Human chorionic gonadotropin (hCG) stimulates testosterone production by the testicles. Because of the potential for abuse, hCG is banned (males only) in most sports and has been placed on the World Anti-Doping Agency list of prohibited substances. Intact hCG, free β-subunit (hCGβ), and β-subunit core fragment (hCGβcf) are the major variants or isoforms in urine. Immunoassays are used by antidoping laboratories to measure urinary hCG. Cross-reactivity with isoforms differs among immunoassays, resulting in widely varying results. We developed a sequential im-munoextraction method with LC-MS/MS detection for quantification of intact hCG, hCGβ, and hCGβcf in urine.
hCG isoforms were immunoextracted with antibody-conjugated magnetic beads and digested with trypsin, and hCGβ and hCGβcf unique peptides were quantified by LC-MS/MS with the corresponding heavy peptides as internal standard. hCG isoform concentrations were determined in urine after administration of hCG, and the intact hCG results were compared to immunoassay results.
The method was linear to 20 IU/L. Total imprecision was 6.6%-13.7% (CV), recovery ranged from 91% to 109%, and the limit of quantification was 0.2 IU/L. Intact hCG predominated in the urine after administration of 2 hCG formulations. The window of detection ranged from 6 to 9 days. Mean immunoassay results were 12.4-15.5 IU/L higher than LC-MS/MS results.
The performance characteristics of the method are acceptable for measuring hCG isoforms, and the method can quantify intact hCG and hCGβ separately. The limit of quantification will allow LC-MS/MS hCG reference intervals to be established in nondoping male athletes for improved doping control.
The management options for the autosomal recessive neurodegenerative disorder spinal muscular atrophy (SMA) are evolving; however, their efficacy may require presymptom diagnosis and continuous treatment. To identify presymptomatic SMA patients, we created a DNA-based newborn-screening assay to identify the homozygous deletions of the SMN1 (survival of motor neuron 1, telomeric) gene observed in 95%–98% of affected patients.
We developed primers that amplify a 52-bp PCR product from homologous regions in the SMN1 and SMN2 (survival of motor neuron 2, centromeric) genes that flank a divergent site at site c.840. Post-PCR high-resolution melt profiling assessed the amplification product, and we used a unique means of melt calibration to normalize profiles. Samples that we had previously characterized for the numbers of SMN1 and SMN2 copies established genotypes associated with particular profiles. The system was evaluated with approximately 1000 purified DNA samples, 100 self-created dried blood spots, and >1200 dried blood spots from newborn-screening tests.
Homozygous deletion of SMN1 exon 7 produced a distinctive melt profile that identified SMA patients. Samples with different numbers of SMN1 and SMN2 copies were resolved by their profiles. All samples with homozygous deletions were unambiguously recognized, and no normal sample was misidentified as a positive.
This assay has characteristics suitable for population-based screening. A reliable screening test will facilitate the identification of an SMA-affected cohort to receive early intervention to maximize the benefit from treatment. A prospective screening trial will allow the efficacy of treatment options to be assessed, which may justify the inclusion of SMA as a target for population screening.
The analysis of bodily fluids using SELDI-TOF MS has been reported to identify signatures of spectral peaks that can be used to differentiate patients with a specific disease from normal or control patients. This report is the 2nd of 2 companion articles describing a validation study of a SELDI-TOF MS approach with IMAC surface sample processing to identify prostatic adenocarcinoma.
We sought to derive a decision algorithm for classification of prostate cancer from SELDI-TOF MS spectral data from a new retrospective sample cohort of 400 specimens. This new cohort was selected to minimize possible confounders identified in the previous study described in the companion paper.
The resulting new classifier failed to separate patients with prostate cancer from biopsy-negative controls; nor did it separate patients with prostate cancer with Gleason scores <7 from those with Gleason scores ≥7.
In this, the 2nd stage of our planned validation process, the SELDI-TOF MS– based protein expression profiling approach did not perform well enough to advance to the 3rd (prospective study) stage. We conclude that the results from our previous studies—in which differentiation between prostate cancer and noncancer was demonstrated—are not generalizable. Earlier study samples likely had biases in sample selection that upon removal, as in the present study, resulted in inability of the technique to discriminate cancer from non-cancer cases.
It is critical to develop new metrics to determine whether high density lipoprotein (HDL) is cardioprotective in humans. One promising approach is HDL particle concentration (HDL-P) – the size and concentration of HDL in plasma or serum. However, the two methods currently used to determine HDL-P yield concentrations that differ more than 5-fold. We therefore developed and validated an improved approach to quantify HDL-P, termed calibrated ion mobility analysis (calibrated IMA).
HDL was isolated from plasma by ultracentrifugation, introduced into the gas phase with electrospray ionization, separated by size, and quantified by particle counting. A calibration curve constructed with purified proteins was used to correct for the ionization efficiency of HDL particles.
The concentrations of gold nanoparticles and reconstituted HDLs measured by calibrated IMA were indistinguishable from concentrations determined by orthogonal methods. In plasma of control (n=40) and cerebrovascular disease (n=40) subjects, three subspecies of HDL were reproducibility measured, with an estimated total HDL-P of 13.4±2.4 µM (mean±SD). HDL-C accounted for 48% of the variance in HDL-P. HDL-P was significantly lower in subjects with cerebrovascular disease, and this difference remained significant after adjustment for HDL cholesterol levels.
Calibrated IMA accurately and reproducibly determined the concentration of gold nanoparticles and synthetic HDL, strongly suggesting the method could accurately quantify HDL particle concentration. Importantly, the estimated stoichiometry of apoA-I determined by calibrated IMA was 3–4 per HDL particle, in excellent agreement with current structural models. Furthermore, HDL-P associated with cardiovascular disease status in a clinical population independently of HDL cholesterol.
cardiovascular disease; carotid cerebrovascular disease; native electrospray ionization; HDL
Risk prediction is an integral part of the current US guidelines for cardiovascular disease in women. While current risk prediction algorithms exist to identify women at elevated 10-year risk of cardiovascular disease (CVD), clinicians and researchers have been interested in developing novel biomarkers that might improve predictive accuracy further. These biomarkers have led to important insights in the pathophysiology of CVD, but their ability to improve prediction or guide preventive therapy has been more mixed. Women have a lower incidence of CVD than men and the effect of a number of traditional biomarkers on CVD risk differs. Both of these factors influence the ability to accurately predict CVD risk.
In this article, we review the distinctive aspects of CVD risk prediction in women, discuss the statistical challenges to improved risk prediction, and discuss a number of biomarkers in varying stages of development with a range of performance in prediction.
A variety of biomarkers from different pathophysiologic pathways have evaluated for improving CVD risk. While many have been incompletely studied or have not been shown to improve risk prediction in women, others, such as high sensitivity troponin T, have shown promise in improving risk prediction. Increasing inclusion of women in CVD studies will be crucial to providing opportunities to evaluate future biomarkers.
Fetuin-A, a protein secreted primarily by the liver, has been associated with non-alcoholic fatty liver disease and insulin resistance. In a recent study, higher circulating fetuin-A was associated with cardiovascular events, particularly ischemic stroke. However, these data have not been replicated.
A nested case-control design was utilized to examine the relationship between fetuin-A and ischemic stroke among female participants of the Nurses’ Health Study. Fetuin-A was measured in blood samples collected and stored between 1989–1990. A total of 459 incident cases of ischemic stroke were identified and confirmed by medical records according to the National Survey of Stroke criteria between 1990–2006 and matched to 459 controls by age, menopausal status, postmenopausal hormone use, and smoking status. The association between fetuin-A and ischemic stroke was modeled using conditional logistic regression.
Circulating Fetuin-A was higher in women (P<0.01), who reported increased body mass index (BMI≥25 kg/m2), total cholesterol ≥200 mg/dL, high-sensitivity C-reactive protein ≥3 mg/L and current hormone use at baseline. Significant partial Spearman correlations (P<0.001), adjusted for matching factors, were found between measured concentrations of fetuin-A and triglycerides (r=0.20), C-reactive protein (r=0.14), and BMI (r=0.15). Fetuin-A quartiles were not significantly associated with increased risk of incident ischemic stroke when adjusted for matching factors (RR=1.03; 95% CI: 0.69–1.54, extreme quartiles); additional adjustment for lifestyle factors or CVD risk factors and biomarkers did not alter results.
In this sample of women, fetuin-A was not significantly associated with risk of ischemic stroke. Further research is needed to explore this association.
Ischemic stroke; fetuin-A; α2-Heremans-Schmid glycoprotein
Endometrial cancer is responsible for ~74,000 deaths amongst women worldwide each year. It is a heterogeneous disease that consists of multiple different histological subtypes. In the United States, the majority of deaths from endometrial carcinoma are attributed to the serous and endometrioid subtypes. An understanding of the fundamental genomic alterations that drive serous and endometrioid endometrial carcinomas lays the foundation for the identification of molecular markers that could improve the clinical management of patients presenting with these tumors.
Herein we review the current state of knowledge of the somatic genomic alterations that are present in serous and endometrioid endometrial tumors. We present this knowledge in a historical context – reviewing the genomic alterations that have been identified over the past two decades or more, from studies of individual genes and proteins, followed by a review of very recent studies that have conducted comprehensive, systematic surveys of genomic, exomic, transcriptomic, epigenomic, and proteomic alterations in serous and endometrioid endometrial carcinomas.
The recent mapping of the genomic landscape of serous and endometrioid endometrial carcinomas has resulted in the first comprehensive molecular classification of these tumors and has distinguished four molecular subgroups: a POLE ultramutated subgroup, a hypermutated/microsatellite unstable subgroup, a copy number low/microsatellite stable subgroup, and a copy number high subgroup. This molecular classification may ultimately serve to refine the diagnosis and treatment of women with endometrioid and serous endometrial tumors.
We investigated the prognostic performance of ST2 with respect to cardiovascular death (CVD) and heart failure (HF) in patients with non–ST-elevation acute coronary syndrome (NSTE-ACS) in a large multinational trial.
Myocytes that are subjected to mechanical stress secrete ST2, a soluble interleukin-1 receptor family member that is associated with HF after STE-ACS.
We measured ST2 with a high-sensitivity assay in all available baseline samples (N = 4426) in patients enrolled in the Metabolic Efficiency With Ranolazine for Less Ischemia in the Non–ST-Elevation Acute Coronary Syndrome Thrombolysis in Myocar-dial Infarction 36 (MERLIN-TIMI 36), a placebo-controlled trial of ranolazine in NSTE-ACS. All events, including cardiovascular death and new or worsening HF, were adjudicated by an independent events committee.
Patients with ST2 concentrations in the top quartile (>35 μg/L) were more likely to be older and male and have diabetes and renal dysfunction. ST2 was only weakly correlated with troponin and B-type natriuretic peptide. High ST2 was associated with increased risk for CVD/HF at 30 days (6.6% vs 1.6%, P <0.0001) and 1 year (12.2% vs 5.2%, P <0.0001). The risk associated with ST2 was significant after adjustment for clinical covariates and biomarkers (adjusted hazard ratio CVD/HF 1.90, 95% CI 1.15–3.13 at 30 days, P = 0.012; 1.51, 95% CI 1.15–1.98 at 1 year, P = 0.003), with a significant integrated discrimination improvement (P < 0.0001). No significant interaction was found between ST2 and ranolazine (Pinteraction = 0.15).
ST2 correlates weakly with biomarkers of acute injury and hemodynamic stress but is strongly associated with the risk of HF after NSTE-ACS. This biomarker and related pathway merit further investigation as potential therapeutic targets for patients with ACS at risk for cardiac remodeling.
Biomarkers for estimating reduced glucose tolerance, insulin sensitivity, or impaired insulin secretion would be clinically useful, since these physiologic measures are important in the pathogenesis of type 2 diabetes mellitus.
We conducted a cross-sectional study in which 94 individuals, of whom 84 had 1 or more risk factors and 10 had no known risk factors for diabetes, underwent oral glucose tolerance testing. We measured 34 protein biomarkers associated with diabetes risk in 250-μL fasting serum samples. We applied multiple regression selection techniques to identify the most informative biomarkers and develop multivariate models to estimate glucose tolerance, insulin sensitivity, and insulin secretion. The ability of the glucose tolerance model to discriminate between diabetic individuals and those with impaired or normal glucose tolerance was evaluated by area under the ROC curve (AUC) analysis.
Of the at-risk participants, 25 (30%) were found to have impaired glucose tolerance, and 11 (13%) diabetes. Using molecular counting technology, we assessed multiple biomarkers with high accuracy in small volume samples. Multivariate biomarker models derived from fasting samples correlated strongly with 2-h postload glucose tolerance (R2 = 0.45, P < 0.0001), composite insulin sensitivity index (R2 = 0.91, P < 0.0001), and insulin secretion (R2 = 0.45, P < 0.0001). Additionally, the glucose tolerance model provided strong discrimination between diabetes vs impaired or normal glucose tolerance (AUC 0.89) and between diabetes and impaired glucose tolerance vs normal tolerance (AUC 0.78).
Biomarkers in fasting blood samples may be useful in estimating glucose tolerance, insulin sensitivity, and insulin secretion.
Oral Δ9-tetrahydrocannabinol (THC) is effective for attenuating cannabis withdrawal and may benefit treatment of cannabis use disorders. Oral fluid (OF) cannabinoid testing, increasing in forensic and workplace settings, could be valuable for monitoring during cannabis treatment.
Eleven cannabis smokers resided on a closed research unit for 51 days, and received daily 0, 30, 60, and 120 mg oral THC in divided doses for 5 days. There was a 5-puff smoked cannabis challenge on the 5th day. Each medication session was separated by 9 days of ad libitum cannabis smoking. OF was collected the evening prior to and throughout oral THC sessions and analyzed by 2-dimensional GC-MS for THC, cannabidiol (CBD), cannabinol (CBN), 11-hydroxy-THC (11-OH-THC), and 11-nor-9-carboxy-THC (THCCOOH).
During all oral THC administrations, THC OF concentrations decreased to ≤78.2, 33.2, and 1.4 μg/L by 24, 48, and 72h, respectively. CBN also decreased over time with concentrations 10-fold lower than THC, with none detected beyond 69h. CBD and 11-OH-THC were rarely detected, only within 19 and 1.6h post smoking, respectively. THCCOOH OF concentrations were dose-dependent and increased over time during 120 mg THC dosing. After cannabis smoking, THC, CBN, and THCCOOH concentrations showed a significant dose-effect and decreased significantly over time.
Oral THC dosing significantly affected OF THCCOOH but minimally contributed to THC OF concentrations; prior ad libitum smoking was the primary source of THC, CBD and CBN. Higher cannabinoid concentrations following active oral THC administrations versus placebo suggest a compensatory effect of THC tolerance on smoking topography.
dronabinol; cannabis; oral fluid; marijuana; delta9-tetrahydrocannabinol
Among the various cardiovascular diseases, heart failure (HF) is projected to have the largest increases in incidence over the coming decades; therefore, improving HF prediction is of significant value. We evaluated whether cardiac troponin T (cTnT) measured with a high-sensitivity assay and N-terminal-pro-B-type natriuretic peptide (NT-proBNP), biomarkers strongly associated with incident HF, improve HF risk prediction in the Atherosclerosis Risk In Communities (ARIC) study.
Using gender-specific models, cTnT and NT-proBNP were added to age and race (“laboratory report” model), and to the ARIC HF model (includes age, race, systolic blood pressure, antihypertensive-medication use, current/former smoking, diabetes, body mass index, prevalent coronary heart disease and heart rate) in 9868 subjects without prevalent HF; area under the receiver operating characteristic curve (AUC), integrated discrimination improvement, net reclassification improvement (NRI) and model fit were described.
Over a mean follow-up of 10.4 years, 970 subjects developed incident HF. Adding cTnT and NT-proBNP to the ARIC HF model significantly improved all statistical parameters (AUCs increased by 0.040 and 0.057; the continuous NRI was 50.7% and 54.7% in women and men, respectively). Interestingly, the simpler laboratory report model was statistically no different than the ARIC HF model.
cTnT and NT-proBNP have significant value in HF risk prediction. A simple gender-specific model that includes age, race, cTnT and NT-proBNP (which can be incorporated in a laboratory report) provides a good model, whereas adding cTnT and NT-proBNP to clinical characteristics results in an excellent HF prediction model.
cardiac troponin T; NT-proBNP; heart failure; ARIC; risk prediction
inhibition; digital PCR; real-time PCR
Rigorous studies are necessary to demonstrate suitability of metabolomics platforms to profile metabolites in archived plasma within epidemiologic studies of human disease, for which attenuation of effect estimates due to measurement error is a key concern.
Using a liquid chromatography-tandem mass spectrometry platform, we quantified 257 metabolites from archived plasma to evaluate metabolite inter-assay reproducibility, reproducibility with delayed processing, and within-person reproducibility over time. Inter-assay reproducibility was assessed with coefficients of variation (CVs) from 60 duplicate plasma samples donated by Nurses’ Health Study and Health Professionals Follow-up Study participants, and 20 quality control pool plasma replicates. Metabolite reproducibility over a 24- to 48-hour processing delay (n=48 samples) and within-person reproducibility over 1-2 years (n=80 samples) were assessed using Spearman and intraclass correlation coefficients (ICCs).
CVs were <20% for 92% of metabolites and generally were similar by plasma anticoagulant type (Heparin or EDTA) and fasting time. Approximately 75% of metabolites were reproducible over delays in processing of blood specimens (Spearman correlation or ICC ≥0.75, comparing immediate and 24-hour delayed processing). Carbohydrates and purine/pyrimidine derivatives were most adversely affected by the processing delay. Ninety percent of metabolites were reproducible over 1-2 years within individuals (Spearman correlation or ICC ≥0.4).
For potential use in epidemiologic studies, the majority of plasma metabolites had low CVs and were reproducible over a 24-hour processing delay and within individuals over 1-2 years. Certain metabolites, such as carbohydrates and purine/pyrimidine derivatives, may be challenging to evaluate if samples have delayed processing.
Blood sample collection; Cohort studies; Metabolomics; Reproducibility of Results; Tandem mass spectrometry
The measurement of hemoglobin concentration ([Hb]) is performed routinely as a part of a complete blood cell count to evaluate the oxygen-carrying capacity of blood. Devices currently available to physicians and clinical laboratories for measuring [Hb] are accurate, operate on small samples and provide results rapidly, but may be prohibitively expensive for resource-limited settings. The unavailability of accurate but inexpensive diagnostic tools often precludes proper diagnosis of anemia in low-income developing countries. Therefore, we developed a simple paper-based assay for measuring [Hb].
A 20-μL droplet of a mixture of blood and Drabkin’s reagent was deposited onto patterned chromatography paper. The resulting blood stain was digitized with a portable scanner and analyzed. The mean color intensity of the blood stain was used to quantify [Hb]. We compared the performance of the paper-based Hb assay with a hematology analyzer (comparison method) using blood samples from 54 subjects.
The values of [Hb] measured using the paper-based assay and the comparison method were highly correlated (R2 = 0.9598); the standard deviation of the difference between the two measurements was 0.62 g/dL. The assay was accurate within 1 g/dL 90.7% of the time, overestimating [Hb] by ≥1 g/dL in 1.9% and underestimating [Hb] by ≥1 g/dL in 7.4% of the subjects.
This study demonstrates the feasibility of the paper-based Hb assay. This simple, low-cost test should be useful for diagnosing anemia in resource-limited settings, particularly in the context of care for malaria, HIV and sickle cell disease patients in sub-Saharan Africa.
The addition of a calibration curve with every run is both time-consuming and expensive for clinical mass spectrometry assays. We present alternative calibration strategies that eliminate the need for a calibration curve except as required by laboratory regulations.
We measured serum nortriptyline concentrations prospectively in 68 patients on 16 days over a 2-month period using a method employing calibration schemes that relied on the measurement of the response ratio (RR) corrected by the response factor (RF), i.e., a measurement of the RR for an equimolar mixture of the analyte and internal standard. Measurements were taken with contemporaneous RF (cRF) measurements as well as sporadic RF (sRF) measurements. The measurements with these alternative calibration schemes were compared against the clinical results obtained by interpolation on a calibration curve, and those differences were evaluated for analytical and clinical significance.
The differences between the values measured by cRF and sRF calibration and interpolation on a calibration curve were not significant (P = 0.088 and P = 0.091, respectively). Both the cRF-and sRF-based calibration results demonstrated a low mean bias against the calibration curve interpolations of 3.69% (95% CI, −15.8% to 23.2%) and 3.11% (95% CI, −16.4% to 22.6%), respectively. When these results were classified as subtherapeutic, therapeutic, or supratherapeutic, there was categorical agreement in 95.6% of the cRF calibration results and 94.1% of the sRF results.
cRF and sRF calibration in a clinically validated liquid chromatography–tandem mass spectrometry assay yields results that are analytically and clinically commensurate to those produced by interpolation with a calibration curve.
Over the past 2 decades, clinical studies have provided evidence that cerebrospinal fluid (CSF) amyloid β1–42 (Aβ1–42), total τ(t-τ), and τ phosphorylated at Thr181 (p-τ181) are reliable biochemical markers of Alzheimer disease (AD) neuropathology.
In this review, we summarize the clinical performance and describe the major challenges for the analytical performance of the most widely used immunoassay platforms [based on ELISA or microbead-based multianalyte profiling (xMAP) technology] for the measurement of CSF AD biomarkers (Aβ1–42, t-τ, and p-τ181). With foundational immunoassay data providing the diagnostic and prognostic values of CSF AD biomarkers, the newly revised criteria for the diagnosis of AD include CSF AD biomarkers for use in research settings. In addition, it has been suggested that the selection of AD patients at the predementia stage by use of CSF AD biomarkers can improve the statistical power of clinical trial design. Owing to the lack of a replenishable and commutable human CSF-based standardized reference material (SRM) and significant differences across different immunoassay platforms, the diagnostic–prognostic cutpoints of CSF AD biomarker concentrations are not universal at this time. These challenges can be effectively met in the future, however, through collaborative ongoing standardization efforts to minimize the sources of analytical variability and to develop reference methods and SRMs.
Measurements of CSF Aβ1–42, t-τ, and p-τ181 with analytically qualified immunoassays reliably reflect the neuropathologic hallmarks of AD in patients at the early predementia stage of the disease and even in presymptomatic patients. Thus these CSF biomarker tests are useful for early diagnosis of AD, prediction of disease progression, and efficient design of drug intervention clinical trials.
Luminescent nanobioprobes with cell-targeting specificity are likely to find important applications in bioanalysis, biomedicine, and clinical diagnosis. Quantum dots (QDs) are unique and promising materials for such a purpose because of their fluorescence and large surface area for attaching cell-targeting molecules.
We produced water-dispersible QDs by coating hydrophobic QDs with small amphiphilic polyethylene glycol (PEG) molecules via hydrophobic interactions. We covalently coupled folate (FA) onto the water-dispersible PEG-coated QDs (PEG-QDs) to produce FA-coupled PEG-QDs (FA-PEG-QDs).
These FA-PEG-QD nanoparticles functioned as fluorescent nanobioprobes that specifically recognized folate receptors (FRs) overexpressed in human nasopharyngeal cells (KB cells) but not in an FR-deficient lung carcinoma cell line (A549 cells). Using confocal fluorescence microscopy, we demonstrated uptake of FA-PEG-QDs by KB cells but no uptake of folate-free PEG-QDs. The specificity of this receptor-mediated internalization was confirmed by comparing the uptake by KB vs A549 cells.
Our results suggest that such cell-targeting fluorescent nanobioprobes are potentially very powerful tools for recognizing target cells and delivering and tracking drugs and other therapeutic materials.
The recent revolutionary advances made in genome-wide sequencing technology have transformed biology and molecular diagnostics, allowing new sRNA (small RNA) classes to be discovered as potential disease-specific biological indicators. Cell-free microRNAs (miRNAs) have been shown to exist stably in a wide spectrum of body fluids and their expression profiles have been shown to reflect an assortment of physiological conditions, underscoring the utility of this new class of molecules to function as noninvasive biomarkers of disease.
We summarize information on the known mechanisms of miRNA protection and release into extracellular space and compile the current literature on extracellular miRNAs that have been investigated as biomarkers of 20 different cancers, 11 organ damage conditions and 10 diverse disease states. We also discuss the various strategies involved in the miRNA biomarker discovery workflow and provide a critical opinion on the impediments faced by this advancing field that need to be overcome in the laboratory.
The field of miRNA-centered diagnostics is still in its infancy, and basic questions with regard to the exact role of miRNAs in the pathophysiology of diseases, and the mechanisms of their release from affected cells into biological fluids are yet to be completely understood. Nevertheless, these noninvasive micromarkers have immense potential in translational medicine not only for use in monitoring the efficacy and safety of therapeutic regimens but also to guide the diagnosis of diseases, to determine the risk of developing diseases or conditions, and more importantly, to inform treatment options.
Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine produced in cardiovascular cells under conditions of inflammation and oxidative stress, and is emerging as an important prognostic marker in individuals with and without existing cardiovascular disease. Thus, we examined the clinical and genetic correlates of circulating GDF-15 levels, which have not been collectively investigated.
A total of 2,991 participants of the Framingham Offspring Study free of clinically overt cardiovascular disease underwent measurement of plasma GDF-15 levels (mean age 59 years, 56% women). Clinical correlates of GDF-15 were examined in multivariable analyses. A genome-wide association study of GDF-15 levels was then conducted, including participants of the Framingham Offspring Study and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study.
GDF-15 was positively associated with age, smoking, antihypertensive treatment, diabetes, worse kidney function, and non-steroidal anti-inflammatory drug use, but it was negatively associated with total and high-density lipoprotein cholesterol. Clinical correlates accounted for 38% of inter-individual variation in circulating GDF-15, whereas genetic factors account for up to 38% of residual variability (h2=0.38; P=2.5 × 10−11). We identified one genome-wide significant locus, which included the GDF15 gene, on chromosome 19p13.11 associated with GDF-15 concentrations (smallest P=2.74−32 for rs888663). Conditional analyses revealed two independent association signals at this locus (rs888663 and rs1054564), which were associated with altered cis-gene expression in blood cell lines.
In ambulatory individuals, both cardiometabolic risk factors and genetic factors play an important role in determining circulating GDF-15 concentrations, and contribute similarly to overall variation.
Epidemiology; Genetics; Risk factors; Cardiovascular diseases
The current gold standard for diagnostic classification of many solid-tissue neoplasms is immunohistochemistry (IHC) performed on formalin-fixed, paraffin-embedded (FFPE) tissue. Although IHC is commonly used, there remain important issues related to preanalytic variability, nonstandard methods, and operator bias that may contribute to clinically significant error. To increase the quantitative accuracy and reliability of FFPE tissue-based diagnosis, we sought to develop a clinical proteomic method to characterize protein expression in pathologic tissue samples rapidly and quantitatively.
We subclassified FFPE tissue from 136 clinical pituitary adenoma samples according to hormone translation with IHC and then extracted tissue proteins and quantified pituitary hormones with multiplex bead-based immunoassays. Hormone concentrations were normalized and compared across diagnostic groups. We developed a quantitative classification scheme for pituitary adenomas on archived samples and validated it on prospectively collected clinical samples.
The most abundant relative hormone concentrations differentiated sensitively and specifically between IHC-classified hormone-expressing adenoma types, correctly predicting IHC-positive diagnoses in 85% of cases overall, with discrepancies found only in cases of clinically nonfunctioning adenomas. Several adenomas with clinically relevant hormone-expressing phenotypes were identified with this assay yet called “null” by IHC, suggesting that multiplex immunoassays may be more sensitive than IHC for detecting clinically meaningful protein expression.
Multiplex immunoassays performed on FFPE tissue extracts can provide diagnostically relevant information and may exceed the performance of IHC in classifying some pituitary neoplasms. This technique is simple, largely amenable to automation, and likely applicable to other diagnostic problems in molecular pathology.
Microfluidic devices can create hemodynamic conditions for platelet assays. We validated an 8-channel device in a study of interdonor response to acetylsalicylic acid (ASA, aspirin) with whole blood from 28 healthy individuals.
Platelet deposition was assessed before treatment or 24 h after ingestion of 325 mg ASA. Whole blood (plus 100 μmol/L H-D-Phe-Pro-Arg-chloromethylketone to inhibit thrombin) was further treated ex vivo with ASA (0–500 μmol/L) and perfused over fibrillar collagen for 300 s at a venous wall shear rate (200 s−1).
Ex vivo ASA addition to blood drawn before aspirin ingestion caused a reduction in platelet deposition [half-maximal inhibitory concentration (IC50) approximately 10–20 μmol/L], especially between 150 and 300 s of perfusion, when secondary aggregation mediated by thromboxane was expected. Twenty-seven of 28 individuals displayed smaller deposits (45% mean reduction; range 10%–90%; P < 0.001) from blood obtained 24 h after ASA ingestion (no ASA added ex vivo). In replicate tests, an R value to score secondary aggregation [deposition rate from 150 to 300 s normalized by rate from 60 to 150 s] showed R < 1 in only 2 of 28 individuals without ASA ingestion, with R > 1 in only 3 of 28 individuals after 500 μmol/L ASA addition ex vivo. At 24 h after ASA ingestion, 21 of 28 individuals displayed poor secondary aggregation (R < 1) without ex vivo ASA addition, whereas the 7 individuals with residual secondary aggregation (R > 1) displayed insensitivity to ex vivo ASA addition. Platelet deposition was not correlated with platelet count. Ex vivo ASA addition caused similar inhibition at venous and arterial wall shear rates.
Microfluidic devices quantified platelet deposition after ingestion or ex vivo addition of aspirin.
Well-annotated clinical samples are valuable resources for biomarker discovery and validation. Multiplex and integrated methods that simultaneously measure multiple analytes and generate integrated information about these analytes from a single measurement are desirable because these methods help conserve precious samples. We developed a magnetic bead–based system for multiplex and integrated glycoprotein quantification by immunoassays and glycan detection by lectin immunosorbent assays (LISAs).
Magnetic beads coupled with antibodies were used for capturing proteins of interest. Biotinylated antibodies in combination with streptavidin-labeled phycoerythrin were used for protein quantification. In the LISAs, biotinylated detection antibodies were replaced by biotinylated lectins for glycan detection.
Using tissue inhibitor of metallopeptidase 1 (TIMP-1), tissue plasminogen activator, membrane metallo-endopeptidase, and dipeptidyl peptidase-IV (DPP-4) as models, we found that the multiplex integrated system was comparable to single immunoassays in protein quantification and LISAs in glycan detection. The merits of this system were demonstrated when applied to well-annotated prostate cancer tissues for validation of biomarkers in aggressive prostate cancer. Because of the system’s multiplex ability, we used only 300 ng of tissue protein for the integrated detection of glycans in these proteins. Fucosylated TIMP-1 and DPP-4 offered improved performance over the proteins in distinguishing aggressive and nonaggressive prostate cancer.
The multiplex and integrated system conserves samples and is a useful tool for validation of glycoproteins and their glycoforms as biomarkers.
Circulating cell-free DNA (ccf-DNA) is becoming an important biomarker for cancer diagnostics and therapy monitoring. The isolation of ccf-DNA from plasma as a “liquid biopsy” may begin to replace more invasive tissue biopsies for the detection and analysis of cancer-related mutations. Conventional methods for the isolation of ccf-DNA from plasma are costly, time-consuming, and complex, preventing the use of ccf-DNA biomarkers for point-of-care diagnostics and limiting other biomedical research applications.
We used an AC electrokinetic device to rapidly isolate ccf-DNA from 25 μL unprocessed blood. ccf-DNA from 15 chronic lymphocytic leukemia (CLL) patients and 3 healthy individuals was separated into dielectrophoretic (DEP) high-field regions, after which other blood components were removed by a fluidic wash. Concentrated ccf-DNA was detected by fluorescence and eluted for quantification,PCR,and DNA sequencing. The complete process, blood to PCR, required <10 min. ccf-DNA was amplified by PCR with immunoglobulin heavy chain variable region (IGHV)-specific primers to identify the unique IGHV gene expressed by the leukemic B-cell clone, and then sequenced.
PCR and DNA sequencing results obtained by DEP from 25 μL CLL blood matched results obtained by use of conventional methods for ccf-DNA isolation from 1 mL plasma and for genomic DNA isolation from CLL patient leukemic B cells isolated from 15–20 mL blood.
Rapid isolation of ccf-DNA directly from a drop of blood will advance disease-related biomarker research, accelerate the transition from tissue to liquid biopsies, and enable point-of-care diagnostic systems for patient monitoring.