Genome-wide association study identifies novel loci for type 2 diabetes-attributed end-stage kidney disease in African Americans

Additive interaction of family medical history of diabetes with hypertension on the diagnosis of diabetes among older adults in India: longitudinal ageing study in India

BACKGROUND

The present study aimed to estimate the additive interaction of family history of diabetes and hypertension on the diagnosis of diabetes among individuals aged 45 years and above in India. The coexistence of these two exposures may act synergistically on the risk of diabetes, leading to adverse health outcomes.

METHODS

The study utilized the data from the Longitudinal Ageing Study in India (LASI) Wave 1 (2017-2018). The total sample size for the current study was 58,612 individuals aged 45 years and above. Multivariable logistic regression models were employed to determine the individual and joint effect of a family history of diabetes with hypertension on diabetes. An additive model was applied to assess the interaction effect of the family medical history of diabetes with hypertension on the diagnosis of diabetes by calculating three different measures of additive interaction such as the relative excess risk ratio (RERI), attribution proportion due to interaction (AP), and synergy index (S).

RESULTS

The prevalence of diabetes was three times higher among individuals with family history of diabetes (27.8% vs. 9.2%) than those without family history. Individuals with family history of diabetes (AOR: 2.47, CI: 2.11 2.89) had 2.47 times higher odds of having diabetes than those without family history. The prevalence of diabetes was significantly higher among individuals with hypertension and family history of diabetes (46.6%, 95% CI: 39.7-53.6) than those without the coexistence of family history of diabetes and hypertension (9.9%, 95% CI: 9.5-10.4), individuals with hypertension and without a family history of diabetes (22.7%, 95% CI: 21.2-24.2), and individuals with family history of diabetes and without hypertension (16.5%, 95% CI: 14.5-18.7). Moreover, the adjusted odds ratio (AOR) of the joint effect between family medical history of diabetes and hypertension on diabetes was 9.28 (95% CI: 7.51-11.46). In the adjusted model, the RERI, AP, and S for diabetes were 3.5 (95% CI: 1.52-5.47), 37% (0.37; 95% CI: 0.22-0.51), and 1.69 (95% CI: 1.31-2.18) respectively, which indicates that there is a significant positive interaction between family history of diabetes and hypertension on the diagnosis of diabetes. The study findings on interaction effects further demonstrate consistent results for two models of hypertension (self-reported hypertension and hypertensive individuals receiving medication) even after adjustment with potential confounding factors on diabetes (self-reported diabetes and individuals with diabetes receiving medication).

CONCLUSIONS

The study findings strongly suggest that the interaction of family history of diabetes with hypertension has a positive and significant effect on the risk of diabetes even after adjustment with potential confounding factors. Furthermore, the findings indicate a synergistic effect, emphasizing the importance of considering both family medical history of diabetes and hypertension when assessing diabetes risk and designing preventive strategies or interventions.

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

Progress in genetics of type 2 diabetes and diabetic complications

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.

Harnessing Genomic Analysis to Explore the Role of Telomeres in the Pathogenesis and Progression of Diabetic Kidney Disease

The prevalence of diabetes is increasing globally, and this trend is predicted to continue for future decades. Research is needed to uncover new ways to manage diabetes and its co-morbidities. A significant secondary complication of diabetes is kidney disease, which can ultimately result in the need for renal replacement therapy, via dialysis or transplantation. Diabetic kidney disease presents a substantial burden to patients, their families and global healthcare services. This review highlights studies that have harnessed genomic, epigenomic and functional prediction tools to uncover novel genes and pathways associated with DKD that are useful for the identification of therapeutic targets or novel biomarkers for risk stratification. Telomere length regulation is a specific pathway gaining attention recently because of its association with DKD. Researchers are employing both observational and genetics-based studies to identify telomere-related genes associated with kidney function decline in diabetes. Studies have also uncovered novel functions for telomere-related genes beyond the immediate regulation of telomere length, such as transcriptional regulation and inflammation. This review summarises studies that have revealed the potential to harness therapeutics that modulate telomere length, or the associated epigenetic modifications, for the treatment of DKD, to potentially slow renal function decline and reduce the global burden of this disease.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Identification of genetic variants associated with diabetic kidney disease in multiple Korean cohorts via a genome-wide association study mega-analysis

BACKGROUND

The pathogenesis of diabetic kidney disease (DKD) is complex, involving metabolic and hemodynamic factors. Although DKD has been established as a heritable disorder and several genetic studies have been conducted, the identification of unique genetic variants for DKD is limited by its multiplex classification based on the phenotypes of diabetes mellitus (DM) and chronic kidney disease (CKD). Thus, we aimed to identify the genetic variants related to DKD that differentiate it from type 2 DM and CKD.

METHODS

We conducted a large-scale genome-wide association study mega-analysis, combining Korean multi-cohorts using multinomial logistic regression. A total of 33,879 patients were classified into four groups-normal, DM without CKD, CKD without DM, and DKD-and were further analyzed to identify novel single-nucleotide polymorphisms (SNPs) associated with DKD. Additionally, fine-mapping analysis was conducted to investigate whether the variants of interest contribute to a trait. Conditional analyses adjusting for the effect of type 1 DM (T1D)-associated HLA variants were also performed to remove confounding factors of genetic association with T1D. Moreover, analysis of expression quantitative trait loci (eQTL) was performed using the Genotype-Tissue Expression project. Differentially expressed genes (DEGs) were analyzed using the Gene Expression Omnibus database (GSE30529). The significant eQTL DEGs were used to explore the predicted interaction networks using search tools for the retrieval of interacting genes and proteins.

RESULTS

We identified three novel SNPs [rs3128852 (P = 8.21×10^-25), rs117744700 (P = 8.28×10^-10), and rs28366355 (P = 2.04×10^-8)] associated with DKD. Moreover, the fine-mapping study validated the causal relationship between rs3128852 and DKD. rs3128852 is an eQTL for TRIM27 in whole blood tissues and HLA-A in adipose-subcutaneous tissues. rs28366355 is an eQTL for HLA-group genes present in most tissues.

CONCLUSIONS

We successfully identified SNPs (rs3128852, rs117744700, and rs28366355) associated with DKD and verified the causal association between rs3128852 and DKD. According to the in silico analysis, TRIM27 and HLA-A can define DKD pathophysiology and are associated with immune response and autophagy. However, further research is necessary to understand the mechanism of immunity and autophagy in the pathophysiology of DKD and to prevent and treat DKD.

Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression

The proximal tubule is a key regulator of kidney function and glucose metabolism. Diabetic kidney disease leads to proximal tubule injury and changes in chromatin accessibility that modify the activity of transcription factors involved in glucose metabolism and inflammation. Here we use single nucleus RNA and ATAC sequencing to show that diabetic kidney disease leads to reduced accessibility of glucocorticoid receptor binding sites and an injury-associated expression signature in the proximal tubule. We hypothesize that chromatin accessibility is regulated by genetic background and closely-intertwined with metabolic memory, which pre-programs the proximal tubule to respond differently to external stimuli. Glucocorticoid excess has long been known to increase risk for type 2 diabetes, which raises the possibility that glucocorticoid receptor inhibition may mitigate the adverse metabolic effects of diabetic kidney disease.

Molecular Mechanisms and Therapeutic Targets for Diabetic Kidney Disease

Diabetic kidney disease has a high global disease burden and substantially increases risk of kidney failure and cardiovascular events. Despite treatment, there is substantial residual risk of disease progression with existing therapies. Therefore, there is an urgent need to better understand the molecular mechanisms driving diabetic kidney disease to help identify new therapies that slow progression and reduce associated risks. Diabetic kidney disease is initiated by diabetes-related disturbances in glucose metabolism, which then trigger other metabolic, hemodynamic, inflammatory, and fibrotic processes that contribute to disease progression. This review summarizes existing evidence on the molecular drivers of diabetic kidney disease onset and progression, focusing on inflammatory and fibrotic mediators-factors that are largely unaddressed as primary treatment targets and for which there is increasing evidence supporting key roles in the pathophysiology of diabetic kidney disease. Results from recent clinical trials highlight promising new drug therapies, as well as a role for dietary strategies, in treating diabetic kidney disease.

Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.

A potent HNF4α agonist reveals that HNF4α controls genes important in inflammatory bowel disease and Paneth cells

HNF4α has been implicated in IBD through a number of genome-wide association studies. Recently, we developed potent HNF4α agonists, including N-trans caffeoyltyramine (NCT). NCT was identified by structural similarity to previously the previously identified but weak HNF4α agonists alverine and benfluorex. Here, we administered NCT to mice fed a high fat diet, with the goal of studying the role of HNF4α in obesity-related diseases. Intestines from NCT-treated mice were examined by RNA-seq to determine the role of HNF4α in that organ. Surprisingly, the major classes of genes altered by HNF4α were involved in IBD and Paneth cell biology. Multiple genes downregulated in IBD were induced by NCT. Paneth cells identified by lysozyme expression were reduced in high fat fed mice. NCT reversed the effect of high fat diet on Paneth cells, with multiple markers being induced, including a number of defensins, which are critical for Paneth cell function and intestinal barrier integrity. NCT upregulated genes that play important role in IBD and that are downregulated in that disease. It reversed the loss of Paneth cell markers that occurred in high fat diet fed mice. These data suggest that HNF4α could be a therapeutic target for IBD and that the agonists that we have identified could be candidate therapeutics.

KDOQI US Commentary on the KDIGO 2020 Clinical Practice Guideline for Diabetes Management in CKD

In October 2020, KDIGO (Kidney Disease: Improving Global Outcomes) published its first clinical practice guideline directed specifically to the care of patients with diabetes and chronic kidney disease (CKD). This commentary presents the views of the KDOQI (Kidney Disease Outcomes Quality Initiative) work group for diabetes in CKD, convened by the National Kidney Foundation to provide an independent expert perspective on the new guideline. The KDOQI work group believes that the KDIGO guideline takes a major step forward in clarifying glycemic targets and use of specific antihyperglycemic agents in diabetes and CKD. The purpose of this commentary is to carry forward the conversation regarding optimization of care for patients with diabetes and CKD. Recent developments for prevention of CKD progression and cardiovascular events in people with diabetes and CKD, particularly related to sodium/glucose cotransporter 2 (SGLT2) inhibitors, have filled a longstanding gap in nephrology's approach to the care of persons with diabetes and CKD. The multifaceted benefits of SGLT2 inhibitors have facilitated interactions between nephrology, cardiology, endocrinology, and primary care, underscoring the need for innovative approaches to multidisciplinary care in these patients. We now have more interventions to slow kidney disease progression and prevent or delay kidney failure in patients with diabetes and kidney disease, but methods to streamline their implementation and overcome barriers in access to care, particularly cost, are essential to ensuring all patients may benefit.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes

BACKGROUND

Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage.

METHODS

Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (n=2372/1115 events all cohorts) and replicating in two retrospective case-control studies (n=1072 cases, 752 controls). Deep resequencing of the top associated gene in five cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models.

RESULTS

Protein coding variants in the hydroxysteroid 17-β dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (n=4196; P value=3.3 × 10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other CKD-associated renal pathologies.

CONCLUSIONS

HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Metabolomic architecture of obesity implicates metabolonic lactone sulfate in cardiometabolic disease

OBJECTIVE

Identify and characterize circulating metabolite profiles associated with adiposity to inform precision medicine.

METHODS

Untargeted plasma metabolomic profiles in the Insulin Resistance Atherosclerosis Family Study (IRASFS) Mexican American cohort (n = 1108) were analyzed for association with anthropometric (body mass index, BMI; waist circumference, WC; waist-to-hip ratio, WHR) and computed tomography measures (visceral adipose tissue, VAT; subcutaneous adipose tissue, SAT; visceral-to-subcutaneous ratio, VSR) of adiposity. Genetic data, inclusive of genome-wide array-based genotyping, whole exome sequencing (WES) and whole genome sequencing (WGS), were evaluated to identify the genetic contributors. Phenotypic and genetic association signals were replicated across ancestries. Transcriptomic data were analyzed to explore the relationship between genetic and metabolomic data.

RESULTS

A partially characterized metabolite, tentatively named metabolonic lactone sulfate (X-12063), was consistently associated with BMI, WC, WHR, VAT, and SAT in IRASFS Mexican Americans (P_MA <2.02 × 10^-27). Trait associations were replicated in IRASFS African Americans (P_AA < 1.12 × 10^-07). Expanded analyses revealed associations with multiple phenotypic measures of cardiometabolic health, e.g. insulin sensitivity (S_I), triglycerides (TG), diastolic blood pressure (DBP) and plasminogen activator inhibitor-1 (PAI-1) in both ancestries. Metabolonic lactone sulfate levels were heritable (h² > 0.47), and a significant genetic signal at the ZSCAN25/CYP3A5 locus (P_MA = 9.00 × 10^-41, P_AA = 2.31 × 10^-10) was observed, highlighting a putative functional variant (rs776746, CYP3A5∗3). Transcriptomic analysis in the African American Genetics of Metabolism and Expression (AAGMEx) cohort supported the association of CYP3A5 with metabolonic lactone sulfate levels (P_FDR = 6.64 × 10^-07).

CONCLUSIONS

Variant rs776746 is associated with a decrease in the transcript levels of CYP3A5, which in turn is associated with increased metabolonic lactone sulfate levels and poor cardiometabolic health.

Elevated expression of the RNA-binding motif protein 43 predicts poor prognosis in esophageal squamous cell carcinoma

RNA-binding proteins (RBPs) play crucial roles in the post-transcriptional regulation of mRNA during numerous physiological and pathological processes, including tumor genesis and development. However, the role of RNA-binding motif protein 43 (RBM43) in esophageal squamous cell carcinoma (ESCC) has not been reported so far. The current study was the first to evaluate RBM43 protein expression by immunohistochemistry (IHC) in an independent cohort of 207 patients with ESCC, to explore its potential prognostic value and clinical relevance in ESCC. The results indicated that RBM43 protein levels were significantly elevated in ESCC tissues and increased RBM43 expression was associated with age and N categories. In addition, ESCC patients with high expression of RBM43 had shorter overall survival (OS) and disease‐free survival (DFS) than those with low RBM43 expression. Furthermore, when survival analyses were conducted at different clinical stages, overexpression of RBM43 was significantly correlated with shortened survival in patients with ESCC at early stages (TNM stage I–II and N0 stage). Cox regression analysis further proved that high RBM43 expression was an independent predictor of poor prognosis in ESCC patients. In conclusion, increased expression of RBM43 is correlated with malignant attributes to ESCC and predicts unfavorable prognosis, suggesting an effective prognostic biomarker and potential therapeutic target for ESCC.

Identification of genetic loci affecting body mass index through interaction with multiple environmental factors using structured linear mixed model

Multiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value < 5.00 × 10^-6). Of the 8 environmental factors, PAMET score was excluded for further analysis since it had an average Bayes Factor (BF) value < 1 (BF = 0.88). Interaction analysis using 7 environmental factors identified 11 SNPs (P value < 5.00 × 10^-6). Of these, rs2391331 had the most significant interaction (P value = 7.27 × 10^-9) and was located within the intron of EFNB2 (Chr 13). In addition, the gene-based genome-wide association study verified EFNB2 gene significantly interacting with 7 environmental factors (P value = 5.03 × 10^-10). BF analysis indicated that most environmental factors, except carbohydrate intake, contributed to the interaction of rs2391331 on BMI. Although the replication of the results in other cohorts is warranted, these findings proved the usefulness of Struct-LMM to identify the gene-environment interaction affecting disease.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of UBE3C Variants with Reduced Kidney Function in Patients with Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of morbidity and mortality in patients with diabetes mellitus (DM) and the most common variant of end-stage renal disease (ESRD) globally. The economic burden of ESRD treatment with dialysis is substantial. The incidence and prevalence of ESRD in Taiwan remain the highest worldwide. Therefore, identifying genetic factors affecting kidney function would have valuable clinical implications. We performed microarray experiments and identified that ubiquitin protein ligase E3C (UBE3C) is differentially expressed in two DKD patient groups with extreme (low and high) urine protein-to-creatinine ratios. A follow-up genotyping study was performed in a larger group to investigate any specific variants of UBE3C associated with DKD. A total of 263 patients were included in the study, comprising 172 patients with DKD and 91 control subjects (patients with DM without chronic kidney disease (CKD)). Two UBE3C variants (rs3802129(AA) and rs7807(CC)) were determined to be associated with reduced kidney function. The haplotype analysis revealed that rs3802129/rs3815217 (block 1) with A/G haplotype and rs8101/rs7807 (block 2) with T/C haplotype were associated with higher risks of CKD phenotypes. These findings suggest a clinical role of UBE3C variants in DKD risk.

Recent advances in drug discovery for diabetic kidney disease

INTRODUCTION

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD), and 40% of patients with diabetes develop DKD. Although some pathophysiological mechanisms and drug targets of DKD have been described, the effectiveness or clinical usefulness of such treatment has not been well validated. Therefore, searching for new targets and potential therapeutic candidates has become an emerging research area.

AREAS COVERED

The pathophysiological mechanisms, new drug targets and potential therapeutic compounds for DKD are addressed in this review.

EXPERT OPINION

Although preclinical and clinical evidence has shown some positive results for controlling DKD progression, treatment regimens have not been well developed to reduce the mortality in patients with DKD globally. Therefore, the discovery of new therapeutic targets and effective target-based drugs to achieve better and safe treatment are urgently required. Preclinical screening and clinical trials for such drugs are needed.

The genetic map of diabetic nephropathy: evidence from a systematic review and meta-analysis of genetic association studies

Despite the extensive efforts of scientists, the genetic background of diabetic nephropathy (DN) has not yet been clarified. To elucidate the genetic variants that predispose to the development of DN, we conducted a systematic review and meta-analysis of all available genetic association studies (GAS) of DN. We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available GAS of DN. The threshold for meta-analysis was three studies per genetic variant. The association between genotype distribution and DN was examined using the generalized linear odds ratio (OR_G). For variants with available allele frequencies, the examined model was the allele contrast. The pooled OR was estimated using the DerSimonian and Laird random effects model. The publication bias was assessed with Egger’s test. We performed pathway analysis of significant genes with DAVID 6.7. Genetic data of 606 variants located in 228 genes were retrieved from 360 GASs and were synthesized with meta-analytic methods. ACACB, angiotensin I-converting enzyme (ACE), ADIPOQ, AGT, AGTR1, AKR1B1, APOC1, APOE, ATP1B2, ATP2A3, CARS, CCR5, CGNL1, Carnosine dipeptidase 1 (CNDP1), CYGB-PRCD, EDN1, Engulfment and cell motility 1 (ELMO1), ENPP1, EPO, FLT4, FTO, GLO1, HMGA2, IGF2/INS/TH cluster, interleukin 1B (IL1B), IL8, IL10, KCNQ1, KNG, LOC101927627, Methylenetetrahydrofolate reductase, nitric oxide synthase 3 (NOS3), SET domain containing seven, histone lysine methyltransferase (SETD7), Sirtuin 1 (SIRT1), SLC2A1, SLC2A2, SLC12A3, SLC19A3, TCF7L2, TGFB1, TIMP1, TTC39C, UNC13B, VEGFA, WTAPP1, WWC1 as well as XYLT1 and three intergenic polymorphisms showed significant association with DN. Pathway analysis revealed the overrepresentation of six signalling pathways. The significant findings provide further evidence for genetic factors implication in DN offering new perspectives in discovery of new therapies.

RNA-binding motif protein 43 (RBM43) suppresses hepatocellular carcinoma progression through modulation of cyclin B1 expression

RNA-binding proteins play key roles in the posttranscriptional regulation of mRNA during cancer progression. Here, we show that RNA-binding motif protein 43 (RBM43) is significantly downregulated in human tumors, and its low expression is correlated with poor prognosis in patients with HCC. Overexpression of RBM43 suppressed cell proliferation in culture and resulted in the growth arrest of tumor xenografts, whereas downregulating RBM43 played an opposite role. We have also demonstrated that overexpression or knockdown of RBM43 affects the cell-cycle progression of liver cancer cells. Mechanistically, RBM43 directly associated with the 3'UTR of Cyclin B1 mRNA and regulated its expression. Moreover, loss of Rbm43 in mice promoted liver carcinogenesis and HCC development after diethylnitrosamine (DEN)-carbon tetrachloride (CCl₄) treatment. Taken together, our data indicate that RBM43 is a tumor suppressor that controls the cell cycle through modulation of Cyclin B1 expression, providing evidence that RBM43 is particularly important in HCC.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Pathophysiologic mechanisms in diabetic kidney disease: A focus on current and future therapeutic targets

Diabetic kidney disease (DKD) is the primary cause of chronic kidney disease around the globe and is one of the main complications in patients with type 1 and 2 diabetes. The standard treatment for DKD is drugs controlling hyperglycemia and high blood pressure. Renin angiotensin aldosterone system blockade and sodium glucose cotransporter 2 (SGLT2) inhibition have yielded promising results in DKD, but many diabetic patients on such treatments nevertheless continue to develop DKD, leading to kidney failure and cardiovascular comorbidities. New therapeutic options are urgently required. We review here the promising therapeutic avenues based on insights into the mechanisms of DKD that have recently emerged, including mineralocorticoid receptor antagonists, SGLT2 inhibitors, glucagon-like peptide-1 receptor agonist, endothelin receptor A inhibition, anti-inflammatory agents, autophagy activators and epigenetic remodelling. The involvement of several molecular mechanisms in DKD pathogenesis, together with the genetic and epigenetic variability of this condition, makes it difficult to target this heterogeneous patient population with a single drug. Personalized medicine, taking into account the genetic and mechanistic variability, may therefore improve renal and cardiovascular protection in diabetic patients with DKD.

The Impact of New Biomarkers and Drug Targets on Age-Related Disorders

The increase in the human lifespan has not been paralleled by an increase in healthy life. With the increase in the proportion of the aged population, there has been a natural increase in the prevalence of age-related disorders, such as Alzheimer's disease, type 2 diabetes mellitus, frailty, and various other disorders. A continuous rise in these conditions could lead to a widespread medical and social burden. There are now considerable efforts underway to address these deficits in preclinical and clinical studies, which include the use of better study cohorts, longitudinal designs, improved translation of data from preclinical models, multi-omics profiling, identification of new biomarker candidates and refinement of computational tools and databases containing relevant information. Such efforts will support future interdisciplinary studies and help to identify potential new targets that are amenable to therapeutic approaches such as pharmacological interventions to increase the human healthspan in parallel with the lifespan.

ACTB Variants Confer the Genetic Susceptibility to Diabetic Kidney Disease in a Han Chinese Population

Beta-actin (ACTB) loss-of-function mutations result in a pleiotropic developmental disorder of kidney. The present study aims to explore whether the common variants at the ACTB gene contribute to diabetic kidney disease (DKD) susceptibility in patients with type 2 diabetes mellitus (T2DM). From the baseline population of 20,340 diabetic patients, 1,510 DKD cases and 1,510 age-matched T2DM controls were selected. All subjects were Han Chinese. Three tagging single nucleotide polymorphisms (SNPs), rs852423, rs852426, and rs2966449, at the ACTB gene were genotyped. Logistic regression was performed to estimate the association with DKD. SNPs, rs852426 and rs2966449, were significantly associated with DKD [additive model; odds ratio (OR), 1.217 and 1.151; P = 0.001 and 0.018, respectively]. The association of rs852426 with DKD still remained statistically significant after Bonferroni correction and particularly significant in the population older than 70 years rather than the 70 years or younger (P = 0.047 for heterogeneity test). Furthermore, the association of rs852426 with DKD was observed in populations of male and females without smoking, drinking, and with duration for T2DM 10–20 years. The association of rs2966449 with DKD was also found in the populations older than 70 years, male, not smoking, not drinking, and with duration for T2DM over 20 years. The estimated glomerular filtration rate (eGFR) levels of the individuals with TT or CC genotypes of rs2966449 were significantly lower than that of TC genotype in DKD cases (P = 0.021). The present study provides evidence that the ACTB variants, i.e., rs852426 and rs2966449, may confer the genetic susceptibility to DKD in a Han Chinese population.