Associations of Proteomics With Hypertension and Systolic Blood Pressure: KORA S4/F4/FF4 and KORA Age1/Age2 Cohort Studies

BACKGROUND

Hypertension, a complex condition, is primarily defined based on blood pressure readings without involving its pathophysiological mechanisms. We aimed to identify biomarkers through a proteomic approach, thereby enhancing the future definition of hypertension with insights into its molecular mechanisms.

METHODS

The discovery analysis included 1560 participants, aged 55 to 74 years at baseline, from the KORA (Cooperative Health Research in the Region of Augsburg) S4/F4/FF4 cohort study, with 3332 observations over a median of 13.4 years of follow-up. Generalized estimating equations were used to estimate the associations of 233 plasma proteins with hypertension and systolic blood pressure (SBP). For validation, proteins significantly associated with hypertension or SBP in the discovery analysis were validated in the KORA Age1/Age2 cohort study (1024 participants, 1810 observations). A 2-sample Mendelian randomization analysis was conducted to infer causalities of validated proteins with SBP.

RESULTS

Discovery analysis identified 49 proteins associated with hypertension and 99 associated with SBP. Validation in the KORA Age1/Age2 study replicated 7 proteins associated with hypertension and 23 associated with SBP. Three proteins, NT-proBNP (N-terminal pro-B-type natriuretic peptide), KIM1 (kidney injury molecule 1), and OPG (osteoprotegerin), consistently showed positive associations with both outcomes. Five proteins demonstrated potential causal associations with SBP in Mendelian randomization analysis, including NT-proBNP and OPG.

CONCLUSIONS

We identified and validated 7 hypertension-associated and 23 SBP-associated proteins across 2 cohort studies. KIM1, NT-proBNP, and OPG demonstrated robust associations, and OPG was identified for the first time as associated with blood pressure. For NT-proBNP (protective) and OPG, causal associations with SBP were suggested.

CT-guided high dose rate brachytherapy can induce multiple systemic proteins of proliferation and angiogenesis predicting outcome in HCC

BACKGROUND AND PURPOSE

To determine the potential prognostic value of proliferation and angiogenesis plasma proteins following CT-guided high dose rate brachytherapy (HDR-BT) of hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

For this prospective study, HDR-BT (1 × 15 Gy) was administered to 24 HCC patients. Plasma was obtained and analyzed using an Olink proteomics Target-96 immuno-oncology-panel that included multiple markers of angiogenesis and proliferation. Fold-change (FC) ratios were calculated by comparing baseline and 48 h post HDR-BT paired samples. Patients were classified as responders (n = 12) if they had no local progression within 6 months or systemic progression within 2 years. Non-responders (n = 12) had recurrence within 6 months and/or tumor progression or extrahepatic disease within 2 years.

RESULTS

Proliferation marker EGF was significantly elevated in non-responders compared to responders (p = 0.0410) while FGF-2, HGF, and PlGF showed no significant differences. Angiogenesis markers Angiopoietin-1 and PDGF-B were likewise significantly elevated in non-responders compared to responders (p = 0.0171, p = 0.0462, respectively) while Angiopoietin-2, VEGF-A, and VEGFR-2 did not differ significantly. Kaplan-Meier analyses demonstrated significantly shorter time to systemic progression in patients with increased EGF and Angiopoietin-1 (p = 0.0185, both), but not in patients with one of the remaining proteins elevated (all p > 0.1). Pooled analysis for these 9 proteins showed significantly shorter time to systemic progression for FC ≥1.3 and ≥1.5 for at least 3 proteins elevated (p = 0.0415, p = 0.0193, respectively).

CONCLUSION

Increased plasma levels of EGF and Angiopoietin-1 after HDR-BT for HCC are associated with poor response and may therefore function as predictive biomarkers of outcome.

Addition of inflammation-related biomarkers to the CAIDE model for risk prediction of all-cause dementia, Alzheimer's disease and vascular dementia in a prospective study

BACKGROUND

It is of interest whether inflammatory biomarkers can improve dementia prediction models, such as the widely used Cardiovascular Risk Factors, Aging and Dementia (CAIDE) model.

METHODS

The Olink Target 96 Inflammation panel was assessed in a nested case-cohort design within a large, population-based German cohort study (n = 9940; age-range: 50-75 years). All study participants who developed dementia over 20 years of follow-up and had complete CAIDE variable data (n = 562, including 173 Alzheimer's disease (AD) and 199 vascular dementia (VD) cases) as well as n = 1,356 controls were selected for measurements. 69 inflammation-related biomarkers were eligible for use. LASSO logistic regression and bootstrapping were utilized to select relevant biomarkers and determine areas under the curve (AUCs).

RESULTS

The CAIDE model 2 (including Apolipoprotein E (APOE) ε4 carrier status) predicted all-cause dementia, AD, and VD better than CAIDE model 1 (without APOE ε4) with AUCs of 0.725, 0.752 and 0.707, respectively. Although 20, 7, and 4 inflammation-related biomarkers were selected by LASSO regression to improve CAIDE model 2, the AUCs did not increase markedly. CAIDE models 1 and 2 generally performed better in mid-life (50-64 years) than in late-life (65-75 years) sub-samples of our cohort, but again, inflammation-related biomarkers did not improve their predictive abilities.

CONCLUSIONS

Despite a lack of improvement in dementia risk prediction, the selected inflammation-related biomarkers were significantly associated with dementia outcomes and may serve as a starting point to further elucidate the pathogenesis of dementia.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study

BACKGROUND

Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D.

METHODS

The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI).

RESULTS

We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465).

CONCLUSIONS

This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

Age-related influence on DNA damage, proteomic inflammatory markers and oxidative stress in hospitalized COVID-19 patients compared to healthy controls

COVID-19 infections are accompanied by adverse changes in inflammatory pathways that are also partly influenced by increased oxidative stress and might result in elevated DNA damage. The aim of this case-control study was to examine whether COVID-19 patients show differences in oxidative stress-related markers, unconjugated bilirubin (UCB), an inflammation panel and DNA damage compared to healthy, age-and sex-matched controls. The Comet assay with and without the treatment of formamidopyrimidine DNA glycosylase (FPG) and H2O2 challenge was used to detect DNA damage in whole blood. qPCR was applied for gene expression, UCB was analyzed via HPLC, targeted proteomics were applied using Olink® inflammation panel and various oxidative stress as well as clinical biochemistry markers were analyzed in plasma. Hospitalized COVID-19 patients (n = 48) demonstrated higher serum levels of 55 inflammatory proteins (p < 0.001), including hs-C-reactive protein levels (p < 0.05), compared to healthy controls (n = 48). Interestingly, significantly increased age-related DNA damage (%-DNA in tail) after formamidopyrimidine DNA glycosylase (FPG) treatment was measured in younger (n = 24, average age 55.7 years; p < 0.05) but not in older COVID-19 patients (n = 24, average age 83.5 years; p > 0.05). Although various oxidative stress markers were not altered (e.g., FRAP, malondialdehyde, p > 0.05), a significant increased ratio of oxidized to reduced glutathione was detected in COVID-19 patients compared to healthy controls (p < 0.05). UCB levels were significantly lower in individuals with COVID-19, especially in younger COVID-19 patients (p < 0.05). These results suggest that COVID-19 infections exert effects on DNA damage related to age in hospitalized COVID-19 patients that might be driven by changes in inflammatory pathways but are not altered by oxidative stress parameters.

Severe hematotoxicity after CD19 CAR-T therapy is associated with suppressive immune dysregulation and limited CAR-T expansion

Prolonged cytopenias after chimeric antigen receptor (CAR) T cell therapy are a significant clinical problem and the underlying pathophysiology remains poorly understood. Here, we investigated how (CAR) T cell expansion dynamics and serum proteomics affect neutrophil recovery phenotypes after CD19-directed CAR T cell therapy. Survival favored patients with "intermittent" neutrophil recovery (e.g., recurrent neutrophil dips) compared to either "quick" or "aplastic" recovery. While intermittent patients displayed increased CAR T cell expansion, aplastic patients exhibited an unfavorable relationship between expansion and tumor burden. Proteomics of patient serum collected at baseline and in the first month after CAR-T therapy revealed higher markers of endothelial dysfunction, inflammatory cytokines, macrophage activation, and T cell suppression in the aplastic phenotype group. Prolonged neutrophil aplasia thus occurs in patients with systemic immune dysregulation at baseline with subsequently impaired CAR-T expansion and myeloid-related inflammatory changes. The association between neutrophil recovery and survival outcomes highlights critical interactions between host hematopoiesis and the immune state stimulated by CAR-T infusion.

Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study

AIMS/HYPOTHESIS

This study aimed to elucidate the aetiological role of plasma proteins in glucose metabolism and type 2 diabetes development.

METHODS

We measured 233 proteins at baseline in 1653 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 cohort study (median follow-up time: 13.5 years). We used logistic regression in the cross-sectional analysis (n=1300), and Cox regression accounting for interval-censored data in the longitudinal analysis (n=1143). We further applied two-level growth models to investigate associations with repeatedly measured traits (fasting glucose, 2 h glucose, fasting insulin, HOMA-B, HOMA-IR, HbA1c), and two-sample Mendelian randomisation analysis to investigate causal associations. Moreover, we built prediction models using priority-Lasso on top of Framingham-Offspring Risk Score components and evaluated the prediction accuracy through AUC.

RESULTS

We identified 14, 24 and four proteins associated with prevalent prediabetes (i.e. impaired glucose tolerance and/or impaired fasting glucose), prevalent newly diagnosed type 2 diabetes and incident type 2 diabetes, respectively (28 overlapping proteins). Of these, IL-17D, IL-18 receptor 1, carbonic anhydrase-5A, IL-1 receptor type 2 (IL-1RT2) and matrix extracellular phosphoglycoprotein were novel candidates. IGF binding protein 2 (IGFBP2), lipoprotein lipase (LPL) and paraoxonase 3 (PON3) were inversely associated while fibroblast growth factor 21 was positively associated with incident type 2 diabetes. LPL was longitudinally linked with change in glucose-related traits, while IGFBP2 and PON3 were linked with changes in both insulin- and glucose-related traits. Mendelian randomisation analysis suggested causal effects of LPL on type 2 diabetes and fasting insulin. The simultaneous addition of 12 priority-Lasso-selected biomarkers (IGFBP2, IL-18, IL-17D, complement component C1q receptor, V-set and immunoglobulin domain-containing protein 2, IL-1RT2, LPL, CUB domain-containing protein 1, vascular endothelial growth factor D, PON3, C-C motif chemokine 4 and tartrate-resistant acid phosphatase type 5) significantly improved the predictive performance (ΔAUC 0.0219; 95% CI 0.0052, 0.0624).

CONCLUSIONS/INTERPRETATION

We identified new candidates involved in the development of derangements in glucose metabolism and type 2 diabetes and confirmed previously reported proteins. Our findings underscore the importance of proteins in the pathogenesis of type 2 diabetes and the identified putative proteins can function as potential pharmacological targets for diabetes treatment and prevention.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

BACKGROUND

Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal.

METHODS

We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality.

RESULTS

In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline.

CONCLUSIONS

We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.

Identifying Early Infections in the Setting of CRS With Routine and Exploratory Serum Proteomics and the HT10 Score Following CD19 CAR-T for Relapsed/Refractory B-NHL

Early fever after chimeric antigen receptor T-cell (CAR-T) therapy can reflect both an infection or cytokine release syndrome (CRS). Identifying early infections in the setting of CRS and neutropenia represents an unresolved clinical challenge. In this retrospective observational analysis, early fever events (day 0-30) were characterized as infection versus CRS in 62 patients treated with standard-of-care CD19.CAR-T for relapsed/refractory B-cell non-Hodgkin lymphoma. Routine serum inflammatory markers (C-reactive protein [CRP], interleukin-6 [IL-6], procalcitonin [PCT]) were recorded daily. Exploratory plasma proteomics were performed longitudinally in 52 patients using a multiplex proximity extension assay (Olink proteomics). Compared with the CRS^only cohort, we noted increased event-day IL-6 (median 2243 versus 64 pg/mL, P = 0.03) and particularly high PCT levels (median 1.6 versus 0.3 µg/L, P < 0.0001) in the patients that developed severe infections. For PCT, an optimal discriminatory threshold of 1.5 µg/L was established (area under the receiver operating characteristic curve [AUC_ROC] = 0.78). Next, we incorporated day-of-fever PCT levels with the patient-individual CAR-HEMATOTOX score. In a multicenter validation cohort (n = 125), we confirmed the discriminatory capacity of this so-called HT10 score for early infections at first fever (AUC_ROC = 0.87, P < 0.0001, sens. 86%, spec. 86%). Additionally, Olink proteomics revealed pronounced immune dysregulation and endothelial dysfunction in patients with severe infections as evidenced by an increased ANGPT2/1 ratio and an altered CD40/CD40L-axis. In conclusion, the high discriminatory capacity of the HT10 score for infections highlights the advantage of dynamic risk assessment and supports the incorporation of PCT into routine inflammatory panels. Candidate markers from Olink proteomics may further refine risk-stratification. If validated prospectively, the score will enable risk-adapted decisions on antibiotic use.

Non-Oncogene Addiction of KRAS-Mutant Cancers to IL-1β via Versican and Mononuclear IKKβ

Kirsten rat sarcoma virus (KRAS)-mutant cancers are frequent, metastatic, lethal, and largely undruggable. While interleukin (IL)-1β and nuclear factor (NF)-κB inhibition hold promise against cancer, untargeted treatments are not effective. Here, we show that human KRAS-mutant cancers are addicted to IL-1β via inflammatory versican signaling to macrophage inhibitor of NF-κB kinase (IKK) β. Human pan-cancer and experimental NF-κB reporter, transcriptome, and proteome screens reveal that KRAS-mutant tumors trigger macrophage IKKβ activation and IL-1β release via secretory versican. Tumor-specific versican silencing and macrophage-restricted IKKβ deletion prevents myeloid NF-κB activation and metastasis. Versican and IKKβ are mutually addicted and/or overexpressed in human cancers and possess diagnostic and prognostic power. Non-oncogene KRAS/IL-1β addiction is abolished by IL-1β and TLR1/2 inhibition, indicating cardinal and actionable roles for versican and IKKβ in metastasis.

The Acute Cytokine Response to 30-Minute Exercise Bouts Before and After 8-Week Endurance Training in Individuals With Obesity

CONTEXT

One acute bout of exercise leads to a rapid increase in the systemic cytokine concentration. Regular exercise might alter the cytokine response, in particular in beforehand untrained and obese individuals.

OBJECTIVE

Using a proximity extension assay, we studied the effects of acute exercise as well as endurance training on a panel of 92 cytokines related to inflammation.

METHODS

A total of 22 individuals (30 ± 9 years; peak oxygen uptake [VO2peak] 25.2 ± 4.2 mL/[kg × min]; body mass index [BMI] 31.7 ± 4.4) participated in an 8-week endurance exercise intervention. Blood samples were collected before and immediately after 30 minutes' ergometer exercise at 80% VO2peak.

RESULTS

Before and after the training intervention, 40 and 37 cytokines, respectively, were acutely increased more than 1.2-fold (Benjamini-Hochberg [BH]-adjusted P < .05). The exercise intervention did not change the acute increase in cytokines nor the resting cytokine levels, whereas fitness was improved and adiposity reduced. The increase in fitness led to a slight increase in power output when exercising at the same heart rate, which might explain the comparable increase in cytokines before and after the intervention. The largest acute increase was found for OSM, TGFA, CXCL1 and 5, and TNFSF14 (≥ 1.9-fold, BH-adjusted P < .001). The transcript levels of these proteins in whole blood were also elevated, particularly in the trained state. Only the acute increase in IL6 (1.3-fold) was related to the increase in lactate, confirming the lactate-driven secretion of IL6.

CONCLUSION

Our comprehensive proteomics approach detected several underexplored serum exerkines with up to now less understood function in the adaptation to exercise.

Serum neurofilament light chain: a novel biomarker for early diabetic sensorimotor polyneuropathy

AIMS/HYPOTHESIS

No established blood-based biomarker exists to monitor diabetic sensorimotor polyneuropathy (DSPN) and evaluate treatment response. The neurofilament light chain (NFL), a blood biomarker of neuroaxonal damage in several neurodegenerative diseases, represents a potential biomarker for DSPN. We hypothesised that higher serum NFL levels are associated with prevalent DSPN and nerve dysfunction in individuals recently diagnosed with diabetes.

METHODS

This cross-sectional study included 423 adults with type 1 and type 2 diabetes and known diabetes duration of less than 1 year from the prospective observational German Diabetes Study cohort. NFL was measured in serum samples of fasting participants in a multiplex approach using proximity extension assay technology. DSPN was assessed by neurological examination, nerve conduction studies and quantitative sensory testing. Associations of serum NFL with DSPN (defined according to the Toronto Consensus criteria) were estimated using Poisson regression, while multivariable linear and quantile regression models were used to assess associations with nerve function measures. In exploratory analyses, other biomarkers in the multiplex panel were also analysed similarly to NFL.

RESULTS

DSPN was found in 16% of the study sample. Serum NFL levels increased with age. After adjustment for age, sex, waist circumference, height, HbA_1c, known diabetes duration, diabetes type, cholesterol, eGFR, hypertension, CVD, use of lipid-lowering drugs and use of non-steroidal anti-inflammatory drugs, higher serum NFL levels were associated with DSPN (RR [95% CI] per 1-normalised protein expression increase, 1.92 [1.50, 2.45], p<0.0001), slower motor (all p<0.0001) and sensory (all p≤0.03) nerve conduction velocities, lower sural sensory nerve action potential (p=0.0004) and higher thermal detection threshold to warm stimuli (p=0.023 and p=0.004 for hand and foot, respectively). There was no evidence for associations between other neurological biomarkers and DSPN or nerve function measures.

CONCLUSIONS/INTERPRETATION

Our findings in individuals recently diagnosed with diabetes provide new evidence associating higher serum NFL levels with DSPN and peripheral nerve dysfunction. The present study advocates NFL as a potential biomarker for DSPN.

Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients

SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Previous studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited. We addressed the gap of existing knowledge with regard to a differentiated understanding of disease dynamics in SARS-CoV-2 infection while specifically considering disease stage and severity. We biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of the individualized disease phase assignment, proteome analysis revealed a severity dependent general type-2-centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response characterizing severe disease was successfully validated in a second cohort. Together with the regulation of proteins related to SARS-CoV-2-specific symptoms identified by proteome screening, we not only confirmed results from previous studies but provide novel information for biomarker and therapy development.

Proteomics biomarker discovery for individualized prevention of familial pancreatic cancer using statistical learning

BACKGROUND

The low five-year survival rate of pancreatic ductal adenocarcinoma (PDAC) and the low diagnostic rate of early-stage PDAC via imaging highlight the need to discover novel biomarkers and improve the current screening procedures for early diagnosis. Familial pancreatic cancer (FPC) describes the cases of PDAC that are present in two or more individuals within a circle of first-degree relatives. Using innovative high-throughput proteomics, we were able to quantify the protein profiles of individuals at risk from FPC families in different potential pre-cancer stages. However, the high-dimensional proteomics data structure challenges the use of traditional statistical analysis tools. Hence, we applied advanced statistical learning methods to enhance the analysis and improve the results' interpretability.

METHODS

We applied model-based gradient boosting and adaptive lasso to deal with the small, unbalanced study design via simultaneous variable selection and model fitting. In addition, we used stability selection to identify a stable subset of selected biomarkers and, as a result, obtain even more interpretable results. In each step, we compared the performance of the different analytical pipelines and validated our approaches via simulation scenarios.

RESULTS

In the simulation study, model-based gradient boosting showed a more accurate prediction performance in the small, unbalanced, and high-dimensional datasets than adaptive lasso and could identify more relevant variables. Furthermore, using model-based gradient boosting, we discovered a subset of promising serum biomarkers that may potentially improve the current screening procedure of FPC.

CONCLUSION

Advanced statistical learning methods helped us overcome the shortcomings of an unbalanced study design in a valuable clinical dataset. The discovered serum biomarkers provide us with a clear direction for further investigations and more precise clinical hypotheses regarding the development of FPC and optimal strategies for its early detection.

Relationship between impaired BMP signalling and clinical risk factors at early-stage vascular injury in the preterm infant

INTRODUCTION

Chronic lung disease, that is, bronchopulmonary dysplasia (BPD) is the most common complication in preterm infants and develops as a consequence of the misguided formation of the gas-exchange area undergoing prenatal and postnatal injury. Subsequent vascular disease and its progression into pulmonary arterial hypertension critically determines long-term outcome in the BPD infant but lacks identification of early, disease-defining changes.

METHODS

We link impaired bone morphogenetic protein (BMP) signalling to the earliest onset of vascular pathology in the human preterm lung and delineate the specific effects of the most prevalent prenatal and postnatal clinical risk factors for lung injury mimicking clinically relevant conditions in a multilayered animal model using wild-type and transgenic neonatal mice.

RESULTS

We demonstrate (1) the significant reduction in BMP receptor 2 (BMPR2) expression at the onset of vascular pathology in the lung of preterm infants, later mirrored by reduced plasma BMP protein levels in infants with developing BPD, (2) the rapid impairment (and persistent change) of BMPR2 signalling on postnatal exposure to hyperoxia and mechanical ventilation, aggravated by prenatal cigarette smoke in a preclinical mouse model and (3) a link to defective alveolar septation and matrix remodelling through platelet derived growth factor-receptor alpha deficiency. In a treatment approach, we partially reversed vascular pathology by BMPR2-targeted treatment with FK506 in vitro and in vivo.

CONCLUSION

We identified impaired BMP signalling as a hallmark of early vascular disease in the injured neonatal lung while outlining its promising potential as a future biomarker or therapeutic target in this growing, high-risk patient population.

Association of the inflammation-related proteome with dementia development at older age: results from a large, prospective, population-based cohort study

Background

Chronic inflammation is a central feature of several forms of dementia. However, few details on the associations of blood-based inflammation-related proteins with dementia incidence have been explored yet.

Methods

The Olink Target 96 Inflammation panel was measured in baseline serum samples (collected 07/2000–06/2002) of 1782 older adults from a German, population-based cohort study in a case-cohort design. Logistic regression models were used to assess the associations of biomarkers with all-cause dementia, Alzheimer’s disease, and vascular dementia incidence.

Results

During 17 years of follow-up, 504 participants were diagnosed with dementia, including 163 Alzheimer’s disease and 195 vascular dementia cases. After correction for multiple testing, 58 out of 72 tested (80.6%) biomarkers were statistically significantly associated with all-cause dementia, 22 with Alzheimer’s disease, and 33 with vascular dementia incidence. We identified four biomarker clusters, among which the strongest representatives, CX3CL1, EN-RAGE, LAP TGF-beta-1, and VEGF-A, were significantly associated with dementia endpoints independently from other inflammation-related proteins. CX3CL1 (odds ratio [95% confidence interval] per 1 standard deviation increase: 1.41 [1.24–1.60]) and EN-RAGE (1.41 [1.25–1.60]) were associated with all-cause dementia incidence, EN-RAGE (1.51 [1.25–1.83]) and LAP TGF-beta-1 (1.46 [1.21–1.76]) with Alzheimer’s disease incidence, and VEGF-A (1.43 [1.20–1.70]) with vascular dementia incidence. All named associations were stronger among APOE ε4-negative subjects.

Conclusion

With this large, population-based cohort study, we show for the first time that the majority of inflammation-related proteins measured in blood samples are associated with total dementia incidence. Future studies should concentrate not only on single biomarkers but also on the complex relationships in biomarker clusters.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01063-y.

A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes

Background

Diabetes in childhood and adolescence includes autoimmune and non-autoimmune forms with heterogeneity in clinical and biochemical presentations. An unresolved question is whether there are subtypes, endotypes, or theratypes within these forms of diabetes.

Methods

The multivariable classification and regression tree (CART) analysis method was used to identify subgroups of diabetes with differing residual C-peptide levels in patients with newly diagnosed diabetes before 20 years of age (n=1192). The robustness of the model was assessed in a confirmation and prognosis cohort (n=2722).

Findings

The analysis selected age, haemoglobin A1c (HbA1c), and body mass index (BMI) as split parameters that classified patients into seven islet autoantibody-positive and three autoantibody-negative groups. There were substantial differences in genetics, inflammatory markers, diabetes family history, lipids, 25-OH-Vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity among the groups, and the method stratified patients with potentially different pathogeneses and prognoses. Interferon-ɣ and/or tumour necrosis factor inflammatory signatures were enriched in the youngest islet autoantibody-positive groups and in patients with the lowest C-peptide values, while higher BMI and type 2 diabetes characteristics were found in older patients. The prognostic relevance was demonstrated by persistent differences in HbA1c at 7 years median follow-up.

Interpretation

This multivariable analysis revealed subgroups of young patients with diabetes that have potential pathogenetic and therapeutic relevance.

Funding

The work was supported by funds from the German Federal Ministry of Education and Research (01KX1818; FKZ 01GI0805; DZD e.V.), the Innovative Medicine Initiative 2 Joint Undertaking INNODIA (grant agreement No. 115797), the German Robert Koch Institute, and the German Diabetes Association.

Proteomics of the phase angle: Results from the population-based KORA S4 study

BACKGROUND & AIMS

The phase angle (PhA) measured with bioelectrical impedance analysis is considered to reflect the interrelated components body cell mass and fluid distribution based on technical and physical aspects of the PhA measurement. However, the biomedical meaning of the PhA remains vague. Previous studies mainly assessed associations of the PhA with numerous diseases and health outcomes, but few connected protein markers to the PhA. To broaden our understanding of the biomedical background of the PhA, we aimed to explore a proteomics profile associated with the PhA and related biological factors.

METHODS

The study sample encompassed 1484 participants (725 women and 759 men) aged 55-74 years from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 study. Proteomics measurements were performed with a proximity extension assay. We employed boosting with stability selection to establish a set of markers that was strongly associated with the PhA from a group of 233 plasma protein markers. We integrated the selected protein markers into a network and enrichment analysis to identify gene ontology (GO) terms significantly overrepresented for the selected PhA protein markers.

RESULTS

Boosting with stability selection identified seven protein markers that were strongly and independently associated with the PhA: N-terminal prohormone brain natriuretic peptide (NT-proBNP), insulin-like growth factor-binding protein 2 (IGFBP2), adrenomedullin (ADM), myoglobin (MB), matrix metalloproteinase-9 (MMP9), protein-glutamine gamma-glutamyltransferase 2 (TGM2), and fractalkine (CX3CL1) [beta coefficient per 1 standard deviation increase in normalized protein expression values on a log 2 scale (95% confidence interval): -0.12 (-0.15, -0.08), -0.13 (-0.17, -0.09), -0.14 (-0.18, -0.10), 0.10 (0.07, 0.14), 0.07 (0.04, 0.10), 0.08 (0.05, 0.11), -0.06 (-0.10, -0.03), respectively]. According to the enrichment analysis, this protein profile was significantly overrepresented in the following top five GO terms: positive regulation of cell population proliferation (p-value: 1.32E-04), extracellular space (p-value: 1.34E-04), anatomical structure formation involved in morphogenesis (p-value: 2.92E-04), regulation of multicellular organismal development (p-value: 5.72E-04), and metal ion homeostasis (p-value: 8.86E-04).

CONCLUSION

Implementing a proteomics approach, we identified six new protein markers strongly associated with the PhA and confirmed that NT-proBNP is a key PhA marker. The main biological processes that were related to this PhA's protein profile are involved in regulating the amount and growth of cells, reinforcing, from a biomedical perspective, the current technical-based consensus of the PhA to reflect body cell mass.

Genetically regulated gene expression and proteins revealed discordant effects

Background

Although gene-expression (GE) and protein levels are typically strongly genetically regulated, their correlation is known to be low. Here we investigate this phenomenon by focusing on the genetic background of this correlation in order to understand the similarities and differences in the genetic regulation of these omics layers.

Methods and results

We performed locus-wide association studies of 92 protein levels measured in whole blood for 2,014 samples of European ancestry and found that 66 are genetically regulated. Three female- and one male-specific effects were detected. We estimated the genetically regulated GE for all significant genes in 49 GTEx v8 tissues. A total of 7 proteins showed negative correlations with their respective GE across multiple tissues. Finally, we tested for causal links of GE on protein expression via Mendelian Randomization, and confirmed a negative causal effect of GE on protein level for five of these genes in a total of 63 gene-tissue pairs: BLMH, CASP3, CXCL16, IL6R, and SFTPD. For IL6R, we replicated the negative causal effect on coronary-artery disease (CAD), while its GE was positively linked to CAD.

Conclusion

While total GE and protein levels are only weakly correlated, we found high correlations between their genetically regulated components across multiple tissues. Of note, strong negative causal effects of tissue-specific GE on five protein levels were detected. Causal network analyses revealed that GE effects on CAD risks was in general mediated by protein levels.

Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer

BACKGROUND

CA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer.

METHODS

In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer.

RESULTS

Nine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9-18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone.

CONCLUSION

Using pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0-9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.

Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study

BACKGROUND

The coexistence of low muscle mass and high fat mass, two interrelated conditions strongly associated with declining health status, has been characterized by only a few protein biomarkers. High-throughput proteomics enable concurrent measurement of numerous proteins, facilitating the discovery of potentially new biomarkers.

METHODS

Data derived from the prospective population-based Cooperative Health Research in the Region of Augsburg S4/FF4 cohort study (median follow-up time: 13.5 years) included 1478 participants (756 men and 722 women) aged 55-74 years in the cross-sectional and 608 participants (315 men and 293 women) in the longitudinal analysis. Appendicular skeletal muscle mass (ASMM) and body fat mass index (BFMI) were determined through bioelectrical impedance analysis at baseline and follow-up. At baseline, 233 plasma proteins were measured using proximity extension assay. We implemented boosting with stability selection to enable false positives-controlled variable selection to identify new protein biomarkers of low muscle mass, high fat mass, and their combination. We evaluated prediction models developed based on group least absolute shrinkage and selection operator (lasso) with 100× bootstrapping by cross-validated area under the curve (AUC) to investigate if proteins increase the prediction accuracy on top of classical risk factors.

RESULTS

In the cross-sectional analysis, we identified kallikrein-6, C-C motif chemokine 28 (CCL28), and tissue factor pathway inhibitor as previously unknown biomarkers for muscle mass [association with low ASMM: odds ratio (OR) per 1-SD increase in log2 normalized protein expression values (95% confidence interval (CI)): 1.63 (1.37-1.95), 1.31 (1.14-1.51), 1.24 (1.06-1.45), respectively] and serine protease 27 for fat mass [association with high BFMI: OR (95% CI): 0.73 (0.61-0.86)]. CCL28 and metalloproteinase inhibitor 4 (TIMP4) constituted new biomarkers for the combination of low muscle and high fat mass [association with low ASMM combined with high BFMI: OR (95% CI): 1.32 (1.08-1.61), 1.28 (1.03-1.59), respectively]. Including protein biomarkers selected in ≥90% of group lasso bootstrap iterations on top of classical risk factors improved the performance of models predicting low ASMM, high BFMI, and their combination [delta AUC (95% CI): 0.16 (0.13-0.20), 0.22 (0.18-0.25), 0.12 (0.08-0.17), respectively]. In the longitudinal analysis, N-terminal prohormone brain natriuretic peptide (NT-proBNP) was the only protein selected for loss in ASMM and loss in ASMM combined with gain in BFMI over 14 years [OR (95% CI): 1.40 (1.10-1.77), 1.60 (1.15-2.24), respectively].

CONCLUSIONS

Proteomic profiling revealed CCL28 and TIMP4 as new biomarkers of low muscle mass combined with high fat mass and NT-proBNP as a key biomarker of loss in muscle mass combined with gain in fat mass. Proteomics enable us to accelerate biomarker discoveries in muscle research.

Plasma Proteomics of Renal Function: A Transethnic Meta-Analysis and Mendelian Randomization Study

BACKGROUND

Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

METHODS

A cross-sectional study of 993 plasma proteins among 2882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified transethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR.

RESULTS

In total, 57 plasma proteins were associated with eGFR, including one novel protein. Of these, 23 were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

CONCLUSIONS

In a discovery-replication setting, we identified 57 proteins transethnically associated with eGFR. The revealed causal relationships are an important stepping stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

High glucose treatment promotes extracellular matrix proteome remodeling in Mller glial cells

Background

The underlying pathomechanisms in diabetic retinopathy (DR) remain incompletely understood. The aim of this study was to add to the current knowledge about the particular role of retinal Mller glial cells (RMG) in the initial processes of DR.

Methods

Applying a quantitative proteomic workflow, we investigated changes of primary porcine RMG under short term high glucose treatment as well as glycolysis inhibition treatment.

Results

We revealed significant changes in RMG proteome primarily in proteins building the extracellular matrix (ECM) indicating fundamental remodeling processes of ECM as novel rapid response to high glucose treatment. Among others, Osteopontin (SPP1) as well as its interacting integrins were significantly downregulated and organotypic retinal explant culture confirmed the selective loss of SPP1 in RMG upon treatment. Since SPP1 in the retina has been described neuroprotective for photoreceptors and functions against experimentally induced cell swelling, its rapid loss under diabetic conditions may point to a direct involvement of RMG to the early neurodegenerative processes driving DR. Data are available via ProteomeXchange with identifier PXD015879.

Multiplatform Approach for Plasma Proteomics: Complementarity of Olink Proximity Extension Assay Technology to Mass Spectrometry-Based Protein Profiling

The plasma proteome is the ultimate target for biomarker discovery. It stores an endless amount of information on the pathophysiological status of a living organism, which is, however, still difficult to comprehensively access. The high complexity of the plasma proteome can be addressed by either a system-wide and unbiased tool such as mass spectrometry (LC-MS/MS) or a highly sensitive targeted immunoassay such as the proximity extension assay (PEA). To address relevant differences and important shared characteristics, we tested the performance of LC-MS/MS in the data-dependent and data-independent acquisition modes and Olink PEA to measure circulating plasma proteins in 173 human plasma samples from a Southern German population-based cohort. We demonstrated the measurement of more than 300 proteins with both LC-MS/MS approaches applied, mainly including high-abundance plasma proteins. By the use of the PEA technology, we measured 728 plasma proteins, covering a broad dynamic range with high sensitivity down to pg/mL concentrations. Then, we quantified 35 overlapping proteins with all three analytical platforms, verifying the reproducibility of data distributions, measurement correlation, and gender-based differential expression. Our work highlights the limitations and the advantages of both targeted and untargeted approaches and proves their complementary strengths. We demonstrated a significant gain in proteome coverage depth and subsequent biological insight by a combination of platforms-a promising approach for future biomarker and mechanistic studies.

Inherited diseases caused by mutations in cathepsin protease genes

Lysosomal cathepsins are proteolytic enzymes increasingly recognized as prognostic markers and potential therapeutic targets in a variety of diseases. In those conditions, the cathepsins are mostly overexpressed, thereby driving the respective pathogenic processes. Although less known, there are also diseases with a genetic deficiency of cathepsins. In fact, nowadays 6 of the 15 human proteases called 'cathepsins' have been linked to inherited syndromes. However, only three of these syndromes are typical lysosomal storage diseases, while the others are apparently caused by defective cleavage of specific protein substrates. Here, we will provide an introduction on lysosomal cathepsins, followed by a brief description of the clinical symptoms of the various genetic diseases. For each disease, we focus on the known mutations of which many have been only recently identified by modern genome sequencing approaches. We further discuss the effect of the respective mutation on protease structure and activity, the resulting pathogenesis, and possible therapeutic strategies.

Proteomic Profiling of Cardiomyocyte-Specific Cathepsin A Overexpression Links Cathepsin A to the Oxidative Stress Response

Cathepsin A (CTSA) is a lysosomal carboxypeptidase present at the cell surface and secreted outside the cell. Additionally, CTSA binds to β-galactosidase and neuraminidase 1 to protect them from degradation. CTSA has gained attention as a drug target for the treatment of cardiac hypertrophy and heart failure. Here, we investigated the impact of CTSA on the murine cardiac proteome in a mouse model of cardiomyocyte-specific human CTSA overexpression using liquid chromatography-tandem mass spectrometry in conjunction with an isotopic dimethyl labeling strategy. We identified up to 2000 proteins in each of three biological replicates. Statistical analysis by linear models for microarray data (limma) found >300 significantly affected proteins (moderated p-value ≤0.01), thus establishing CTSA as a key modulator of the cardiac proteome. CTSA strongly impaired the balance of the proteolytic system by upregulating several proteases such as cathepsin B, cathepsin D, and cathepsin Z while down-regulating numerous protease inhibitors. Moreover, cardiomyocyte-specific human CTSA overexpression strongly reduced the levels of numerous antioxidative stress proteins, i.e., peroxiredoxins and protein deglycase DJ-1. In vitro, using cultured rat cardiomyocytes, ectopic overexpression of CTSA resulted in accumulation of reactive oxygen species. Collectively, our proteomic and functional data strengthen an association of CTSA with the cellular oxidative stress response.

Comprehensive Proteomic Analysis of Nitrogen-Starved Mycobacterium smegmatis Δpup Reveals the Impact of Pupylation on Nitrogen Stress Response

Pupylation is a bacterial ubiquitin-like protein modification pathway, which results in the attachment of the small protein Pup to specific lysine residues of cellular targets. Pup was shown to serve as a degradation signal, directing proteins toward the bacterial proteasome for turnover. Recently, it was hypothesized that pupylation and proteasomal protein degradation support the survival of Mycobacterium smegmatis (Msm) during nitrogen starvation by supplying recycled amino acids. In the present study we generated a Pup deletion strain to investigate the influence of pupylation on Msm proteome in the absence of nitrogen sources. Quantitative proteomic analyses revealed a relatively low impact of Pup on MsmΔpup proteome immediately after exposure to growth medium lacking nitrogen. Less than 5.4% of the proteins displayed altered cellular levels when compared to Msm wild type. In contrast, post 24 h of nitrogen starvation 501 proteins (41% of the total quantified proteome) of Msm pup deletion strain showed significant changes in abundance. Noteworthy, important players involved in nitrogen assimilation were significantly affected in MsmΔpup. Furthermore, we quantified pupylated proteins of nitrogen-starved Msm to gain more detailed insights in the role of pupylation in surviving and overcoming the lack of nitrogen.

Cathepsin A inhibition attenuates myocardial infarction-induced heart failure on the functional and proteomic levels

Background

Myocardial infarction (MI) is a major cause of heart failure. The carboxypeptidase cathepsin A is a novel target in the treatment of cardiac failure. We aim to show that recently developed inhibitors of the protease cathepsin A attenuate post-MI heart failure.

Methods

Mice were subjected to permanent left anterior descending artery (LAD) ligation or sham operation. 24 h post–surgery, LAD-ligated animals were treated with daily doses of the cathepsin A inhibitor SAR1 or placebo. After 4 weeks, the three groups (sham, MI-placebo, MI-SAR1) were evaluated.

Results

Compared to sham-operated animals, placebo-treated mice showed significantly impaired cardiac function and increased plasma BNP levels. Cathepsin A inhibition prevented the increase of plasma BNP levels and displayed a trend towards improved cardiac functionality. Proteomic profiling was performed for the three groups (sham, MI-placebo, MI-SAR1). More than 100 proteins were significantly altered in placebo-treated LAD ligation compared to the sham operation, including known markers of cardiac failure as well as extracellular/matricellular proteins. This ensemble constitutes a proteome fingerprint of myocardial infarction induced by LAD ligation in mice. Cathepsin A inhibitor treatment normalized the marked increase of the muscle stress marker CA3 as well as of Igγ 2b and fatty acid synthase. For numerous further proteins, cathepsin A inhibition partially dampened the LAD ligation-induced proteome alterations.

Conclusions

Our proteomic and functional data suggest that cathepsin A inhibition has cardioprotective properties and support a beneficial effect of cathepsin A inhibition in the treatment of heart failure after myocardial infarction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0907-8) contains supplementary material, which is available to authorized users.

The emerging role of the peptidome in biomarker discovery and degradome profiling

The peptidome represents the array of endogenous peptides that are present in both the intracellular and extracellular space of the body. Peptides are constantly generated in vivo by active synthesis, and by proteolytic processing of larger precursor proteins, often yielding protein fragments that mediate a variety of physiological functions. Given that aberrant proteolysis is a hallmark of various pathological diseases, many studies have now turned to the peptidome. Differential regulation of endogenous peptides may play a role in many pathological conditions. Mass spectrometry (MS) -based investigation of peptides in a system-wide manner is currently facilitating the identification of potential biomarkers. Furthermore, peptidomic approaches have provided major contributions to the identification of protease-substrate relationships; representing one of the major challenges in understanding and therapeutically exploiting protease function in health and disease. As such, degradomic studies looking for cleavage products via peptidomics in particular, have warranted a significant research interest in recent years. Given that substantial studies are accumulating in the field of peptidomics, this review highlights recent advances of MS-based peptidomic strategies in facilitating the identification of potential peptides as novel clinical markers and protease-substrate profiling.

Carboxyterminal protein processing in health and disease: key actors and emerging technologies

Carboxypeptidases are important mediators of cellular behavior. Through C-terminal truncations, they alter protein functionality and participate in proteome turnover. Similarly, carboxypeptidases shape the human peptidome by targeting neuroendocrine and vasoactive peptides, thereby regulating signaling pathways in the nervous and cardiovascular systems as well as in embryonic development. Carboxypeptidases are widely connected to various pathological processes such as carcinogenesis and neurodegenerative and cardiovascular diseases. The repertoire of carboxypeptidase in vivo substrates still remains poorly defined, largely due to the lack of suitable experimental approaches. Understanding the precise role of carboxypeptidases is pivotal in the future development of diagnostic/prognostic markers in such diseases. To date, very little attention has been paid to the implication of carboxypeptidases in shaping the proteome as well as the peptidome. This review focuses on the patho-physiological function of carboxypeptidases and highlights the approaches by which proteomics-based technologies can be applied to characterize carboxypeptidases and to quantify the differential regulation of proteins by carboxypeptidases in a proteome-wide manner.

BCG Δzmp1 vaccine induces enhanced antigen specific immune responses in cattle

Mycobacterium bovis (M. bovis) causes major economy and public health problem in numerous countries. In Great Britain, despite the use of a test-and-slaughter strategy, the incidence of bovine tuberculosis (bTB) in cattle has steadily risen in recent years. One strategy being considered to reduce the burden of bTB in cattle is the development of an efficient vaccine. The only current potentially available vaccine against tuberculosis, live attenuated M. bovis bacille Calmette-Guérin (BCG), has demonstrated variable efficacy in both humans and cattle and the development of improved vaccination strategies for cattle is a research priority. In this study we assessed the immunogenicity in cattle of two recombinant BCG strains, namely BCG Pasteur Δzmp1::aph and BCG Danish Δzmp1. By applying a recently defined predictive immune-correlate of protection (T cell memory responses measured by cultured ELISPOT), we have compared these two recombinant BCG with wild-type BCG Danish SSI. Our results demonstrated that both strains induced superior T cell memory responses compared to wild-type BCG. These data provide support for the prioritisation of testing BCG Danish Δzmp1 in vaccination/M. bovis challenge studies to determine its protective efficacy.

Functional characterization of the Mycobacterium tuberculosis zinc metallopeptidase Zmp1 and identification of potential substrates

Zinc metallopeptidases of bacterial pathogens are widely distributed virulence factors and represent promising pharmacological targets. In this work, we have characterized Zmp1, a zinc metallopeptidase identified as a virulence factor of Mycobacterium tuberculosis and belonging to the neprilysin (NEP; M13) family, whose X-ray structure has been recently solved. Interestingly, this enzyme shows an optimum activity toward a fluorogenic substrate at moderately acidic pH values (i.e., 6.3), which corresponds to those reported for the Mtb phagosome where this enzyme should exert its pathological activity. Substrate specificity of Zmp1 was investigated by screening a peptide library. Several sequences derived from biologically relevant proteins were identified as possible substrates, including the neuropeptides bradykinin, neurotensin, and neuropeptide FF. Further, subsequences of other small bioactive peptides were found among most frequently cleaved sites, e.g., apelin-13 and substance P. We determined the specific cleavage site within neuropeptides by mass spectrometry, observing that hydrophobic amino acids, mainly phenylalanine and isoleucine, are overrepresented at position P1′. In addition, the enzymatic mechanism of Zmp1 toward these neuropeptides has been characterized, displaying some differences with respect to the synthetic fluorogenic substrate and indicating that the enzyme adapts its enzymatic action to different substrates.

Crystal structure of Mycobacterium tuberculosis zinc-dependent metalloprotease-1 (Zmp1), a metalloprotease involved in pathogenicity

Mycobacterium tuberculosis, the causative agent of tuberculosis, parasitizes host macrophages. The resistance of the tubercle bacilli to the macrophage hostile environment relates to their ability to impair phagosome maturation and its fusion with the lysosome, thus preventing the formation of the phago-lysosome and eventually arresting the process of phagocytosis. The M. tuberculosis zinc-dependent metalloprotease Zmp1 has been proposed to play a key role in the process of phagosome maturation inhibition and emerged as an important player in pathogenesis. Here, we report the crystal structure of wild-type Zmp1 at 2.6 Å resolution in complex with the generic zinc metalloprotease inhibitor phosphoramidon, which we demonstrated to inhibit the enzyme potently. Our data represent the first structural characterization of a bacterial member of the zinc-dependent M13 endopeptidase family and revealed a significant degree of conservation with eukaryotic enzymes. However, structural comparison of the Zmp1-phosphoramidon complex with homologous human proteins neprilysin and endothelin-converting enzyme-1 revealed unique features of the Zmp1 active site to be exploited for the rational design of specific inhibitors that may prove useful as a pharmacological tool for better understanding Zmp1 biological function.

PGK1, the gene encoding the glycolitic enzyme phosphoglycerate kinase, acts as a multicopy suppressor of apoptotic phenotypes in S. cerevisiae

In a previous paper we reported the construction of a S. cerevisiae strain lacking the essential gene LSM4, which could survive by the introduction of a truncated form of the orthologous gene from Kluyveromyces lactis. This strain showed apoptotic hallmarks and other phenotypes, including an increased sensitivity to caffeine and acetic acid. The suppression of the latter phenotype by overexpressing yeast genes allowed the isolation of PGK1, the gene encoding the glycolytic enzyme phosphoglycerate kinase. This gene restored normal ageing, oxygen peroxide resistance and nuclear integrity in the mutant. Other phenotypes, such as caffeine sensitivity and glycerol utilization, were also suppressed.