Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using addi...
Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth. Findings: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75–0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The po
Background IFITM3, an innate immune response protein and inhibitor of viral infection, was reported to modulate amyloid-β production in Alzheimer’s disease (AD). We aimed to identify single-nucleotide polymorphisms ...
Background IFITM3, an innate immune response protein and inhibitor of viral infection, was reported to modulate amyloid-β production in Alzheimer’s disease (AD). We aimed to identify single-nucleotide polymorphisms (SNPs) in IFITM3 associated with cognition and AD biomarkers. Method We used genetic, longitudinal cognition and AD biomarker data from Alzheimer’s Disease Neuroimaging Initiative (ADNI; N = 1,565) and AddNeuroMed (N = 633) as discovery and replication samples, respectively. First, we performed gene-based association analysis of SNPs in IFITM3 with cognitive performance. Second, we performed SNP-based association analysis in IFITM3 with cognitive decline and AD biomarkers from amyloid positron emission tomography (PET), cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI). Result Gene-based association analysis showed that IFITM3 was significantly associated with cognitive performance (permutation-corrected p = 1.25×10 −3 ). Particularly, among two SNPs (rs10751647, rs2091850) in IFITM3 significantly associated with cognitive performance, rs10751647 was associated with cognitive decline in ADNI, which was replicated in AddNeuroMed. In addition, rs10751647 was significantly associated with amyloid-β deposition measured by amyloid PET scan, CSF phosphorylated tau levels, and entorhinal cortical thickness measured by MRI scan in ADNI. The association of rs10751647 with entorhinal cortical thickness was replicated in AddNeuroMed. Participants with minor alleles (C) of rs10751647 have less cognitive decline, less amyloid and tau burden, and less brain atrophy. eQTL analysis showed that rs10751647 is associated with IFITM3 expression levels in blood and brain. Conclusion This suggests that rs10751647 in IFITM3 is associated with less vulnerability for cognitive decline and AD biomarkers, providing mechanistic insight regarding involvement of immune activity and infection in AD.
We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, u...
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We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.
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