Canagliflozin Attenuates PromarkerD Diabetic Kidney Disease Risk Prediction Scores.

PromarkerD is a biomarker-based blood test that predicts kidney function decline in people with type 2 diabetes (T2D) who may otherwise be missed by current standard of care tests. This study examined the association between canagliflozin and change in PromarkerD score (Δ score) over a three-year period in T2D participants in the CANagliflozin cardioVascular Assessment Study (CANVAS). PromarkerD scores were measured at baseline and Year 3 in 2008 participants with preserved kidney function (baseline eGFR ≥60 mL/min/1.73 m2). Generalized estimating equations were used to assess the effect of canagliflozin versus placebo on PromarkerD scores. At baseline, the participants (mean age 62 years, 32% females) had a median PromarkerD score of 3.9%, with 67% of participants categorized as low risk, 14% as moderate risk, and 19% as high risk for kidney function decline. After accounting for the known acute drop in eGFR following canagliflozin initiation, there was a significant treatment-by-time interaction (p < 0.001), whereby participants on canagliflozin had decreased mean PromarkerD scores from baseline to Year 3 (Δ score: -1.0% [95% CI: -1.9%, -0.1%]; p = 0.039), while the scores of those on placebo increased over the three-year period (Δ score: 6.4% [4.9%, 7.8%]; p < 0.001). When stratified into PromarkerD risk categories, participants with high risk scores at baseline who were randomized to canagliflozin had significantly lower scores at Year 3 (Δ score: -5.6% [-8.6%, -2.5%]; p < 0.001), while those on placebo retained high scores (Δ score: 4.5% [0.3%, 8.8%]; p = 0.035). This post hoc analysis of data from CANVAS showed that canagliflozin significantly lowered PromarkerD risk scores, with the effect greatest in those T2D participants who were classified at study entry as at high risk of a subsequent decline in kidney function.

Immunoaffinity Mass Spectrometry Diagnostic Tests for Multi-Biomarker Assays.

Immunoaffinity mass spectrometry as an approach for diagnostic biomarker assays combines the advantages of antibody selectivity with the multiplexing and analytical performance of mass spectrometry. A method has been developed to detect and quantify three protein biomarkers for a diabetic kidney disease prognostic assay, PromarkerD. The methodology reflects an immunoaffinity approach compatible with higher throughput and robust clinical application. After preparation and purification of antibody-bead conjugates for the three target proteins, an immunoaffinity capture step provides a solution for reduction, alkylation, and digestion on-bead. Targeted mass spectrometry provides a quantitative measure of each biomarker in a rapid 8 min run using a microflow LCMS workflow.

Semi-Automated Lectin Magnetic Bead Array (LeMBA) for Translational Serum Glycoprotein Biomarker Discovery and Validation.

Aberrant protein glycosylation is a characteristic of diverse diseases which has been explored as biomarkers. To support translational serum glycoprotein biomarker discovery and validation, we developed a semi-automated workflow using individual lectin-coupled magnetic beads to conduct lectin pulldowns in a high-throughput format. Lectins are naturally occurring glycoprotein binding proteins widely used in glycobiology. While lectin-affinity isolation has been coupled to mass spectrometry-based proteomics, the lectin magnetic bead array (LeMBA) platform allows technically robust screening and measurement of clinical cohorts. This chapter describes detailed lectin-magnetic bead coupling, serum denaturation, lectin magnetic bead pulldown, and on-bead trypsin digest. The resulting tryptic peptides are analyzed by untargeted or targeted liquid chromatography-mass spectrometry (LC-MS), for biomarker discovery, or qualification/validation, respectively. LeMBA-MS generates quantitative data for glycoforms based on lectin affinity of the glycoprotein coupled with MS measurement of one or more prototypic peptides and has successfully been used to discover and validate novel serum cancer glycoprotein biomarkers. This chapter includes detailed protocols for two different liquid handlers, along with recommendations on quality control measures for clinical biomarker studies.

Gene Validation and Remodelling Using Proteogenomics of Phytophthora cinnamomi, the Causal Agent of Dieback.

Phytophthora cinnamomi is a pathogenic oomycete that causes plant dieback disease across a range of natural ecosystems and in many agriculturally important crops on a global scale. An annotated draft genome sequence is publicly available (JGI Mycocosm) and suggests 26,131 gene models. In this study, soluble mycelial, extracellular (secretome), and zoospore proteins of P. cinnamomi were exploited to refine the genome by correcting gene annotations and discovering novel genes. By implementing the diverse set of sub-proteomes into a generated proteogenomics pipeline, we were able to improve the P. cinnamomi genome annotation. Liquid chromatography mass spectrometry was used to obtain high confidence peptides with spectral matching to both the annotated genome and a generated 6-frame translation. Two thousand seven hundred sixty-four annotations from the draft genome were confirmed by spectral matching. Using a proteogenomic pipeline, mass spectra were used to edit the P. cinnamomi genome and allowed identification of 23 new gene models and 60 edited gene features using high confidence peptides obtained by mass spectrometry, suggesting a rate of incorrect annotations of 3% of the detectable proteome. The novel features were further validated by total peptide support, alongside functional analysis including the use of Gene Ontology and functional domain identification. We demonstrated the use of spectral data in combination with our proteogenomics pipeline can be used to improve the genome annotation of important plant diseases and identify missed genes. This study presents the first use of spectral data to edit and manually annotate an oomycete pathogen.

Pyroxasulfone-Resistant Annual Ryegrass (Lolium rigidum) Has Enhanced Capacity for Glutathione Transferase-Mediated Pyroxasulfone Conjugation.

The herbicide pyroxasulfone was widely introduced in 2012, and cases of evolved resistance in weeds such as annual ryegrass (Lolium rigidum Gaud.) and tall waterhemp [Amaranthus tuberculatus (Moq.) Sauer] have started to emerge. Pyroxasulfone is detoxified by tolerant crops, and by annual ryegrass that has been recurrently selected with pyroxasulfone, in a pathway that is hypothesized to involve glutathione conjugation. In the current study, it was confirmed that pyroxasulfone is conjugated to glutathione in vitro by glutathione transferases (GSTs) purified from susceptible and resistant annual ryegrass populations and from a tolerant crop species, wheat. The extent of conjugation corresponded to the pyroxasulfone resistance level. Pyroxasulfone-conjugating activity was higher in radicles, roots, and seeds compared to coleoptiles or expanded leaves. Among the GSTs purified from annual ryegrass radicles and seeds, an orthologue of Brachypodium distachyon GSTF13 was >20-fold more abundant in the pyroxasulfone-resistant population, suggesting that this protein could be responsible for pyroxasulfone conjugation.

Assessment of biomarkers associated with rapid renal decline in the detection of retinopathy and its progression in type 2 diabetes: The Fremantle Diabetes Study Phase II.

AIMS: To determine whether biomarkers for diabetic kidney disease (DKD) can be used to determine the prevalence, progression and/or incidence of diabetic retinopathy (DR) complicating type 2 diabetes. METHODS: Proteomic biomarkers were measured in baseline fasting plasma from 958 Fremantle Diabetes Study Phase II participants whose baseline and, in those returning for follow-up (n = 764), Year 4 fundus photographs were graded for DR presence/severity. The performance of PromarkerD (three biomarkers and readily available clinical variables which identify prevalent DKD and predict incident DKD and estimated glomerular filtration rate decline ≥30% over four years) for detecting DR prevalence, progression and incidence was assessed using the area under the receiver operating curve (AUC). Logistic regression determined whether individual proteins were associated with DR outcomes after adjusting for the most parsimonious model. RESULTS: Plasma apolipoprotein A-IV (APOA4) was independently associated with moderate non-proliferative DR at baseline (OR (95% CI): 1.64 (1.01, 2.67), P = 0.047). Model discrimination was poor for all PromarkerD predicted probabilities against all DR outcomes (AUC ≤0.681). CONCLUSIONS: PromarkerD and its constituent biomarkers were not consistently associated with DR prevalence or temporal change. APOA4 was associated with prevalent DR, but not DR incidence or progression. Distinct pathophysiological mechanisms may underlie DKD and DR.

The New and the Old: Platform Cross-Validation of Immunoaffinity MASS Spectrometry versus ELISA for PromarkerD, a Predictive Test for Diabetic Kidney Disease.

PromarkerD is a proteomics derived test for predicting diabetic kidney disease that measures the concentrations of three plasma protein biomarkers, APOA4, CD5L and IBP3. Antibodies against these proteins were developed and applied to a multiplexed immunoaffinity capture mass spectrometry assay. In parallel, and facilitating current clinical laboratory workflows, a standard ELISA was also developed to measure each protein. The performance characteristics of the two technology platforms were compared using a cohort of 100 samples, with PromarkerD test scores demonstrating a high correlation (R = 0.97). These technologies illustrate the potential for large scale, high throughput clinical applications of proteomics now and into the future.

A robust multiplex immunoaffinity mass spectrometry assay (PromarkerD) for clinical prediction of diabetic kidney disease.

BACKGROUND: PromarkerD is a novel proteomics derived blood test for predicting diabetic kidney disease (DKD). The test is based on an algorithm that combines the measurement of three plasma protein biomarkers (CD5L, APOA4, and IBP3) with three clinical variables (age, HDL-cholesterol, and eGFR). The initial format of the assay used immunodepletion of plasma samples followed by targeted mass spectrometry (MRM-LCMS). The aim of this study was to convert the existing assay into an immunoaffinity approach compatible with higher throughput and robust clinical application. METHODS: A newly optimised immunoaffinity-based assay was developed in a 96 well format with MRM measurements made using a low-flow LCMS method. The stability, reproducibility and precision of the assay was evaluated. A direct comparison between the immunoaffinity method and the original immunodepletion method was conducted on a 100-person cohort. Subsequently, an inter-lab study was performed of the optimised immunoaffinity method in two independent laboratories. RESULTS: Processing of plasma samples was greatly simplified by switching to an immunoaffinity bead capture method, coupled to a faster and more robust microflow LCMS system. Processing time was reduced from seven to two days and the chromatography reduced from 90 to 8 min. Biomarker stability by temperature and time difference treatments passed acceptance criteria. Intra/Inter-day test reproducibility and precision were within 11% CV for all biomarkers. PromarkerD test results from the new immunoaffinity method demonstrated excellent correlation (R = 0.96) to the original immunodepletion method. The immunoaffinity assay was successfully transferred to a second laboratory (R = 0.98) demonstrating the robustness of the methodology and ease of method transfer. CONCLUSIONS: An immunoaffinity capture targeted mass spectrometry assay was developed and optimised. It showed statistically comparable results to those obtained from the original immunodepletion method and was also able to provide comparable results when deployed to an independent laboratory. Taking a research grade assay and optimising to a clinical grade workflow provides insights into the future of multiplex biomarker measurement with an immunoaffinity mass spectrometry foundation. In the current format the PromarkerD immunoaffinity assay has the potential to make a significant impact on prediction of diabetic kidney disease with consequent benefit to patients.

PromarkerD Predicts Renal Function Decline in Type 2 Diabetes in the Canagliflozin Cardiovascular Assessment Study (CANVAS).

The ability of current tests to predict chronic kidney disease (CKD) complicating diabetes is limited. This study investigated the prognostic utility of a novel blood test, PromarkerD, for predicting future renal function decline in individuals with type 2 diabetes from the CANagliflozin CardioVascular Assessment Study (CANVAS). PromarkerD scores were measured at baseline in 3568 CANVAS participants (n = 1195 placebo arm, n = 2373 canagliflozin arm) and used to predict incident CKD (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 during follow-up in those above this threshold at baseline) and eGFR decline ≥30% during the 4 years from randomization. Biomarker concentrations (apolipoprotein A-IV (apoA4), CD5 antigen-like (CD5L/AIM) and insulin-like growth factor-binding protein 3 (IGFBP3) measured by mass spectrometry were combined with clinical data (age, serum high-density lipoprotein (HDL)-cholesterol, eGFR) using a previously defined algorithm to provide PromarkerD scores categorized as low-, moderate- or high-risk. The participants (mean age 63 years, 33% females) had a median PromarkerD score of 2.9%, with 70.5% categorized as low-risk, 13.6% as moderate-risk and 15.9% as high-risk for developing incident CKD. After adjusting for treatment, baseline PromarkerD moderate-risk and high-risk scores were increasingly prognostic for incident CKD (odds ratio 5.29 and 13.52 versus low-risk, respectively; both p < 0.001). Analysis of the PromarkerD test system in CANVAS shows the test can predict clinically significant incident CKD in this multi-center clinical study but had limited utility for predicting eGFR decline ≥30%.

Peptide analysis of mammalian decomposition fluid in relation to the post-mortem interval.

We report the results of a semi-quantitative peptide analysis of decomposition fluid under field-based conditions in the absence of a soil matrix. Sixteen domestic pig (Sus scrofa domesticus) cadavers were used to model human decomposition in trials conducted in the summer and winter months in Western Australia. Physical characteristics were recorded and targeted peptide components of decomposition fluid were analysed using high performance liquid chromatography-triple quadrupole mass spectrometry. Principal component analysis identified 29 peptides, originating from haemoglobin subunits alpha and beta, creatine kinase, beta-enolase and lactate dehydrogenase, that contributed to differences in the mean peak areas of samples collected during the early period of decomposition (days 6-12 and day 2 in winter and summer, respectively) and during the later period (days 24-34 and days 8-10 in winter and summer, respectively). Fold changes for 8 peptides between these periods were significantly different. Three peptides derived from haemoglobin subunit beta, one from beta-enolase and two from lactate dehydrogenase displayed consistent trends, in that a notable increase in mean peak area was followed by a marked decrease in both the summer and winter samples. When temperature was accounted for, these trends occurred at different time points in summer and winter, indicating that factors other than temperature had impacted the rate of degradation of the proteins involved. The single peptides derived from haemoglobin subunit alpha and creatine kinase displayed consistent increases in mean peak area for the summer samples, suggesting that temperature played the most significant role in their degradation. Further analyses revealed that 7 peptides (one originating from haemoglobin subunit alpha, three from haemoglobin subunit beta and three from lactate dehydrogenase) displayed consistent trends that could be correlated with total body score and with the early stages of decomposition. The consistent trends (mean peak area versus time) for peptides derived from several proteins during decomposition trials conducted under different temperature regimes further emphasised the potential of peptide analysis in time since death estimation.