A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits.

The development of polygenic risk scores (PRSs) has proved useful to stratify the general European population into different risk groups. However, PRSs are less accurate in non-European populations due to genetic differences across different populations. To improve the prediction accuracy in non-European populations, we propose a cross-population analysis framework for PRS construction with both individual-level (XPA) and summary-level (XPASS) GWAS data. By leveraging trans-ancestry genetic correlation, our methods can borrow information from the Biobank-scale European population data to improve risk prediction in the non-European populations. Our framework can also incorporate population-specific effects to further improve construction of PRS. With innovations in data structure and algorithm design, our methods provide a substantial saving in computational time and memory usage. Through comprehensive simulation studies, we show that our framework provides accurate, efficient, and robust PRS construction across a range of genetic architectures. In a Chinese cohort, our methods achieved 7.3%-198.0% accuracy gain for height and 19.5%-313.3% accuracy gain for body mass index (BMI) in terms of predictive R2 compared to existing PRS approaches. We also show that XPA and XPASS can achieve substantial improvement for construction of height PRSs in the African population, suggesting the generality of our framework across global populations.

A PD-L1-targeting Regulator for Metabolic Reprogramming to Enhance Glutamine Inhibition-Mediated Synergistic Antitumor Metabolic and Immune Therapy.

Inhibition of glutamine metabolism in tumor cells can cause metabolic compensation-mediated glycolysis enhancement and PD-L1 upregulation-induced immune evasion, significantly limiting the therapeutic efficacy of glutamine inhibitors. Here, inspired by the specific binding of receptor and ligand, a PD-L1-targeting metabolism and immune regulator (PMIR) are constructed by decorating the glutaminase inhibitor (BPTES)-loading zeolitic imidazolate framework (ZIF) with PD-L1-targeting peptides for regulating the metabolism within the tumor microenvironment (TME) to improve immunotherapy. At tumor sites, PMIR inhibits glutamine metabolism of tumor cells for elevating glutamine levels within the TME to improve the function of immune cells. Ingeniously, the accompanying PD-L1 upregulation on tumor cells causes self-amplifying accumulation of PMIR through PD-L1 targeting, while also blocking PD-L1, which has the effects of converting enemies into friends. Meanwhile, PMIR exactly offsets the compensatory glycolysis, while disrupting the redox homeostasis in tumor cells via the cooperation of components of the ZIF and BPTES. These together cause immunogenic cell death of tumor cells and relieve PD-L1-mediated immune evasion, further reshaping the immunosuppressive TME and evoking robust immune responses to effectively suppress bilateral tumor progression and metastasis. This work proposes a rational strategy to surmount the obstacles in glutamine inhibition for boosting existing clinical treatments.