Proteomic Indicators of Health Predict Alzheimer's Disease Biomarker Levels and Dementia Risk

OBJECTIVE

Few studies have comprehensively examined how health and disease risk influence Alzheimer's disease (AD) biomarkers. The present study examined the association of 14 protein-based health indicators with plasma and neuroimaging biomarkers of AD and neurodegeneration.

METHODS

In 706 cognitively normal adults, we examined whether 14 protein-based health indices (ie, SomaSignal® tests) were associated with concurrently measured plasma-based biomarkers of AD pathology (amyloid-β [Aβ]42/40 , tau phosphorylated at threonine-181 [pTau-181]), neuronal injury (neurofilament light chain [NfL]), and reactive astrogliosis (glial fibrillary acidic protein [GFAP]), brain volume, and cortical Aβ and tau. In a separate cohort (n = 11,285), we examined whether protein-based health indicators associated with neurodegeneration also predict 25-year dementia risk.

RESULTS

Greater protein-based risk for cardiovascular disease, heart failure mortality, and kidney disease was associated with lower Aβ42/40 and higher pTau-181, NfL, and GFAP levels, even in individuals without cardiovascular or kidney disease. Proteomic indicators of body fat percentage, lean body mass, and visceral fat were associated with pTau-181, NfL, and GFAP, whereas resting energy rate was negatively associated with NfL and GFAP. Together, these health indicators predicted 12, 31, 50, and 33% of plasma Aβ42/40 , pTau-181, NfL, and GFAP levels, respectively. Only protein-based measures of cardiovascular risk were associated with reduced regional brain volumes; these measures predicted 25-year dementia risk, even among those without clinically defined cardiovascular disease.

INTERPRETATION

Subclinical peripheral health may influence AD and neurodegenerative disease processes and relevant biomarker levels, particularly NfL. Cardiovascular health, even in the absence of clinically defined disease, plays a central role in brain aging and dementia. ANN NEUROL 2024;95:260-273.

Defining the serum proteomic signature of hepatic steatosis, inflammation, ballooning and fibrosis in non-alcoholic fatty liver disease

BACKGROUND & AIMS

Despite recent progress, non-invasive tests for the diagnostic assessment and monitoring of non-alcoholic fatty liver disease (NAFLD) remain an unmet need. Herein, we aimed to identify diagnostic signatures of the key histological features of NAFLD.

METHODS

Using modified-aptamer proteomics, we assayed 5,220 proteins in each of 2,852 single serum samples from 636 individuals with histologically confirmed NAFLD. We developed and validated dichotomized protein-phenotype models to identify clinically relevant severities of steatosis (grade 0 vs. 1-3), hepatocellular ballooning (0 vs. 1 or 2), lobular inflammation (0-1 vs. 2-3) and fibrosis (stages 0-1 vs. 2-4).

RESULTS

The AUCs of the four protein models, based on 37 analytes (18 not previously linked to NAFLD), for the diagnosis of their respective components (at a clinically relevant severity) in training/paired validation sets were: fibrosis (AUC 0.92/0.85); steatosis (AUC 0.95/0.79), inflammation (AUC 0.83/0.72), and ballooning (AUC 0.87/0.83). An additional outcome, at-risk NASH, defined as steatohepatitis with NAFLD activity score ≥4 (with a score of at least 1 for each of its components) and fibrosis stage ≥2, was predicted by multiplying the outputs of each individual component model (AUC 0.93/0.85). We further evaluated their ability to detect change in histology following treatment with placebo, pioglitazone, vitamin E or obeticholic acid. Component model scores significantly improved in the active therapies vs. placebo, and differential effects of vitamin E, pioglitazone, and obeticholic acid were identified.

CONCLUSIONS

Serum protein scanning identified signatures corresponding to the key components of liver biopsy in NAFLD. The models developed were sufficiently sensitive to characterize the longitudinal change for three different drug interventions. These data support continued validation of these proteomic models to enable a "liquid biopsy"-based assessment of NAFLD.

CLINICAL TRIAL NUMBER

Not applicable.

IMPACT AND IMPLICATIONS

An aptamer-based protein scan of serum proteins was performed to identify diagnostic signatures of the key histological features of non-alcoholic fatty liver disease (NAFLD), for which no approved non-invasive diagnostic tools are currently available. We also identified specific protein signatures related to the presence and severity of NAFLD and its histological components that were also sensitive to change over time. These are fundamental initial steps in establishing a serum proteome-based diagnostic signature of NASH and provide the rationale for using these signatures to test treatment response and to identify several novel targets for evaluation in the pathogenesis of NAFLD.

Proteomic signatures for identification of impaired glucose tolerance

The implementation of recommendations for type 2 diabetes (T2D) screening and diagnosis focuses on the measurement of glycated hemoglobin (HbA1c) and fasting glucose. This approach leaves a large number of individuals with isolated impaired glucose tolerance (iIGT), who are only detectable through oral glucose tolerance tests (OGTTs), at risk of diabetes and its severe complications. We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79-0.86), P = 0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D. Assessment of a limited number of proteins can identify individuals likely to be missed by current diagnostic strategies and at high risk of T2D and its complications.

Response to comment on "A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk"

A 27-protein signature has been proposed to predict cardiovascular disease, and its applicability in some clinical decision-making situations is discussed.

Comparative effectiveness and cardiovascular safety of abaloparatide and teriparatide in postmenopausal women new to anabolic therapy: A US administrative claims database study

Real-world evidence on the comparative effectiveness and safety of abaloparatide versus teriparatide in women with osteoporosis may help inform treatment decisions. Following 18 months of treatment, abaloparatide was comparable to teriparatide for prevention of nonvertebral fractures, resulted in a 22% risk reduction for hip fractures, and demonstrated similar cardiovascular safety. Osteoporotic fracture risk can be reduced with anabolic or antiresorptive medications. In addition to efficacy and safety data from controlled clinical trials, real-world evidence on comparative effectiveness and safety may help inform treatment decisions.

INTRODUCTION

The real-world effectiveness of abaloparatide versus teriparatide on nonvertebral fracture (NVF) incidence and cardiovascular safety during the 19-month period after treatment initiation were evaluated (NCT04974723).

METHODS

Anonymized US patient claims data from Symphony Health, Integrated Dataverse (IDV)®, May 1, 2017 to July 31, 2019, included women aged ≥ 50 years with ≥ 1 prescription of abaloparatide or teriparatide and no prior anabolic therapy. Most were enrolled in commercial and Medicare health plans. Index was the date of the initial prescription dispensed during the identification period. In 1:1 propensity score matched cohorts, time to first NVF following index date, major adverse cardiovascular events (MACE), and MACE + heart failure (HF) were compared between cohorts using a Cox proportional hazards model.

RESULTS

Propensity score matching yielded 11,616 patients per cohort. Overall median age (interquartile range) was 67 (61, 75) years, and 25.6% had a fracture history. Over 19 months, 335 patients on abaloparatide and 375 on teriparatide had a NVF (hazard ratio [95% confidence interval]: 0.89 [0.77, 1.03]), and 121 and 154 patients, respectively, had a hip fracture [HR (95% CI): 0.78 (0.62, 1.00)]. The MACE and MACE + HF rates were similar between cohorts.

CONCLUSIONS

Following 18 months of treatment, abaloparatide was comparable to teriparatide for prevention of NVF and similar cardiovascular safety was demonstrated between cohorts.

A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk

A reliable, individualized, and dynamic surrogate of cardiovascular risk, synoptic for key biologic mechanisms, could shorten the path for drug development, enhance drug cost-effectiveness and improve patient outcomes. We used highly multiplexed proteomics to address these objectives, measuring about 5000 proteins in each of 32,130 archived plasma samples from 22,849 participants in nine clinical studies. We used machine learning to derive a 27-protein model predicting 4-year likelihood of myocardial infarction, stroke, heart failure, or death. The 27 proteins encompassed 10 biologic systems, and 12 were associated with relevant causal genetic traits. We independently validated results in 11,609 participants. Compared to a clinical model, the ratio of observed events in quintile 5 to quintile 1 was 6.7 for proteins versus 2.9 for the clinical model, AUCs (95% CI) were 0.73 (0.72 to 0.74) versus 0.64 (0.62 to 0.65), c-statistics were 0.71 (0.69 to 0.72) versus 0.62 (0.60 to 0.63), and the net reclassification index was +0.43. Adding the clinical model to the proteins only improved discrimination metrics by 0.01 to 0.02. Event rates in four predefined protein risk categories were 5.6, 11.2, 20.0, and 43.4% within 4 years; median time to event was 1.71 years. Protein predictions were directionally concordant with changed outcomes. Adverse risks were predicted for aging, approaching an event, anthracycline chemotherapy, diabetes, smoking, rheumatoid arthritis, cancer history, cardiovascular disease, high systolic blood pressure, and lipids. Reduced risks were predicted for weight loss and exenatide. The 27-protein model has potential as a "universal" surrogate end point for cardiovascular risk.

Plasma proteins, cognitive decline, and 20-year risk of dementia in the Whitehall II and Atherosclerosis Risk in Communities studies

INTRODUCTION

Plasma proteins affect biological processes and are common drug targets but their role in the development of Alzheimer's disease and related dementias remains unclear. We examined associations between 4953 plasma proteins and cognitive decline and risk of dementia in two cohort studies with 20-year follow-ups.

METHODS

In the Whitehall II prospective cohort study proteins were measured using SOMAscan technology. Cognitive performance was tested five times over 20 years. Linkage to electronic health records identified incident dementia. The results were replicated in the Atherosclerosis Risk in Communities (ARIC) study.

RESULTS

Fifteen non-amyloid/non-tau-related proteins were associated with cognitive decline and dementia, were consistently identified in both cohorts, and were not explained by known dementia risk factors. Levels of six of the proteins are modifiable by currently approved medications for other conditions.

DISCUSSION

This study identified several plasma proteins in dementia-free people that are associated with long-term risk of cognitive decline and dementia.

Differential Proteomics of Cardiovascular Risk and Coronary Artery Disease in Humans

Background

Proteomics of atypical phenotypes may help unravel cardiovascular disease mechanisms.

Aim

We aimed to prospectively screen the proteome of four types of individuals: with or without coronary artery disease (CAD), each with or without multiple risk factors. Associations with individual risk factors and circulating biomarkers were also tested to provide a functional context to the protein hits.

Materials and Methods

The CAPIRE study (ClinicalTrials.gov Identifier: NCT02157662) is a cross-sectional study aimed at identifying possible new mechanisms promoting or protecting against atherothrombosis. Quantification (by aptamer technology), ranking (using partial least squares), and correlations (by multivariate regression) of ~5000 plasma proteins were performed in consecutive individuals aged 45–75 years, without previous cardiovascular disease, undergoing computed tomography angiography for suspected CAD, showing either >5/16 atherosclerotic segments (CAD+) or completely clean arteries (CAD−) and either ≤ 1 risk factor (RF+) or ≥3 risk factors (RF−) (based on history, blood pressure, glycemia, lipids, and smoking).

Results

Of 544 individuals, 39% were atypical (93 CAD+/RF−; 120 CAD−/RF+) and 61% typical (102 CAD+/RF+; 229 CAD−/RF−). In the comparison with CAD+/RF− adjusted for sex and age, CAD−/RF+ was associated with increased atrial myosin regulatory light chain 2 (MYO) and C-C motif chemokine-22 (C-C-22), and reduced protein shisa-3 homolog (PS-3) and platelet-activating factor acetylhydrolase (PAF-AH). Extending the analysis to the entire cohort, an additional 8 proteins were independently associated with CAD or RF; by logistic regression, the 12-protein panel alone discriminated the four groups with AUCROC's of 0.72–0.81 (overall p = 1.0e−38). Among them, insulin-like growth factor binding protein-3 is positively associated with RF, lower BMI, and HDL-cholesterol, renin with CAD higher glycated hemoglobin HbA1c, and smoking.

Conclusions

In a CCTA-based cohort, four proteins, involved in opposing vascular processes (healing vs. adverse remodeling), are specifically associated with low CAD burden in high CV-risk individuals (high MYO and C-C-22) and high CAD burden in low-risk subjects (high PS-3 and PAF-AH), in interaction with BMI, smoking, diabetes, HDL-cholesterol, and HbA1c. These findings could contribute to a deeper understanding of the atherosclerotic process beyond traditional risk profile assessment and potentially constitute new treatment targets.

Fixation in Form-Acetic allows hyaluronic acid detection in mouse ovaries

To visualise tissues to determine the presence of disease or simply to understand anatomy, it is important to preserve fresh tissue. Fixatives are chemical solutions that preserve tissues to enable microscopic evaluation. However, some fixatives introduce artefact such as shrinkage of cells. Recently, a new fixative, Form-Acetic, was developed that is superior for preserving the structure of ovary tissue and allows investigation of ovary composition. One component of the ovary is hyaluronic acid (HA), which plays a crucial role in normal ovary function and fertility. Importantly, HA is sensitive to different fixative solutions. Therefore, it is meaningful to verify whether Form-Acetic is suitable for detecting HA. In this study, adult mouse ovaries were fixed in Form-Acetic and HA was detected. All HA-containing structures in the ovary were clearly distinguished which proves that the novel fixative allows the detection of HA.

Modeling nitrous oxide mitigation potential of enhanced efficiency nitrogen fertilizers from agricultural systems

Agriculture soils are responsible for a large proportion of global nitrous oxide (N₂O) emissions-a potent greenhouse gas and ozone depleting substance. Enhanced-efficiency nitrogen (N) fertilizers (EENFs) can reduce N₂O emission from N-fertilized soils, but their effect varies considerably due to a combination of factors, including climatic conditions, edaphic characteristics and management practices. In this study, we further developed the DayCent ecosystem model to simulate two EENFs: controlled-release N fertilizers (CRNFs) and nitrification inhibitors (NIs) and evaluated their N₂O mitigation potentials. We implemented a Bayesian calibration method using the sampling importance resampling (SIR) algorithm to derive a joint posterior distribution of model parameters that was informed by N₂O flux measurements from corn production systems a network of experimental sites within the GRACEnet program. The joint posterior distribution can be applied to estimate predictions of N₂O reduction factors when EENFs are adopted in place of conventional urea-based N fertilizer. The resulting median reduction factors were - 11.9% for CRNFs (ranging from -51.7% and 0.58%) and - 26.7% for NIs (ranging from -61.8% to 3.1%), which is comparable to the measured reduction factors in the dataset. By incorporating EENFs, the DayCent ecosystem model is able to simulate a broader suite of options to identify best management practices for reducing N₂O emissions.

Cognitive stimulation in the workplace, plasma proteins, and risk of dementia: three analyses of population cohort studies

OBJECTIVES

To examine the association between cognitively stimulating work and subsequent risk of dementia and to identify protein pathways for this association.

DESIGN

Multicohort study with three sets of analyses.

SETTING

United Kingdom, Europe, and the United States.

PARTICIPANTS

Three associations were examined: cognitive stimulation and dementia risk in 107 896 participants from seven population based prospective cohort studies from the IPD-Work consortium (individual participant data meta-analysis in working populations); cognitive stimulation and proteins in a random sample of 2261 participants from one cohort study; and proteins and dementia risk in 13 656 participants from two cohort studies.

MAIN OUTCOME MEASURES

Cognitive stimulation was measured at baseline using standard questionnaire instruments on active versus passive jobs and at baseline and over time using a job exposure matrix indicator. 4953 proteins in plasma samples were scanned. Follow-up of incident dementia varied between 13.7 to 30.1 years depending on the cohort. People with dementia were identified through linked electronic health records and repeated clinical examinations.

RESULTS

During 1.8 million person years at risk, 1143 people with dementia were recorded. The risk of dementia was found to be lower for participants with high compared with low cognitive stimulation at work (crude incidence of dementia per 10 000 person years 4.8 in the high stimulation group and 7.3 in the low stimulation group, age and sex adjusted hazard ratio 0.77, 95% confidence interval 0.65 to 0.92, heterogeneity in cohort specific estimates I²=0%, P=0.99). This association was robust to additional adjustment for education, risk factors for dementia in adulthood (smoking, heavy alcohol consumption, physical inactivity, job strain, obesity, hypertension, and prevalent diabetes at baseline), and cardiometabolic diseases (diabetes, coronary heart disease, stroke) before dementia diagnosis (fully adjusted hazard ratio 0.82, 95% confidence interval 0.68 to 0.98). The risk of dementia was also observed during the first 10 years of follow-up (hazard ratio 0.60, 95% confidence interval 0.37 to 0.95) and from year 10 onwards (0.79, 0.66 to 0.95) and replicated using a repeated job exposure matrix indicator of cognitive stimulation (hazard ratio per 1 standard deviation increase 0.77, 95% confidence interval 0.69 to 0.86). In analysis controlling for multiple testing, higher cognitive stimulation at work was associated with lower levels of proteins that inhibit central nervous system axonogenesis and synaptogenesis: slit homologue 2 (SLIT2, fully adjusted β -0.34, P<0.001), carbohydrate sulfotransferase 12 (CHSTC, fully adjusted β -0.33, P<0.001), and peptidyl-glycine α-amidating monooxygenase (AMD, fully adjusted β -0.32, P<0.001). These proteins were associated with increased dementia risk, with the fully adjusted hazard ratio per 1 SD being 1.16 (95% confidence interval 1.05 to 1.28) for SLIT2, 1.13 (1.00 to 1.27) for CHSTC, and 1.04 (0.97 to 1.13) for AMD.

CONCLUSIONS

The risk of dementia in old age was found to be lower in people with cognitively stimulating jobs than in those with non-stimulating jobs. The findings that cognitive stimulation is associated with lower levels of plasma proteins that potentially inhibit axonogenesis and synaptogenesis and increase the risk of dementia might provide clues to underlying biological mechanisms.

Improved preservation of ovarian tissue morphology that is compatible with antigen detection using a fixative mixture of formalin and acetic acid

STUDY QUESTION

Can ovarian tissue morphology be better preserved whilst enabling histological molecular analyses following fixation with a novel fixative, neutral buffered formalin (NBF) with 5% acetic acid (referred to hereafter as Form-Acetic)?

SUMMARY ANSWER

Fixation with Form-Acetic improved ovarian tissue histology compared to NBF in multiple species while still enabling histological molecular analyses.

WHAT IS KNOWN ALREADY

NBF fixation results in tissue shrinkage in various tissue types including the ovary. Components of ovarian tissue, notably follicles, are particularly susceptible to NBF-induced morphological alterations and can lead to data misrepresentation. Bouin’s solution (which contains 5% acetic acid) better preserves tissue architecture compared to NBF but is limited for immunohistochemical analyses.

STUDY DESIGN, SIZE, DURATION

A comparison of routinely used fixatives, NBF and Bouin’s, and a new fixative, Form-Acetic was carried out. Ovarian tissue was used from three different species: human (n = 5 patients), sheep (n = 3; 6 ovaries; 3 animals per condition) and mouse (n = 14 mice; 3 ovaries from 3 different animals per condition).

PARTICIPANTS/MATERIALS, SETTING, METHODS

Ovarian tissue from humans (aged 13 weeks to 32 years), sheep (reproductively young i.e. 3–6 months) and mice (10 weeks old) were obtained and fixed in 2 ml NBF, Bouin’s or Form-Acetic for 4, 8, and 24 h at room temperature. Tissues were embedded and sectioned. Five-micron sections were stained with haemotoxylin and eosin (H&E) and the percentage of artefact (clear space as a result of shrinkage) between ovarian structures was calculated. Additional histological staining using Periodic acid-Schiff and Masson’s trichrome were performed on 8 and 24 h NBF, Bouin’s and Form-Acetic fixed samples to assess the compatibility of the new fixative with stains. On ovarian tissue fixed for both 8 and 24 h in NBF and Form-Acetic, immunohistochemistry (IHC) studies to detect FOXO3a, FoxL2, collagen IV, laminin and anti-Müllerian hormone (AMH) proteins were performed in addition to the terminal deoxynucleotidyl transferase nick end labelling (TUNEL) assay to determine the compatibility of Form-Acetic fixation with types of histological molecular analyses.

MAIN RESULTS AND THE ROLE OF CHANCE

Fixation in Form-Acetic improved ovarian tissue morphology compared to NBF from all three species and either slightly improved or was comparable to Bouin’s for human, mouse and sheep tissues. Form-Acetic was compatible with H&E, Periodic acid-Schiff and Masson’s trichrome staining and all proteins (FOXO3a, FoxL2, collagen IV and laminin and AMH) could be detected via IHC. Furthermore, Form-Acetic, unlike NBF, enabled antigen recognition for most of the proteins tested without the need for antigen retrieval. Form-Acetic also enabled the detection of damaged DNA via the TUNEL assay using fluorescence.

LARGE SCALE DATA

N/A

LIMITATIONS, REASONS FOR CAUTION

In this study, IHC analysis was performed on a select number of protein types in ovarian tissue thus encouraging further studies to confirm the use of Form-Acetic in enabling the detection of a wider range of protein forms in addition to other tissue types.

WIDER IMPLICATIONS OF THE FINDINGS

The simplicity in preparation of Form-Acetic and its superior preservative properties whilst enabling forms of histological molecular analyses make it a highly valuable tool for studying ovarian tissue. We, therefore, recommend that Form-Acetic replaces currently used fixatives and encourage others to introduce it into their research workflow.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the Oxford Medical Research Council Doctoral Training Programme (Oxford MRC-DTP) grant awarded to B.D.B. (Grant no. MR/N013468/1), the Fondation Hoffmann supporting R.A. and the Petroleum Technology Development Fund (PTDF) awarded to B.V.A.

Characterizing patients initiating abaloparatide, teriparatide, or denosumab in a real-world setting: a US linked claims and EMR database analysis

We characterized patients initiating abaloparatide (ABL), teriparatide (TPTD), or denosumab (DMAB) in a real-world clinical setting from a large medical and pharmacy claims database. Differences were noted in sex, age, pathologic fractures, comorbidity index, and prior bisphosphonate use for patients initiating ABL and TPTD compared with those receiving DMAB.

INTRODUCTION

To characterize patients initiating abaloparatide (ABL), teriparatide (TPTD), or denosumab (DMAB) treatment in a real-world clinical setting.

METHODS

Patients aged ≥ 18 years initiating ABL, TPTD, or DMAB between May 1, 2017, and September 24, 2018 (without receiving the same drug in the previous 12 months), were identified using the OM1 Data Cloud, which contains medical and pharmacy claims from approximately 200 million US patients. The index date was the date of initial prescription or dispensing for ABL, TPTD, or DMAB during the study period.

RESULTS

During the study period, 2666 patients initiated ABL, 9210 TPTD, and 116,718 DMAB. Mean age (standard deviation) was 69.2 (10.6) years for the ABL cohort, 68.6 (11.3) for TPTD, and 72.1 (10.2) for DMAB (P < 0.001; ABL vs DMAB). Proportionally more patients initiating ABL were female (95.2% ABL, 86.9% TPTD, and 91.3% DMAB, P < 0.001 ABL vs TPTD or DMAB). Nearly twice as many patients initiating ABL (19.1%) and TPTD (18.8%) had a previous pathologic/fragility fracture vs DMAB (9.6%; P < 0.001 ABL vs DMAB). Fewer patients initiating ABL (36.3%) or TPTD (39.7%) had Charlson comorbidity index of ≥ 2 vs DMAB (48.4%; P < 0.001 ABL vs DMAB). Before initiating ABL, TPTD, or DMAB, 44.3%, 33.8%, and 33.9% of patients had prior osteoporosis treatment, respectively. Bisphosphonate use was more common before initiating ABL (19.2%) or TPTD (19.6%), than before initiating DMAB (16.6%; P < 0.001 ABL vs DMAB).

CONCLUSIONS

Patients initiating ABL and TPTD differed in sex, age, pathologic fractures, comorbidity index, and prior bisphosphonate use compared with those initiating DMAB.

Mechanisms of Sodium-Glucose Cotransporter 2 Inhibition: Insights From Large-Scale Proteomics

OBJECTIVE

To assess the effects of empagliflozin, a selective sodium-glucose cotransporter 2 (SGLT2) inhibitor, on broad biological systems through proteomics.

RESEARCH DESIGN AND METHODS

Aptamer-based proteomics was used to quantify 3,713 proteins in 144 paired plasma samples obtained from 72 participants across the spectrum of glucose tolerance before and after 4 weeks of empagliflozin 25 mg/day. The biology of the plasma proteins significantly changed by empagliflozin (at false discovery rate-corrected P < 0.05) was discerned through Ingenuity Pathway Analysis.

RESULTS

Empagliflozin significantly affected levels of 43 proteins, 6 related to cardiomyocyte function (fatty acid-binding protein 3 and 4 [FABPA], neurotrophic receptor tyrosine kinase, renin, thrombospondin 4, and leptin receptor), 5 to iron handling (ferritin heavy chain 1, transferrin receptor protein 1, neogenin, growth differentiation factor 2 [GDF2], and β2-microglobulin), and 1 to sphingosine/ceramide metabolism (neutral ceramidase), a known pathway of cardiovascular disease. Among the protein changes achieving the strongest statistical significance, insulin-like binding factor protein-1 (IGFBP-1), transgelin-2, FABPA, GDF15, and sulphydryl oxidase 2 precursor were increased, while ferritin, thrombospondin 3, and Rearranged during Transfection (RET) were decreased by empagliflozin administration.

CONCLUSIONS

SGLT2 inhibition is associated, directly or indirectly, with multiple biological effects, including changes in markers of cardiomyocyte contraction/relaxation, iron handling, and other metabolic and renal targets. The most significant differences were detected in protein species (GDF15, ferritin, IGFBP-1, and FABP) potentially related to the clinical and metabolic changes that were actually measured in the same patients. These novel results may inform further studies using targeted proteomics and a prospective design.

Impact of Kidney Function on the Blood Proteome and on Protein Cardiovascular Risk Biomarkers in Patients With Stable Coronary Heart Disease

Background

Chronic kidney disease (CKD) confers increased cardiovascular risk, not fully explained by traditional factors. Proteins regulate biological processes and inform the risk of diseases. Thus, in 938 patients with stable coronary heart disease from the Heart and Soul cohort, we quantified 1054 plasma proteins using modified aptamers (SOMAscan) to: (1) discern how reduced glomerular filtration influences the circulating proteome, (2) learn of the importance of kidney function to the prognostic information contained in recently identified protein cardiovascular risk biomarkers, and (3) identify novel and even unique cardiovascular risk biomarkers among individuals with CKD.

Methods and Results

Plasma protein levels were correlated to estimated glomerular filtration rate (eGFR) using Spearman‐rank correlation coefficients. Cox proportional hazard models were used to estimate the association between individual protein levels and the risk of the cardiovascular outcome (first among myocardial infarction, stroke, heart failure hospitalization, or mortality). Seven hundred and nine (67.3%) plasma proteins correlated with eGFR at P<0.05 (ρ 0.06–0.74); 218 (20.7%) proteins correlated with eGFR moderately or strongly (ρ 0.2–0.74). Among the previously identified 196 protein cardiovascular biomarkers, just 87 remained prognostic after correction for eGFR. Among patients with CKD (eGFR <60 mL/min per 1.73 m²), we identified 21 protein cardiovascular risk biomarkers of which 8 are unique to CKD.

Conclusions

CKD broadly alters the composition of the circulating proteome. We describe protein biomarkers capable of predicting cardiovascular risk independently of glomerular filtration, and those that are prognostic of cardiovascular risk specifically in patients with CKD and even unique to patients with CKD.

Osteoporotic fracture trends in a population of US managed care enrollees from 2007 to 2017

This study expands on previous findings that hip fracture rates may no longer be declining. We found that age- and sex-adjusted fracture rates in the US plateaued or increased through mid-2017 in a population of commercially insured and Medicare Advantage health plan enrollees, in contrast to a decline from 2007 to 2013.

INTRODUCTION

The purpose of this study was to evaluate fracture trends in US commercial and Medicare Advantage health plan members aged ≥ 50 years between 2007 and 2017.

METHODS

Retrospective analysis of the Optum Research Database from January 1, 2007, to May 31, 2017.

RESULTS

Of 1,841,263 patients identified with an index fracture, 930,690 were case-qualifying and included in this analysis. The overall age- and sex-adjusted fracture rate decreased from 14.67/1000 person-years (py) in 2007 to 11.79/1000 py in 2013, followed by a plateau for the next 3 years and then an increase to 12.50/1000 py in mid-2017. In females aged ≥ 65 years, fracture rates declined from 27.49/1000 py in 2007 to 22.08/1000 py in 2013, then increased to 24.92/1000 py in mid-2017. Likewise, fracture rates in males aged ≥ 65 years declined from 2007 (12.00/1000 py) to 2013 (10.72/1000 py), then increased to 12.04/1000 py in mid-2017. The age- and sex-adjusted fracture rates for most fracture sites declined from 2007 to 2013 by 3.7% per year (P = 0.310).

CONCLUSIONS

Following a consistent decline in fracture rate from 2007 to 2013, trends from 2014 to 2017 indicate fracture rates are no longer declining and, for some fracture types, rates are rising.

Coronary Artery Disease and Type 2 Diabetes: A Proteomic Study

OBJECTIVE

Coronary artery disease (CAD) is a major challenge in patients with type 2 diabetes (T2D). Coronary computed tomography angiography (CCTA) provides a detailed anatomic map of the coronary circulation. Proteomics are increasingly used to improve diagnostic and therapeutic algorithms. We hypothesized that the protein panel is differentially associated with T2D and CAD.

RESEARCH DESIGN AND METHODS

In CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation-a cohort of 528 individuals with no previous cardiovascular event undergoing CCTA), participants were grouped into CAD^- (clean coronaries) and CAD⁺ (diffuse lumen narrowing or plaques). Plasma proteins were screened by aptamer analysis. Two-way partial least squares was used to simultaneously rank proteins by diabetes status and CAD.

RESULTS

Though CAD⁺ was more prevalent among participants with T2D (HbA_1c 6.7 ± 1.1%) than those without diabetes (56 vs. 30%, P < 0.0001), CCTA-based atherosclerosis burden did not differ. Of the 20 top-ranking proteins, 15 were associated with both T2D and CAD, and 3 (osteomodulin, cartilage intermediate-layer protein 15, and HTRA1) were selectively associated with T2D only and 2 (epidermal growth factor receptor and contactin-1) with CAD only. Elevated renin and GDF15, and lower adiponectin, were independently associated with both T2D and CAD. In multivariate analysis adjusting for the Framingham risk panel, patients with T2D were "protected" from CAD if female (P = 0.007), younger (P = 0.021), and with lower renin levels (P = 0.02).

CONCLUSIONS

We concluded that 1) CAD severity and quality do not differ between participants with T2D and without diabetes; 2) renin, GDF15, and adiponectin are shared markers by T2D and CAD; 3) several proteins are specifically associated with T2D or CAD; and 4) in T2D, lower renin levels may protect against CAD.

Plasma protein patterns as comprehensive indicators of health

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3-10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12-16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.

Abaloparatide for risk reduction of nonvertebral and vertebral fractures in postmenopausal women with osteoporosis: a network meta-analysis

This network meta-analysis assessed the efficacy of abaloparatide versus other treatment options to reduce the risk of fractures in women with postmenopausal osteoporosis. The analysis indicates that abaloparatide reduces the risk of fractures in women with postmenopausal osteoporosis versus placebo and compared with other treatment options.

INTRODUCTION

This network meta-analysis (NMA) assessed the relative efficacy of abaloparatide versus other treatments to reduce the risk of fractures in women with postmenopausal osteoporosis (PMO).

METHODS

PubMed®, Embase®, and the Cochrane Central Register of Controlled Trials were searched for randomized controlled trials published before December 20, 2017, that included women with PMO who were eligible to receive interventions for primary or secondary fracture prevention. The NMA was conducted by fracture site (vertebral [VF], nonvertebral [NVF], and wrist), with the relative risk (RR) of fracture versus placebo the main clinical endpoint. The NMA used fixed-effects and random-effects approaches.

RESULTS

A total of 4978 articles were screened, of which 22 were included in the analysis. Compared with other treatments, abaloparatide demonstrated the greatest treatment effect relative to placebo in the VF network (RR = 0.13; 95% credible interval [CrI] 0.04-0.34), the NVF network (RR = 0.50; 95% CrI 0.28-0.85), and the wrist fracture network (RR = 0.39; CrI 0.15-0.90). Treatment ranking showed that abaloparatide had the highest estimated probability of preventing fractures in each of the networks (79% for VF, 70% for NVF, and 53% for wrist fracture) compared with other treatments. Individual networks demonstrated a good level of agreement with direct trial evidence and direct pair-wise comparisons.

CONCLUSIONS

This NMA indicates that abaloparatide reduces the RR of VF, NVF, and wrist fracture in women with PMO with or without prior fracture versus placebo, compared with other treatment options. Limitations include that adverse events and drug costs were not considered, and that generalizability is limited to the trial populations and endpoints included in the NMA.

Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib

Supplemental Digital Content is available in the text.

Background:

Early detection of adverse effects of novel therapies and understanding of their mechanisms could improve the safety and efficiency of drug development. We have retrospectively applied large-scale proteomics to blood samples from ILLUMINATE (Investigation of Lipid Level Management to Understand its Impact in Atherosclerotic Events), a trial of torcetrapib (a cholesterol ester transfer protein inhibitor), that involved 15 067 participants at high cardiovascular risk. ILLUMINATE was terminated at a median of 550 days because of significant absolute increases of 1.2% in cardiovascular events and 0.4% in mortality with torcetrapib. The aims of our analysis were to determine whether a proteomic analysis might reveal biological mechanisms responsible for these harmful effects and whether harmful effects of torcetrapib could have been detected early in the ILLUMINATE trial with proteomics.

Methods:

A nested case-control analysis of paired plasma samples at baseline and at 3 months was performed in 249 participants assigned to torcetrapib plus atorvastatin and 223 participants assigned to atorvastatin only. Within each treatment arm, cases with events were matched to controls 1:1. Main outcomes were a survey of 1129 proteins for discovery of biological pathways altered by torcetrapib and a 9-protein risk score validated to predict myocardial infarction, stroke, heart failure, or death.

Results:

Plasma concentrations of 200 proteins changed significantly with torcetrapib. Their pathway analysis revealed unexpected and widespread changes in immune and inflammatory functions, as well as changes in endocrine systems, including in aldosterone function and glycemic control. At baseline, 9-protein risk scores were similar in the 2 treatment arms and higher in participants with subsequent events. At 3 months, the absolute 9-protein derived risk increased in the torcetrapib plus atorvastatin arm compared with the atorvastatin-only arm by 1.08% (P=0.0004). Thirty-seven proteins changed in the direction of increased risk of 49 proteins previously associated with cardiovascular and mortality risk.

Conclusions:

Heretofore unknown effects of torcetrapib were revealed in immune and inflammatory functions. A protein-based risk score predicted harm from torcetrapib within just 3 months. A protein-based risk assessment embedded within a large proteomic survey may prove to be useful in the evaluation of therapies to prevent harm to patients.

Clinical Trial Registration:

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00134264.

Use of inverse modeling to evaluate CENTURY-predictions for soil carbon sequestration in US rain-fed corn production systems

We evaluated the accuracy and precision of the CENTURY soil organic matter model for predicting soil organic carbon (SOC) sequestration under rainfed corn-based cropping systems in the US. This was achieved by inversely modeling long-term SOC data obtained from 10 experimental sites where corn, soybean, or wheat were grown with a range of tillage, fertilization, and organic matter additions. Inverse modeling was accomplished using a surrogate model for CENTURY's SOC dynamics sub-model wherein mass balance and decomposition kinetics equations from CENTURY are coded and solved by using a nonlinear regression routine of a standard statistical software package. With this approach we generated statistics of CENTURY parameters that are associated with the effects of N fertilization and organic amendment on SOC decay, which are not as well quantified as those of tillage, and initial status of SOC. The results showed that the fit between simulated and observed SOC prior to inverse modeling (R2 = 0.41) can be improved to R2 = 0.84 mainly by increasing the rate of SOC decay up to 1.5 fold for the year in which N fertilizer application rates are over 200 kg N ha-1. We also observed positive relationships between C inputs and the rate of SOC decay, indicating that the structure of CENTURY, and therefore model accuracy, could be improved by representing SOC decay as Michaelis-Menten kinetics rather than first-order kinetics. Finally, calibration of initial status of SOC against observed levels allowed us to account for site history, confirming that values should be adjusted to account for soil condition during model initialization. Future research should apply this inverse modeling approach to explore how C input rates and N abundance interact to alter SOC decay rates using C inputs made in various forms over a wider range of rates.

Outcome of nutritional screening in the acute paediatric setting

INTRODUCTION

Multiple nutritional risk assessment tools are available, but there are limited data on their application in the acute setting. We explored the validity of two tools in a tertiary Children's Hospital's acute unit and the cohort's nutritional status using WHO definitions.

METHODS

Prospective study n=300 (median 38 months; 44.6% female; 25.7% ≤12 months). Participants had standard anthropometry measured, all were screened using the Screening Tool for the Assessment of Malnutrition in Paediatrics (STAMP), the Paediatric Malnutrition Screening Tool (PMST) (modified STAMP) and 125 were additionally screened using the Paediatric Yorkhill Malnutrition Screening (PYMS) tool.

RESULTS

The percentages with medium/high nutritional risk were as follows: STAMP 73.1%, PMST 79.3% and PYMS 30%. Height/weight were normally distributed with: 3.4% stunted (height-for-age z-score <-2); aged ≤ 5 years, 6.8% wasted (weight-for-height z-score (WHZ) <-2), 17.9% overweight (WHZ 1-2) and 6.2% obese (WHZ >2); aged >5 years, 5.8% thin (body mass index (BMI)-z-score (BAZ) <-2), 17.3% overweight (BAZ 1-2) and 5.8% obese (BAZ >2). The tools showed poor specificity and variable sensitivities when compared with WHO malnutrition criteria, with positive predictive values of <50%. κ-Analysis also showed poor agreement between the tools and the WHO cut-offs.

CONCLUSION

These results suggest that nutritional screening tools have poor sensitivity and are difficult to interpret in the acute setting. It may be more effective to include the assessment of weight and height and nutritional intake in the context of the acute presentation as part of routine clinical assessment rather than relying on screening tools to identify those at risk.

Dysregulation of follicle development in a mouse model of premature ovarian insufficiency

Premature ovarian insufficiency (POI) occurs in 1% of reproductive-age women. The ovarian manifestation ranges from the presence of a variable population of follicles (follicular) to the absence of follicles (afollicular), and in the majority of cases the cause is unknown. A transgenic mouse model of follicular POI, the Double Mutant (DM), arises from oocyte-specific deletion of Mgat1 and C1galt1 required for the generation of O- and N-glycans. DM females are subfertile at 6 weeks, infertile by 9 weeks and exhibit POI by 12 weeks of age. In this study we investigate the cause of the reduced fertility at 6 weeks and infertility at 9 weeks of DM females. Ovary sections were used to analyse follicle and corpora lutea (CL) numbers, apoptosis, and levels of laminin and 3β-hydroxysteroid dehydrogenase using immunohistochemistry. After POI, DM females unexpectedly remained sexually receptive. At both 6 and 9 weeks, DM ovaries contained more primary follicles, however, at 9 weeks DM follicles were proportionally healthier, revealed by TUNEL analysis compared with Controls. In 9 week DM ovaries (collected post-mating), secondary follicles had theca and basal lamina structure abnormalities, whilst preovulatory follicles failed to ovulate resulting in the presence of numerous luteinised unruptured follicles, indicative of ovulation failure. Finally, DM ovaries contained more regressing CL with decreased luteal cell apoptosis indicative of a defect in CL regression. Identifying these follicular modifications have provided insight into the aetiology of a model of POI and highlight targets to investigate with the hope of developing new fertility treatments.

Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease

IMPORTANCE

Precise stratification of cardiovascular risk in patients with coronary heart disease (CHD) is needed to inform treatment decisions.

OBJECTIVE

To derive and validate a score to predict risk of cardiovascular outcomes among patients with CHD, using large-scale analysis of circulating proteins.

DESIGN, SETTING, AND PARTICIPANTS

Prospective cohort study of participants with stable CHD. For the derivation cohort (Heart and Soul study), outpatients from San Francisco were enrolled from 2000 through 2002 and followed up through November 2011 (≤11.1 years). For the validation cohort (HUNT3, a Norwegian population-based study), participants were enrolled from 2006 through 2008 and followed up through April 2012 (5.6 years).

EXPOSURES

Using modified aptamers, 1130 proteins were measured in plasma samples.

MAIN OUTCOMES AND MEASURES

A 9-protein risk score was derived and validated for 4-year probability of myocardial infarction, stroke, heart failure, and all-cause death. Tests, including the C statistic, were used to assess performance of the 9-protein risk score, which was compared with the Framingham secondary event model, refit to the cohorts in this study. Within-person change in the 9-protein risk score was evaluated in the Heart and Soul study from paired samples collected 4.8 years apart.

RESULTS

From the derivation cohort, 938 samples were analyzed, participants' median age at enrollment was 67.0 years, and 82% were men. From the validation cohort, 971 samples were analyzed, participants' median age at enrollment was 70.2 years, and 72% were men. In the derivation cohort, C statistics were 0.66 for refit Framingham, 0.74 for 9-protein, and 0.75 for refit Framingham plus 9-protein models. In the validation cohort, C statistics were 0.64 for refit Framingham, 0.70 for 9-protein, and 0.71 for refit Framingham plus 9-protein models. Adding the 9-protein risk score to the refit Framingham model increased the C statistic by 0.09 (95% CI, 0.06-0.12) in the derivation cohort, and in the validation cohort, the C statistic was increased by 0.05 (95% CI, 0.02-0.09). Compared with the refit Framingham model, the integrated discrimination index for the 9-protein model was 0.12 (95% CI, 0.08-0.16) in the derivation cohort and 0.08 (95% CI, 0.05-0.10) in the validation cohort. In analysis of paired samples among 139 participants with cardiovascular events after the second sample, absolute within-person annualized risk increased more for the 9-protein model (median, 1.86% [95% CI, 1.15%-2.54%]) than for the refit Framingham model (median, 1.00% [95% CI, 0.87%-1.19%]) (P = .002), while among 375 participants without cardiovascular events, both scores changed less and similarly (P = .30).

CONCLUSIONS AND RELEVANCE

Among patients with stable CHD, a risk score based on 9 proteins performed better than the refit Framingham secondary event risk score in predicting cardiovascular events, but still provided only modest discriminative accuracy. Further research is needed to assess whether the score is more accurate in a lower-risk population.

Association of growth differentiation factor 11/8, putative anti-ageing factor, with cardiovascular outcomes and overall mortality in humans: analysis of the Heart and Soul and HUNT3 cohorts

AIMS

Growth differentiation factor 11 and/or its homologue growth differentiation factor 8 (GDF11/8) reverses age-related cardiac hypertrophy and vascular ageing in mice. We investigated whether GDF11/8 associates with cardiovascular outcomes, left ventricular hypertrophy (LVH), or age in humans.

METHODS AND RESULTS

We measured plasma GDF11/8 levels in 928 participants with stable ischaemic heart disease in the Heart and Soul study. We adjudicated heart failure hospitalization, stroke, myocardial infarction, death, and their composite endpoint. Left ventricular hypertrophy was evaluated by echocardiography. We used multivariable Cox proportional hazards models to compare rates of cardiovascular events and death across GDF11/8 quartiles and logistic regression models to evaluate the association between GDF11/8 and LVH. Four hundred and fifty participants (48.5%) experienced a cardiovascular event or death during 8.9 years of follow-up. The adjusted risk of the composite endpoint was lower in the highest compared with the lowest GDF11/8 quartile [hazard ratio (HR), 0.45; 95% confidence interval (CI), 0.33-0.60; P < 0.001]. We replicated this relationship of GDF11/8 to adverse events in 971 participants in the HUNT3 cohort (adjusted HR, 0.34; 95% CI, 0.23-0.51; P < 0.001). Left ventricular hypertrophy was present in 368 participants (39.7%) at baseline. Participants in the highest quartile of GDF11/8 were less likely to have LVH than those in the lowest quartile (adjusted OR, 0.55; 95% CI, 0.35-0.86; P = 0.009). GDF11/8 levels were lower in older individuals (P < 0.001).

CONCLUSION

In patients with stable ischaemic heart disease, higher GDF11/8 levels are associated with lower risk of cardiovascular events and death. Our findings suggest that GDF11/8 has similar cardioprotective properties in humans to those demonstrated in mice.

Validation of a blood protein signature for non-small cell lung cancer

Background

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results

Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.

Conclusions

Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.

A TaqMan-based multiplex real-time PCR assay for the simultaneous detection of Wuchereria bancrofti and Brugia malayi

With the Global Program for the Elimination of Lymphatic Filariasis continuing to make strides towards disease eradication, many locations endemic for the causative parasites of lymphatic filariasis are realizing a substantial decrease in levels of infection and rates of disease transmission. However, with measures of disease continuing to decline, the need for time-saving and economical molecular diagnostic assays capable of detecting low levels of parasite presence is increasing. This need is greatest in locations co-endemic for both Wuchereria bancrofti and Brugia parasites because testing for both causative agents individually results in significant increases in labor and reagent costs. Here we describe a multiplex, TaqMan-based, real-time PCR assay capable of simultaneously detecting W. bancrofti and Brugia malayi DNA extracted from human bloodspots or vector mosquito pools. With comparable sensitivity to established singleplex assays, this assay provides significant cost and labor savings for disease monitoring efforts in co-endemic locations.

Early detection of malignant pleural mesothelioma in asbestos-exposed individuals with a noninvasive proteomics-based surveillance tool

BACKGROUND

Malignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.

METHODOLOGY/PRINCIPAL FINDINGS

We conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.

SIGNIFICANCE

The SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.

Tug of war in the haematopoietic stem cell niche: do myeloma plasma cells compete for the HSC niche?

In the adult mammal, normal haematopoiesis occurs predominantly in the bone marrow, where primitive haematopoietic stem cells (HSC) and their progeny reside in specialised microenvironments. The bone marrow microenvironment contains specific anatomical areas (termed niches) that are highly specialised for the development of certain blood cell types, for example HSCs. The HSC niche provides important cell–cell interactions and signalling molecules that regulate HSC self-renewal and differentiation processes. These same signals and interactions are also important in the progression of haematological malignancies, such as multiple myeloma (MM). This review provides an overview of the bone marrow microenvironment and its involvement in normal, physiological HSC maintenance and plasma cell growth throughout MM disease progression.

Impact of historical land-use changes on greenhouse gas exchange in the U.S. Great Plains, 1883-2003

European settlement of North America has involved monumental environmental change. From the late 19th century to the present, agricultural practices in the Great Plains of the United States have dramatically reduced soil organic carbon (C) levels and increased greenhouse gas (GHG) fluxes in this region. This paper details the development of an innovative method to assess these processes. Detailed land-use data sets that specify complete agricultural histories for 21 representative Great Plains counties reflect historical changes in agricultural practices and drive the biogeochemical model, DAYCENT, to simulate 120 years of cropping and related ecosystem consequences. Model outputs include yields of all major crops, soil and system C levels, soil trace-gas fluxes (N2O emissions and CH4 consumption), and soil nitrogen mineralization rates. Comparisons between simulated and observed yields allowed us to adjust and refine model inputs, and then to verify and validate the results. These verification and validation exercises produced measures of model fit that indicated the appropriateness of this approach for estimating historical changes in crop yield. Initial cultivation of native grass and continued farming produced a significant loss of soil C over decades, and declining soil fertility led to reduced crop yields. This process was accompanied by a large GHG release, which subsided as soil fertility decreased. Later, irrigation, nitrogen-fertilizer application, and reduced cultivation intensity restored soil fertility and increased crop yields, but led to increased N2O emissions that reversed the decline in net GHG release. By drawing on both historical evidence of land-use change and scientific models that estimate the environmental consequences of those changes, this paper offers an improved way to understand the short- and long-term ecosystem effects of 120 years of cropping in the Great Plains.

Abstract 2812: Detection of mesothelioma in asbestos exposed individuals with aptamer proteomic technology

Malignant pleural mesothelioma is an aggressive, asbestos-related pulmonary cancer which is increasing in incidence. This disease causes an estimated 15,000 to 20,000 deaths per year worldwide. Between 1940 and 1979, approximately 27.5 million people were occupationally exposed to asbestos in the United States. The incidence of pleural mesothelioma in the US is 3,000 new cases/year and will not peak for another 20 years. Mesothelioma has a latency period of 20-40 years from asbestos exposure, but once diagnosed this aggressive disease is often fatal within 14 months. Because diagnosis is difficult, most patients present at a clinically advanced stage where possibility of cure is minimal. Therefore, we have conducted a broad search for new serum biomarkers with our aptamer-based proteomic platform and defined a classifier for the detection of mesothelioma in asbestos exposed individuals.

Secreted proteins and those released during apoptosis from tumor cells and surrounding tissues contain important biologic information that may enable early diagnosis and prognostic and therapeutic decisions in oncology. However, there is great difficulty in finding and quantifying such signals for large numbers of low abundance proteins. We therefore created a highly multiplexed proteomic assay that currently measures ∼850 proteins simultaneously from 15ul blood, with throughput of 300 samples/day. The average dynamic range of each protein in the assay is &gt;3 logs – with nearly seven logs of dynamic range achieved through multiple dilutions – and the median lower limit of quantification is below 1 pM. The median coefficient of variation for each protein is &lt;5%. This assay performance arises from the selection of high affinity aptamers that bind selectively to their target proteins with slow off-rates.

The objective of this study was to discover proteins which are involved in malignant mesothelioma and to develop algorithms and classifiers for detection of the disease. To this end, blood samples from three study centers were analyzed with the aptamer proteomics platform in a prospectively designed case:control study. We compared 170 serum samples from 90 patients diagnosed with malignant mesothelioma to 80 asbestos exposed controls. These samples were divided into 75% for training and 25% set aside as a blinded test set for classifier development and verification.

Nineteen significant biomarkers were discovered by applying a backwards selection strategy. Classifiers were built with subsets of these biomarkers resulting in an AUC of 0.95 or better with an overall accuracy of 93%. Applying a 13-plex Random Forest classifier to the blinded test set resulted in a specificity of 100% and sensitivity of 80% for distinction of asbestos exposed controls from mesothelioma, including detection of 15/19 Stage I/II cases. Refinement and confirmation of classifier performance will be established through ongoing validation studies.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2812. doi:10.1158/1538-7445.AM2011-2812

Cloning the Gene for the Malolactic Fermentation of Wine from Lactobacillus delbrueckii in Escherichia coli and Yeasts

The gene responsible for the malolactic fermentation of wine was cloned from the bacterium Lactobacillus delbrueckii into Escherichia coli and the yeast Saccharomyces cerevisiae. This gene codes for the malolactic enzyme which catalyzes the conversion of l-malate to l-lactate. A genetically engineered yeast strain with this enzymatic capability would be of considerable value to winemakers. L. delbrueckii DNA was cloned in E. coli on the plasmid pBR322, and two E. coll clones able to convert l-malate to l-lactate were selected. Both clones contained the same 5-kilobase segment of L. delbrueckii DNA. The DNA segment was transferred to E. coli-yeast shuttle vectors, and gene expression was analyzed in both hosts by using enzymatic assays for l-lactate and l-malate. When grown nonaerobically for 5 days, E. coli cells harboring the malolactic gene converted about 10% of the l-malate in the medium to l-lactate. The best expression in S. cerevisiae was attained by transfer of the gene to a shuttle vector containing both a yeast 2-mum plasmid and yeast chromosomal origin of DNA replication. When yeast cells harboring this plasmid were grown nonaerobically for 5 days, ca. 1.0% of the l-malate present in the medium was converted to l-lactate. The L. delbrueckii controls grown under these same conditions converted about 25%. A laboratory yeast strain containing the cloned malolactic gene was used to make wine in a trial fermentation, and about 1.5% of the l-malate in the grape must was converted to l-lactate. Increased expression of the malolactic gene in wine yeast will be required for its use in winemaking. This will require an increased understanding of the factors governing the expression of this gene in yeasts.

Genetics of platelet reactivity in normal, healthy individuals

BACKGROUND

The Platelet Function Analyzer-100 (PFA-100) is widely used to measure platelet reactivity in whole blood under high shear.

OBJECTIVE

To characterize the genetic component of platelet reactivity among normal individuals, using the PFA-100.

METHODS

We compared baseline platelet reactivity with sex, age, platelet count, hematocrit, plasma von Willebrand factor antigen (VWF:Ag), and alleles of seven candidate genes: integrin subunits alpha2 (ITGA2) and beta3 (ITGB3), platelet glycoproteins GPIbalpha (GP1BA) and GPVI (GP6), purinogenic receptors (P2RY1 and P2RY12) and cyclooxygenase-1 (COX1).

RESULTS

Based on linear and logistic regression models, we report an inverse correlation between baseline closure time (CT) initiated by collagen plus epinephrine (CEPI) and plasma VWF:Ag level, ITGA2 807T and P2RY1 893C, and an inverse correlation between baseline CT initiated by collagen plus adenosine diphosphate (CADP) and P2RY1 893C or GP1BA -5C.

CONCLUSIONS

These results indicate that genetic polymorphisms in ITGA2 and P2RY1 combine with plasma VWF:Ag levels to modulate baseline platelet reactivity in response to collagen plus EPI, while genetic differences in P2RY1 and GP1BA significantly effect platelet responses to collagen plus ADP. Our results demonstrate that the PFA-100 can be used to evaluate the effects of genetic predictors of platelet function.

Seroprevalence of dengue in Trinidad using rapid test kits: a cord blood survey

A cross-sectional sero-epidemiological study was conducted to determine the prevalence of dengue in Trinidad. Two commercial rapid test kits, PanBio Dengue Duo IgM and IgG Rapid Strip Test and the Bio-Check Plus Dengue G/M Cassette Test (Brittney) were used. The immunosorbent assay (ELISA) (FOCUS Technologies, California) was used as the control. One hundred and twenty five cord blood samples were collected (46 from Mt. Hope Women's Hospital (MH) and 79 from the San Fernando General Hospital (SF)). All blood samples were tested in accordance with the two rapid kits and ELISA assay manufacturer's instructions. From 125 cord blood samples, the IgG FOCUS ELISA results showed 93.5 and 95% infections at MH and SF, respectively. Whereas the Brittney and PanBio kits showed 10.9 and 5.1%, and 26.1 and 50.6% for MH and SF, respectively. Based on the FOCUS ELISA (control) assays, the combined seroprevalence rate from north and south Trinidad was 94.4%. IgG and IgM sensitivity and specificity levels were higher in the PanBio than Brittney test kits. The high seroprevalence rates observed in Trinidad are discussed to stimulate more research to explain this phenomenon and to prevent the Southeast Asian scenario from developing in the Americas.

Biomarkers and surrogate end points for fit-for-purpose development and regulatory evaluation of new drugs

A consistent framework for the acceptance and qualification of biomarkers for regulatory use is needed to facilitate innovative and efficient research and subsequent application of biomarkers in drug development. One key activity is biomarker qualification, a graded, "fit-for-purpose" evidentiary process linking a biomarker with biology and clinical end points. A biomarker consortium model will distribute cost and risk, and drive efficient execution of research and ultimately regulatory acceptance of biomarkers for specific indications.

A cost-effectiveness approach to the qualification and acceptance of biomarkers

The flow of new medicines to patients depends on the development of new biomarkers and their correct interpretation, yet there are no widely accepted and practically applicable criteria that facilitate adequate biomarker qualification. As a result, case-by-case qualifications are based on subjective assessments that do not lead to optimal decisions for patients, which have contributed to the 'stagnation' in drug productivity identified by the FDA. An alternative is to qualify biomarkers in terms of cost effectiveness using a set of principles that enable the evaluation of biomarkers even with incomplete knowledge. This approach could minimize harm to patients, improve access to medicines and reduce healthcare costs.

The ultimate model organism: progress in experimental medicine

Experimental medicine is the use of innovative measurements, models and designs in studying human subjects for establishing proof of mechanism and concept of new drugs, for exploring the potential for market differentiation for successful drug candidates, and for efficiently terminating the development of unsuccessful ones. Humans are the ultimate 'model' because of the uncertain validity and efficacy of novel targets and drug candidates that emerge from genomics, combinatorial chemistry and high-throughput screening and the use of poorly predictive preclinical models. The in-depth investigation of the effects of drugs and the nature of disease progression is becoming ever more feasible because of advances in clinical biomarkers.

Social images of medicine and dentistry in Japan. An exploratory study using correspondence analysis

OBJECTIVE

To investigate social images associated with dentistry in comparison with nine other medical disciplines.

DESIGN

A questionnaire survey among members of the general public. Subjects were asked to state, in not more than five words, the images which they associated with each of the ten disciplines.

SETTING

Komaki City, Shikatsu Town and Nagoya City in Japan.

PARTICIPANTS

261 respondents from a convenience sample of 300 residents, not associated with any branch of medicine.

OUTCOME MEASURES

Frequency distribution of word images used on at least five occasions and a correspondence analysis of the responses for the ten disciplines.

RESULTS

Of the 163 coded image items, 60 were related to internal medicine, 56 to dentistry, 55 to dermatology, 51 to orthopaedic surgery, 51 to ophthalmology, 50 to surgery, 47 to obstetrics and gynaecology, 43 to otolaryngology, 40 to paediatrics and 33 to psychiatry. Correspondence analysis applied to the 163 items and 10 medical disciplines indicated that three similar paired image groups were found, namely between dermatology and ophthalmology, surgery and orthopaedic surgery, and between dentistry and internal medicine, which were the more commonly encountered disciplines across all age groups. However, compared with the other specialities, dentistry had a significantly greater association with pain, this response being four times more common than for surgery.

CONCLUSIONS

This group of members of the public in Japan perceived dentistry-associated images in a similar way to internal medicine, but the negative associations with pain need to be addressed by the dental profession and health educators alike.

DNA sequence and analysis of human chromosome 9

Chromosome 9 is highly structurally polymorphic. It contains the largest autosomal block of heterochromatin, which is heteromorphic in 6-8% of humans, whereas pericentric inversions occur in more than 1% of the population. The finished euchromatic sequence of chromosome 9 comprises 109,044,351 base pairs and represents >99.6% of the region. Analysis of the sequence reveals many intra- and interchromosomal duplications, including segmental duplications adjacent to both the centromere and the large heterochromatic block. We have annotated 1,149 genes, including genes implicated in male-to-female sex reversal, cancer and neurodegenerative disease, and 426 pseudogenes. The chromosome contains the largest interferon gene cluster in the human genome. There is also a region of exceptionally high gene and G + C content including genes paralogous to those in the major histocompatibility complex. We have also detected recently duplicated genes that exhibit different rates of sequence divergence, presumably reflecting natural selection.