scholarly journals A single genetic locus controls both expression of DPEP1/CHMP1A and kidney disease development via ferroptosis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuting Guan ◽  
Xiujie Liang ◽  
Ziyuan Ma ◽  
Hailong Hu ◽  
Hongbo Liu ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Association Studies ◽  
Genetic Locus ◽  
Human Kidney ◽  
Multivesicular Body ◽  
Chromatin Accessibility ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Disease Development ◽  
Body Protein

AbstractGenome-wide association studies (GWAS) have identified loci for kidney disease, but the causal variants, genes, and pathways remain unknown. Here we identify two kidney disease genes Dipeptidase 1 (DPEP1) and Charged Multivesicular Body Protein 1 A (CHMP1A) via the triangulation of kidney function GWAS, human kidney expression, and methylation quantitative trait loci. Using single-cell chromatin accessibility and genome editing, we fine map the region that controls the expression of both genes. Mouse genetic models demonstrate the causal roles of both genes in kidney disease. Cellular studies indicate that both Dpep1 and Chmp1a are important regulators of a single pathway, ferroptosis and lead to kidney disease development via altering cellular iron trafficking.

scholarly journals Kidney disease genetic risk variants alter lysosomal beta-mannosidase (MANBA) expression and disease severity

2021 ◽  
Vol 13 (576) ◽  
pp. eaaz1458 ◽  
Author(s):  
Xiangchen Gu ◽  
Hongliu Yang ◽  
Xin Sheng ◽  
Yi-An Ko ◽  
Chengxiang Qiu ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Kidney Function ◽  
Association Studies ◽  
Inflammasome Activation ◽  
Genome Wide Association Studies ◽  
Disease Development ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Specific Expression ◽  
Coding Variants

More than 800 million people in the world suffer from chronic kidney disease (CKD). Genome-wide association studies (GWAS) have identified hundreds of loci where genetic variants are associated with kidney function; however, causal genes and pathways for CKD remain unknown. Here, we performed integration of kidney function GWAS and human kidney–specific expression quantitative trait analysis and identified that the expression of beta-mannosidase (MANBA) was lower in kidneys of subjects with CKD risk genotype. We also show an increased incidence of renal failure in subjects with rare heterozygous loss-of-function coding variants in MANBA using phenome-wide association analysis of 40,963 subjects with exome sequencing data. MANBA is a lysosomal gene highly expressed in kidney tubule cells. Deep phenotyping revealed structural and functional lysosomal alterations in human kidneys from subjects with CKD risk alleles and mice with genetic deletion of Manba. Manba heterozygous and knockout mice developed more severe kidney fibrosis when subjected to toxic injury induced by cisplatin or folic acid. Manba loss altered multiple pathways, including endocytosis and autophagy. In the absence of Manba, toxic acute tubule injury induced inflammasome activation and fibrosis. Together, these results illustrate the convergence of common noncoding and rare coding variants in MANBA in kidney disease development and demonstrate the role of the endolysosomal system in kidney disease development.

scholarly journals Causal Inference Between Chronic Periodontitis and Chronic Kidney Disease: A Bidirectional Mendelian Randomization Analysis in a European Population

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Yang ◽  
Tianyi Chen ◽  
Yahong Zhu ◽  
Mingxia Bai ◽  
Xingang Li
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Causal Inference ◽  
Causal Relationship ◽  
Instrumental Variables ◽  
Chronic Periodontitis ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics

BackgroundPrevious epidemiological studies have shown significant associations between chronic periodontitis (CP) and chronic kidney disease (CKD), but the causal relationship remains uncertain. Aiming to examine the causal relationship between these two diseases, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis with multiple MR methods.MethodsFor the casual effect of CP on CKD, we selected seven single-nucleotide polymorphisms (SNPs) specific to CP as genetic instrumental variables from the genome-wide association studies (GWAS) in the GLIDE Consortium. The summary statistics of complementary kidney function measures, i.e., estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), were derived from the GWAS in the CKDGen Consortium. For the reversed causal inference, six SNPs associated with eGFR and nine with BUN from the CKDGen Consortium were included and the summary statistics were extracted from the CLIDE Consortium.ResultsNo significant causal association between genetically determined CP and eGFR or BUN was found (all p > 0.05). Based on the conventional inverse variance-weighted method, one of seven instrumental variables supported genetically predicted CP being associated with a higher risk of eGFR (estimate = 0.019, 95% CI: 0.012–0.026, p < 0.001).ConclusionEvidence from our bidirectional causal inference does not support a causal relation between CP and CKD risk and therefore suggests that associations reported by previous observational studies may represent confounding.

scholarly journals Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Matthias Thurner ◽  
Martijn van de Bunt ◽  
Jason M Torres ◽  
Anubha Mahajan ◽  
Vibe Nylander ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Pancreatic Islet ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Human Islets ◽  
Chromatin Accessibility ◽  
Chromatin State ◽  
Open Chromatin ◽  
Genome Wide Association Studies

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

scholarly journals Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

2020 ◽  
Vol 11 ◽  
Author(s):  
Haimiao Chen ◽  
Ting Wang ◽  
Jinna Yang ◽  
Shuiping Huang ◽  
Ping Zeng
Keyword(s):  
Coronary Artery Disease ◽  
Chronic Kidney Disease ◽  
Coronary Artery ◽  
Kidney Disease ◽  
Association Studies ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genetic Determination ◽  
Artery Disease

The coexistence of coronary artery disease (CAD) and chronic kidney disease (CKD) implies overlapped genetic foundation. However, the common genetic determination between the two diseases remains largely unknown. Relying on summary statistics publicly available from large scale genome-wide association studies (n = 184,305 for CAD and n = 567,460 for CKD), we observed significant positive genetic correlation between CAD and CKD (rg = 0.173, p = 0.024) via the linkage disequilibrium score regression. Next, we implemented gene-based association analysis for each disease through MAGMA (Multi-marker Analysis of GenoMic Annotation) and detected 763 and 827 genes associated with CAD or CKD (FDR < 0.05). Among those 72 genes were shared between the two diseases. Furthermore, by integrating the overlapped genetic information between CAD and CKD, we implemented two pleiotropy-informed informatics approaches including cFDR (conditional false discovery rate) and GPA (Genetic analysis incorporating Pleiotropy and Annotation), and identified 169 and 504 shared genes (FDR < 0.05), of which 121 genes were simultaneously discovered by cFDR and GPA. Importantly, we found 11 potentially new pleiotropic genes related to both CAD and CKD (i.e., ARHGEF19, RSG1, NDST2, CAMK2G, VCL, LRP10, RBM23, USP10, WNT9B, GOSR2, and RPRML). Five of the newly identified pleiotropic genes were further repeated via an additional dataset CAD available from UK Biobank. Our functional enrichment analysis showed that those pleiotropic genes were enriched in diverse relevant pathway processes including quaternary ammonium group transmembrane transporter, dopamine transport. Overall, this study identifies common genetic architectures overlapped between CAD and CKD and will help to advance understanding of the molecular mechanisms underlying the comorbidity of the two diseases.

scholarly journals A suppressor locus for MODY3-diabetes

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Miguel A. Garcia-Gonzalez ◽  
Claire Carette ◽  
Alessia Bagattin ◽  
Magali Chiral ◽  
Munevver Parla Makinistoglu ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Human Genetics ◽  
Association Studies ◽  
Genetic Locus ◽  
Genome Wide Association Studies ◽  
Fasting Glycemia ◽  
Genome Wide ◽  
A Genome ◽  
Resistant Strains ◽  
Type 3

Abstract Maturity Onset Diabetes of the Young type 3 (MODY3), linked to mutations in the transcription factor HNF1A, is the most prevalent form of monogenic diabetes mellitus. HNF1alpha-deficiency leads to defective insulin secretion via a molecular mechanism that is still not completely understood. Moreover, in MODY3 patients the severity of insulin secretion can be extremely variable even in the same kindred, indicating that modifier genes may control the onset of the disease. With the use of a mouse model for HNF1alpha-deficiency, we show here that specific genetic backgrounds (C3H and CBA) carry a powerful genetic suppressor of diabetes. A genome scan analysis led to the identification of a major suppressor locus on chromosome 3 (Moda1). Moda1 locus contains 11 genes with non-synonymous SNPs that significantly interacts with other loci on chromosomes 4, 11 and 18. Mechanistically, the absence of HNF1alpha in diabetic-prone (sensitive) strains leads to postnatal defective islets growth that is remarkably restored in resistant strains. Our findings are relevant to human genetics since Moda1 is syntenic with a human locus identified by genome wide association studies of fasting glycemia in patients. Most importantly, our results show that a single genetic locus can completely suppress diabetes in Hnf1a-deficiency.

scholarly journals Causal effect of atrial fibrillation/flutter on chronic kidney disease: A bidirectional two-sample Mendelian randomization study

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261020
Author(s):  
Masahiro Yoshikawa ◽  
Kensuke Asaba ◽  
Tomohiro Nakayama
Keyword(s):  
Atrial Fibrillation ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
European Population ◽  
Genome Wide Association Studies ◽  
The Uk

Chronic kidney disease (CKD) and atrial fibrillation are both major burdens on the health care system worldwide. Several observational studies have reported clinical associations between CKD and atrial fibrillation; however, causal relationships between these conditions remain to be elucidated due to possible bias by confounders and reverse causations. Here, we conducted bidirectional two-sample Mendelian randomization analyses using publicly available summary statistics of genome-wide association studies (the CKDGen consortium and the UK Biobank) to investigate causal associations between CKD and atrial fibrillation/flutter in the European population. Our study suggested a causal effect of the risk of atrial fibrillation/flutter on the decrease in serum creatinine-based estimated glomerular filtration rate (eGFR) and revealed a causal effect of the risk of atrial fibrillation/flutter on the risk of CKD (odds ratio, 9.39 per doubling odds ratio of atrial fibrillation/flutter; 95% coefficient interval, 2.39–37.0; P = 0.001), while the causal effect of the decrease in eGFR on the risk of atrial fibrillation/flutter was unlikely. However, careful interpretation and further studies are warranted, as the underlying mechanisms remain unknown. Further, our sample size was relatively small and selection bias was possible.

scholarly journals Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

2018 ◽  
Author(s):  
Sarvenaz Choobdar ◽  
Mehmet E. Ahsen ◽  
Jake Crawford ◽  
Mattia Tomasoni ◽  
Tao Fang ◽  
...  
Keyword(s):  
Complex Traits ◽  
Gene Networks ◽  
Association Studies ◽  
Molecular Network ◽  
Molecular Networks ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Identification Methods ◽  
Module Identification ◽  
Network Modules

AbstractIdentification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).

scholarly journals Combining SNP-to-gene linking strategies to pinpoint disease genes and assess disease omnigenicity

2021 ◽  
Author(s):  
Steven Gazal ◽  
Omer Weissbrod ◽  
Farhad Hormozdiari ◽  
Kushal Dey ◽  
Joseph Nasser ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Complex Traits ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Common Disease ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Functional Interpretation ◽  
Genome Wide

Although genome-wide association studies (GWAS) have identified thousands of disease-associated common SNPs, these SNPs generally do not implicate the underlying target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate in cis, but it is unclear how these strategies should be applied in the context of interpreting common disease risk variants. We developed a framework for evaluating and combining different S2G strategies to optimize their informativeness for common disease risk, leveraging polygenic analyses of disease heritability to define and estimate their precision and recall. We applied our framework to GWAS summary statistics for 63 diseases and complex traits (average N=314K), evaluating 50 S2G strategies. Our optimal combined S2G strategy (cS2G) included 7 constituent S2G strategies (Exon, Promoter, 2 fine-mapped cis-eQTL strategies, EpiMap enhancer-gene linking, Activity-By-Contact (ABC), and Cicero), and achieved a precision of 0.75 and a recall of 0.33, more than doubling the precision and/or recall of any individual strategy; this implies that 33% of SNP-heritability can be linked to causal genes with 75% confidence. We applied cS2G to fine-mapping results for 49 UK Biobank diseases/traits to predict 7,111 causal SNP-gene-disease triplets (with S2G-derived functional interpretation) with high confidence. Finally, we applied cS2G to genome-wide fine-mapping results for these traits (not restricted to GWAS loci) to rank genes by the heritability linked to each gene, providing an empirical assessment of disease omnigenicity; averaging across traits, we determined that the top 200 (1%) of ranked genes explained roughly half of the heritability linked to all genes. Our results highlight the benefits of our cS2G strategy in providing functional interpretation of GWAS findings; we anticipate that precision and recall will increase further under our framework as improved functional assays lead to improved S2G strategies. 

scholarly journals Hybrid allele-specific ChIP-Seq analysis links variation in transcription factor binding to traits in maize

2021 ◽  
Author(s):  
Thomas Hartwig ◽  
Michael Banf ◽  
Gisele Prietsch ◽  
Julia Engelhorn ◽  
Jinliang Yang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Target Genes ◽  
Phenotypic Diversity ◽  
Association Studies ◽  
Chromatin Accessibility ◽  
Genome Wide Association Studies ◽  
Functional Variants ◽  
Genome Wide ◽  
Allele Specific ◽  
Hybrid Allele

Abstract Variation in transcriptional regulation is a major cause of phenotypic diversity. Genome-wide association studies (GWAS) have shown that most functional variants reside in non-coding regions, where they potentially affect transcription factor (TF) binding and chromatin accessibility to alter gene expression. Pinpointing such regulatory variations, however, remains challenging. Here, we developed a hybrid allele-specific chromatin binding sequencing (HASCh-seq) approach and identified variations in target binding of the brassinosteroid (BR) responsive transcription factor ZmBZR1 in maize. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) in B73xMo17 F1s identified thousands of target genes of ZmBZR1. Allele-specific ZmBZR1 binding (ASB) was observed for about 14.3% of target genes. It correlated with over 550 loci containing sequence variation in BZR1-binding motifs and over 340 loci with haplotype-specific DNA methylation, linking genetic and epigenetic variations to ZmBZR1 occupancy. Comparison with GWAS data linked hundreds of ASB loci to important yield, growth, and disease-related traits. Our study provides a robust method for analyzing genome-wide variations of transcription factor occupancy and identified genetic and epigenetic variations of the BR response transcription network in maize.

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