bioETH-PRS: Confidential Polygenic Risk Scoring without a Trusted Evaluator via Fully Homomorphic Encryption on a Programmable Blockchain

TL;DR

bioETH-PRS introduces a blockchain-based protocol that performs confidential polygenic risk scoring entirely within encrypted data, eliminating the need for a trusted evaluator and enhancing privacy in genetic risk prediction.

Contribution

It replaces the evaluator with smart contracts supporting Fully Homomorphic Encryption, enabling secure, on-chain computation of polygenic risk scores without exposing raw data.

Findings

Complete encrypted PRS computation within a blockchain environment.

Achieved 37% reduction in gas costs using streaming path.

Prototype confirms linear gas scaling and potential cost competitiveness.

Abstract

Polygenic risk scores (PRSs) aggregate genetic effect estimates to predict disease susceptibility, yet clinical deployment often exposes raw genotype data to third-party compute infrastructure. Prior homomorphic-encryption approaches, still require trust in a designated evaluator. We present bioETH-PRS, a protocol that replaces that evaluator role with immutable smart contracts on a blockchain supporting Fully Homomorphic Encryption (fhEVM). Using the integer-exact TFHE scheme, bioETH-PRS computes the PRS dot product entirely within the encrypted domain, keeping both genotype dosage vectors and GWAS weight vectors hidden from external parties throughout execution. We introduce a three-step fixed-point quantisation scheme for representing signed GWAS weights as unsigned 64-bit integers, achieving machine-epsilon reconstruction accuracy on validated fixtures. A four-contract architecture separates data custody, model publication, computation, and output release, and supports both a classic chunked path and a streaming path, with the latter reducing mock-measured gas by 37%. An on-chain noisy output oracle emits an encrypted noisy-score handle and a publicly decryptable ternary category, reducing raw score exposure and probing risk. Prototype evaluation on real GWAS fixtures confirms linear gas scaling and suggests that the approach may be cost-competitive in low-gas deployment environments.