HIV-2 mediated effects on target and bystander cells induce plasma proteome remodeling.

Despite low or undetectable plasma viral load, people living with HIV-2 (PLWH2) typically progress toward AIDS. The driving forces behind HIV-2 disease progression and the role of viremia are still not known, but low-level replication in tissues is believed to play a role. To investigate the impact of viremic and aviremic HIV-2 infection on target and bystander cell pathology, we used data-independent acquisition mass spectrometry to determine plasma signatures of tissue and cell type engagement. Proteins derived from target and bystander cells in multiple tissues, such as the gastrointestinal tract and brain, were detected at elevated levels in plasma of PLWH2, compared with HIV negative controls. Moreover, viremic HIV-2 infection appeared to induce enhanced release of proteins from a broader range of tissues compared to aviremic HIV-2 infection. This study expands the knowledge on the link between plasma proteome remodeling and the pathological cell engagement in tissues during HIV-2 infection.

A survey of ficolin-3 activity in Systemic Lupus Erythematosus reveals a link to hematological disease manifestations and autoantibody profile.

The complement system plays a central role in the pathogenesis of Systemic Lupus Erythematosus (SLE), but most studies have focused on the classical pathway. Ficolin-3 is the main initiator of the lectin pathway of complement in humans, but its role in systemic autoimmune disease has not been conclusively determined. Here, we combined biochemical and genetic approaches to assess the contribution of ficolin-3 to SLE risk and disease manifestations. Ficolin-3 activity was measured by a functional assay in serum or plasma samples from Swedish SLE patients (n = 786) and controls matched for age and sex (n = 566). Genetic variants in an extended 300 kb genomic region spanning the FCN3 locus were analyzed for their association with ficolin-3 activity and SLE manifestations in a Swedish multicenter cohort (n = 985). Patients with ficolin-3 activity in the highest tertile showed a strong enrichment in an SLE cluster defined by anti-Sm/DNA/nucleosome antibodies (OR 3.0, p < 0.001) and had increased rates of hematological disease (OR 1.4, p = 0.078) and lymphopenia (OR = 1.6, p = 0.039). Genetic variants associated with low ficolin-3 activity mapped to an extended haplotype in high linkage disequilibrium upstream of the FCN3 gene. Patients carrying the lead genetic variant associated with low ficolin-3 activity had a lower frequency of hematological disease (OR 0.67, p = 0.018) and lymphopenia (OR 0.63, p = 0.031) and fewer autoantibodies (p = 0.0019). Loss-of-function variants in the FCN3 gene were not associated with SLE, but four (0.5 %) SLE patients developed acquired ficolin-3 deficiency where ficolin-3 activity in serum was depleted following diagnosis of SLE. Taken together, our results provide genetic and biochemical evidence that implicate the lectin pathway in hematological SLE manifestations. We also identify lectin pathway activation through ficolin-3 as a factor that contributes to the autoantibody response in SLE.

Screening for Circulating Inflammatory Proteins Does Not Reveal Plasma Biomarkers of Constant Tinnitus.

BACKGROUND AND OBJECTIVE: Tinnitus would benefit from an objective biomarker. The goal of this study is to identify plasma biomarkers of constant and chronic tinnitus among selected circulating inflammatory proteins. METHODS: A case-control retrospective study on 548 cases with constant tinnitus and 548 matched controls from the Swedish Tinnitus Outreach Project (STOP), whose plasma samples were examined using Olink's Inflammatory panel. Replication and meta-analysis were performed using the same method on samples from the TwinsUK cohort. Participants from LifeGene, whose blood was collected in Stockholm and Umeå, were recruited to STOP for a tinnitus subtyping study. An age and sex matching was performed at the individual level. TwinsUK participants (n = 928) were selected based on self-reported tinnitus status over 2 to 10 years. Primary outcomes include normalized levels for 96 circulating proteins, which were used as an index test. No reference standard was available in this study. RESULTS: After adjustment for age, sex, BMI, smoking, hearing loss, and laboratory site, the top proteins identified were FGF-21, MCP4, GDNF, CXCL9, and MCP-1; however, these were no longer statistically significant after correction for multiple testing. Stratification by sex did not yield any significant associations. Similarly, associations with hearing loss or other tinnitus-related comorbidities such as stress, anxiety, depression, hyperacusis, temporomandibular joint disorders, and headache did not yield any significant associations. Analysis in the TwinsUK failed in replicating the top candidates. Meta-analysis of STOP and TwinsUK did not reveal any significant association. Using elastic net regularization, models exhibited poor predictive capacity tinnitus based on inflammatory markers [sensitivity = 0.52 (95% CI 0.47-0.57), specificity = 0.53 (0.48-0.58), positive predictive value = 0.52 (0.47-0.56), negative predictive values = 0.53 (0.49-0.58), and AUC = 0.53 (0.49-0.56)]. DISCUSSION: Our results did not identify significant associations of the selected inflammatory proteins with constant tinnitus. Future studies examining longitudinal relations among those with more severe tinnitus and using more recent expanded proteomics platforms and sampling of cerebrospinal fluid could increase the likelihood of identifying relevant molecular biomarkers.

Mitochondrial heteroplasmic shifts reveal a positive selection of breast cancer.

BACKGROUND: Breast cancer is, despite screening, not always detected early enough and is together with other tumor types known to shed genetic information in circulation. Unlike single-copy nuclear DNA, mitochondrial DNA (mtDNA) copies range from 100s to 10,000s per cell, thus providing a potentially alternative to identify potential missing cancer information in circulation at an early stage. METHODS: To characterize mitochondrial mutation landscapes in breast cancer, whole mtDNA sequencing and bioinformatics analyses were performed on 86 breast cancer biopsies and 50 available matched baseline cancer-free whole blood samples from the same individuals, selected from a cohort of middle-aged women in Sweden. To determine whether the mutations can be detected in blood plasma prior to cancer diagnosis, we further designed a nested case-control study (n = 663) and validated the shortlisted mutations using droplet digital PCR. RESULTS: We detected different mutation landscapes between biopsies and matched whole blood samples. Compared to whole blood samples, mtDNA from biopsies had higher heteroplasmic mutations in the D-loop region (P = 0.02), RNR2 (P = 0.005), COX1 (P = 0.037) and CYTB (P = 0.006). Furthermore, the germline mtDNA mutations had higher heteroplasmy level than the lost (P = 0.002) and de novo mutations (P = 0.04). The nonsynonymous to synonymous substitution ratio (dN/dS) was higher for the heteroplasmic mutations (P = 7.25 × 10-12) than that for the homoplasmic mutations, but the de novo (P = 0.06) and lost mutations (P = 0.03) had lower dN/dS than the germline mutations. Interestingly, we found that the critical regions for mitochondrial transcription: MT-HSP1 (odds ratio [OR]: 21.41), MT-TFH (OR: 7.70) and MT-TAS2 (OR: 3.62), had significantly higher heteroplasmic mutations than the rest of the D-loop sub-regions. Finally, we found that the presence of mt.16093T > C mutation increases 67% risk of developing breast cancer. CONCLUSIONS: Our findings show that mitochondrial genetic landscape changes during cancer pathogenesis and positive selection of mtDNA heteroplasmic mutations in breast cancer. Most importantly, the mitochondrial mutations identified in biopsies can be traced back in matched plasma samples and could potentially be used as early breast cancer diagnostic biomarkers.

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism.

Venous thromboembolism (VTE) is a common, multi-causal disease with potentially serious short- and long-term complications. In clinical practice, there is a need for improved plasma biomarker-based tools for VTE diagnosis and risk prediction. Here we show, using proteomics profiling to screen plasma from patients with suspected acute VTE, and several case-control studies for VTE, how Complement Factor H Related 5 protein (CFHR5), a regulator of the alternative pathway of complement activation, is a VTE-associated plasma biomarker. In plasma, higher CFHR5 levels are associated with increased thrombin generation potential and recombinant CFHR5 enhanced platelet activation in vitro. GWAS analysis of ~52,000 participants identifies six loci associated with CFHR5 plasma levels, but Mendelian randomization do not demonstrate causality between CFHR5 and VTE. Our results indicate an important role for the regulation of the alternative pathway of complement activation in VTE and that CFHR5 represents a potential diagnostic and/or risk predictive plasma biomarker.

Soluble CD14 and Osteoprotegerin Associate with Ankle-Brachial Index as a Measure of Arterial Stiffness in Patients with Mild-to-Moderate Chronic Kidney Disease in a Five-Year Prospective Study.

INTRODUCTION: Vascular lesions and arterial stiffness appear at early stages of chronic kidney disease (CKD) and follow an accelerated course with disease progression, contributing to high cardiovascular mortality. There are limited prospective data on mechanisms contributing to progression of arterial stiffness in mild-to-moderate CKD (stages 2-3). METHODS: We applied an affinity proteomics approach to identify candidates of circulating biomarkers with potential impact on vascular lesions in CKD and selected soluble cluster of differentiation 14 (sCD14), angiogenin (ANG), and osteoprotegerin (OPG) for further analysis. We studied their association with ankle-brachial index (ABI) and carotid intima-media thickness, as measures of arteriosclerosis and atherosclerosis, respectively, in 48 patients with CKD stages 2-3, who were prospectively followed and intensively treated for 5 years, and 44 healthy controls. RESULTS: Concentrations of sCD14 (p < 0.001), ANG (p < 0.001), and OPG (p < 0.05) were higher in patients with CKD 2-3 at baseline, and sCD14 (p < 0.001) and ANG (p < 0.001) remained elevated in CKD patients at follow-up. There were positive correlations between ABI and sCD14 levels (r = 0.36, p = 0.01) and between ABI and OPG (r = 0.31, p = 0.03) at 5 years. The changes in sCD14 during follow-up correlated to changes in ABI from baseline to 5 years (r = 0.41, p = 0.004). CONCLUSION: Elevated levels of circulating sCD14 and OPG in patients with CKD 2-3 were significantly associated with ABI, a measure of arterial stiffness. An increase in sCD14 over time in CKD 2-3 patients was associated with a corresponding increase in ABI. Further studies are needed to examine if early intensive multifactorial medication to align with international treatment targets may influence cardiovascular outcomes.

Characterization of the Mitochondrial Genetic Landscape in Abdominal Aortic Aneurysm.

Background Abdominal aortic aneurysm (AAA) is a vascular disease with a mortality rate of >80% if ruptured. Mitochondrial dysfunction has been previously implicated in AAA pathogenesis. In this study, we aimed to characterize the mitochondrial genetic landscape in AAA. Methods and Results Whole mitochondrial genome sequencing and bioinformatics analysis were performed in comorbidity matched 48 cases without AAA and 48 cases with AAA, objectively diagnosed, and selected from a cohort of 65-year-old men recruited for a screening program. We identified differential mutational landscapes in men with and without AAA, with errors in mitochondrial DNA replication or repair as potential sources. Heteroplasmic insertions and overall heteroplasmy of structural rearrangements were significantly elevated in AAA cases. Three heteroplasmic variants were associated with risk factors of AAA: leukocyte concentration, plasma glucose, and cholesterol levels, respectively. Interestingly, mutations were more prevalent in regulatory part of the mitochondria, the displacement loop region, in AAA as compared with controls (P value <0.05), especially in the conserved and critical mitochondrial extended termination-associated sequence region. Moreover, we report a novel 24 bp mitochondrial DNA duplication present exclusively in cases with AAA (4%) and 75% of the unmatched AAA biopsies. Finally, the haplogroup cluster JTU was overrepresented in AAA and significantly associated with a positive family history of AAA (odds ratio, 2.9 [95% CI, 1.1-8.1]). Conclusions This is the first study investigating the mitochondrial genome in AAA, where important genetic alterations and haplogroups associated with AAA and clinical risk factors were identified. Our findings have the potential to fill in gaps in the missing genetic information on AAA.

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials.

BACKGROUND: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. METHODS: In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. FINDINGS: 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04-0·12] or 0·9 mmol/mol lower reduction in HbA1c per serine, p=6·0 × 10-5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10-8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol  [SE 0·7] greater HbA1c reduction per methionine, p=5·2 × 10-6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6-11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA1c than the 9% of the population with the worse response. INTERPRETATION: This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists. FUNDING: Innovative Medicines Initiative and the Wellcome Trust.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Elevated circulating follistatin associates with an increased risk of type 2 diabetes.

The hepatokine follistatin is elevated in patients with type 2 diabetes (T2D) and promotes hyperglycemia in mice. Here we explore the relationship of plasma follistatin levels with incident T2D and mechanisms involved. Adjusted hazard ratio (HR) per standard deviation (SD) increase in follistatin levels for T2D is 1.24 (CI: 1.04-1.47, p < 0.05) during 19-year follow-up (n = 4060, Sweden); and 1.31 (CI: 1.09-1.58, p < 0.01) during 4-year follow-up (n = 883, Finland). High circulating follistatin associates with adipose tissue insulin resistance and non-alcoholic fatty liver disease (n = 210, Germany). In human adipocytes, follistatin dose-dependently increases free fatty acid release. In genome-wide association study (GWAS), variation in the glucokinase regulatory protein gene (GCKR) associates with plasma follistatin levels (n = 4239, Sweden; n = 885, UK, Italy and Sweden) and GCKR regulates follistatin secretion in hepatocytes in vitro. Our findings suggest that GCKR regulates follistatin secretion and that elevated circulating follistatin associates with an increased risk of T2D by inducing adipose tissue insulin resistance.

Identification of Endothelial Proteins in Plasma Associated With Cardiovascular Risk Factors.

OBJECTIVE: Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response. Approach and Results: We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (N=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles. CONCLUSIONS: EC proteins in plasma could reflect vascular health status.

Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2.

Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgG+IgM+ against several SARS-CoV-2 proteins, as well as 2.1% being IgG-IgM+ and 5.0% being IgG+IgM- for the virus' S protein. Subjects classified as IgG+ for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG+ for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.

Circulating proteins associated with allergy development in infants-an exploratory analysis.

BACKGROUND: Protein profiles that can predict allergy development in children are lacking and the ideal sampling age is unknown. By applying an exploratory proteomics approach in the prospective FARMFLORA birth cohort, we sought to identify previously unknown circulating proteins in early life that associate to protection or risk for development of allergy up to 8 years of age. METHODS: We analyzed plasma prepared from umbilical cord blood (n = 38) and blood collected at 1 month (n = 42), 4 months (n = 39), 18 months (n = 42), 36 months (n = 42) and 8 years (n = 44) of age. We profiled 230 proteins with a multiplexed assay and evaluated the global structure of the data with principal component analysis (PCA). Protein profiles informative to allergic disease at 18 months, 36 months and/or 8 years were evaluated using Lasso logistic regression and random forest. RESULTS: Two clusters emerged in the PCA analysis that separated samples obtained at birth and at 1 month of age from samples obtained later. Differences between the clusters were mostly driven by abundant plasma proteins. For the prediction of allergy, both Lasso logistic regression and random forest were most informative with samples collected at 1 month of age. A Lasso model with 27 proteins together with farm environment differentiated children who remained healthy from those developing allergy. This protein panel was primarily composed of antigen-presenting MHC class I molecules, interleukins and chemokines. CONCLUSION: Sampled at one month of age, circulating proteins that reflect processes of the immune system may predict the development of allergic disease later in childhood.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality.

Despite recognizing aging as a common risk factor of many human diseases, little is known about its molecular traits. To identify age-associated proteins circulating in human blood, we screened 156 individuals aged 50-92 using exploratory and multiplexed affinity proteomics assays. Profiling eight additional study sets (N = 3,987), performing antibody validation, and conducting a meta-analysis revealed a consistent age association (P = 6.61 × 10-6) for circulating histidine-rich glycoprotein (HRG). Sequence variants of HRG influenced how the protein was recognized in the immunoassays. Indeed, only the HRG profiles affected by rs9898 were associated with age and predicted the risk of mortality (HR = 1.25 per SD; 95% CI = 1.12-1.39; P = 6.45 × 10-5) during a follow-up period of 8.5 yr after blood sampling (IQR = 7.7-9.3 yr). Our affinity proteomics analysis found associations between the particular molecular traits of circulating HRG with age and all-cause mortality. The distinct profiles of this multipurpose protein could serve as an accessible and informative indicator of the physiological processes related to biological aging.