Reviewing and assessing existing meta-analysis models and tools

Integrative analysis of gene expression datasets in corneal endothelium samples of Fuchs endothelial corneal dystrophy

FECD is an age-related progressive ocular disorder characterized by the gradual loss of corneal endothelial cells. Although the exact pathogenesis of FECD remains incompletely understood, differentially expressed genes in the corneal endothelium of FECD patients compared to controls have been reported in several studies. However, a consensus regarding consistently affected genes in FECD has not been established. To address this issue, we conducted a comprehensive meta-analysis incorporating five studies with data that met our predefined inclusion criteria. The combined dataset included 41 FECD patients and 26 controls. We conducted study-level analyses, followed by a meta-analysis, and subsequent functional enrichment analysis targeting the topmost DEGs. Our findings revealed a total of 1537 consistently dysregulated genes in the corneal endothelium of FECD patients. Notably, only 14.6% (224/1537) of these DEGs had been previously identified as statistically significant in individual datasets. Functional enrichment analysis revealed that the upregulated DEGs were significantly enriched in immune-related signaling pathways, with a particularly high enrichment in "The NLRP3 inflammasome" and "Inflammasomes" pathways. In conclusion, we successfully identify a set of consistently dysregulated genes in FECD, which are associated with both established and novel biological pathways. This study highlights the importance of further investigating the role of inflammasomes in FECD pathogenesis and exploring strategies to modulate inflammasome activation for the management of this debilitating condition.

A Positive Association between Working Memory Capacity and Human Creativity: A Meta-Analytic Evidence

Creativity serves as a fountain for social and scientific development. As one of the most crucial human capabilities, creativity has been believed to be supported by the core component of higher cognitive functions—working memory capacity (WMC). However, the evidence supporting the association between WMC and creativity remains contradictory. Here, we conducted a meta-analysis using random-effects models to investigate the linear association between WMC and creativity by pooling the individual effect size from the previous literature. Further, a subgroup analysis was performed to examine whether such association is specific for different WMC categories (i.e., verbal WMC, visual−spatial WMC and dual-task WMC). The main meta-analytic results showed a significantly positive association between WMC and creativity (r = .083, 95% CI: .050−.115, p < .001, n = 3104, k = 28). The subgroup analysis demonstrated consistent results by showing a significantly positive association between them, irrespective of WMC category. We also found that cultural environments could moderate this association, and we identified a strong correlation in participants from an Asian cultural context. In conclusion, this study provides the evidence to clarify the positive association between WMC and creativity, and implies that the Asian cultural context may boost such an association.

Candidate loci for leaf angle in maize revealed by a combination of genome-wide association study and meta-analysis

Leaf angle (LA) is a key component of maize plant architecture that can simultaneously govern planting density and improve final yield. However, the genetic mechanisms underlying LA have not been fully addressed. To broaden our understanding of its genetic basis, we scored three LA-related traits on upper, middle, and low leaves of 492 maize inbred lines in five environments. Phenotypic data revealed that the three LA-related traits were normally distributed, and significant variation was observed among environments and genotypes. A genome-wide association study (GWAS) was then performed to dissect the genetic factors that control natural variation in maize LA. In total, 85 significant SNPs (involving 32 non-redundant QTLs) were detected (p ≤ 2.04 × 10–6), and individual QTL explained 4.80%–24.09% of the phenotypic variation. Five co-located QTL were detected in at least two environments, and two QTLs were co-located with multiple LA-related traits. Forty-seven meta-QTLs were identified based on meta-analysis combing 294 LA-related QTLs extracted from 18 previously published studies, 816 genes were identified within these meta-QTLs, and seven co-located QTLs were jointly identified by both GWAS and meta-analysis. ZmULA1 was located in one of the co-located QTLs, qLA7, and its haplotypes, hap1 and hap2, differed significantly in LA-related traits. Interestingly, the temperate materials with hap2 had smallest LA. Finally, we also performed haplotype analysis using the reported genes that regulate LA, and identified a lot of maize germplasms that aggregated favorable haplotypes. These results will be helpful for elucidating the genetic basis of LA and breeding new maize varieties with ideal plant architecture.

Formal Meta-Analysis of Hypoxic Gene Expression Profiles Reveals a Universal Gene Signature

Integrating transcriptional profiles results in identifying gene expression signatures that are more robust than those obtained for individual datasets. However, a direct comparison of datasets derived from heterogeneous experimental conditions is problematic, hence their integration requires applying of specific meta-analysis techniques. The transcriptional response to hypoxia has been the focus of intense research due to its central role in tissue homeostasis and prevalent diseases. Accordingly, many studies have determined the gene expression profile of hypoxic cells. Yet, despite this wealth of information, little effort has been made to integrate these datasets to produce a robust hypoxic signature. We applied a formal meta-analysis procedure to datasets comprising 430 RNA-seq samples from 43 individual studies including 34 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression in human cell lines grown ingin vitro. This approach revealed that a large proportion of the transcriptome is significantly regulated by hypoxia (8556 out of 20,888 genes identified across studies). However, only a small fraction of the differentially expressed genes (1265 genes, 15%) show an effect size that, according to comparisons to gene pathways known to be regulated by hypoxia, is likely to be biologically relevant. By focusing on genes ubiquitously expressed, we identified a signature of 291 genes robustly and consistently regulated by hypoxia. Overall, we have developed a robust gene signature that characterizes the transcriptomic response of human cell lines exposed to hypoxia in vitro by applying a formal meta-analysis to gene expression profiles.