The ras responsive transcription factor RREB1 is a novel candidate gene for type 2 diabetes associated end-stage kidney disease

Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry

Background

Genome-wide association studies (GWAS) have predominantly focused on populations of European and Asian ancestry, limiting our understanding of genetic factors influencing kidney disease in Sub-Saharan African (SSA) populations. This study presents the largest GWAS for urinary albumin-to-creatinine ratio (UACR) in SSA individuals, including 8,970 participants living in different African regions and an additional 9,705 non-resident individuals of African ancestry from the UK Biobank and African American cohorts.

Methods

Urine biomarkers and genotype data were obtained from two SSA cohorts (AWI-Gen and ARK), and two non-resident African-ancestry studies (UK Biobank and CKD-Gen Consortium). Association testing and meta-analyses were conducted, with subsequent fine-mapping, conditional analyses, and replication studies. Polygenic scores (PGS) were assessed for transferability across populations.

Results

Two genome-wide significant (P < 5 × 10-8) UACR-associated loci were identified, one in the BMP6 region on chromosome 6, in the meta-analysis of resident African individuals, and another in the HBB region on chromosome 11 in the meta-analysis of non-resident SSA individuals, as well as the combined meta-analysis of all studies. Replication of previous significant results confirmed associations in known UACR-associated regions, including THB53, GATM, and ARL15. PGS estimated using previous studies from European ancestry, African ancestry, and multi-ancestry cohorts exhibited limited transferability of PGS across populations, with less than 1% of observed variance explained.

Conclusion

This study contributes novel insights into the genetic architecture of kidney disease in SSA populations, emphasizing the need for conducting genetic research in diverse cohorts. The identified loci provide a foundation for future investigations into the genetic susceptibility to chronic kidney disease in underrepresented African populations Additionally, there is a need to develop integrated scores using multi-omics data and risk factors specific to the African context to improve the accuracy of predicting disease outcomes.

Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing

Renal proximal tubule epithelial cells have considerable intrinsic repair capacity following injury. However, a fraction of injured proximal tubule cells fails to undergo normal repair and assumes a proinflammatory and profibrotic phenotype that may promote fibrosis and chronic kidney disease. The healthy to failed repair change is marked by cell state-specific transcriptomic and epigenomic changes. Single nucleus joint RNA- and ATAC-seq sequencing offers an opportunity to study the gene regulatory networks underpinning these changes in order to identify key regulatory drivers. We develop a regularized regression approach to construct genome-wide parametric gene regulatory networks using multiomic datasets. We generate a single nucleus multiomic dataset from seven adult human kidney samples and apply our method to study drivers of a failed injury response associated with kidney disease. We demonstrate that our approach is a highly effective tool for predicting key cis- and trans-regulatory elements underpinning the healthy to failed repair transition and use it to identify NFAT5 as a driver of the maladaptive proximal tubule state.

Integrative single-cell characterization of a frugivorous and an insectivorous bat kidney and pancreas

Frugivory evolved multiple times in mammals, including bats. However, the cellular and molecular components driving it remain largely unknown. Here, we use integrative single-cell sequencing (scRNA-seq and scATAC-seq) on insectivorous (Eptesicus fuscus; big brown bat) and frugivorous (Artibeus jamaicensis; Jamaican fruit bat) bat kidneys and pancreases and identify key cell population, gene expression and regulatory differences associated with the Jamaican fruit bat that also relate to human disease, particularly diabetes. We find a decrease in loop of Henle and an increase in collecting duct cells, and differentially active genes and regulatory elements involved in fluid and electrolyte balance in the Jamaican fruit bat kidney. The Jamaican fruit bat pancreas shows an increase in endocrine and a decrease in exocrine cells, and differences in genes and regulatory elements involved in insulin regulation. We also find that these frugivorous bats share several molecular characteristics with human diabetes. Combined, our work provides insights from a frugivorous mammal that could be leveraged for therapeutic purposes.

Genome-wide meta-analysis identifies new candidate genes for sickle cell disease nephropathy

Sickle cell disease nephropathy (SCDN), a common SCD complication, is strongly associated with mortality. Polygenic risk scores calculated from recent transethnic meta-analyses of urinary albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) trended toward association with proteinuria and eGFR in SCD but the model fit was poor (R2 < 0.01), suggesting that there are likely unique genetic risk factors for SCDN. Therefore, we performed genome-wide association studies (GWAS) for 2 critical manifestations of SCDN, proteinuria and decreased eGFR, in 2 well-characterized adult SCD cohorts, representing, to the best of our knowledge, the largest SCDN sample to date. Meta-analysis identified 6 genome-wide significant associations (false discovery rate, q ≤ 0.05): 3 for proteinuria (CRYL1, VWF, and ADAMTS7) and 3 for eGFR (LRP1B, linc02288, and FPGT-TNNI3K/TNNI3K). These associations are independent of APOL1 risk and represent novel SCDN loci, many with evidence for regulatory function. Moreover, GWAS SNPs in CRYL1, VWF, ADAMTS7, and linc02288 are associated with gene expression in kidney and pathways important to both renal function and SCD biology, supporting the hypothesis that SCDN pathophysiology is distinct from other forms of kidney disease. Together, these findings provide new targets for functional follow-up that could be tested prospectively and potentially used to identify patients with SCD who are at risk, before onset of kidney dysfunction.

Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus

Background

Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM.

Methods

The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes.

Results

A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes.

Conclusion

The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.

Integrative single-cell characterization of frugivory adaptations in the bat kidney and pancreas

Frugivory evolved multiple times in mammals, including bats. However, the cellular and molecular components driving it remain largely unknown. Here, we used integrative single-cell sequencing on insectivorous and frugivorous bat kidneys and pancreases and identified key cell population, gene expression and regulatory element differences associated with frugivorous adaptation that also relate to human disease, particularly diabetes. We found an increase in collecting duct cells and differentially active genes and regulatory elements involved in fluid and electrolyte balance in the frugivore kidney. In the frugivorous pancreas, we observed an increase in endocrine and a decrease in exocrine cells and differences in genes and regulatory elements involved in insulin regulation. Combined, our work provides novel insights into frugivorous adaptation that also could be leveraged for therapeutic purposes.

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.

Distinct whole-blood transcriptome profile of children with metabolic healthy overweight/obesity compared to metabolic unhealthy overweight/obesity

BACKGROUND

Youth populations with overweight/obesity (OW/OB) exhibit heterogeneity in cardiometabolic health phenotypes. The underlying mechanisms for those differences are still unclear. This study aimed to analyze the whole-blood transcriptome profile (RNA-seq) of children with metabolic healthy overweight/obesity (MHO) and metabolic unhealthy overweight/obesity (MUO) phenotypes.

METHODS

Twenty-seven children with OW/OB (10.1 ± 1.3 years, 59% boys) from the ActiveBrains project were included. MHO was defined as having none of the following criteria for metabolic syndrome: elevated fasting glucose, high serum triglycerides, low high-density lipoprotein-cholesterol, and high systolic or diastolic blood pressure, while MUO was defined as presenting one or more of these criteria. Inflammatory markers were additionally determined. Total blood RNA was analyzed by 5'-end RNA-sequencing.

RESULTS

Whole-blood transcriptome analysis revealed a distinct pattern of gene expression in children with MHO compared to MUO children. Thirty-two genes differentially expressed were linked to metabolism, mitochondrial, and immune functions.

CONCLUSIONS

The identified gene expression patterns related to metabolism, mitochondrial, and immune functions contribute to a better understanding of why a subset of the population remains metabolically healthy despite having overweight/obesity.

IMPACT

A distinct pattern of whole-blood transcriptome profile (RNA-seq) was identified in children with metabolic healthy overweight/obesity (MHO) compared to metabolic unhealthy overweight/obesity (MUO) phenotype. The most relevant genes in understanding the molecular basis underlying the MHO/MUO phenotypes in children could be: RREB1, FAM83E, SLC44A1, NRG1, TMC5, CYP3A5, TRIM11, and ADAMTSL2. The identified whole-blood transcriptome profile related to metabolism, mitochondrial, and immune functions contribute to a better understanding of why a subset of the population remains metabolically healthy despite having overweight/obesity.

MiR-137 Restricts the Viability and Migration of HTR-8/SVneo Cells by Downregulating FNDC5 in Gestational Diabetes Mellitus

BACKGROUND

An increasing number of studies have described the pathological changes of placenta tissues in gestational diabetes mellitus (GDM), although the underlying mechanisms involved in this process remain uncertain. The aim of the present study was to verify the possible role of microRNA-137 (miR)-137 and FNDC5 in regulating the biological function of trophoblasts in high glucose (HG) conditions during the GDM period.

METHODS

Expression levels of miR-137 and FNDC5 were measured in placenta specimens, the HG-treated trophoblast cell line HTR-8/SVneo and miR-137- overexpressing HTR-8/SVneo cells using reverse transcription quantitative-PCR or western blotting. The viability of HTR-8/SVneo cells was tested using a Cell Counting kit- 8 (CCK8) assay, with cell migration assessed using scratch and transwell assays.

RESULTS

It was observed that the expression levels of miR-137 were increased and the expression levels of FNDC5 were decreased in the placenta tissues of women with severe GDM and in HG-exposed HTR-8/SVneo cells. In addition, upregulating miR-137 in HTR-8/SVneo cells downregulated the expression levels of FNDC5. The viability and migration of HTR-8/SVneo cells were suppressed by increased miR-137 expression levels, and upregulating FNDC5 in miR-137-overexpressing HTR-8/SVneo cells resulted in the reversal of all these effects.

CONCLUSIONS

The data from the present study suggest that miR-137 suppresses the viability and migration of trophoblasts via downregulating FNDC5 in GDM, which may contribute to the pathology of placenta tissues and occurrence of adverse pregnancy outcomes.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.

Molecular mechanism of myofibroblast formation and strategies for clinical drugs treatments in hypertrophic scars

Hypertrophic scars (HTS) commonly occurred after burn and trauma. It was characterized by the excessive deposition of extracellular matrix with the inadequate remodeling, which could result in severe physiological and psychological problems. However, the effective available prevention and treatment measures were still limited. The main pathological feature of HTS was the excessive formation of myofibroblasts, and they persist in the repaired tissue. To better understand the mechanics of this process, this review focused on the characteristics and formation of myofibroblasts, the main effector cells in HTS. We summarized the present theories and opinions on myofibroblasts formation from the perspective of related signaling pathways and epigenetic regulation, such as DNA methylation, miRNA/lncRNA/ceRNA action, histone modification, and so forth for a better understanding on the development of HTS. This information might assist in developing effective experimental and clinical treatment strategies. Additionally, we also summarized currently known clinical strategies for HTS treatment, including traditional drugs, molecular medicine, stem cells, and exosomes.

Genetics, Genomics, and Precision Medicine in End-Stage Kidney Disease

Recent advances in genetics of renal disease have deepened our understanding of progressive kidney disease. Here, we review genetic variants that are of particular importance to progressive glomerular disease that result in end-stage kidney disease (ESKD). Some of the most striking findings relate to APOL1 genetic variants, seen exclusively in individuals of sub-Saharan African descent, that create a predisposition to particular renal disorders, including focal segmental glomerulosclerosis and arterionephrosclerosis. We also review the genetics of cardiovascular disease in ESKD and note that little work has been published on the genetics of other ESKD complications, including anemia, bone disease, and infections. Deeper understanding of the genetics of ESKD and its complications may lead to new therapies that are tailored to an individual patient's genetic profile or are discovered based on genetic approaches that identify novel pathways of renal cell injury and repair.

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

Genome-wide identification of m6A-associated SNPs as potential functional variants for bone mineral density

This study investigated the effect of the N⁶-methyladenosine (m⁶A)-associated SNPs on bone mineral density (BMD) and found plenty of m⁶A-SNPs that were associated with BMD. This study increases our understanding on the regulation patterns of SNP and may provide new clues for further detection of functional mechanism underlying the associations between SNPs and osteoporosis.

INTRODUCTION

m⁶A plays critical roles in many fundamental biological processes and a variety of diseases. The m⁶A-associated SNPs may be potential functional variants for BMD. The aim of this study was to investigate the effect of the genome-wide m⁶A-SNPs on BMD.

METHODS

We examined the association of m⁶A-SNPs with femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and quantitative heel ultrasounds (eBMD) in 142,487 individuals. Furthermore, we performed expression quantitative trait locus (eQTL) analyses for the m⁶A-SNPs using whole genome data of about 10.5 million SNPs and 21,323 mRNAs from 43 Chinese individuals, as well as public available data. Differential expression analyses were also performed to support the identified genes.

RESULTS

We found 138, 125, and 993 m⁶A-SNPs which were associated with FN-BMD, LS-BMD, and eBMD (P < 0.05), respectively. The associations of rs11614913 (P = 8.92 × 10^-10) in MIR196A2 and rs1110720 (P = 2.05 × 10^-10) in ESPL1 with LS-BMD reached the genome-wide significance level. In addition, a total of 24 m⁶A-SNPs were significantly associated with eBMD (P < 5.0 × 10^-8). Further eQTL analyses showed that 47 of these BMD-associated m⁶A-SNPs were associated with expressions of the 46 corresponding local genes. Moreover, the expressions of 26 of these genes were associated with BMD.

CONCLUSION

The present study represents the first effort of investigating the associations and the mechanisms underlying the link between m⁶A-SNPs and BMD. The results suggested that m⁶A-SNP may play important roles in the pathology of osteoporosis.

Proteomic and bioinformatic discovery of biomarkers for diabetic nephropathy

Diabetes is associated with numerous metabolic and vascular risk factors that contribute to a high rate of micro-vascular and macro-vascular disorders leading to mortality and morbidity from diabetic complications. In this case, the major cause of death in overall diabetic patients results from diabetic nephropathy (DN) or renal failure. The risk factors and mechanisms that correspond to the development of DN are not fully understood and so far, no specific and sufficient diagnostic biomarkers are currently available other than micro- or macroalbuminuria. Therefore, this review describes current and novel protein biomarkers in the context of DN as well as probable proteins biomarkers associated with pathological processes for the early stage of DN via proteomics data together with bioinformatics. In addition, the mechanisms involved in early development of diabetic vascular disorders and complications resulting from glucose induced oxidative stress will also be explored.

Plasma proteomic analysis reveals altered protein abundances in cardiovascular disease

BACKGROUND

Cardiovascular disease (CVD) describes the pathological conditions of the heart and blood vessels. Despite the large number of studies on CVD and its etiology, its key modulators remain largely unknown. To this end, we performed a comprehensive proteomic analysis of blood plasma, with the scope to identify disease-associated changes after placing them in the context of existing knowledge, and generate a well characterized dataset for further use in CVD multi-omics integrative analysis.

METHODS

LC-MS/MS was employed to analyze plasma from 32 subjects (19 cases of various CVD phenotypes and 13 controls) in two steps: discovery (13 cases and 8 controls) and test (6 cases and 5 controls) set analysis. Following label-free quantification, the detected proteins were correlated to existing plasma proteomics datasets (plasma proteome database; PPD) and functionally annotated (Cytoscape, Ingenuity Pathway Analysis). Differential expression was defined based on identification confidence (≥ 2 peptides per protein), statistical significance (Mann-Whitney p value ≤ 0.05) and a minimum of twofold change.

RESULTS

Peptides detected in at least 50% of samples per group were considered, resulting in a total of 3796 identified proteins (838 proteins based on ≥ 2 peptides). Pathway annotation confirmed the functional relevance of the findings (representation of complement cascade, fibrin clot formation, platelet degranulation, etc.). Correlation of the relative abundance of the proteins identified in the discovery set with their reported concentrations in the PPD was significant, confirming the validity of the quantification method. The discovery set analysis revealed 100 differentially expressed proteins between cases and controls, 39 of which were verified (≥ twofold change) in the test set. These included proteins already studied in the context of CVD (such as apolipoprotein B, alpha-2-macroglobulin), as well as novel findings (such as low density lipoprotein receptor related protein 2 [LRP2], protein SZT2) for which a mechanism of action is suggested.

CONCLUSIONS

This proteomic study provides a comprehensive dataset to be used for integrative and functional studies in the field. The observed protein changes reflect known CVD-related processes (e.g. lipid uptake, inflammation) but also novel hypotheses for further investigation including a potential pleiotropic role of LPR2 but also links of SZT2 to CVD.

An Exome-wide Association Study for Type 2 Diabetes-Attributed End-Stage Kidney Disease in African Americans

Introduction

Compared with European Americans, African Americans (AAs) are at higher risk for developing end-stage kidney disease (ESKD). Genome-wide association studies (GWAS) have identified >70 genetic variants associated with kidney function and chronic kidney disease (CKD) in patients with and without diabetes. However, these variants explain a small proportion of disease liability. This study examined the contribution of coding genetic variants for risk of type 2 diabetes (T2D)-attributed ESKD and advanced CKD in AAs.

Methods

Exome sequencing was performed in 456 AA T2D-ESKD cases, and 936 AA nondiabetic, non-nephropathy control individuals at the discovery stage. A mixed logistic regression model was used for association analysis. Nominal associations (P < 0.05) were replicated in an additional 2020 T2D-ESKD cases and 1121 nondiabetic, non-nephropathy control individuals. A meta-analysis combining 4533 discovery and replication samples was performed. Putative T2D-ESKD associations were tested in additional 1910 nondiabetic ESKD and 219 T2D-ESKD cases, as well as 912 AA nondiabetic non-nephropathy control individuals.

Results

A total of 11 suggestive T2D-ESKD associations (P < 1 x 10⁻⁴) from 8 loci (PLEKHN1, NADK, RAD51AP2, RREB1, PEX6, GRM8, PRX, APOL1) were apparent in the meta-analysis. Exclusion of APOL1 renal-risk genotype carriers identified 3 additional suggestive loci (OTUD7B, IFITM3, DLGAP5). Rs41302867 in RREB1 displayed consistent association with T2D-ESKD and nondiabetic ESKD (odds ratio: 0.47; P = 1.2 x 10⁻⁶ in 4605 all-cause ESKD and 2969 nondiabetic non-nephropathy control individuals).

Conclusion

Our findings suggest that coding genetic variants are implicated in predisposition to T2D-ESKD in AAs.

Progress in Defining the Genetic Basis of Diabetic Complications

PURPOSE OF REVIEW

Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies.

RECENT FINDINGS

Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10^-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.

T2DiACoD: A Gene Atlas of Type 2 Diabetes Mellitus Associated Complex Disorders

We performed integrative analysis of genes associated with type 2 Diabetes Mellitus (T2DM) associated complications by automated text mining with manual curation and also gene expression analysis from Gene Expression Omnibus. They were analysed for pathogenic or protective role, trends, interaction with risk factors, Gene Ontology enrichment and tissue wise differential expression. The database T2DiACoD houses 650 genes, and 34 microRNAs associated with T2DM complications. Seven genes AGER, TNFRSF11B, CRK, PON1, ADIPOQ, CRP and NOS3 are associated with all 5 complications. Several genes are studied in multiple years in all complications with high proportion in cardiovascular (75.8%) and atherosclerosis (51.3%). T2DM Patients’ skeletal muscle tissues showed high fold change in differentially expressed genes. Among the differentially expressed genes, VEGFA is associated with several complications of T2DM. A few genes ACE2, ADCYAP1, HDAC4, NCF1, NFE2L2, OSM, SMAD1, TGFB1, BDNF, SYVN1, TXNIP, CD36, CYP2J2, NLRP3 with details of protective role are catalogued. Obesity is clearly a dominant risk factor interacting with the genes of T2DM complications followed by inflammation, diet and stress to variable extents. This information emerging from the integrative approach used in this work could benefit further therapeutic approaches. The T2DiACoD is available at www.http://t2diacod.igib.res.in/.

Clinical worthlessness of genetic prediction of common forms of diabetes mellitus and related chronic complications: A position statement of the Italian Society of Diabetology

AIM

We are currently facing several attempts aimed at marketing genetic data for predicting multifactorial diseases, among which diabetes mellitus is one of the more prevalent. The present document primarily aims at providing to practicing physicians a summary of available data regarding the role of genetic information in predicting diabetes and its chronic complications.

DATA SYNTHESIS

Firstly, general information about characteristics and performance of risk prediction tools will be presented in order to help clinicians to get acquainted with basic methodological information related to the subject at issue. Then, as far as type 1 diabetes is concerned, available data indicate that genetic information and counseling may be useful only in families with many affected individuals. However, since no disease prevention is possible, the utility of predicting this form of diabetes is at question. In the case of type 2 diabetes, available data really question the utility of adding genetic information on top of well performing, easy available and inexpensive non-genetic markers. Finally, the possibility of using the few available genetic data on diabetic complications for improving our ability to predict them will also be presented and discussed. For cardiovascular complication, the addition of genetic information to models based on clinical features does not translate in a substantial improvement in risk discrimination. For all other diabetic complications genetic information are currently very poor and cannot, therefore, be used for improving risk stratification.

CONCLUSIONS

In all, nowadays the use of genetic testing for predicting diabetes and its chronic complications is definitively of little value in clinical practice.

Identification and characterization of novel single nucleotide polymorphism markers for fat deposition in muscle tissue of pigs using amplified fragment length polymorphism

Objective

This study was conducted to identify and evaluate the effective single nucleotide polymorphism (SNP) markers for fat deposition in the longissimus dorsi muscles of pigs using the amplified fragment length polymorphism (AFLP) approach.

Methods

Sixty-four selective primer combinations were used to identify the AFLP markers in the 20 highest- and 20 lowest-intramuscular fat (IMF) content phenotypes. Five AFLP fragments were converted into simple codominant SNP markers. These SNP markers were tested in terms of their association with IMF content and fatty acid (FA) composition traits in 620 commercially crossbred pigs.

Results

The SSC7 g.4937240C>G marker showed an association with IMF content (p<0.05). The SSC9 g.5496647_5496662insdel marker showed a significant association with IMF content and arachidonic levels (p<0.05). The SSC10 g.71225134G>A marker revealed an association with palmitoleic and ω9 FA levels (p<0.05), while the SSC17 g.61976696G>T marker showed a significant association with IMF content and FA levels of palmitoleic, eicosenoic, arachidonic, monounsaturated fatty acids, and ω9 FA levels. However, no significant association of SSC8 g.47338181G>A was observed with any IMF and FA levels in this study.

Conclusion

Four SNP markers (SSC7 g.4937240C>G, SSC9 g.5496647_5496662insdel, SSC10 g.71225134G>A, and SSC17 g.61976696G>T) were found to be associated with IMF and/or FA content traits in commercially crossbred pigs. These findings provide evidence of the novel SNP markers as being potentially useful for selecting pigs with the desirable IMF content and FA composition.

Association of kidney structure-related gene variants with type 2 diabetes-attributed end-stage kidney disease in African Americans

African Americans (AAs) are at higher risk for developing end-stage kidney disease (ESKD) compared to European Americans. Genome-wide association studies have identified variants associated with diabetic and non-diabetic kidney diseases. Nephropathy loci, including SLC7A9, UMOD, and SHROOM3, have been implicated in the maintenance of normal glomerular and renal tubular structure and function. Herein, 47 genes important in podocyte, glomerular basement membrane, mesangial cell, mesangial matrix, renal tubular cell, and renal interstitium structure were examined for association with type 2 diabetes (T2D)-attributed ESKD in AAs. Single-variant association analysis was performed in the discovery stage, including 2041 T2D-ESKD cases and 1140 controls (non-diabetic, non-nephropathy). Discrimination analyses in 667 T2D cases-lacking nephropathy excluded T2D-associated SNPs. Nominal associations were tested in an additional 483 T2D-ESKD cases and 554 controls in the replication stage. Meta-analysis of 4218 discovery and replication samples revealed three significant associations with T2D-ESKD at CD2AP and MMP2 (P _corr < 0.05 corrected for effective number of SNPs in each locus). Removal of APOL1 renal-risk genotype carriers revealed additional association at five loci, TTC21B, COL4A3, NPHP3-ACAD11, CLDN8, and ARHGAP24 (P _corr < 0.05). Genetic variants at COL4A3, CLDN8, and ARHGAP24 were potentially pathogenic. Gene-based associations revealed suggestive significant aggregate effects of coding variants at four genes. Our findings suggest that genetic variation in kidney structure-related genes may contribute to T2D-attributed ESKD in the AA population.

Association Analysis of the Cubilin (CUBN) and Megalin (LRP2) Genes with ESRD in African Americans

BACKGROUND AND OBJECTIVES

Genetic variation in the cubilin (CUBN) gene is associated with albuminuria and CKD. Common and rare coding variants in CUBN and the gene encoding its transport partner megalin (LRP2) were assessed for association with ESRD in blacks.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Sixty-six CUBN and LRP2 single-nucleotide polymorphisms (SNPs) were selected and analyzed in this multistage study. Exome sequencing data from 529 blacks with type 2 diabetes (T2D) -associated ESRD and 535 controls lacking T2D or nephropathy (the Type 2 Diabetes Genes [T2D-GENES] Consortium) were first evaluated, focusing on coding variants in CUBN and LRP2; 15 potentially associated SNPs identified from the T2D-GENES Consortium as well as 51 other selected SNPs were then assessed in an independent T2D-ESRD sample set of blacks (the Affymetrix Axiom Biobank Genotyping Array [AXIOM]; 2041 patients with T2D-ESRD, 627 patients with T2D without nephropathy, and 1140 nondiabetic, non-nephropathy controls). A meta-analysis combining the T2D-GENES Consortium and the AXIOM data was performed for 18 overlapping SNPs. Additionally, all 66 SNPs were genotyped in the Wake Forest School of Medicine samples of blacks with nondiabetic ESRD (885 patients with nondiabetic ESRD and 721 controls). Association testing with ESRD was performed in models including age, sex, African ancestry proportion, and apolipoprotein L1 gene renal-risk variants.

RESULTS

CUBN SNP rs1801239 (I2984V), previously associated with albuminuria, was significantly associated with T2D-ESRD in blacks (the T2D-GENES Consortium and the AXIOM meta-analysis, P=0.03; odds ratio, 1.31; 95% confidence interval, 1.03 to 1.67; minor allele frequency =0.028). A novel LRP2 missense variant, rs17848169 (N2632D), was also significantly protective from T2D-ESRD (the T2D-GENES Consortium and the AXIOM, P<0.002; odds ratio, 0.47; 95% confidence interval, 0.29 to 0.75; meta-analysis minor allele frequency =0.007). Neither SNP was associated with T2D when contrasting patients with T2D with controls lacking diabetes. CUBN and LRP2 SNPs were not associated with nondiabetic etiologies of ESRD.

CONCLUSIONS

Evidence for genetic association exists between a cubilin and a rare megalin variant with diabetes-associated ESRD in populations with recent African ancestry.

Bioinformatic Evaluation of Transcriptional Regulation of WNT Pathway Genes with reference to Diabetic Nephropathy

OBJECTIVE

WNT/β-catenin pathway members have been implicated in interstitial fibrosis and glomerular sclerosis disease processes characteristic of diabetic nephropathy (DN), processes partly controlled by transcription factors (TFs) that bind to gene promoter regions attenuating regulation. We sought to identify predicted cis-acting transcription factor binding sites (TFBSs) overrepresented within WNT pathway members.

METHODS

We assessed 62 TFBS motif frequencies from the JASPAR databases in 65 WNT pathway genes. P values were estimated on the hypergeometric distribution for each TF. Gene expression profiles of enriched motifs were examined in DN-related datasets to assess clinical significance.

RESULTS

Transcription factor AP-2 alpha (TFAP2A), myeloid zinc finger 1 (MZF1), and specificity protein 1 (SP1) were significantly enriched within WNT pathway genes (P values < 6.83 × 10(-29), 1.34 × 10(-11), and 3.01 × 10(-6), resp.). MZF1 expression was significantly increased in DN in a whole kidney dataset (fold change = 1.16; 16% increase; P = 0.03). TFAP2A expression was decreased in an independent dataset (fold change = -1.02; P = 0.03). No differential expression of SP1 was detected.

CONCLUSIONS

Three TFBS profiles are significantly enriched within WNT pathway genes highlighting the potential of in silico analyses for identification of pathway regulators. Modification of TF binding may possibly limit DN progression, offering potential therapeutic benefit.

Association Analysis of the Reticulon 1 Gene in End-Stage Kidney Disease

BACKGROUND

The reticulon 1 gene (RTN1) encodes reticulons, endoplasmic reticulum stress proteins recently implicated in kidney disease progression.

METHODS

RTN1 single nucleotide polymorphisms (SNPs) were tested for association with type 2 diabetes (T2D)-associated end-stage kidney disease (ESKD) in African Americans (AAs) and European Americans (EAs), and AAs with non-diabetic ESKD. RTN1 SNPs that were associated with T2D-ESKD in AA cases compared to non-nephropathy controls were identified from a discovery genome-wide association study (n=1,797), then tested for replication in 1,847 additional AA T2D-ESKD cases and controls.

RESULTS

Three intronic RTN1 variants were nominally associated with T2D-ESKD in both discovery and replication analyses: rs1952034, rs12431381 and rs12434215 (additive models); combined T2D-ESKD (discovery+replication) p values were 0.015-3.0×10(-4) (ORs 0.67-0.77; minor alleles protective). In addition, rs12434215 was weakly associated with T2D-ESKD in 557 EA T2D-ESKD cases contrasted with 753 EA non-nephropathy controls (p=0.019; OR 0.69, dominant model). Nominal association extended to non-diabetic causes of ESKD in 1,459 additional AA cases (rs12431381 and rs12434215 p values 0.014-0.015; OR 0.77). An all-cause ESKD association analysis contrasted the 3,594 AA ESKD cases with 1,489 AA non-nephropathy controls and detected association with rs12434215 (p=6.7×10(-4), OR 0.73) and rs12431381 (p=7.5×10(-4), OR 0.75) in dominant models. Of the 3 SNPs, only rs12434215 was weakly associated with T2D per se when contrasting T2D non-nephropathy cases with non-diabetic controls (additive model p=0.032 AAs; p=0.048 EAs).

CONCLUSIONS

These results suggest evidence of genetic association between common variants in RTN1 and ESKD in AAs and EAs.

An update on the genetic architecture of hyperuricemia and gout

Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.