Advancing Equity for BIPOC Veterans Through Population-Specific Genomics

BIPOC veterans have served this country for generations, yet datasets to diagnose and treat them have not mirrored their representation, leading to misdiagnoses and inadequate treatment options.

The Challenge: When “Standard” Is not Standard for Everyone

Across the Department of Veterans Affairs (VA), clinicians are charged with delivering consistent, high-quality care to a veteran population that is uniquely diverse - for example, in ancestry, lived experience, service history, environmental exposure, and social determinants of health. Yet at the molecular level, “standard” tools can fail to represent that diversity. Most widely used human reference genomes and variant databases were assembled with disproportionate contributions from individuals of European ancestry. That skew is not merely academic; it shapes how variants are labeled (benign, pathogenic, uncertain) and how clinical decisions are made in primary care, oncology, cardiology, psychiatry, and beyond.

For BIPOC (Black, Indigenous, and People of Color) veterans, the consequences are profound. When a truly common variant in African, Afro-Caribbean, Indigenous, or Latino populations is misclassified as “rare,” it often lands in the chart as a Variant of Uncertain Significance (VUS), which is an ambiguity that delays decisions, triggers unnecessary follow-up testing, and sows mistrust. Conversely, risk alleles that are prevalent in specific ancestries may be missed or underweighted, muting opportunities for earlier screening, targeted prevention, or pharmacogenomic guidance. Add the complexity of military toxic exposures, chronic stress, relocations, and uneven access to specialty care, and you have a system in which veterans of color are statistically more likely to receive less precise guidance from the most advanced tools we possess.

This is not a failure of science; it is a failure of representation. The VA’s mandate for equitable care cannot be met with one-size-fits-all genomic references. To deliver on precision medicine’s promise, we must make the reference fit the patient and not force the patient to fit the reference.

Why Population-Specific Genomics Matters

Population-specific genomics center ancestry, geography, environment, and community context in variant interpretation. It augments mainstream references with ancestry-aware allele frequencies, functionally annotated panels, and continuously updated regional data, all curated alongside rigorous clinical guidelines. In practical terms, this approach turns a “maybe” into a “yes/no,” reducing VUS rates and improving the sensitivity and specificity of findings for veterans of color.

Equity here is not an abstract moral imperative; it is a measurable clinical improvement. Fewer VUS calls mean fewer diagnostic cul-de-sacs. Better ancestry matches mean better risk stratification for cardiometabolic disease, cancer predisposition, autoimmune conditions, and neuropsychiatric disorders. And better pharmacogenomic calls mean fewer adverse drug reactions and faster time-to-effect for medications used widely within the VA (e.g., antidepressants, analgesics, anticoagulants).

The Cost of Uncertainty: Clinical, Emotional, and Economic

Uncertainty is expensive. For clinicians, indeterminate results consume time, require secondary consults, and complicate shared decision-making. For patients, ambiguity fuels anxiety and erodes confidence in the care plan, especially for veterans who have long histories of institutional distrust. System-wide, inconclusive genetic results lead to redundant tests, avoidable imaging, deferred preventive strategies, and missed chances to align care with genomic risk. When these frictions fall disproportionately on BIPOC veterans, uncertainty becomes an equity issue.

 

Precision Medicine Capabilities That Close the Gap

Ancestry-Aware Variant Interpretation

At the heart of population-specific genomics is an interpretation engine that weighs variants against ancestry-matched reference sets. That includes:

• Ancestry-matched allele frequencies: to distinguish truly rare from locally common variants.

• Functional annotations and gene–environment context: to interpret effects where exposures (burn pits, solvents, radiation) interact with genomic susceptibility.

• Continuous curation: community-sourced updates from Minority-Serving Institutions (MSIs), Federally Qualified Health Centers (FQHCs) serving veterans, and VA cohorts to keep panels current.

When the reference reflects the patient, “uncertain” becomes “actionable.”

Integrated Multi-Omics + Clinical Context

Precision medicine gains power as multiple data layers converge:

• Genomics/PGx: risk alleles and drug–gene interactions tailored to ancestry.

• Transcriptomic/epigenetic signals (where appropriate): especially relevant in chronic inflammation, stress biology, and exposure-related pathways.

• Clinical phenotypes: vital signs, labs, imaging, problem lists.

• Exposure and social context: deployment history, MOS-specific hazards, ZIP-code-level SDOH indicators, benefits and claims data.

This integrated view enables more accurate risk modeling, earlier detection, and tighter alignment between guideline-based care and the veteran’s lived environment.

Pharmacogenomics for Safer, Faster Prescribing

BIPOC veterans experience higher rates of adverse drug reactions and “trial-and-error” titration when pharmacogenomic (PGx) differences are overlooked. An ancestry-aware PGx program standardizes testing for high-impact drug classes (e.g., antidepressants, analgesics, cardiovascular agents), codifies results into the electronic health record (EHR) with clear clinical decision support (CDS) rules, and empowers clinicians with confident first-line choices, which lowers medication burden and improves adherence.

Oncology, Cardio-Metabolic, and Autoimmune Use Cases

• Oncology: Better classification of hereditary cancer risk in underrepresented groups avoids both under- and over-surveillance; tumor profiling guided by ancestry-aware germline context refines targeted therapy choices.

• Cardio-Metabolic Disease: Polygenic risk scoring calibrated for diverse ancestry enhances the early identification of high-risk veterans for diabetes, hypertension, and hyperlipidemia, enabling proactive lifestyle, nutrition, and medication strategies.

• Autoimmune/Inflammatory Conditions: Genomic and human Leukocyte Antigen (HLA) diversity captured in population-specific panels clarifies disease subtypes and treatment response.

 

Implementing Population-Specific Genomics in the VA

A Practical Pilot Blueprint (2-3 Sites)

1. Site Selection & Cohort Definition

   Choose two to three VA medical centers with large BIPOC veteran populations and strong community ties (including affiliated MSIs). Define starter cohorts across three domains: cardio-metabolic prevention, behavioral health with PGx, and hereditary cancer risk.

2. Community-Led Consent & Governance

   Establish Community Advisory Boards (CABs), including veterans, caregivers, and MSI partners. Use plain-language consent, tiered data use permissions, and transparent data governance, addressing privacy, GINA protections, data sharing boundaries, and return-of-results pathways.

3. Data Integration & Clinical Decision Support

   Integrate results into the EHR with unambiguous CDS prompts: “Actionable,” “Recommend follow-up,” or “No action.” Ensure Result Access & Communication (RAC) protocols: clinician education, patient-friendly reports, and warm handoffs to genetics counselors.

4. Population-Specific Panels & Continuous Curation

   Deploy ancestry-aware panels validated across African, Afro-Caribbean, Indigenous, and Latino populations. Stand up a curation workstream with MSI partners to update frequencies and reclassify variants on a scheduled cadence with audit trails.

5. Metrics & Outcomes

   Track: VUS rate reduction, change in diagnostic yield, PGx-guided prescribing accuracy, time-to-appropriate therapy, patient-reported trust/understanding, and cost offsets from avoided tests or ED visits. Publish a learning report at 6 and 12 months.

Ethics, Privacy, and Trust by Design

Trust is the currency of precision medicine. Veterans of color are justifiably cautious about how genomic information could be used. A high-integrity program builds safeguards from Day One:

• HIPAA/VA data standards, encryption in transit and at rest, role-based access, and immutable audit logs.

• De-identification and data minimization for research; identifiable data retained only where clinically necessary.

• Community control and transparency – e.g., what is collected, where it lives, who can see it, how long it is kept, and how to revoke consent.

When veterans know their data serves them and only them, engagement rises and care improves.

 

The Equity Dividend – What Success Looks Like

Fewer Unknowns, More Precision

Measurable reductions in VUS rates for BIPOC veterans, higher diagnostic yield in hereditary conditions, and clearer risk stratification translate to timely screenings, targeted interventions, and confidence at the point of care.

Safer Prescribing, Better Adherence

Ancestry-aware PGx reduces adverse events and trial-and-error prescribing. Veterans stabilize faster on effective regimens, which lower hospitalizations and improve quality of life.

Research That Reflects Reality

Partnering with MSIs and VA centers to curate population-specific references ensures that future science is more inclusive than the past. The result: better algorithms, better evidence, and a virtuous cycle where equity and accuracy reinforce each other.

 

How Phronetik Powers Population-Specific Genomics in Veteran Care

Treatment for our veterans is at hand with precision in our capabilities and in our enablement.

Ancestry-Aware Interpretation, Built with Community Partners

Phronetik’s in-house bioinformatics team builds and maintains population-specific genomics reference panels in partnership with MSIs, FQHCs serving veterans, and local community cohorts. Our pipelines incorporate ancestry inference, region-specific allele frequencies, functional annotations, and gene-environment context, so every variant call is read through the lens of the veteran’s ancestry and exposures.

End-to-End Precision Enablement

• Next Generation Sequencing (NGS) & PGx Testing: CLIA-aligned workflows from sample to report, including mobile collection where access barriers exist.

• iConcordia® Data Platform: Secure integration of EHR + omics + exposure + SDOH, with AI-assisted interpretation and clear, clinician-friendly outputs.

• Point-of-Care Acceleration: iHarmony-Seq™ (under development) for rapid sequencing and near real-time reads in community or outpatient settings, which shrinks the gap between sample and clinical action.

• Clinician Uplift: Just-in-time education modules, templated documentation, and embedded CDS ensure results are used and not just filed.

• Community Governance: CABs, tiered consent, and transparent data policies that protect veterans and build durable trust.

A VA-Ready Pilot Charting Vision to Value

We co-design pilots with VA leadership and local stakeholders, focusing first on high-impact use cases: cardio-metabolic prevention, PGx in behavioral health and pain, and hereditary cancer risk. We instrument everything for learning: baseline VUS rates, clinical outcomes, prescribing changes, patient-reported trust, and economic impact. Within 6–12 months, the pilot yields a replicable playbook for scale across the VA.

 

Call to Action – From Underrepresentation to Understanding

Equity in veteran care is not a future aspiration; it is a present obligation. Population-specific genomics gives clinicians a sharper lens and veterans a fairer chance. By aligning ancestry-aware science with ethical governance and community partnership, the VA can set a new national standard: precision that includes everyone.

If you are a VA leader, clinician, researcher, or veteran advocate ready to move from discussion to deployment, let’s design a pilot that proves what is possible, and then make it standard practice.

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