1. INTRODUCTION

Polygenic risk scores (PRS) are statistical tools that combine the effects of numerous genetic variants to estimate an individual's predisposition to a complex disease, such as cardiovascular disease, diabetes, or certain cancers. Unlike a diagnostic test that identifies an existing condition, a PRS generally estimates probability and does not establish that an individual will develop a disease.

Predictive inaccuracies may arise from limited training data, population differences, inappropriate statistical models, poor calibration, incorrect interpretation, or the use of a score outside its validated clinical setting. Research indicates that scores developed predominantly using European-ancestry populations may perform less accurately in other ancestry groups, potentially worsening health disparities. <Cite refs={["turn544042search3","turn544042search10"]}/>

The legal implications include medical negligence, misleading commercial representations, discrimination, privacy violations, and defective clinical decision-making. Liability depends on the applicable law, the intended use of the score, the foreseeability of harm, and whether the relevant party breached a legal duty.

2. LEGAL AND REGULATORY FRAMEWORK

A. CLINICAL VALIDITY AND PROFESSIONAL DUTY

Healthcare professionals must exercise reasonable care when interpreting genetic-risk information. A score should be assessed for analytical validity, clinical validity, calibration, and clinical utility before being relied upon for a particular medical decision. Treating a probabilistic score as a definitive diagnosis may lead to unnecessary interventions or missed opportunities for prevention.

B. MEDICAL DEVICE AND DIAGNOSTIC REGULATION

Depending on the jurisdiction and intended use, a PRS test and its associated software may fall within diagnostic or medical-device regulation. In the European Union, the In Vitro Diagnostic Medical Devices Regulation (EU) 2017/746 may apply to relevant genetic tests and associated software. Classification and conformity-assessment requirements depend on the product and applicable rules. <Cite refs={["turn544042search5"]}/>

C. DATA PROTECTION AND GENETIC PRIVACY

Genetic data can reveal information about an individual and biological relatives. Collection, processing, storage, and disclosure must comply with applicable data-protection law. In India, the Digital Personal Data Protection Act, 2023, and other applicable laws must be considered according to their commencement, scope, and exemptions.

D. ANTI-DISCRIMINATION LAW

In the United States, the Genetic Information Nondiscrimination Act of 2008 (GINA) restricts specified uses of genetic information in employment and health insurance. Whether a particular PRS falls within the statutory definition requires analysis of its contents and intended use. GINA does not provide comprehensive protection against genetic discrimination in every insurance market or social context. <Cite refs={["turn544042search6","turn544042search9"]}/>

3. PRINCIPAL LEGAL IMPLICATIONS

A. MEDICAL NEGLIGENCE: A clinician may face liability where unreasonable reliance on an inaccurate score causes foreseeable harm and the applicable elements of negligence are established.

B. PRODUCT AND PROFESSIONAL LIABILITY: A laboratory or developer may face claims concerning defective testing, inadequate validation, negligent interpretation, or misleading performance claims, subject to applicable statutory requirements.

C. INFORMED CONSENT: Patients should understand that PRS estimates risk rather than certainty, including relevant limitations and the possibility of population-specific inaccuracies.

D. DISCRIMINATION: Employers or insurers may misuse genetic-risk estimates to make prohibited decisions. Liability depends on the applicable anti-discrimination statute and whether the information and conduct fall within its protections.

E. EVIDENTIARY RELIABILITY: Inaccurate or poorly validated scores may be challenged when offered as evidence in litigation, insurance disputes, or regulatory proceedings.

F. PUBLIC-HEALTH CONSEQUENCES: Inaccurate population-level predictions may misallocate screening resources, produce unequal access to preventive care, or undermine trust in genomic medicine.4. IMPORTANT CASE LAWS

There is no established body of reported judgments specifically deciding liability for inaccurate polygenic risk scores. The following cases provide relevant direct or analogous legal principles.

A. LOWE v. ATLAS LOGISTICS GROUP RETAIL SERVICES (ATLANTA), LLC, 102 F. SUPP. 3D 136 (N.D. GA. 2015) — DIRECT GENETIC-DISCRIMINATION AUTHORITY

The United States District Court considered alleged violations of GINA arising from an employer's collection of employees' DNA samples to investigate workplace theft. The case illustrates that genetic information may attract statutory protection even when collected for a purpose unrelated to medical diagnosis. Its relevance to PRS lies in the potential unlawful acquisition or use of genetic information, although it did not concern predictive-score accuracy.

B. JUSTICE K.S. PUTTASWAMY v. UNION OF INDIA (2017) 10 SCC 1 — ANALOGOUS PRIVACY AUTHORITY

The Supreme Court of India recognised privacy as a fundamental right, including informational privacy and individual autonomy. The principles are relevant to the collection and use of genomic data underlying PRS calculations, particularly where sensitive information is disclosed or processed without a valid legal basis.

C. SAMIRA KOHLI v. DR. PRABHA MANCHANDA (2008) 2 SCC 1 — DIRECT MEDICAL-CONSENT AUTHORITY

The Supreme Court of India explained that valid medical consent requires adequate information about the proposed intervention and cannot be assumed merely because a patient has agreed to one procedure. Applied by analogy, patients receiving PRS-guided care should be informed of material limitations, uncertainties, and alternatives where these affect the proposed intervention.

D. MONTGOMERY v. LANARKSHIRE HEALTH BOARD [2015] UKSC 11 — DIRECTLY RELEVANT TO RISK DISCLOSURE

The United Kingdom Supreme Court held that doctors must take reasonable care to ensure patients are aware of material risks of a recommended treatment and reasonable alternatives. The decision is relevant where a clinician's failure to explain the limitations of a PRS materially affects a patient's treatment decision. It does not establish a separate universal duty to disclose every statistical uncertainty.

E. DAUBERT v. MERRELL DOW PHARMACEUTICALS, INC., 509 U.S. 579 (1993) — ANALOGOUS SCIENTIFIC-EVIDENCE AUTHORITY

The United States Supreme Court addressed the admissibility of expert scientific evidence under the Federal Rules of Evidence. It emphasised the trial judge's gatekeeping responsibility in assessing whether scientific reasoning or methodology is sufficiently reliable and relevant. This principle is useful when challenging PRS evidence based on inadequate validation, unreliable methodology, or unjustified extrapolation.

F. KUMHO TIRE CO. v. CARMICHAEL, 526 U.S. 137 (1999) — ANALOGOUS EXPERT-EVIDENCE AUTHORITY

The Supreme Court clarified that the reliability requirement for expert evidence applies to technical and specialised knowledge as well as scientific testimony. The case supports scrutiny of the methods used by experts who interpret polygenic predictions in legal proceedings. Neither Daubert nor Kumho Tire establishes a specific legal accuracy threshold for PRS.

5. PRACTICAL COMPLIANCE AND RISK MANAGEMENT

Healthcare providers, laboratories, and developers should implement the following safeguards:

VALIDATION: Establish analytical and clinical validity for the intended use and relevant population.

CALIBRATION: Verify that absolute-risk estimates are appropriately calibrated rather than relying solely on relative-risk rankings.

POPULATION REPRESENTATIVENESS: Assess performance across relevant ancestry groups and investigate disparities.

INFORMED COMMUNICATION: Explain uncertainty, limitations, and the distinction between genetic predisposition and actual disease.

HUMAN CLINICAL REVIEW: Integrate PRS results with family history, clinical findings, and other established risk factors.

DOCUMENTATION: Preserve validation studies, model versions, limitations, quality-control records, and communications with patients.

PRIVACY AND SECURITY: Restrict access to genetic information and comply with applicable data-protection requirements.

CORRECTIVE ACTION: Investigate inaccurate results, notify affected parties where legally required, correct records, and reassess clinical decisions when material errors are identified.

6. CONCLUSION

Predictive inaccuracies in polygenic scores can create significant legal risks when unreliable estimates influence diagnosis, treatment, insurance, employment, or public-health decisions. However, a prediction that proves incorrect does not automatically establish negligence or liability: the applicable duty, standard of care, causation, and legally recognised harm must be evaluated.

The cited judgments provide guidance on genetic discrimination, privacy, informed consent, and scientific evidence. Most are analogous to PRS-specific disputes, and none should be represented as establishing a universal legal standard for polygenic-score accuracy. Effective governance requires validated models, transparent risk communication, population-sensitive performance assessment, appropriate human oversight, and meaningful remedies when unlawful conduct causes harm.