Association between <i>LEKR1‐CCNL1</i> and <i>IGSF21‐KLHDC7A</i> gene polymorphisms and diabetic retinopathy of type 2 diabetes mellitus in the Chinese Han population

Lin, Xiaohui; Wang, Jihong; Yun, Lixia; Jiang, Shiqin; Li, Langen; Chen, Xiaohai; Li, Zhen; Lü, Qiang; Zhang, Yihui; Ma, Xiaocheng

doi:10.1002/jgm.2926

Cited by 6 publications

(6 citation statements)

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“…CCNL1 is a member of the cell cycle protein family. It is involved in the precursor mRNA shearing and RNA processing and is associated with the action of cell cycle protein-dependent kinases ( 46 ). Additionally, CCNL1 may contribute to cell survival during cellular stress, such as cold stimulation ( 47 ).…”

Section: Discussionmentioning

confidence: 99%

Effect of SARS-CoV-2 infection on asthma patients

Wang

et al. 2022

Front. Med.

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BackgroundSARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma.MethodsTo investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates.ResultsThere were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets.ConclusionWe investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

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Section: Discussionmentioning

confidence: 99%

Effect of SARS-CoV-2 infection on asthma patients

Wang

et al. 2022

Front. Med.

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“…Of particular interest, the CCNL1 gene was ranked 4th from a meta-analysis for association with severe diabetic retinopathy ( P = 7.1 × 10 –7 ), but was no longer top-ranked for association with diabetic retinopathy when individuals with nephropathy were removed from the case group ( Grassi et al, 2011 ). Subsequent studies have highlighted CCNL1 SNPs associated with retinopathy and measures of renal function ( Lin et al, 2016 ). Genetic variation near the CCNL1 gene is robustly associated with low birth weight in European individuals ( Freathy et al, 2010 ; Yaghootkar and Freathy, 2012 ; Horikoshi et al, 2013 ), specifically with growth restriction from early pregnancy onward ( Mook-Kanamori et al, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA

Smyth

Patterson

Swan

et al. 2020

Front. Cell Dev. Biol.

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A subset of individuals with type 1 diabetes will develop diabetic kidney disease (DKD). DKD is heritable and large-scale genome-wide association studies have begun to identify genetic factors that influence DKD. Complementary to genetic factors, we know that a person's epigenetic profile is also altered with DKD. This study reports analysis of DNA methylation, a major epigenetic feature, evaluating methylome-wide loci for association with DKD. Unique features (n = 485,577; 482,421 CpG probes) were evaluated in blood-derived DNA from carefully phenotyped White European individuals diagnosed with type 1 diabetes with (cases) or without (controls) DKD (n = 677 samples). Explicitly, 150 cases were compared to 100 controls using the 450K array, with subsequent analysis using data previously generated for a further 96 cases and 96 controls on the 27K array, and de novo methylation data generated for replication in 139 cases and 96 controls. Following stringent quality control, raw data were quantile normalized and beta values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls; resultant P-values for array-based data were adjusted for multiple testing. Genes with significantly increased (hypermethylated) and/or decreased (hypomethylated) levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways. Twenty-two loci demonstrated statistically significant fold changes associated with DKD and additional support for these associated loci was sought using independent samples derived from patients recruited with similar inclusion criteria. Markers associated with CCNL1 and ZNF187 genes are supported as differentially regulated loci (P < 10 −8), with evidence also presented for AFF3, which has been identified from a meta-analysis and subsequent replication of genomewide association studies. Further supporting evidence for differential gene expression in CCNL1 and ZNF187 is presented from kidney biopsy and blood-derived RNA in people with and without kidney disease from NephroSeq. Evidence confirming that methylation sites influence the development of DKD may aid risk prediction tools and stimulate research to identify epigenomic therapies which might be clinically useful for this disease.

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“…Moving to genes altered in early stage of DR, except for one study on IGSF21 (Immunoglobin Superfamily Member 21) (Lin et al, 2016), none of the genes have been studied in context to DR. However, ROCK2 (Rho Associated Coiled-Coil Containing Protein Kinase 2) (Koch et al, 2014;Lu et al,…”

Section: Discussionmentioning

confidence: 99%

Integrative Computational Approach Revealed Crucial Genes Associated With Different Stages of Diabetic Retinopathy

et al. 2020

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The increased incidence of diabetic retinopathy (DR) and the legacy effect associated with it has raised a great concern toward the need to find early diagnostic and treatment strategies. Identifying alterations in genes and microRNAs (miRNAs) is one of the most critical steps toward understanding the mechanisms by which a disease progresses, and this can be further used in finding potential diagnostic and prognostic biomarkers and treatment methods. We selected different datasets to identify altered genes and miRNAs. The integrative analysis was employed to find potential candidate genes (differentially expressed and aberrantly methylated genes that are also the target of altered miRNAs) and early genes (genes showing altered expression and methylation pattern during early stage of DR) for DR. We constructed a protein-protein interaction (PPI) network to find hub genes (potential candidate genes showing a greater number of interactions) and modules. Gene ontologies and pathways associated with the identified genes were analyzed to determine their role in DR progression. A total of 271 upregulated-hypomethylated genes, 84 downregulated-hypermethylated genes, 11 upregulated miRNA, and 30 downregulated miRNA specific to DR were identified. 40 potential candidate genes and 9 early genes were also identified. PPI network analysis revealed 7 hub genes (number of interactions >5) and 1 module (score = 5.67). Gene ontology and pathway analysis predicted enrichment of genes in oxidoreductase activity, binding to extracellular matrix, immune responses, leukocyte migration, cell adhesion, PI3K-Akt signaling pathway, ECM receptor interaction, etc., and thus their association with DR pathogenesis. In conclusion, we identified 7 hub genes and 9 early genes that could act as a potential prognostic, diagnostic, or therapeutic target for DR, and a few early genes could also play a role in metabolic memory phenomena.

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Association between LEKR1‐CCNL1 and IGSF21‐KLHDC7A gene polymorphisms and diabetic retinopathy of type 2 diabetes mellitus in the Chinese Han population

Abstract: Our results suggest that LEKR1-CCNL1 and IGSF21-KLHDC7A influence the development of DR.

Cited by 6 publications

References 24 publications

Effect of SARS-CoV-2 infection on asthma patients

Effect of SARS-CoV-2 infection on asthma patients

DNA Methylation Associated With Diabetic Kidney Disease in Blood-Derived DNA

Integrative Computational Approach Revealed Crucial Genes Associated With Different Stages of Diabetic Retinopathy

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