Abstract
Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation. While single-gene analyses often lack power due to rare variant sparsity, expanding the unit of association to networks offers a powerful alternative, provided it integrates network connections. Here, we introduce NERINE, a hierarchical model-based association test that integrates gene interactions that integrates gene interactions while remaining robust to network inaccuracies. Applied to biobanks, NERINE uncovers compelling network associations for breast cancer, cardiovascular diseases, and type II diabetes, undetected by single-gene tests. For Parkinson's disease (PD), NERINE newly substantiates several GWAS candidate loci with rare variant signal and synergizes human genetics with experimental screens targeting cardinal PD pathologies: dopaminergic neuron survival and alpha-synuclein pathobiology. CRISPRi-screening in human neurons and NERINE converge on PRL, revealing an intraneuronal α-synuclein/prolactin stress response that may impact resilience to PD pathologies.