RESUMEN
Transcriptome-wide association study (TWAS) tools have been applied to conduct proteome-wide association studies (PWASs) by integrating proteomics data with genome-wide association study (GWAS) summary data. The genetic effects of PWAS-identified significant genes are potentially mediated through genetically regulated protein abundance, thus informing the underlying disease mechanisms better than GWAS loci. However, existing TWAS/PWAS tools are limited by considering only one statistical model. We propose an omnibus PWAS pipeline to account for multiple statistical models and demonstrate improved performance by simulation and application studies of Alzheimer disease (AD) dementia. We employ the Aggregated Cauchy Association Test to derive omnibus PWAS (PWAS-O) p values from PWAS p values obtained by three existing tools assuming complementary statistical models-TIGAR, PrediXcan, and FUSION. Our simulation studies demonstrated improved power, with well-calibrated type I error, for PWAS-O over all three individual tools. We applied PWAS-O to studying AD dementia with reference proteomic data profiled from dorsolateral prefrontal cortex of postmortem brains from individuals of European ancestry. We identified 43 risk genes, including 5 not identified by previous studies, which are interconnected through a protein-protein interaction network that includes the well-known AD risk genes TOMM40, APOC1, and APOC2. We also validated causal genetic effects mediated through the proteome for 27 (63%) PWAS-O risk genes, providing insights into the underlying biological mechanisms of AD dementia and highlighting promising targets for therapeutic development. PWAS-O can be easily applied to studying other complex diseases.
RESUMEN
Characterizing the genetic mechanisms underlying Alzheimer's disease (AD) dementia is crucial for developing new therapeutics. Proteome-wide association study (PWAS) integrating proteomics data with genome-wide association study (GWAS) summary data was shown as a powerful tool for detecting risk genes. The identified PWAS risk genes can be interpretated as having genetic effects mediated through the genetically regulated protein abundances. Existing PWAS analyses of AD often rely on the availability of individual-level proteomics and genetics data of a reference cohort. Leveraging summary-level protein quantitative trait loci (pQTL) reference data of multiple relevant tissues is expected to improve PWAS findings for studying AD. Here, we applied our recently developed OTTERS tool to conduct PWAS of AD dementia, by leveraging summary-level pQTL data of brain, cerebrospinal fluid (CSF), and plasma tissues, and multiple statistical methods. For each target protein, imputation models of the protein abundance with genetic predictors were trained from summary-level pQTL data, estimating a set of pQTL weights for considered genetic predictors. PWAS p-values were obtained by integrating GWAS summary data of AD dementia with estimated pQTL weights. PWAS p-values from multiple statistical methods were combined by the aggregated Cauchy association test to yield one omnibus PWAS p-value for the target protein. We identified significant PWAS risk genes through omnibus PWAS p-values and analyzed their protein-protein interactions using STRING. Their potential causal effects were assessed by the probabilistic Mendelian randomization (PMR-Egger). As a result, we identified a total of 23 significant PWAS risk genes for AD dementia in brain, CSF, and plasma tissues, including 7 novel findings. We showed that 15 of these risk genes were interconnected within a protein-protein interaction network involving the well-known AD risk gene of APOE and 5 novel findings, and enriched in immune functions and lipids pathways including positive regulation of immune system process, positive regulation of macrophage proliferation, humoral immune response, and high-density lipoprotein particle clearance. Existing biological evidence was found to relate our novel findings with AD. We validated the mediated causal effects of 14 risk genes (60.8%). In conclusion, we identified both known and novel PWAS risk genes, providing novel insights into the genetic mechanisms in brain, CSF, and plasma tissues, and targeted therapeutics development of AD dementia. Our study also demonstrated the effectiveness of integrating public available summary-level pQTL data with GWAS summary data for mapping risk genes of complex human diseases.
RESUMEN
Background: Through preoperative localization, surgeons can easily locate ground glass nodules (GGNs) and effectively control the extent of resection. Therefore, it is necessary to choose an appropriate puncture positioning method. The purpose of this study was to evaluate the effectiveness and safety of medical glue and positioning hooks in the preoperative positioning of GGNs and to provide a reference for clinical selection. Methods: From March 30, 2020 to June 13, 2022, a total of 859 patients with a CT diagnosis of GGNs requiring surgical resection were included in our study at the hospital. Among them, 21 patients who either opted out or could not undergo preoperative localization for various reasons were excluded. Additionally, 475 patients who underwent preoperative localization using medical glue and 363 patients who underwent preoperative localization through positioning hooks were also excluded. We conducted statistical analyses on the baseline data, success rates, complications, and pathological results of the remaining patients. The success rates, complication rates, and pathological results were compared between the two groups-those who received medical glue localization and those who received positioning hook localization. Results: There was no statistically significant difference between the two groups of patients in terms of age, body mass index, smoking history, location of the nodule, distance of the nodule from the pleura, or postoperative pathological results (P > 0.05). The success rate of medical glue and positioning hooks was 100%. The complication rates of medical glue and positioning hooks during single nodule positioning were 39.18% and 23.18%, respectively, which were significantly different (p < 0.001); the complication rates during multiple nodule positioning were 49.15% and 49.18%, respectively, with no statistically significant differences (p > 0.05). In addition, the method of positioning and the clinical characteristics of the patients were not found to be independent risk factors for the occurrence of complications. The detection rate of pulmonary nodules also showed some positive correlation with the spread of COVID-19 during the 2020-2022 period when COVID-19 was prevalent. Conclusion: When positioning a single node, the safety of positioning hooks is greater than when positioning multiple nodes, the safety of medical glue and positioning hooks is comparable, and the appropriate positioning method should be chosen according to the individual situation of the patient.