Week 1 HW: Principles and Practices

Synthetic Biology for Early Detection of Postpartum Depression

Postpartum depression (PPD) is one of the most common complications of childbirth, affecting roughly 10–20% of mothers worldwide, with a recent large meta-analysis estimating a global prevalence around 17%. Untreated PPD harms not only maternal health but also infant development, attachment, and long-term family well-being.

Despite this burden, most health systems rely on short questionnaires like the Edinburgh Postnatal Depression Scale (EPDS) or PHQ-9, which vary widely in what proportion of affected women they detect and are not always followed up with clinical evaluation. Many women never receive a formal diagnosis or treatment, due to under-screening, stigma, and uneven access to mental health care.

At the same time, emerging work suggests that specific blood biomarkers and epigenetic signatures during late pregnancy can predict which women are likely to develop PPD, with some studies reporting predictive accuracies close to 88%. This opens the door to biological sensing, rather than relying only on self-report.

The tool I want to develop

Concept: a biomarker-sensing synthetic biology platform for PPD risk

My idea is to design a modular synthetic biology platform that can sense molecular markers associated with postpartum depression risk in a minimally invasive sample (for example, finger-prick blood or saliva) and produce an easy-to-interpret readout that could be integrated into postpartum care.

Key features:

• Uses known or emerging PPD-associated biomarkers (for example, genes regulating estrogen signaling, epigenetic changes around targets like TTC9B, or other stress-response–linked markers).
• Implements biosensors in a safe, cell-free or contained system (for example, paper-based or microfluidic cell-free expression system) to avoid releasing live GMOs.
• Outputs a semi-quantitative risk score that must be interpreted by a clinician, not a stand-alone diagnosis.

Why synthetic biology?

• Synthetic biology has already been used to build low-cost, paper-based diagnostics for infectious diseases and metabolic markers, suggesting similar architectures could be adapted for mental health–relevant biomarkers.
• A synthetic biosensor could ultimately enable decentralized, low-cost PPD risk screening, including in settings where mental health professionals are scarce, if developed responsibly.

For this class, my project focus is to:

• Map from current knowledge about PPD biomarkers to plausible synthetic sensing strategies.
• Prototype in-silico designs for sensor circuits and outline a feasible wet‑lab pipeline in a safe, scoped way (no actual patient samples).
• Analyze governance and policy implications to avoid harm and promote equitable, ethical use.

Policy and governance goals

My overarching ethical goal is: Enable earlier detection of postpartum depression in a way that reduces harm, respects autonomy, and does not exacerbate inequities.

I break this into four concrete policy/governance goals:

1. Ensure safety and biosecurity
   Prevent misuse of any biological components or data in ways that could harm mothers or infants, and ensure lab work uses appropriate containment and avoids unnecessary handling of human samples or high-risk constructs.

2. Protect autonomy, privacy, and informed consent
   Avoid creating tools that pressure women into testing or treatment, and ensure any real-world deployment would require informed, voluntary participation with clear explanations of limitations.

3. Promote equity and access
   Avoid building a “luxury diagnostic” that only wealthy health systems can implement, and consider how design choices affect low‑resource settings and marginalized groups who already face higher PPD risk.

4. Support constructive, evidence-based use
   Ensure any biosensor results are used as one input in holistic care, not as a binary label, and encourage integration with follow‑up support, not just risk labeling.

Governance actions

Action 1: Institutional review and mental‑health ethics checklist

Purpose

Currently, many early‑stage synthetic biology projects in academic settings are reviewed primarily for biosafety, not for mental‑health–specific ethical risks such as stigma, coercion, and data privacy. I propose that any institutional project involving PPD biomarkers or synthetic biosensors for mental health must undergo standard biosafety/IRB review plus a short mental‑health–focused ethics checklist.

Design

• Actors: university IRBs, biosafety committees, mental health professionals, PIs.
• Requirements:
  • Projects submit a one‑page statement describing: target population, potential harms (false positives/negatives, stigma), data handling plans, and strategies to ensure results do not replace clinical judgment.
  • At least one reviewer with psychiatric or maternal health expertise participates in review for these projects.
  • For class projects, an adapted, lighter checklist is integrated into the syllabus (for example, an “ethics box” in weekly assignments).

Assumptions

• Institutions have access to at least one clinician or ethicist with maternal mental health expertise.
  • Extra review burden does not discourage students or early‑career researchers from working on maternal mental health at all.
  • Checklists actually change design decisions rather than becoming a box‑ticking exercise.

Risks of failure and “success”

• Failure: the checklist becomes performative, and projects move to less regulated settings (DIY labs, startups) to avoid oversight.
• “Success” risks: higher perceived sensitivity of mental‑health projects may stigmatize the topic further, and over‑cautious review could delay low‑risk, beneficial work.

Action 2: Voluntary technical standard for low‑risk, cell‑free PPD biosensors

Purpose

Right now, biosensor design choices (cell‑free vs. live cells, DNA format, kill‑switches) are largely left to individual labs or companies. I propose a voluntary technical standard for “low‑risk” PPD biosensor prototypes that:

• Strongly favors cell‑free systems and non‑replicating genetic material.
• Recommends no direct use of patient samples in early prototyping (use synthetic oligos or spiked serum from standard sources).
• Specifies minimal documentation for transparency.

Design

• Actors: academic consortia, funding agencies, community labs.
• Elements:
  • A short guidance document: acceptable chassis (for example, E. coli cell‑free extract on paper), permitted sample types (synthetic controls), safe storage and disposal.
  • Template protocol library emphasizing: use of standard constructs, safe waste handling, no clinical claims.
  • Funding incentives: grants and awards preferentially support projects that adhere to the standard.

Assumptions

• Cell‑free systems are sufficient for proof-of-concept sensing of relevant biomarkers.
• Labs will adopt a voluntary standard if funders and journals signal support.
• Standards can be updated as biomarker science evolves.

Risks of failure and “success”

• Failure: low adoption in high‑pressure environments where speed and novelty trump safety conventions, and standards become outdated as new biomarkers or assay technologies emerge.
• “Success” risks: creates a de facto “approved” technical pathway that may unintentionally lock out innovative but safe alternatives, and could be misinterpreted as safety certification.

Action 3: Public sector guidance on responsible PPD biomarker testing and data use

Purpose

There is increasing interest in blood‑based or genetic tests to predict psychiatric risk, including PPD, but little clear public guidance on how these results should be communicated and used, particularly around stigma and insurance discrimination. I propose that national health agencies publish official guidance on:

• Appropriate use of PPD biomarker or biosensor tests (always as adjuncts, never stand-alone diagnoses).
• Communication of probabilistic risk and uncertainty to patients.
  • Data protection and non‑discrimination principles.

Design

• Actors: national health agencies, professional societies in psychiatry and obstetrics, regulators.
• Steps:
  • Convene working groups including obstetricians, psychiatrists, ethicists, and patient advocates.
  • Draft guidelines on consent forms, counselling before/after testing, limits of interpretation, and how to integrate test results into care pathways.
  • Encourage insurers and employers to sign on to non‑discrimination commitments for PPD biomarker information.

Assumptions

• PPD biomarker tests will become increasingly accurate and available, making pre‑existing guidance necessary.
• Public agencies are willing to act proactively rather than waiting for commercial products to force reactive regulation.
  • Non‑discrimination norms can be enforced or at least monitored.

Risks of failure and “success”

• Failure: guidance exists but is poorly implemented at clinic level, while commercial tests emerge that sidestep guidance and create confusion.
• “Success” risks: guidance that is too conservative may discourage investment in beneficial diagnostics, and strong data‑protection rules might make it harder to study which tests truly improve outcomes if not designed carefully.

Using a 1–3 scale (1 = best, 3 = worst, n/a = not applicable):

Which options I would prioritize and for whom

For an HTGAA‑scale class project and early‑stage academic work, I would prioritize a combination of Action 1 and Action 2:

• Action 2 (low‑risk technical standard) directly shapes the design of my synthetic biology experiments: favor cell‑free systems, standard genetic parts, synthetic controls instead of patient samples, and clear waste‑handling.
• Action 1 (institutional mental‑health ethics review) forces me and other students to explicitly consider how a PPD biosensor might affect real people, even if our class prototype never leaves the lab.

For national or international audiences (for example, a ministry of health or WHO‑like body), Action 3 becomes critical as soon as biomarker‑based PPD tests move from research to clinical or commercial deployment.

Trade‑offs and uncertainties:

• Additional ethical review processes could slow or deter students from working on maternal mental health, a domain that is already under‑resourced.
• It remains uncertain whether current biomarker candidates, even with promising predictive performance, will generalize across populations and avoid worsening inequities if tests are rolled out prematurely.
• My scoring assumes that simple, cell‑free technical standards are enough to meaningfully reduce biosafety risk; future technologies may require revisiting these assumptions.

Experimental plan and documentation

In‑silico experiments

Goal: Explore how PPD‑associated biomarkers could be detected using synthetic circuits, and prototype a sensor design computationally.

1. Literature mapping
   Summarize key PPD biomarker papers on blood biomarkers and epigenetic signatures, noting biomarker type, dynamic range, and sample type.

2. Sensor design sketches
   Choose one biomarker type that is plausible to sense (for this class, assume mRNA or protein), and sketch two architectures: a cell‑free toehold switch and a small‑molecule–responsive transcription-factor system.

3. Sequence design and simulation
   Use tools like NUPACK or Benchling to design and test a toehold switch recognizing a short biomarker-related RNA sequence, checking secondary structures and specificity.

4. Risk reflection in design
   For each sensor variant, add notes about who could be helped or harmed if it worked perfectly, and explicitly state that any risk output would need clinical interpretation.

Lab experiments (safe scope)

Because I will not be working with human samples or real depression biomarkers, the lab work focuses on generic sensor behavior using safe, synthetic targets.

Example pipeline:

1. Cell‑free reporter system setup
   Use a cell‑free expression system to express a fluorescent or colorimetric reporter (for example, GFP or LacZ) under control of a toehold or inducible promoter.

2. Synthetic input testing
   Design synthetic RNA or DNA oligos that mimic a biomarker‑related sequence region and test no‑input, low, medium, and high input conditions, measuring reporter output.

3. Documenting failures
   When the reporter fails to turn on, record hypothesized reasons (for example, misfolding, degradation), troubleshooting steps, and include photos or instrument screenshots.

4. Tie back to governance
   For each experimental step, note biosafety level, how you complied, and how this aligns with the “low‑risk technical standard” idea.

Ethical concerns and additional governance ideas

Working on a synthetic biology concept for postpartum depression highlighted that biomarker-based prediction of mental health conditions can be double-edged: it can enable early support but also increase labeling, discrimination, or pressure to act in certain ways. I also became more aware of how false positives and false negatives in mental-health diagnostics have different ethical implications than in infectious disease, because they intersect with identity and parenting.

Additional governance actions I would suggest:

1. Co‑design with affected communities
   Require that any PPD diagnostic tool development includes consultation with postpartum women from diverse backgrounds, especially those most affected by PPD.

2. Educational materials for clinicians and communities
   Develop plain‑language materials on what PPD is, the limits of biomarker tests, and how to access support regardless of test results.

3. Open documentation of limitations
   Encourage projects (including class projects) to clearly document uncertainty, failed attempts, and limitations, aligning with the HTGAA emphasis on transparent documentation.