 29 independent SUD cases as compared with a serial of control cases (n = 42). Receiver operating characteristic (ROC) analysis illustrated that combination of MYH6 and COX5B achieved optimal diagnostic sensitivity (89.7 %) and specificity (84.4 %), with area under the curve (AUC) being 0.91. A diagnostic software based on the logistic regression formula derived from the training phase was then constructed. In the validation phase, the diagnostic software was applied to eight authentic SUD cases, seven (87.5 %) of which were accurately recognized. Our study provides a valid strategy towards practical diagnosis of SUD by integrating cardiac MYH6 and COX5B as dual diagnostic biomarkers.

Analysis of the aging-related biomarker in a nonhuman primate model using multilayer omics

BACKGROUND

Aging is a prominent risk factor for diverse diseases; therefore, an in-depth understanding of its physiological mechanisms is required. Nonhuman primates, which share the closest genetic relationship with humans, serve as an ideal model for exploring the complex aging process. However, the potential of the nonhuman primate animal model in the screening of human aging markers is still not fully exploited. Multiomics analysis of nonhuman primate peripheral blood offers a promising approach to evaluate new therapies and biomarkers. This study explores aging-related biomarker through multilayer omics, including transcriptomics (mRNA, lncRNA, and circRNA) and proteomics (serum and serum-derived exosomes) in rhesus monkeys (Macaca mulatta).

RESULTS

Our findings reveal that, unlike mRNAs and circRNAs, highly expressed lncRNAs are abundant during the key aging period and are associated with cancer pathways. Comparative analysis highlighted exosomal proteins contain more types of proteins than serum proteins, indicating that serum-derived exosomes primarily regulate aging through metabolic pathways. Finally, eight candidate aging biomarkers were identified, which may serve as blood-based indicators for detecting age-related brain changes.

CONCLUSIONS

Our results provide a comprehensive understanding of nonhuman primate blood transcriptomes and proteomes, offering novel insights into the aging mechanisms for preventing or treating age-related diseases.

Machine learning models based on fluid immunoproteins that predict non-AIDS adverse events in people with HIV

Despite the success of antiretroviral therapy (ART), individuals with HIV remain at risk for experiencing non-AIDS adverse events (NAEs), including cardiovascular complications and malignancy. Several surrogate immune biomarkers in blood have shown predictive value in predicting NAEs; however, composite panels generated using machine learning may provide a more accurate advancement for monitoring and discriminating NAEs. In a nested case-control study, we aimed to develop machine learning models to discriminate cases (experienced an event) and matched controls using demographic and clinical characteristics alongside 49 plasma immunoproteins measured prior to and post-ART initiation. We generated support vector machine (SVM) classifier models for high-accuracy discrimination of individuals aged 30-50 years who experienced non-fatal NAEs at pre-ART and one-year post-ART. Extreme gradient boosting generated a high-accuracy model at pre-ART, while K-nearest neighbors performed poorly all around. SVM modeling may offer guidance to improve disease monitoring and elucidate potential therapeutic interventions.

Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks

Aging is a complex and time-dependent decline in physiological function that affects most organisms, leading to increased risk of age-related diseases. Investigating the molecular underpinnings of aging is crucial to identify geroprotectors, precisely quantify biological age, and propose healthy longevity approaches. This review explores pathways that are currently being investigated as intervention targets and aging biomarkers spanning molecular, cellular, and systemic dimensions. Interventions that target these hallmarks may ameliorate the aging process, with some progressing to clinical trials. Biomarkers of these hallmarks are used to estimate biological aging and risk of aging-associated disease. Utilizing aging biomarkers, biological aging clocks can be constructed that predict a state of abnormal aging, age-related diseases, and increased mortality. Biological age estimation can therefore provide the basis for a fine-grained risk stratification by predicting all-cause mortality well ahead of the onset of specific diseases, thus offering a window for intervention. Yet, despite technological advancements, challenges persist due to individual variability and the dynamic nature of these biomarkers. Addressing this requires longitudinal studies for robust biomarker identification. Overall, utilizing the hallmarks of aging to discover new drug targets and develop new biomarkers opens new frontiers in medicine. Prospects involve multi-omics integration, machine learning, and personalized approaches for targeted interventions, promising a healthier aging population.

Sex and aging signatures of proteomics in human cerebrospinal fluid identify distinct clusters linked to neurodegeneration

Sex and age are major risk factors for chronic diseases. Recent studies examining age-related molecular changes in plasma provided insights into age-related disease biology. Cerebrospinal fluid (CSF) proteomics can provide additional insights into brain aging and neurodegeneration. By comprehensively examining 7,006 aptamers targeting 6,139 proteins in CSF obtained from 660 healthy individuals aged from 43 to 91 years old, we subsequently identified significant sex and aging effects on 5,097 aptamers in CSF. Many of these effects on CSF proteins had different magnitude or even opposite direction as those on plasma proteins, indicating distinctive CSF-specific signatures. Network analysis of these CSF proteins revealed not only modules associated with healthy aging but also modules showing sex differences. Through subsequent analyses, several modules were highlighted for their proteins implicated in specific diseases. Module 2 and 6 were enriched for many aging diseases including those in the circulatory systems, immune mechanisms, and neurodegeneration. Together, our findings fill a gap of current aging research and provide mechanistic understanding of proteomic changes in CSF during a healthy lifespan and insights for brain aging and diseases.

Plasma and Kidney Proteome Profiling Combined with Laser Capture Microdissection Reveal Large Increases in Immunoglobulins with Age

One of the main hallmarks of aging is aging-associated inflammation, also known as inflammaging. In this study, by comparing plasma and kidney proteome profiling of young and old mice using LC-MS profiling, we discovered that immunoglobulins are the proteins that exhibit the highest increase with age. This observation seems to have been disregarded because conventional proteome profiling experiments typically overlook the expression of high-abundance proteins or employ depletion methods to remove them before LC-MS analysis. We show that proteome profiling of immunoglobulins will likely be a useful biomarker of aging. Spatial profiling using immunofluorescence staining of kidney sections indicates that the main increases in immunoglobulins with age are localized in the glomeruli of the kidney. Using laser capture microdissection coupled with LC-MS, we show an increase in multiple immune-related proteins in glomeruli from aged mice. Increased deposition of immunoglobulins, immune complexes, and complement proteins in the kidney glomeruli may be a factor leading to reduced filtering capacity of the kidney with age. Therapeutic strategies to reduce the deposition of immunoglobulins in the kidney may be an attractive strategy for healthy aging.

CheekAge: a next-generation buccal epigenetic aging clock associated with lifestyle and health

Epigenetic aging clocks are computational models that predict age using DNA methylation information. Initially, first-generation clocks were developed to make predictions using CpGs that change with age. Over time, next-generation clocks were created using CpGs that relate to both age and health. Since existing next-generation clocks were constructed in blood, we sought to develop a next-generation clock optimized for prediction in cheek swabs, which are non-invasive and easy to collect. To do this, we collected MethylationEPIC data as well as lifestyle and health information from 8045 diverse adults. Using a novel simulated annealing approach that allowed us to incorporate lifestyle and health factors into training as well as a combination of CpG filtering, CpG clustering, and clock ensembling, we constructed CheekAge, an epigenetic aging clock that has a strong correlation with age, displays high test-retest reproducibility across replicates, and significantly associates with a plethora of lifestyle and health factors, such as BMI, smoking status, and alcohol intake. We validated CheekAge in an internal dataset and multiple publicly available datasets, including samples from patients with progeria or meningioma. In addition to exploring the underlying biology of the data and clock, we provide a free online tool that allows users to mine our methylomic data and predict epigenetic age.

Adding intrinsically disordered proteins to biological ageing clocks

Research into how the young and old differ, and which biomarkers reflect the diverse biological processes underlying ageing, is a current and fast-growing field. Biological clocks provide a means to evaluate whether a molecule, cell, tissue or even an entire organism is old or young. Here we summarize established and emerging molecular clocks as timepieces. We emphasize that intrinsically disordered proteins (IDPs) tend to transform into a β-sheet-rich aggregated state and accumulate in non-dividing or slowly dividing cells as they age. We hypothesize that understanding these protein-based molecular ageing mechanisms might provide a conceptual pathway to determining a cell's health age by probing the aggregation state of IDPs, which we term the IDP clock.

Healthy blood, healthy brain: a window into understanding and treating neurodegenerative diseases

Our limited understanding of complex neurodegenerative disorders has held us back on the development of efficient therapies. While several approaches are currently being considered, it is still unclear what will be most successful. Among the latest and more novel ideas, the concept of blood or plasma transfusion from young healthy donors to diseased patients is gaining momentum and attracting attention beyond the scientific arena. While young or healthy blood is enriched with protective and restorative components, blood from older subjects may accumulate neurotoxic agents or be impoverished of beneficial factors. In this commentary, we present an overview of the compelling evidence collected in various animal models of brain diseases (e.g., Alzheimer, Parkinson, Huntington) to the actual clinical trials that have been conducted to test the validity of blood-related treatments in neurodegenerative diseases and argue in favor of such approach.

Targeting the epigenetically older individuals for geroprotective trials: the use of DNA methylation clocks

Chronological age is the most important risk factor for the incidence of age-related diseases. The pace of ageing determines the magnitude of that risk and can be expressed as biological age. Targeting fundamental pathways of human aging with geroprotectors has the potential to lower the biological age and therewith prolong the healthspan, the period of life one spends in good health. Target populations for geroprotective interventions should be chosen based on the ageing mechanisms being addressed and the expected effect of the geroprotector on the primary outcome. Biomarkers of ageing, such as DNA methylation age, can be used to select populations for geroprotective interventions and as a surrogate outcome. Here, the use of DNA methylation clocks for selecting target populations for geroprotective intervention is explored.

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.

Promises and Challenges of populational Proteomics in Health and Disease

Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.

Aging hallmarks of the primate ovary revealed by spatiotemporal transcriptomics

The ovary is indispensable for female reproduction, and its age-dependent functional decline is the primary cause of infertility. However, the molecular basis of ovarian aging in higher vertebrates remains poorly understood. Herein, we apply spatiotemporal transcriptomics to benchmark architecture organization as well as cellular and molecular determinants in young primate ovaries and compare these to aged primate ovaries. From a global view, somatic cells within the non-follicle region undergo more pronounced transcriptional fluctuation relative to those in the follicle region, likely constituting a hostile microenvironment that facilitates ovarian aging. Further, we uncovered that inflammation, the senescent-associated secretory phenotype, senescence, and fibrosis are the likely primary contributors to ovarian aging (PCOA). Of note, we identified spatial co-localization between a PCOA-featured spot and an unappreciated MT2 (Metallothionein 2) highly expressing spot (MT2high) characterized by high levels of inflammation, potentially serving as an aging hotspot in the primate ovary. Moreover, with advanced age, a subpopulation of MT2high accumulates, likely disseminating and amplifying the senescent signal outward. Our study establishes the first primate spatiotemporal transcriptomic atlas, advancing our understanding of mechanistic determinants underpinning primate ovarian aging and unraveling potential biomarkers and therapeutic targets for aging and age-associated human ovarian disorders.

In vitro heterochronic parabiosis identifies pigment epithelium-derived factor as a systemic mediator of rejuvenation by young blood

Several decades of heterochronic parabiosis (HCPB) studies have demonstrated the restorative impact of young blood, and deleterious influence of aged blood, on physiological function and homeostasis across tissues, although few of the factors responsible for these observations have been identified. Here we develop an in vitro HCPB system to identify these circulating factors, using replicative lifespan (RLS) of primary human fibroblasts as an endpoint of cellular health. We find that RLS is inversely correlated with serum donor age and sensitive to the presence or absence of specific serum components. Through in vitro HCPB, we identify the secreted protein pigment epithelium-derived factor (PEDF) as a circulating factor that extends RLS of primary human fibroblasts and declines with age in mammals. Systemic administration of PEDF to aged mice reverses age-related functional decline and pathology across several tissues, improving cognitive function and reducing hepatic fibrosis and renal lipid accumulation. Together, our data supports PEDF as a systemic mediator of the effect of young blood on organismal health and homeostasis and establishes our in vitro HCPB system as a valuable screening platform for the identification of candidate circulating factors involved in aging and rejuvenation.

Platelet-Rich Plasma in Young and Elderly Humans Exhibits a Different Proteomic Profile

As people age, their ability to resist injury and repair damage decreases significantly. Platelet-rich plasma (PRP) has demonstrated diverse therapeutic effects on tissue repair. However, the inconsistency of patient outcomes poses a challenge to the practical application of PRP in clinical practice. Furthermore, a comprehensive understanding of the specific impact of aging on PRP requires a systematic investigation. We derived PRP from 6 young volunteers and 6 elderly volunteers, respectively. Subsequently, 95% of high-abundance proteins were removed, followed by mass spectrometry analysis. Data are available via ProteomeXchange with the identifier PXD050061. We detected a total of 739 proteins and selected 311 proteins that showed significant differences, including 76 upregulated proteins in the young group and 235 upregulated proteins in the elderly group. Functional annotation and enrichment analysis unveiled upregulation of proteins associated with cell apoptosis, angiogenesis, and complement and coagulation cascades in the elderly. Conversely, IGF1 was found to be upregulated in the young group, potentially serving as the central source of enhanced cell proliferation ability. Our investigation not only provides insights into standardizing PRP preparation but also offers novel strategies for augmenting the functionality of aging cells or tissues.

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.

Gastric GDF15 levels are regulated by age, sex, and nutritional status in rodents and humans

AIM

Growth differentiation factor 15 (GDF15) is a stress response cytokine that has been proposed as a relevant metabolic hormone. Descriptive studies have shown that plasma GDF15 levels are regulated by short term changes in nutritional status, such as fasting, or in obesity. However, few data exist regarding how GDF15 levels are regulated in peripheral tissues. The aim of the present work was to study the variations on gastric levels of GDF15 and its precursor under different physiological conditions, such as short-term changes in nutritional status or overfeeding achieved by HFD. Moreover, we also address the sex- and age-dependent alterations in GDF15 physiology.

METHODS

The levels of gastric and plasma GDF15 and its precursor were measured in lean and obese mice, rats and humans by western blot, RT-PCR, ELISA, immunohistochemistry and by an in vitro organ culture system.

RESULTS

Our results show a robust regulation of gastric GDF15 production by fasting in rodents. In obesity an increase in GDF15 secretion from the stomach is reflected with an increase in circulating levels of GDF15 in rats and humans. Moreover, gastric GDF15 levels increase with age in both rats and humans. Finally, gastric GDF15 levels display sexual dimorphism, which could explain the difference in circulating GFD15 levels between males and females, observed in both humans and rodents.

CONCLUSIONS

Our results provide clear evidence that gastric GDF15 is a critical contributor of circulating GDF15 levels and can explain some of the metabolic effects induced by GDF15.

Organ-specific aging in the plasma proteome predicts disease

In their recent Nature paper, Oh et al. use 4979 plasma proteins collected across multiple cohorts, publicly available gene expression data, and machine learning models to identify 11 organ-specific aging scores that are linked to organ-specific disease and mortality risk, including heart failure, cognitive decline, and Alzheimer's disease.

Plasma proteomic profile of abdominal obesity in older adults

OBJECTIVE

This study examines the plasma proteomic profile of abdominal obesity in older adults.

METHODS

The association of abdominal obesity (waist circumference [WC]) with 4265 plasma proteins identified using the SomaScan Assay was examined in 969 Ashkenazi Jewish participants (LonGenity cohort), aged 65 years and older (mean [SD] age 75.7 [6.7] years, 55.4% women), using regression models. Pathway analysis, as well as weighted correlation network analysis, was performed. WC was determined from the proteome using elastic net regression.

RESULTS

A total of 480 out of 4265 proteins were associated with WC in the linear regression model. Leptin (β [SE] = 12.363 [0.490]), inhibin β C chain (INHBC; β [SE] = 24.324 [1.448]), insulin-like growth factor-binding protein 2 (IGFBP-2; β [SE] = -12.782 [0.841]), heparan-sulfate 6-O-sulfotransferase 3 (H6ST3; β [SE] = -39.995 [2.729]), and matrix-remodeling-associated protein 8 (MXRA8; β [SE] = -27.101 [1.850]) were the top proteins associated with WC. Cell adhesion, extracellular matrix remodeling, and IGF transport pathways were the top enriched pathways associated with WC. WC signature determined from plasma proteins was highly correlated with measured WC (r = 0.80) and was associated with various metabolic and physical traits.

CONCLUSIONS

The study unveiled a multifaceted plasma proteomic profile of abdominal obesity in older adults, offering insights into its wide-ranging impact on the proteome. It also elucidated novel proteins, clusters of correlated proteins, and pathways that are intricately associated with abdominal obesity.

Growth and differentiation factor-15: A link between inflammaging and cardiovascular disease

Age-related disorders are closely linked to the accumulation of senescent cells. The senescence-associated secretory phenotype (SASP) sustains and progresses chronic inflammation, which is involved in cellular and tissue dysfunction. SASP-related growth and differentiation factor-15 (GDF-15) is an immunoregulatory cytokine that is coupled to aging and thus may have a regulatory role in the development and maintenance of atherosclerosis, a major cause of cardiovascular disease (CVD). Although the effects of GDF-15 are tissue-specific and dependent on microenvironmental changes such as inflammation, available data suggest that GDF-15 has a significant role in CVD. Thus, GDF-15 is a promising biomarker and potential therapeutic target for atherosclerotic CVD.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

The sirtuin-associated human senescence program converges on the activation of placenta-specific gene PAPPA

Sirtuins are pro-longevity genes with chromatin modulation potential, but how these properties are connected is not well understood. Here, we generated a panel of isogeneic human stem cell lines with SIRT1-SIRT7 knockouts and found that any sirtuin deficiency leads to accelerated cellular senescence. Through large-scale epigenomic analyses, we show how sirtuin deficiency alters genome organization and that genomic regions sensitive to sirtuin deficiency are preferentially enriched in active enhancers, thereby promoting interactions within topologically associated domains and the formation of de novo enhancer-promoter loops. In all sirtuin-deficient human stem cell lines, we found that chromatin contacts are rewired to promote aberrant activation of the placenta-specific gene PAPPA, which controls the pro-senescence effects associated with sirtuin deficiency and serves as a potential aging biomarker. Based on our survey of the 3D chromatin architecture, we established connections between sirtuins and potential target genes, thereby informing the development of strategies for aging interventions.

Cross-platform proteomics signatures of extreme old age

In previous work we used a Somalogic platform targeting approximately 5000 proteins to generate a serum protein signature of centenarians that we validated in independent studies that used the same technology. We set here to validate and possibly expand the results by profiling the serum proteome of a subset of individuals included in the original study using liquid chromatography tandem mass spectrometry (LC-MS/MS). Following pre-processing, the LC-MS/MS data provided quantification of 398 proteins, with only 266 proteins shared by both platforms. At 1% FDR statistical significance threshold, the analysis of LC-MS/MS data detected 44 proteins associated with extreme old age, including 23 of the original analysis. To identify proteins for which associations between expression and extreme-old age were conserved across platforms, we performed inter-study conservation testing of the 266 proteins quantified by both platforms using a method that accounts for the correlation between the results. From these tests, a total of 80 proteins reached 5% FDR statistical significance, and 26 of these proteins had concordant pattern of gene expression in whole blood. This signature of 80 proteins points to blood coagulation, IGF signaling, extracellular matrix (ECM) organization, and complement cascade as important pathways whose protein level changes provide evidence for age-related adjustments that distinguish centenarians from younger individuals.

Nonlinear DNA methylation trajectories in aging male mice

Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents' life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era

Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying aging across multiple organs, assessment of the contribution of individual organs to overall aging processes is a cutting-edge issue. An organ's biological age might influence the aging of other organs, revealing a multiorgan aging network. Recent data demonstrated a similar yet asynchronous inter-organs and inter-individuals progression of aging, thereby providing a foundation to track sources of declining health in old age. The integration of multiple omics with common clinical parameters through artificial intelligence has allowed the building of organ-specific aging clocks, which can predict the development of specific age-related diseases at high resolution. The peculiar individual aging-trajectory, referred to as ageotype, might provide a novel tool for a personalized anti-aging, preventive medicine. Here, we review data relative to biological aging clocks and omics-based data, suggesting different organ-specific aging rates. Additional research on longitudinal data, including young subjects and analyzing sex-related differences, should be encouraged to apply ageotyping analysis for preventive purposes in clinical practice.

Speeding Up Time: New Urinary Peptide Clock Associates Greater Air Pollution Exposures with Faster Biological Aging

A study in Belgium supports earlier findings on associations between higher air pollution exposures and markers of faster biological aging, this time by using urinary peptide levels instead of DNA-based markers.

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.

The 'middle-aging' brain

Middle age has historically been an understudied period of life compared to older age, when cognitive and brain health decline are most pronounced, but the scope for intervention may be limited. However, recent research suggests that middle age could mark a shift in brain aging. We review emerging evidence on multiple levels of analysis indicating that midlife is a period defined by unique central and peripheral processes that shape future cognitive trajectories and brain health. Informed by recent developments in aging research and lifespan studies in humans and animal models, we highlight the utility of modeling non-linear changes in study samples with wide subject age ranges to distinguish life stage-specific processes from those acting linearly throughout the lifespan.

Application of AI in biological age prediction

The development of anti-aging interventions requires quantitative measurement of biological age. Machine learning models, known as "aging clocks," are built by leveraging diverse aging biomarkers that vary across lifespan to predict biological age. In addition to traditional aging clocks harnessing epigenetic signatures derived from bulk samples, emerging technologies allow the biological age estimating at single-cell level to dissect cellular diversity in aging tissues. Moreover, imaging-based aging clocks are increasingly employed with the advantage of non-invasive measurement, making it suitable for large-scale human cohort studies. To fully capture the features in the ever-growing multi-modal and high-dimensional aging-related data and uncover disease associations, deep-learning based approaches, which are effective to learn complex and non-linear relationships without relying on pre-defined features, are increasingly applied. The use of big data and AI-based aging clocks has achieved high accuracy, interpretability and generalizability, guiding clinical applications to delay age-related diseases and extend healthy lifespans.

Mitochondrial respiration atlas reveals differential changes in mitochondrial function across sex and age

Organ function declines with age, and large-scale transcriptomic analyses have highlighted differential aging trajectories across tissues. The mechanisms underlying shared and organ-selective functional changes across the lifespan, however, still remains poorly understood. Given the central role of mitochondria in powering cellular processes needed to maintain tissue health, we therefore undertook a systematic assessment of respiratory activity across 33 different tissues in young (2.5 months) and old (20 months) mice of both sexes. Our high-resolution mitochondrial respiration atlas reveals: 1) within any group of mice, mitochondrial activity varies widely across tissues, with the highest values consistently seen in heart, brown fat, and kidney; 2) biological sex is a significant but minor contributor to mitochondrial respiration, and its contributions are tissue-specific, with major differences seen in the pancreas, stomach, and white adipose tissue; 3) age is a dominant factor affecting mitochondrial activity, especially across different fat depots and skeletal muscle groups, and most brain regions; 4) age-effects can be sex- and tissue-specific, with some of the largest effects seen in pancreas, heart, adipose tissue, and skeletal muscle; and 5) while aging alters the functional trajectories of mitochondria in a majority of tissues, some are remarkably resilient to age-induced changes. Altogether, our data provide the most comprehensive compendium of mitochondrial respiration and illuminate functional signatures of aging across diverse tissues and organ systems.

A qualitative internet-based study of parental experiences of adolescents suffering from affective disorders with non-suicidal self-injury during the COVID-19 pandemic

Objective

Non-suicidal self-injury (NSSI) behaviors of adolescents with affective disorders can directly deteriorate parents' internal experiences, and negative parental experiences can exacerbate or even worsen NSSI behaviors. This study investigates the impact of NSSI behaviors exhibited by adolescents with affective disorders on the internal experiences of parents. Specifically, our research focuses on the inner experiences of parents when their children engage in NSSI behaviors during social isolation of the COVID-19, offering insights for addressing parental mental health issues related to NSSI and developing positive parental behavioral models to optimize adolescent behavior during major public health events.

Methods

Semi-structured interviews were conducted with 21 parents of adolescents with affective disorders displaying NSSI behaviors during the COVID-19 pandemic. The Colaizzi 7-step analysis was employed to refine and categorize emerging themes.

Results

Our study revealed that parents of adolescents facing NSSI during the COVID-19 pandemic underwent different internal experiences, which could be classified into four themes: negative experience, high caregiving burden, lack of caregiving capacity, and resilience.

Conclusion

This Internet-based research is the first to explore the internal experiences of parents of adolescents with affective disorders experiencing NSSI during the COVID-19 pandemic. It sheds light on how parents, in response to their children's NSSI behaviors, undergo resilience following negative experiences, explore more open and supportive family model. Despite these positive outcomes, parents express a need for increased knowledge about NSSI illness care and a desire for professional assistance.

METS-IR and all-cause mortality in Korean over 60 years old: Korean genome and epidemiology study-health examinees (KoGES-HEXA) cohorts

Background

The metabolic score for insulin resistance index (METS-IR) is a novel non insulin-based marker that indicates the risk for metabolic syndrome and type 2 diabetes mellitus (T2DM). However, METS-IR has not been investigated in relation to all-cause mortality. We investigated the longitudinal effect of METS-IR on all-cause mortality in a significantly large cohort of Korean adults over 60 years old.

Methods

Data were assessed from 30,164 Korean participants over 60 years of age from the Korean Genome and Epidemiology Study-Health Examinees (KoGES-HEXA) cohort data, linked with the death certificate database of the National Statistical Office. The participants were grouped into three according to METS-IR tertiles. We used multivariate Cox proportional-hazard regression models to prospectively assess hazard ratios (HRs) for all-cause mortality with 95% confidence intervals (CIs) over an 11-year postbaseline period.

Results

During the mean 11.7 years of follow-up, 2,821 individuals expired. The HRs of mortality for METS-IR tertiles were 1.16 (95% CI, 1.01-1.34) in T3 after adjustment for metabolic parameters, but the T2 did not show statistical significance towards increases for incident mortality respectively. In subgroup analysis depending on the cause of mortality, higher METS-IR was associated with cancer mortality (HR, 1.23, 95% CI, 1.01-1.51) but not with cardiovascular mortality (HR, 1.14, 95% CI, 0.83-1.57) after adjustment for the same confounding variables.

Conclusion

The METS-IR may be a useful predictive marker for all-cause mortality and cancer mortality, but not for cardiovascular mortality in subjects over 60 years of age. This implies that early detection and intervention strategies for metabolic syndrome could potentially benefit this identified group.

Lifestyle and demographic associations with 47 inflammatory and vascular stress biomarkers in 9876 blood donors

BACKGROUND

The emerging use of biomarkers in research and tailored care introduces a need for information about the association between biomarkers and basic demographics and lifestyle factors revealing expectable concentrations in healthy individuals while considering general demographic differences.

METHODS

A selection of 47 biomarkers, including markers of inflammation and vascular stress, were measured in plasma samples from 9876 Danish Blood Donor Study participants. Using regression models, we examined the association between biomarkers and sex, age, Body Mass Index (BMI), and smoking.

RESULTS

Here we show that concentrations of inflammation and vascular stress biomarkers generally increase with higher age, BMI, and smoking. Sex-specific effects are observed for multiple biomarkers.

CONCLUSION

This study provides comprehensive information on concentrations of 47 plasma biomarkers in healthy individuals. The study emphasizes that knowledge about biomarker concentrations in healthy individuals is critical for improved understanding of disease pathology and for tailored care and decision support tools.

Epigenetic erosion of H4K20me1 induced by inflammation drives aged stem cell ferroptosis

Aging is associated with a decline in stem cell functionality and number across the organism. In this study, we aimed to further unravel Muscle Stem Cells (MuSCs) aging by assessing how systemic factors influence MuSC fate decisions through long-term epigenetic landscape remodelling. As aging is intricately linked to a pro-inflammatory shift, we studied the epigenetic effects of inflammatory signals in MuSCs and measured decreased H4K20me1 levels. This loss disrupts MuSC quiescence, largely through epigenetic silencing of Notch target genes. In the setting of inflammatory signals or aging, the lack of Kmt5a and the subsequent absence of de novoH4K20me1 culminate in cell death by ferroptosis. Aged MuSCs manifest abnormal iron metabolism and reduced Gpx4 levels, resulting in the accumulation of intracellular iron, increased reactive oxygen species, genomic instability, and lipid peroxidation. We showed that ferroptosis is the predominant mode of cell death in aged MuSCs, with remarkably high levels of lipid peroxidation; a phenomenon we also observed in aged hematopoietic stem cells. Implementing preventative strategies to inhibit systemic inflammation prevented aged MuSC ferroptosis, preserving their numbers and regenerative capabilities. This intervention significantly enhanced aged muscle regeneration and strength recovery and extended both lifespan and healthspan in mice. This study delineates a previously underappreciated fate trajectory for stem cell aging, and offers meaningful insights into the treatment of age-related disorders.

Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson's disease

Parkinson's disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research-L-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography-mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as L-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.