Hitting the (bio)mark part 1: selecting and measuring biomarkers in cardiovascular research

Abstract

Cardiovascular studies, including nursing research, frequently integrate biomarkers for diagnostic, prognostic, monitoring, and therapeutic insights. However, effective utilization of biomarker data demands careful consideration. In the study design phase, researchers must select biomarkers that align with study objectives while considering resources and logistical factors. Additionally, a nuanced understanding of disease pathophysiology and biomarker characteristics is needed. During data collection, suitable experimental conditions and assays need to be defined. Whether researchers opt to manage these steps internally or outsource some, a comprehensive understanding of biomarker selection and experiments remains crucial. In this article, part 1 of 2, we provide an overview of considerations for the design to measurement phases of biomarker studies.

Learning objectives.

• Define the role of biomarkers in cardiovascular nursing studies.

• Understand essential considerations in study design involving biomarkers.

• Select appropriate biomarker assay(s) within the experimental design.

Introduction

Many cardiovascular nursing studies incorporate biomarkers into the design and conduct of the study. Reasons for doing so may include, but are not limited to: identifying mechanisms,¹ diagnosing,² staging severity, or tracking response to a treatment or intervention.^3–5 Some biomarkers capture a very specific process, sometimes linked with a single organ or pathology (e.g. troponin and haemoglobin A1C) or a more multi-organ or systemic process (e.g. inflammatory markers). Regardless of the rationale for incorporating a biomarker, several considerations are required from the design to reporting phases, particularly given the costs and resources required to measure biomarkers. In this paper, we provide an overview of considerations for the design to measurement phases (Central Illustration; Box 1 for common definitions; Table 1 for examples). In part 2, we provide an overview of considerations for the analysis, interpretation, and reporting phases.

Central Illustration.

Overview of the four steps for selecting and measuring biomarkers in cardiovascular nursing research.

Box 1. Box of definitions.

Analyte	A substance undergoing analysis.
Assay	A laboratory procedure designed to qualitatively or quantitatively measure the presence, concentration, activity, or other characteristics of a target element in a sample. Examples:
	Enzyme-linked immunoassay (ELISA): detects the presence of a protein using antibodies directed towards the compound of interest on a solid plate.
	Liquid chromatography (LC): separation of molecules using a mobile phase.
	Mass spectrometry (MS): measures and identifies the mass to charge ratio of molecules.
	Polymerase chain reaction (PCR): amplifies DNA or RNA in a sample for further identification and quantification.
Biofluid biomarker	A measurable substance or molecule found in a biological fluid (e.g. blood, urine, cerebrospinal fluid, and saliva) that indicates normal biological processes or the presence or progression of a particular biological condition, disease, or pathophysiological state.
Limit of detection	The lowest analyte concentration that can be distinguished from the assay background.
Limit of quantification	The lowest concentration at which the analyte can be reliably detected, and pre-defined goals for bias and imprecision are met.
Multiplex assay	An assay that enables the simultaneous detection and measurement of multiple analytes in a single run.
Sensitivity	The ability of a test or assay to correctly identify or detect true positive cases.
Specificity	The ability of a test or assay to correctly identify or detect true negative cases.

Table 1.

Examples of applying steps 1–4

	Step 1: identify a biomarker	Step 2: design experiments	Step 3: select the assay	Step 4: perform the assay
Example 1 Butts et al. (2023)4	HF is associated with premature cellular aging, which may relate to inflammation. Telomere length is a measure of cellular aging and has been shown to be related to physical activity.	Collected fasting blood samples at baseline and 3 months from participants enrolled in a 3-month physical activity pilot intervention. Samples were processed (centrifuge, aliquots of plasma and buffy coat) and stored at −80°C.	DNA extraction: QIAamp DNA Mini Kit (Qiagen, Germantown, MD, USA); DNA quantification: Qubit dsDNA HS Assay Kit, (Invitrogen, Waltham, MA, USA); total telomere length: Absolute Human Telomere Length Quantification qPCR Assay Kit (ScienCell, Carlsbad, CA, USA); IL-1β: ELISA (eBioscience, Waltham, MA, USA)	Study PI performed assays using procedures developed by the manufacturer.
Example 2 Butts et al. (2023)6	Chymase is a destructive protease that may be associated with poor outcomes post-cardiac surgery.	Pericardial fluid was collected from persons undergoing cardiac surgery from pericardial drains at 4 h after surgery. ICU and total hospital length of stay were retrieved from the medical record.	Chymase generated 125I-Ang II from 125I-Ang-(1–12) was detected with an in-line flow-through gamma detector (BioScan Inc., Washington, DC). Chymase activity was defined as fmol of Ang II product formed from 125I-Ang-(1–12) substrate/mL/min (fmol Ang II formation/mL/min).	Assays were performed by a collaborator who had previously established the protocol in their lab.
Example 3 Denfeld et al. (2021)7	NT-proBNP and sST2 are two common, yet distinct, biomarkers in HF that may differ between women and men after LVAD placement.	At pre- and 1, 3, and 6 months post-LVAD implantation, whole blood was collected from participants (using sodium heparin tubes). Initial processing done in research lab (centrifuge, aliquots) and samples stored at −80°C.	Plasma NT-proBNP was measured using an ELISA (Cusabio Technology, Houston, TX, USA). sST2 was measured using an ELISA (Critical Diagnostics, San Diego, CA, USA).	NT-proBNP was measured in the research core laboratory. sST2 was measured in a collaborator’s laboratory. Both used procedures developed by the manufacturer.
Example 4 Butts et al. (2019)8	Resistant hypertension is a risk factor for HF, and high salt intake increased xanthine oxidase activity in the hypertrophied left ventricle in a rat model of resistant hypertension.	Collected fasting blood samples from persons with resistant hypertension and normotensive individuals. Samples were processed (centrifuge, aliquots of plasma) and stored at −80°C 24 h urinary output was collected from each participant. Cardiac MRIs were performed on all participants.	Xanthine oxidase activity: high performance liquid chromatography was used. Xanthine oxidase activity was measured by the rate of uric acid production in the presence of xanthine (75 μM) without NAD+. Urinary sodium: measured by the clinical laboratory. MRI: 1.5 T clinical scanner optimized for cardiac imaging (Sigma, GE Healthcare)	Xanthine oxidase assays were developed and performed by the PI and research team. Urinary sodium and MRI measures were completed in the clinic by trained professionals.
Worked example	Insulin resistance is one of the pathophysiological mechanisms of HF; thus, we selected to measure plasma glucose and insulin, which can both be used to also calculate HOMA-IR.	Collected one-time fasting blood samples in laboratory (using sodium heparin tubes). Initial processing done in research lab (centrifuge, aliquots) and stored at −80°C.	Glucose was measured using a colorimetric assay (BioAssay Systems; Hayward, CA, USA) and insulin was measured using an ELISA (Mercodia; Uppsala, Sweden). HOMA-IR was calculated from glucose and insulin concentrations: HOMA-IR = (fasting glucose (mmol/L) × fasting insulin (μU/mL)/22.5.	Research laboratory performed assays using procedures developed by the manufacturer.

Steps 5–8 are presented in part 2.

ELISA, enzyme-linked immunosorbent assay; HF, heart failure; HOMA-IR, homeostatic model assessment for insulin resistance; ICU, intensive care unit; LVAD, left ventricular assist device; MRI, magnetic resonance imaging; NT-proBNP, N-terminal B-type natriuretic peptide; sST2, soluble suppressor of tumorgenicity.

What is a biomarker?

For this methods paper, we focus on biofluid biomarkers specifically. A biofluid biomarker refers to a measurable substance or molecule found in a biological fluid (e.g. blood, urine, cerebrospinal fluid, and saliva) that indicates normal biological processes or the presence or progression of a particular biological condition, disease, or pathophysiological state.⁹ Biofluid biomarkers can be used as indicators of health or disease and provide valuable information for diagnostic, prognostic, and therapeutic purposes. Biomarkers can be measured in different types of biofluids depending on the molecular or metabolic pathway of interest (Figure 1A). Depending on the outcomes and desired goals of the study, there are several types of biomarkers one could consider, including measures of DNA, RNA, epigenetic markers, proteins, metabolites, and microbiota (Figure 1B).

Figure 1.

Biofluid biomarkers in research. (A) Examples of biofluids. (B) Examples of biomarkers. Created with BioRender.com.

Step 1: identify a biomarker

Selecting a suitable biomarker requires consideration of multiple different factors, ranging from the physiology or pathophysiology underlying the research question to the logistics such as available facilities and funds (the latter are discussed below in detail). The chain of events leading from disease pathogenesis to clinical manifestation contains different steps at different levels (e.g. molecular or organ level), and a suitable biomarker could be identified at each point.¹⁰ For example, sympathetic overactivation is a prominent pathophysiologic characteristic of heart failure, and the measurement of norepinephrine (a catecholamine) is one approach to quantify the level of sympathetic activation. However, norepinephrine concentrations differ depending on if they are collected from the coronary sinus (a reflection of cardiac-specific sympathetic activation) or from the antecubital vein (a reflection of more systemic sympathetic activation).¹¹ Moreover, the reuptake and metabolism of norepinephrine may vary, necessitating concurrent measurement of its metabolite, dihydroxyphenylglycol.¹² Thus, it is necessary to clearly understand the relationship between the biomarker, pathophysiology, and the relevant clinical endpoint.

The Austin Bradford Hill guidelines can be useful when identifying a potential causal association between a biomarker and a clinical disorder.¹⁰ The guidelines incorporate: (i) the strength of the association between marker and outcome, (ii) consistency, (iii) specificity, (iv) temporality (indicating parallel changes in marker and outcome), (v) biological gradient (dose-responsiveness), (vi) plausibility (mechanisms connecting the marker, disease pathogenesis, and mode of action of the intervention), (vii) coherence (the association is consistent with natural history), (viii) experimental evidence (results are consistent with the association), and (ix) the analogy.¹⁰

In general, an ideal biomarker would predict the outcome in a real-world setting, preferably tested in a randomized control trial, and it would change reliably in response to changes in the condition or therapy. It is possible that the value of the biomarker will change, but the clinical endpoint will remain the same. Incorporating both objective clinical endpoints (e.g. death and hospitalization) and patient-reported outcomes (e.g. symptom questionnaire) may be useful. Additionally, the mechanism for how the biomarker, intervention (if applicable), and clinical endpoints are linked together needs to be understood and considered.¹⁰ Another consideration is the effect of internal confounding factors on the biomarker value.¹⁰ The biomarker must: (i) reflect the studied biological event, (ii) take into account other relevant characteristics of the disease, and (iii) have a high specificity, sensitivity, and predictive value.¹³ Next, the biological stability of the biomarker should be considered because not all types of samples or biomarkers are suitable to examine after a longer period of time (e.g. vitamins are light-sensitive or proteins may degrade over time).¹³ Finally, when tracking an intervention, the use of a single biomarker may not be sufficient, and multiple biomarkers may need to be included. The key message when choosing a biomarker is to select one appropriate for the research question, whether it is novel or established, and not to choose based solely on what others use in their research.

Step 2: design experiments

After identifying a suitable biomarker, appropriate experimental conditions need to be determined. All (pre-)analytical processes should be outlined and documented in a standard operating procedure, which must be followed to obtain high-quality results and minimize errors.^13,14 Some procedures are available with assay kits (e.g. step-by-step testing procedures provided by the manufacturer) while others need to be developed (e.g. based on prior research or experience); regardless, every time a procedure is followed, the steps need to be documented along with any deviations from the protocol or problems encountered. Errors may arise from processing mistakes, incorrect laboratory measurements, issues with collection equipment or specimen transportation, improper storage, or changes in storage temperature.¹³ Defining the entire process in advance ensures the needed logistics are in place before the start of sample collection. It is important to recognize that different sample types or biomarkers may require different processing methods.¹⁴

First, the sampling procedure must be defined. For example, depending on the type of biomarker, samples may need to be collected while the patient is fasting or during exercise. When collecting blood samples, factors such as patient positioning, tourniquet application time, and needle bore size should be considered.¹⁴ When the latter is too thin, haemolysis may occur, leading to increased free haemoglobin and other protein concentrations in plasma and serum. Additionally, the type of container used for sample collection is crucial.¹⁴ For example, different types of anticoagulants can alter plasma protein profiles and interfere with the analysis [e.g. ethylenediaminetetraacetic acid (EDTA) interferes in assays for enzymatic activities].¹⁵ Consequently, the type of assay you want to perform dictates the specimen type and collection container.¹⁵ Another important consideration is to ensure that only those trained in venipuncture are performing the blood draw (note that training and certification may vary by country, etc.); these personnel vary across settings but may include clinical phlebotomists, research staff trained in venipuncture, or any researchers who also have a clinical background with prior venipuncture experience (e.g. nurse scientists). Lastly, it is important to strongly consider the comfort for the patient; for example, it is ideal to proactively combine clinical and research blood draws as ‘one poke.’ Furthermore, by combining the blood draws, this augments the feasibility of collecting the blood for both patients and staff.

After sample collection, be aware of the recommended temperature and time for sample transportation to the laboratory. Determine the mode of transportation and ensure that processing starts within a specific timeframe upon arrival at the lab.¹⁴ Processing will involve different steps (e.g. centrifugation and aliquoting), and each step requires specific considerations (e.g. centrifugation time and speed, and the type and capacity of the secondary container). After processing, the samples could be stored or analysed directly. In the latter case, follow the instructions of the chosen assay.¹⁴ When storing samples, adhere to temperature and duration guidelines to preserve their quality. Lastly, beware of the effect of freeze and thaw cycles on the samples.¹⁴ It might be beneficial to perform an early quality check on a subset of the samples.¹³ If these indicate insufficient quality, the process can be adjusted.¹³

Step 3: select the assay

When selecting an assay, first ensure that its findings will address your research question. Furthermore, the assay should be suitable for the collected sample type and capable of measuring the chosen biomarker without interference from other substances. Besides being specific to the target analyte, the assay must be sensitive enough to detect low concentrations and small changes in the analyte levels. Similarly, high precision, accuracy, and reproducibility are also crucial, ensuring consistent results when performed by different researchers or at other research institutes following the same protocol.¹⁰ Additionally, the assay should be robust and have a high signal-to-noise ratio, which will improve the signal quality.¹⁰ For evident reasons, using a validated and standardized assay is highly recommended. Pilot studies are needed to establish the assay’s reliability, preferred procedure and limits of detection and quantification.^13,15

Apart from performance factors, other elements may influence the choice of assay. First, consider opting for a commercially available assay to save time and resources. Second, make sure it has a desirable turnaround time. Additionally, consider the cost (e.g. financial and technical resources) and complexity (e.g. specialized training or equipment) associated with the assay. Check for any external confounding factors (e.g. using multiple batches of laboratory kits), and take these into account before using the assay.¹³ Lastly, make sure it is clear what kind of outcomes the assay will generate and be aware of their correct interpretation.¹³

Furthermore, consider the number of analytes you want to detect in one reaction. For example, more traditional immunoassays [e.g. enzyme-linked immunoassay (ELISA)] often measure the presence or absence of a single analyte. However, nowadays, multiplex assays (e.g. cardiovascular disease panels) allow the detection of multiple analytes in a single run.¹⁶ These multiplex panels can be more cost-effective and provide a wealth of additional data that can provide a more comprehensive understanding of the biological processes. Moreover, they are more efficient, save time, and limit sample volume.¹⁶ However, there are also some drawbacks and challenges. The use of multiplex panels may be very complex (e.g. set-up and equipment), requires trained personal and expensive equipment, and bigger volumes of data must be analysed.¹⁶

Lastly, it proves beneficial to conduct multiple measurements, typically in duplicate or triplicate, for each sample. This provides valuable insights into the variation among measurements, assess the validity of the assay, and facilitates the validation of research findings. Additionally, the average of these measurements can be calculated as the response variable.

In addition to conventional laboratory assays, the integration of point-of-care testing (POCT) can be contemplated. Point-of-care testing involves conducting laboratory tests for parameters such as haemoglobin A1C, cholesterol, and others in close proximity to the patient care site, minimizing the need for specimen transportation and processing and thereby reducing pre-analytical effects.¹⁷ The advantage of POCT lies in its ability to deliver results in a shorter time frame compared to traditional laboratory testing, leading to a shorter turnaround time. Furthermore, POCT devices typically necessitate smaller blood volume and can operate without reliance on centralized laboratories.¹⁷ The cost effectiveness of POCT is evident in reduced transportation costs, quicker results and the opportunity of real-time monitoring. Lastly, the devices are often user-friendly and require minimal training for operation. However, it is essential to acknowledge some drawbacks associated with POCT: (i) labour intensive and costly when handling high-volume testing, (ii) potential for incorrect handling by untrained clinical staff, leading to unreliable results, and (iii) regulatory compliance concerns.¹⁷

Step 4: perform the assay

The exact procedure will depend on the type of assay that will be used (e.g. biochemical and immunoassay). However, there are some broad recommendations when performing the assay. First, it is important to understand how the environmental conditions may impact the assay (e.g. temperature and humidity). Second, calibrate the instruments that will be used and ensure that the equipment works properly. Third, it could be useful to create a standard curve of samples with known concentrations. Next, follow the step-by-step instructions of the assay protocol and make sure never to change the experiment partway through. Moreover, document all the experimental steps (e.g. reagent preparation, instrument setting, and protocol deviations), resulting in the availability of contextual information when analysing the data. Lastly, document all findings accurately and precisely. All aforementioned steps will help to ensure high-quality results.

Considerations for facilities and resources

The choice of biomarkers is not only influenced by the research question but also by the available financial resources.¹³ The cost depends, among other things, on the type of biomarker and its collection method, processing steps, equipment, storage, assays, and the number of included patients and/or controls. Practical advice for budgets can be found in Table 2. To save costs, focusing on a subset of participants and using automated, simple laboratory procedures can be more affordable.¹³ Next, the availability of processing and storage facilities is essential. In some cases, it might be cost-effective and time-effective to process samples within your own research institution (e.g. in the clinical core lab), a colleague’s lab, or shared resources (e.g. proteomics lab). If necessary resources are not available, collaboration with other academic institutions, government facilities, or industry could be considered. In the latter cases, logistics and time needed to get your samples to the lab should be accounted for, especially for assays with specific processing timeframes or temperature requirements. Ensure that specific requests from the lab (e.g. sample size for storage and transport method) are met. Furthermore, make sure there is a clear agreement on financial compensation and that the needed paperwork is signed. Additionally, check the timeline for sample processing by the other institutes, as longer wait times (e.g. other academic institutions) can increase study costs. It is also important that trained personnel are available to perform the processing steps and assays. All aforementioned considerations will broaden or narrow the feasibility of biomarker usage.

Table 2.

Budgeting considerations for biomarker research

Stage	Factor	Cost considerations
Blood draw	Personnel	Research staff: cost of their time Clinical phlebotomist: standard rate, potentially bundled with equipment cost
	Equipment	Depends on type of biomarker: collection tubes (e.g. vacutainer tubes) and other blood draw supplies (e.g. needles, gauze, and tourniquets)
Initial processing of the blood	Location	Outsource to a laboratory: standard rate for processing (e.g. centrifuging the sample and pipetting aliquots) In-house laboratory: up-front costs for equipment (e.g. centrifuges, pipettes, and microfuge tubes), and research staff time
Storage	Temperature	Budget for freezer: samples are usually stored at −80°C
Biomarker assays	Method	Using a kit: cost of the kit, additional equipment not provided by the kit (e.g. pipettes, plate shaker, and microplate readers), maintenance costs Outsourcing: negotiated price based on services provided
Data analysis	Complexity of the data	In-house analysis: research staff time (e.g. creating standard curves and interpolating results) Outsourcing: cost of statisticians or bioinformaticians

Conclusion

In conclusion, the integration of biomarkers in cardiovascular nursing studies unfolds as a complex journey from the initial study design to the reporting phase. Researchers may be intricately involved in all of these steps, or they may choose to outsource some of this work. Regardless, understanding every step involved in deriving the biomarker and its findings is crucial. This paper elucidated the different purposes of biomarker usage and the extensive, meticulous considerations involved in this process. Furthermore, this paper and its insights lay the foundation for the upcoming part 2, where considerations relevant to the analysis, interpretation, and reporting phases will be discussed.

Funding

This work is supported, in part, by Research Foundation Flanders through grant G072022N (Daelman), the National Institute of Nursing Research of the National Institutes of Health (NIH) under Award Number R01NR019054 (Denfeld), and the National Institute on Aging of the NIH under Award Number K23AG076977 (Butts). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.