Proposed Implementation

Project Overview

Our project, CADlock, addresses the issues of expensive testing methods such as the echocardiogram and electrocardiogram (EKG). CADlock aims to efficiently detect coronary artery disease (CAD) and determine whether patients are at risk of developing the disease and monitor the progression of the disease in diagnosed patients. Implementation of CADlock will significantly benefit the general population: specifically, doctors and patients who will offer and receive a rapid and reliable testing tool. The following describes how we envision the CADlock implementation process (see Fig. 1a & 1b)

Figure 1. Processes for researchers (a) and doctors (b)

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Putting into Practice: Researchers, Doctors, and Patients

Factors

Various factors such as age, gender, body mass index, hypertension, smoking, and blood levels of glucose and other lipids impact the production of microRNAs(miRNAs). We found that ethnicity and lifestyle play essential roles in the expression of miRNAs in the blood due to cultural and religious differences such as eating habits and exercise (Wakabayashi et al., 2020). Other factors include genetics, sleep, medications, age, environment, medical conditions, injuries, socioeconomic status and development, time of day, circadian rhythm, stress, rest days, participation in drugs, comorbidities such as acute coronary syndrome (ACS), coronary heart disease (CHD), and diabetes. A research article on dietary lactose showed that it could be a risk for CAD or ischemic heart disease (IHD) since IHD mortality trends show a correlation based on the supply of milk. The article continues by commenting that there are inconsistent results with the impact of dietary lactose on mortality which are proven by various other articles (Segall, 1994). Therefore, the insufficient research on the direct influence of CAD due to other lifestyle factors suggests the need for additional research.

HIPAA

CADlock requires patients to undergo laboratory tests with facilities implementing the Health Insurance Portability and Accountability Act (HIPAA), meaning our testing device would be subject to HIPAA compliance (LeFlore, 2017). If medical professionals utilize CADlock as a screening device, they would need to be properly informed about our device to avoid data breaches and manage Protected Health Information (PHI). PHI is classified as patient information protected by the contract a hospital or laboratory is bound to by HIPAA (Compliancy Group, 2021). CADlock requires patients to undergo a blood draw; therefore, any laboratory results derived from a blood extraction will be considered PHI and cannot be disclosed without consent from the patient or a Notice of Privacy Practices (NPP) (Compliancy Group, 2021). To better diagnose coronary artery disease (CAD) in future patients, obtaining patient information such as medical history and geographic location may be useful. These data sets, known as HIPAA-limited data sets, would be beneficial for research papers or clinical studies to contribute to the research on miRNAs and CAD. However, there are some limitations due to the HIPAA privacy rule: this rule dictates that protected data may only be used to fulfill a specific approved purpose and can only be shared with third parties upon signing a Business Associate Agreement (BAA) (HIPAA Journal, 2022). Overall, HIPAA is heavily involved in many aspects of our project and provides regulations that are crucial in being able to successfully implement our project.

Blood Drawing

The first step in diagnosing a potential patient using CADlock is obtaining blood samples. A phlebotomist will draw blood from the patient using appropriate techniques and equipment sterilization. Red top blood collection tubes and a proper type of needle, such as a multisample and butterfly needle, are used for blood collection. (These blood collection tubes indicate that the blood contains no anticoagulant or preservative and is for serum or clotted whole blood. Thus, this tube is appropriate to use to get a reading from the serum.) Then, withdrawn blood is sent to a lab to get centrifuged. The blood and serum should be separated within 2 hours and 45 minutes of blood extraction to prevent the alteration of the serum and plasma’s chemical composition and ensure an accurate test result (see Fig. 1a).

Isolating miRNA

miRNA Criteria

We selected hsa-miR-1-3p, hsa-miR-133-3p, hsa-miR-451-3p as biomarkers for coronary artery disease (CAD). To ensure the success of our design, we utilized hsa-miR-451-3p in place of hsa-miR-208-3p due to the secondary folding of the hsa-miR-208-3p padlocks. We specifically selected these biomarkers because they are involved with gene expression of cardiac myoblast proliferation, muscle development and cell growth, and electrical conduction of cardiac cells (Yu, 2014). The upregulation of the biomarkers will indicate the possibility of CAD because patients with overexpression of the biomarkers will result in comorbidities such as cancer in skeletal muscle and cardiac muscle, cardiac hypertrophy, heart failure, and muscular dystrophy (National Library of Medicine, 2022).

Meta-Study

To determine accurate diagnostic reference ranges for microRNA (miRNA) concentrations in CAD patients, our team conducted a meta-study with the help of Dr. Christian Delles from the University of Glasgow. We used articles from Google Scholar and the GEO NCBI database corresponding to the following keywords: biomarker, diagnosis, miR-1, miR-133a, mir-208a, microRNA, coronary artery disease, CAD, CHD, patient, blood, serum, and circulating. By using this method, we shortlisted approximately 2460 relevant articles. To further narrow search results, we only used CAD, hsa-miR-1, hsa-miR-133, and hsa-miR-208 as keywords, resulting in approximately 22 relevant articles.

Using these selected papers, our team analyzed and extracted necessary information such as reference ranges, sample sizes, and detection methods. After reviewing the data derived for the meta-study, we identified a significant variation in the literature’s miRNA values, patient samples, methods, and results (see Fig. 2). Although our intention for the meta-study was to establish a definite reference range for potential CAD patients, we could not determine an accurate diagnostic reference range due to the lack of data correlating our specific miRNAs with CAD and concluded more research is required. Regarding the continuation of this topic, we plan on collecting more data and reviewing research papers in the field of circulating miRNAs and CAD to pursue the publication of our study.

Serum Extraction

The serum is the liquid portion of human blood that lacks the presence of clotting factors and cells. In serum, the cells and the clotting factors are removed from the blood by “allowing adequate time for the clot to form”. The standard time for clots to form is 30 to 60 minutes at room temperature (Tuck et al., 2009): if blood samples are not given at least 30 minutes to clot, they will contain other cellular components within the sample. Additionally, if any anticoagulants are added to the sample, then it is likely that the sample will require more than 60 minutes. After the clot has formed within the sample, it is essential to isolate the clot by centrifuging between 2,000x for 10 minutes in a refrigerated centrifuge. After centrifuging, the serum should be stored at -20℃ if it is not being used immediately (ThermoFisher Staff, 2007).

RNA Purification

To isolate the desired miRNAs from serum after serum extraction, we recommend using the Zymo Research Direct-zol RNA Miniprep Kit (ZymoResearch Staff, 2022). The kit allows for any RNA between 17 and 200 nucleotides to be purified, so the desired miRNAs, around 22 nucleotides long, will be included in the product of this purification (O'Brien et al., 2018). The Direct-zol Kit also includes Tri Reagent®, which destroys the vesicles surrounding the miRNA. Overall, the kit provides a quick and efficient way to purify serum; additionally, there are no post-purification steps needed. Thus, it is a convenient option for point-of-care RNA purification. A possible alternative testing kit is the Zymo Research Quick cf-RNA Serum & Plasma Kit (ZymoResearch Staff, 2022). However, it is not ideal for extracting miRNAs specific for detection because it only purifies exosomal miRNAs, which are present at lower concentrations than in vesicles and impractical for determining risk for CAD.

Implementation in the Real World

Our biosensors will eventually be implemented in doctors’ offices and research facilities investigating microRNAs (miRNAs) in coronary artery disease (CAD) using a testing kit. The kit will facilitate the reactions necessary by holding our freeze-dried reagents and in vitro reactions. To use our kit, doctors or researchers will first need to attain a serum sample by centrifuging from whole serum or whole blood to eliminate clotting factors. Next, RNA extraction using the Zymo Research Direct-zol RNA Miniprep Kit is required to isolate and purify the miRNAs present in the sample. The kit user will then treat the purified RNA with rehydrated reagents and perform DNA hybridization, ligation, and rolling circle amplification protocols. To yield fluorescence readout, the user will need to utilize reagents and protocols that will activate the reporter mechanisms. Finally, the treated sample will be inserted into and run by Micro-Q to quantify the fluorescence.

In the future, we plan on verifying whether RNA extraction is truly necessary for detecting miRNAs in serum. We will add varying miRNA concentrations into serum, isolate and purify RNAs, and then add the extracts to our padlock probe reactions to obtain RCP. Finally, we will test our linear probes on the yielded RCP and compare the readouts between using our biosensors on extracted miRNAs and on serum treated with RNase inhibitor.

Costs

Lambert iGEM's lower-cost, miRNA testing kit incorporates wet-lab, hardware, and safety materials from various suppliers (see Table 1). Our total kit cost would be $1,588.54, and all of items will be sold in bulk. However, we derived the cost per reaction by dividing bulk costs by the quantity of reactions per kit. Ultimately, our kit costs $14.59 per reaction without capital equipment and $38.96 with capital equipment. The average cost for current CAD detection methods like angiograms and lipid panels cost about $1363 and $156 respectively, our kit provides consumers with an efficient way to measure a user's risk for CAD for under $40 per reaction.

Safety

Although our in vitro reactions are cell-free, we recommend that kit users conduct testing while wearing standard personal protective equipment (PPE), including nitrile gloves, safety goggles/glasses, and lab coats/aprons. Doctors and researchers will only need to work under their facilities’ respective safety protocols for testing and discarding biohazardous samples such as blood and serum.

Reporting Results

False Positives and False Negatives

Ultimately, Lambert iGEM hopes to utilize its research on microRNAs (miRNAs) for the early, accurate detection of coronary artery disease (CAD). However, a medical diagnosis procedure presents the risk of potential false positives (type I error) or false negatives (type II errors). Type I error, in which an issue is incorrectly detected, may lead to unnecessary treatments and medical prescriptions. In contrast, type II errors, in which the test wrongly indicates the absence of a condition, may cause the underlying disease to be neglected, which causes more problems in the future. In hospitals, doctors will run blood tests on patients with risk factors for CAD to detect the disease before symptoms manifest. If Lambert iGEM’s miRNA screening tests positive for CAD, more precise yet expensive procedures like stress tests, echocardiograms, and angiograms can be performed. A type I error may cause hospitals to spend money on expensive procedures to confirm the CAD diagnosis, but it will ensure patients' peace of mind as they leave the hospital. In some scenarios, the shock of long-term degenerative disease may motivate individuals to reevaluate their lifestyles and live more healthily. However, with a type II error, CAD can progress further in an at-risk patient before essential lifestyle changes and medical interventions can be employed, which may become dangerous in the long term. Due to the dangerous effects of type II errors, we aim to minimize the probability of these errors by increasing our sample size and significance levels when calibrating our threshold values.

References