Biomarkers

The primary challenge in attempting to devise a biomarker-based diagnosis for MDD lies not just in the absence of specific established markers but also in the stagnation observed in the research of biomarkers for mental health disorders. We were faced with an acute lack of biomarker data when it came to MDD and this was also affirmed by the words of Dr Krishnan S, the HoD of psychiatry at Govt Medical College and Lekha Dinesh Kumar, a scientist working on cancer research at thе Cеntrе for Cеllular and Molеcular Biology. (Find the detailed report of their inputs on our iHP timeline).

Currently, we have chosen 5 biomarkers that showed the most literature and experts’ backup. We have also compiled a preliminary list of the same kinds of biomarkers and biomarker functions related to MDD which shows almost similar degree of potential to be biological biomarkers of MDD. The exact pathways in which these work to co-relate with MDD is something that is yet to be explored and, again, currently facing a severe lack of data.

1. Cytokines and inflammatory markers ^[4]
• Inflammatory mediators have been found to affect many factors (monoamine and glutamate neurotransmission, GR resistance, and hippocampal neurogenesis) that are thought to be important in the etiopathogenesis of MDD. This suggests that inflammatory markers may be used as a marker for the diagnosis and treatment response of depression
• IL-1, IL-6, and tumor necrosis factor α (TNFα) are known as pro-inflammatory cytokines, and IL-4, IL-10, and IL-13 are known as anti-inflammatory cytokines - they play a role in the maintenance of normal brain function by supporting neuronal integrity, neurogenesis, and synaptic remodeling
• Cytokines released by peripheral immune cells and adipose tissue enter the central nervous system (CNS) through some regions of the blood-brain barrier or by the active reuptake mechanism and thereby affect behaviors.
• Of the inflammatory markers, those which most confirm the changes in depression are proinflammatory cytokines such as IL-1, IL-6 and TNFα, and C reactive protein (CRP) Serum levels of IL-1, IL-6, and TNFα and the messenger ribonucleic acid (mRNA) expressions of these in peripheral cells are increased in patients with MDD ,elevated levels of IL-1, IL-6, and TNFα prior to treatment have been reported to be associated with non-response to antidepressant treatment
• Pro-inflammatory cytokines stimulate IDO in glial cells. IDO converts the tryptophan to kynurenine, which is then converted to neurotoxic quinolinic acid in the brain. Quinolinic acid binds to N-methyl D-aspartate (NMDA) receptors. Thus, because of the pro-inflammatory cytokines inducing IDO, depression may develop as a result of the decrease in serotonin levels due to reduced tryptophan on the one hand and glutamatergic neurotoxicity on the other.
• Serum levels of IL-1, IL-6, and TNFα and the messenger ribonucleic acid (mRNA) expressions of these in peripheral cells are increased in patients with MDD ,elevated levels of IL-1, IL-6, and TNFα prior to treatment have been reported to be associated with non-response to antidepressant treatment.
• Cytokine levels differ for some subtypes of depression. increase in proinflammatory cytokines in those attempting suicide, in depression with suicidal ideas, and in geriatric depression whereas atypical and melancholic depressions show increased levels of CRP and IL-6 compared to typical depressions.
2. miR-144-5p^[5]
In 178 patients with depression, anxiety, or stress and adjustment disorders, 36 inflammatory proteins with significantly different expression in peripheral blood of patients at baseline were seen, including 21 inflammatory proteins with increased levels and 15 with decreased levels, and all were associated with changes in miR-144-5p levels. In addition, the alteration in inflammatory proteins, which occurs after receiving treatment, was demonstrated to be associated with improvement in patients’ psychiatric symptoms.
3. Oxidative stress markers ^[4]
• Increased oxidative stress and reduced antioxidant defenses exist in MDD, and that specific components of oxidative stress play a role in the pathophysiology of depression.
• Levels of lipid peroxidation products such as malondialdehyde (MDA) have been reported to be generally elevated in depressed patients. There are also studies reporting that MDA levels are higher in patients with recurrent depression than in those with a single episode. In depressed patients, several studies have reported that serum SOD is decreased or that erythrocyte SOD is increased .
• A meta-analysis of 17 trials evaluating the majority of lipid peroxidation markers in MDD found that these markers were elevated in patients with depression and found an association between the levels of these and the severity of depression.
4. Growth Factors ^[4]
• A reduction in the hippocampal BDNF activity might be directly related to the pathophysiology of MDD, a stress-related disease.
• BDNF changes are not specific to depression. For instance, the reduction is observed for both bipolar disorder and MDD, although serum BDNF levels are reported to be lower in bipolar depression compared to MDD

Wetlab

Performing temperature-based assays for our aptasensor experiments can be crucial due to the change in aptamer binding affinity which can be temperature-dependent. This is because temperature could affect the secondary structure of the aptamer, which can in turn affect its ability to bind to its target, which in our case is the cDNA strand for the formation of the aptasensor and also the biomolecule once the cDNA has been displaced. For example, some aptamers may have a higher affinity for their target at lower temperatures, while others may have a higher affinity for their target at higher temperatures. Therefore, performing temperature-based assays can help to identify the optimal temperature for aptamer binding. Therefore running the hybridisation fluorescence based experiments for the formation and sensitivity of our aptasensors in varying temperatures will not only aim to hasten the formation of the quantifier molecules but could also in theory provide us with optimal temperature conditions for increased sensitivity of the aptasensor. In addition, temperature-based assays can also be used to study the thermodynamics of aptamer binding. This information can be used to design aptasensors with improved binding affinity and stability.

ITC experiments for nanoprobe
Isothermal Titration Calorimetry (ITC) is a powerful technique that directly measures the heat changes associated with molecular interactions, allowing the determination of thermodynamic parameters of binding events, including enthalpy (ΔH), entropy (ΔS), and the binding constant (Ka). When studying DNA-DNA binding, such as during the formation of DNA duplexes or the interaction between specific DNA sequences, ITC offers several advantages:

• Direct Measurement: ITC provides direct measurement of the binding enthalpy. Unlike other methods where binding constants are the primary data obtained, and thermodynamics must be inferred or calculated, ITC directly measures heat, allowing for a direct determination of ΔH.
• No Labeling Required: ITC doesn't require any labeling of the molecules involved. Many other techniques, like fluorescence or radioactivity-based assays, need tags that might interfere with the binding event or alter the properties of the molecules.
• Comprehensive Thermodynamic Profile: ITC can provide a complete thermodynamic profile of the binding event in a single experiment. It allows determination of ΔH, ΔS, the Gibbs free energy (ΔG), and the binding constant (K_a or K_d).
• Solution-based Measurement: ITC measurements are done in solution, which means that the natural three-dimensional conformation and dynamics of the molecules are retained, ensuring biologically relevant data.
• Multiple Binding Sites: ITC can distinguish between multiple binding sites with different affinities on the same molecule, which can be useful when studying complex systems or interactions with multiple stages. Since it shows multiple binding sites, it’s advantageous since it can prove binding of three different hybridizing sequences together to form the probe.
• No Need for Separation Steps: After binding occurs in an ITC experiment, there's no need to separate bound from unbound molecules. This is a contrast to techniques like gel-shift assays, where separation steps can introduce variability or inaccuracies.
• Determination of Stoichiometry: ITC not only provides information about the strength and thermodynamics of binding but also about the stoichiometry of the interaction, revealing how many molecules of one type bind to the other.
• Probing Molecular Details: By comparing ITC data from experiments conducted with modified DNA sequences or conditions, it's possible to probe the role of specific bases or structural elements in the binding interaction. This can help in understanding the molecular basis for specificity or the role of certain regions in DNA binding.

Protein Expression and Purification

• Bacterial expression involve plating experiments, preparation of secondary inoculum and IPTG induction for protein expression. The lac operon is induced by IPTG molecule for translation of the taget gene.
• Sonication is the process of using sound energy to stir up particles in a sample for a variety of applications, including the extraction of several different chemicals.Any protein purification procedure must begin with the sonication of cells.
• Ni-NTA chromatography, or Nickel-Nitrilotriacetic Acid chromatography, is a widely used technique in molecular biology for the purification and separation of proteins and other biomolecules.Ni-NTA chromatography is based on the principle of affinity chromatography, where a ligand with high affinity for the target molecule is used to selectively bind and separate it from a complex mixture.
• SDS PAGE or sodium dodecyl sulfate-polyacrylamide gel electrophoresis is the most used approach in genetic, biotechnology, biochemistry, and molecular biology labs for separating proteins from a mixed sample and identifying and quantifying a single protein from a mixture.They separate proteins on the basis of their electrophoretic mobility in which the mobility of the molecule is inversely proportional to its size and directly proportional to its charge.
• The Bradford protein assay is used to measure the concentration of total protein in a sample. The principle of this assay is that the binding of protein molecules to Coomassie dye under acidic conditions results in a color change from brown to blue.
• Desalting and Ion Exchange Chromatography are two important steps performed to remove salts and other low molecular weight contaminants from a protein solution; and to separate proteins based on their net charge respectively.

Hardware

Once the assay has been run, the individual fluorescence readouts need to be measured and analyzed. Commercial fluorimetry, due to its relatively high cost, might not be the optimal approach. Consequently, we propose an alternative, cost-effective fluorimetry device, informed by our expertise and insights garnered from available resources. This approach also allows for the readouts of each channel to be measured simultaneously.

Our current prototype uses basic components to showcase the concept, but we plan to use more efficient and affordable components in the future when our product is ready for market.

Towards the future, we are considering upgrading from a microcontroller, like the Arduino uno, to a microprocessor like the ESP32 series. There is a significant upgrade in the allowed memory ( 2 KB RAM to 520 KBRAM, 32 KB flash memory to 4 MB flash memory ) which allows us to expand our product to include more photo sensors and modules and also add more complex programming structures and functions. ESP32 boards have built-in WiFi and Bluetooth, allowing us to connect them to a user-friendly app or website. They can also run Python and TensorFlow, enabling machine learning on the device. This means that the product can measure data, collect it to a server, analyze it with machine learning, and optimize itself for any demographic. All these advantages come along with the point that currently the ESP32 board is ~20% cheaper than the Arduino, which is a key factor as our primary goal is humanitarian and to make the product affordable, even in developing or third-world countries.ESP32 boards are not ideal for beginners or intermediates and add complexity to the device. They require more voltage regulatory components, are more fragile and noise sensitive, and are not built for the simple but rough use that Arduino boards can’t handle.

For our proof of concept and demo, we have decided to forgo aesthetics and additional functionality that the ESP32 offers, and stick to the more simple yet robust Arduino Uno while not compromising on rigorous scientific thoroughness. We will also design a compact circuit board layout to minimize the size of the device. We are considering changing the measurement from voltage to capacitor discharge time, which would allow us to measure very low currents accurately.

We believe that our hardware has the potential to revolutionize the field of diagnostics. By making it easier and more affordable to develop and deploy new diagnostic tests, we can help people get the care they need sooner and start living healthier lives.

Microfluidics

To ensure the collection of more biomarker data using more affordable and accessible means, we plan to go through multiple iterations of Design-Build-Test-Learn cycles to make our system the most efficient way to collect biomarker data.

Our current design that was constructed is only a two channel chip that contains one quantifier of each type to test out the validity of our quantifier-biomarker system. We are also in the process of designing the five-channeled microfluidic chip that can process all five of our biomarkers but requires much refining in order to be used for testing yet. We also plan to leave the domain of prototyping and entering the market as a tool that can be sold, for which we have a number of important steps that we would like to include in our microflidics chip-

• Finger Actuated Pressure system - We want to reduce the hassle of using complicated pumps and syringes in the chip as much as possible, and therefore this is a technique we found that uses just a push of a finger on the device to pump in certain amounts of air pressure.^[6]
• We also wish to create a manufacturing mould for a scaled manufacturing of the chip so that it can be market ready. We were helped by CCAMP in Bangalore to plan this out for our future market endeavours

Software

The initial design of the microfluidic chip is based on extensive research into the identification and quantification of specific biomarkers associated with depression. As the project progresses, we will continually refine the chip's design to enhance its sensitivity, accuracy, and efficiency.

One of the primary functions of the microfluidic chip is to analyze biomarker data obtained from blood samples and provide a degree of risk for clinical depression. This risk assessment will be based on complex algorithms and statistical analysis of the biomarker data. We will continuously refine the algorithms used for risk assessment. This iterative process will involve incorporating newly discovered biomarker data, whether from our tool or independently, and improving the accuracy of of our quantification system.

To support our microfluidic chip's research and diagnostic capabilities, we hope to establish a secure, cloud-based database system. This database will serve as the repository for biomarker data collected from blood samples. The infrastructure of this will be designed to scale seamlessly with the growing volume of biomarker data generated by our chip and other research sources. This ensures that we can accommodate the expanding dataset efficiently.

The database will collect biomarker data, but it is important to stress that this data will be limited to relevant biomarkers and anonymized patient history. The focus is strictly on research and diagnostics, with no personal data involved. Robust encryption, access controls, and regular security audits will be implemented to protect the integrity and confidentiality of the biomarker data. Advanced anonymization techniques will be applied to the data to remove any identifying information, ensuring that patient privacy is preserved throughout the research process. Informed consent will be a fundamental aspect of data collection. Participants contributing their data to the database will be required to provide explicit consent, which will be documented and stored securely. We will establish a clear and user-friendly opt-out mechanism, allowing individuals to withdraw their data from the database at any time if they change their mind or wish to discontinue participation. Our project will adhere to ethical guidelines and data protection regulations. We will seek ethical oversight and approval from relevant authorities to ensure transparency and compliance with ethical standards.

A well-structured database is critical for efficient data retrieval and analysis. Our database will be organized to support various research inquiries related to depression biomarkers. Biomarker data will be categorized and tagged to facilitate easy sorting, filtering, and retrieval based on different parameters, such as sample source, date, or biomarker type.

The database will consist of multiple interconnected data tables that include, but not be limited to:

• Patient Information - This table will store anonymized patient identifiers, such as unique study IDs, demographic data (age, gender), and relevant medical history.
• Biomarker Data - Biomarker data will be stored in a structured format, associating each data point with a specific patient and timestamp. Attributes may include biomarker type, concentration, and any related metadata.
• Consent Records - Consent records will document when and how consent was obtained from participants. It will link consent to specific patient data, ensuring transparency and compliance.
• Researcher Information - If applicable, this table will contain information about authorized researchers with access to the database, including their credentials, roles, and research objectives.

We also pan to develop a mental health tracking app, designed to complement the microfluidic chip and enhance mental health monitoring. The app will prioritize accessibility, user-friendliness, and engagement. To maximize accessibility, the app will be developed to run on multiple platforms, including iOS and Android devices, making it available to a wide range of users.

The app's core functionality will revolve around tracking mental health and well-being, with a range of features to support users in monitoring and improving their mental health. Users will be able to record their daily moods and emotions through the app. This data will be graphically displayed, allowing users to visualize trends and identify patterns in their emotional states. The app will include the option to log daily activities and routines, helping users correlate their activities with changes in their mental well-being. A journaling feature will allow users to document their thoughts, feelings, and experiences. This serves as a therapeutic outlet and provides valuable insights into mental health fluctuations. Links to mental health resources, crisis helplines, and expert advice will be readily available to users.

Respecting user privacy is paramount in the development of the mental health tracking app. We will implement stringent privacy measures to ensure user data remains confidential and secure. Users will be required to provide informed consent before using the app. This consent will explicitly outline what data is collected, how it is used, and users' rights regarding their data. Similar to the database for biomarker data, the app will collect only anonymized data, with no personally identifiable information included.

The app's data can also be a valuable resource for research purposes, particularly in identifying correlations between mental health trends and new biomarkers relevant to clinical depression. Data collected from those undergoing antidepressant treatment along with biomarker tracking may lead to a deeper understanding of the relationship between medicines and biomarkers.

Technical Challenges

Biomarkers and assays
Selecting and validating biomarkers is pivotal. The validation process must extend beyond Cacasian populations to ensure broad applicability. Issues like miRNA stability and assay standardization must be rigorously addressed to guarantee accurate results.
Microfluidic chip
Optimizing mixing and sample dispersion on the microfluidic chip is crucial, emphasizing cost-effectiveness in mass production. Sustainable material use and waste disposal methods are also key considerations for environmental impact.
Fluorimeter
enhancing sensitivity and specificity of the fluorimeter, along with seamless integration between the chip and sensors, demands meticulous attention. Calibration procedures and quality control measures are essential for reliable results.
Data Collection:
Integrating machine learning (ML) into data collection processes is imperative for scalability and efficiency, allowing for large-scale analysis of diverse datasets.

Administrative Challenges

Regulations
Navigating regulatory requirements, including the establishment and continuous oversight of an ethics committee, certification acquisition, and quality control measures, is a persistent challenge.
User Training
Ensuring comprehensible instructions in multiple languages and thorough user training is vital. Ongoing user support from the development team is necessary for effective implementation.
Product
Conducting thorough market research to understand potential applications is essential. Tailoring marketing and pricing strategies, conducting risk assessments, and anticipating market demands are integral aspects of successful produtc management.
Scaling Business
Handling increased demand requires adept resource management and allocation, addressing supply chain logistics, organizing customer support, and establishing robust revenue streams.
IP and Patents
Developing a strategic approach for IP and patent filings, including trademark protection, due diligence, and licensing agreements, is critical for protecting intellectual property.

Social Challenges

Data Management and Privacy
Safeguarding sensitive data involves stringent security measures, adherence to legal and ethical requirements, defining data retention periods, obtaining patient consent, and prioritizing patient privacy.
Education
Addressing the stigma associated with mental health requires a concerted effort in education and sensitivity training, both within the user community and the broader public.

In summary, overcoming the challenges in this ambitious project demands a synergistic approach, combining technical innovation, meticulous administrative planning, and a keen understanding of social dynamics. As the project progresses, continuous adaptation, collaboration, and a commitment to ethical and inclusive practices will be essential to realize the full potential of OASYS.