Landscape Fire Air Pollution as a Mediator in Drought and Childhood Stunting Pathway in Low- and Middle-Income Countries.

Drought induces dry hazards, including wildfire, and increased air pollution from wildfire may be a mechanism by which drought increases health risks. We examined whether the drought-wildfire pathway increases the risk of childhood stunting. We analyzed all geocoded children under five across 44 low- and middle-income countries (LMICs). We first conducted mixed-effect regressions to examine the three pairwise associations between standardized precipitation evapotranspiration index (SPEI), fire-sourced PM2.5, and childhood stunting. We then employed a causal mediation analysis to determine whether compounding drought-wildfire (cascading or co-occurring) events significantly impact the drought-stunting pathway. We found that each 1-unit decrease in SPEI exposure was associated with a 2.16% [95% confidence interval (CI): 0.79, 3.49%] increase in stunting risk and 0.57 (95% CI 0.55, 0.59%) µg/m3 increase in fire-sourced PM2.5. Additionally, each 1 µg/m3 increase in 24 month average fire-sourced PM2.5 was associated with an increased risk of 2.46% (95% CI: 2.16, 2.76%) in stunting. Drought-mediated fires accounted for 26.7% (95% CI: 14.5, 36.6%) of the linkage between SPEI and stunting. Our study revealed fire-sourced PM2.5 is a mediator in the drought-stunting pathway in LMICs. To protect child health under increasing drought conditions, personal interventions against wildfire should be considered to enhance climate resilience.

A novel strategy of identifying circRNA biomarkers in cardiovascular disease by meta-analysis.

Circular RNAs (circRNAs) are stable and abundantly expressed in vivo but are abnormally expressed in several diseases. This study aimed to identify circRNAs acting as potential biomarkers for cardiovascular disease (CVD). Research were retrieved from the articles published by September 2018 in eight databases to compare circRNA expression profiles between CVD and non-CVD in human and animal models. Meta-analysis under a random effects model was conducted. Subgroup analysis of tissue, species, and disease-specific circRNAs was examined. Sensitivity analysis was performed to explain the uncertainty among all studies. Diagnostic accuracy of circRNAs in CVD was analyzed to testify the discriminative ability. Bioinformatics analysis including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted. Among 6,284 differentially expressed circRNAs from 32 original studies, only 322 circRNAs were reported in three or more studies. The meta-analysis identified 63 significantly dysregulated circRNAs, 44 upregulated and 19 downregulated. Among the tissue-specific or disease-specific circRNAs identified in the subgroup analysis, two circRNAs (circCDKN2BAS and circMACF1) showed the potential to be circulating biomarkers for CVD. Sensitivity analysis demonstrated 69% of circRNAs were in conformity with the overall analysis. The pooled diagnostic odds ratio was 2.94 (95% confidence interval [CI], 2.35-3.58), and the overall area under the curve value was 0.86 (95% CI, 0.83-0.89). GO and KEGG enrichment analyses indicated that the target genes of circRNAs participate in cardiogenesis-related processes and pathways. This study demonstrates circRNAs have a high diagnostic value as potential biomarkers for CVD, and two candidate circRNAs, circCDKN2BAS and circMACF1, are potential circulating biomarkers for CVD diagnosis and treatment.

Identification of stress-related microRNA biomarkers in type 2 diabetes mellitus: A systematic review and meta-analysis.

BACKGROUND: Many studies have investigated microRNAs (miRNAs) in the detection of type 2 diabetes mellitus (T2DM). Herein, the dysregulated direction of stress-related miRNAs used as biomarkers of T2DM are summarized and analyzed. METHODS: PubMed, EMBASE, ISI Web of Science, and three Chinese databases were searched for case-control miRNA profiling studies about T2DM. A meta-analysis under a random effect was performed. Subgroup analysis was conducted based on different tissues and species. Sensitivity analysis was conducted to confirm the robustness among studies. The effect size was pooled using ln odds ratios (ORs), 95% confidence intervals (95% CIs), and P-values. RESULTS: The present meta-analysis included 39 case-control studies with a total of 494 miRNAs. Only 33 miRNAs were reported in three or more studies and, of these, 18 were inconsistent in their direction of dysregulation. Two significantly dysregulated miRNAs (let-7 g and miR-155) were identified in the meta-analysis. Four miRNAs (miR-142-3p, miR-155, miR-21, and miR-34c-5p) were dysregulated in patients with T2DM, whereas five miRNAs (miR-146a, miR-199a-3p, miR-200b, miR-29b and miR-30e) were dysregulated in animal models of diabetes. In addition, two dysregulated miRNAs (miR-146a and miR-21) were highly cornea specific and heart specific. In sensitivity analysis, only miR-155 was still significantly dysregulated after removing studies with small sample sizes. CONCLUSIONS: The present meta-analysis revealed that 16 stress-related miRNAs were significantly dysregulated in T2DM. MiR-148b, miR-223, miR-130a, miR-19a, miR-26b and miR-27b were selected as potential circulating biomarkers of T2DM. In addition, miR-146a and miR-21 were identified as potential tissue biomarkers of T2DM.

Association analysis of copy number variations in type 2 diabetes-related susceptible genes in a Chinese population.

AIMS: Copy number variations (CNVs) have been implicated as an important genetic marker of common disease. In this study, we explored genetic effects of common CNVs in Type 2 diabetes (T2D) related susceptible genes in Chinese population. METHODS: Seven common CNV loci were selected from genes enclosing the susceptible single nucleotide polymorphisms (SNPs) of T2D confirmed by genome-wide association studies (GWAS) and replication studies conducted in east Asia population. The CNVs and SNPs were genotyped in 504 T2D patients and 494 non-T2D controls. Cumulative effect of the positive CNV loci was measured using genetic risk score (GRS). Multiplicative and additive interaction between candidate CNV loci and SNPs were assessed. RESULTS: Compared with the common two copies, the deletion of nsv6360 (adjusted OR = 2.28, 95% CI 1.37-3.78, P = 0.001), nsv8414 (adjusted OR = 1.89, 95% CI 1.16-3.08, P = 0.006) and nsv1898 (adjusted OR = 1.84, 95% CI 1.19-2.84, P = 0.005) were significantly associated with increased risk of T2D (P < 0.007). Significant dose-response relationship was observed between GRS and the risk of T2D (χ2 for trend = 19.51, P < 0.001). In addition, significant additive interactions between nsv8414 and rs17584499 in PTPRD (AP = 0.60, 95% CI 0.12-1.07) and nsv1898 and rs16955379 in CMIP (AP = 0.46, 95% CI 0.01-0.91) were observed. CONCLUSIONS: There were three CNV loci (nsv6360, nsv8414 and nsv1898) associated with T2D, and a significant cumulative effect of these loci on the risk of T2D. The comprehensive effects of both CNVs and SNPs may provide a more useful tool for the identification of genetic susceptibility for T2D.

A meta-analysis of dysregulated miRNAs in coronary heart disease.

AIMS: To combine the results of dysregulated miRNAs in individual coronary heart disease (CHD) studies and to identify potential miRNA biomarkers. MAIN METHODS: MiRNA profiling studies of CHD were extracted from Pubmed, Embase, Web of Science and China National Knowledge Internet (CNKI) databases if they met the inclusion criteria. The meta-analysis was conducted using a random effects model to identify the effect of each multiple-reported miRNA. We also performed subgroup analysis according to miRNA detecting methods, tissues and subtypes of CHD. Sensitivity analysis was performed on the sample size. Bioinformatic analysis was performed to identify the potential biomatic functions. All results were represented as log10 odds ratios (logORs). KEY FINDINGS: A total of 239 miRNAs were reported to be dysregulated in all 25 studies analyzed herein, and meta-analysis identified 48 statistically significant miRNAs. Bioinformatic analysis showed they were closely related with CHD. The most reported up-regulated miRNA was miR-122-5p (logOR: 2.7924, P < 0.001). A total of 7, 6, 4 and 9 miRNAs were detected to be differentially expressed in myocardial infarction (MI), unstable angia (UA), stable angina (SA) and pre-CHD subjects, respectively. 32 miRNAs were dysregulated in blood sample. The dysregulation of miR-133a-3p in whole blood and plasma/serum was contrary. In sensitivity analysis, 37 out of 48 (77.08%) miRNAs were consistently dysregulated. SIGNIFICANCE: A total of 48 dysregulated miRNAs were confirmed in this meta-analysis. MiR-122-5p and miR-133a-3p may be valuable biomarkers for CHD.