March 3, 2026Open Access

CL-GIE v4.0: Blockchain-Anchored Cross-Layer Genomic Integrity With Hierarchical Bloom–Merkle Trees for Ethics-Aware, Explainable Personalized Gene Editing

Key Points

CL-GIE provides a verifiable integrity framework for gene editing by utilizing blockchain technology and advanced metrics.
With a state-of-the-art ROC of 0.991, it outperforms traditional models while ensuring minimal latency under 0.02 ms for record verification.
The method uses a hierarchical bloom-merkle tree for efficient proofs, ensuring forensic-level auditability for gene editing processes.
Findings highlight that integrating ethical considerations and environmental shifts achieves optimal operational performance, calling for further research in ethical frameworks.

Abstract

Personalized gene editing demands verifiable integrity, governance-aware decisioning, and forensics-grade auditability across heterogeneous evidence sources (CRISPR logs, phenotype outcomes, and ledger records). We present CL-GIE v4.0, a cross-layer genomic integrity evaluator that fuses: (i) a Hierarchical Bloom–Merkle Tree (HBMT) for O(log N) membership proofs and vertical consistency; (ii) an entropy–KL drift channel that detects distributional shifts across temporal, phenotypic, and edit-type features; (iii) lightweight structural checks (timestamp monotonicity, hash replay); and (iv) an interpretable ethics policy engine. HBMT yields succinct proofs (depth ≈ 14 on our test set) with verified roots, enabling forensics-ready attestations and chain anchoring. CL-GIE operates under tight latency budgets: per-record HBMT verification is ∼0.02 ms, while meta-model scoring remains sub-millisecond, sustaining real-time pipelines. Empirically, CL-GIE surpasses one-class, reconstruction, clustering, and rules baselines. A stacked variant attains state-of-the-art ROC (AUC= 0.991), while isotonic meta-calibration maximizes area under the precision–recall curve (AP = 0.852), reflecting robustness at low prevalence. Confusion matrices corroborate high recall and specificity (e.g., stacked: TP = 480, FN = 23, TN = 9398, FP = 99), aligning with clinical detection priorities and low false-positive exposure. An ablation-driven weight sweep shows that ethics signals and cross-layer drift are pivotal at the optimal operating point, with validation F1≈0.81–0.88 across calibrated and stacked settings. Radar and correlation analyses further indicate balanced gains across AUROC, AUPR, F1, specificity, and calibration metrics. Overall, CL-GIE delivers a principled, explainable, and audit-capable integrity layer for ethically governed gene-editing workflows, unifying cryptographic proofs, drift-aware detection, and policy transparency under a single evaluative framework.

CL-GIE v4.0: Blockchain-Anchored Cross-Layer Genomic Integrity With Hierarchical Bloom–Merkle Trees for Ethics-Aware, Explainable Personalized Gene Editing

Key Points

Abstract

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