The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Integrative analysis of 111 reference human epigenomes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

The genetic architecture of type 2 diabetes

Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ∼150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10−6), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (−0.17 s.d., P = 4.6 × 10−4). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.

Loss-of-function mutations in SLC30A8 protect against type 2 diabetes

Solid organ transplantation (SOT) is a life-saving procedure and an established treatment for patients with end-stage organ failure. However, transplantation is also accompanied by associated cardiovascular risk factors, of which post-transplant diabetes mellitus (PTDM) is one of the most important. PTDM develops in 10-20% of patients with kidney transplants and in 20-40% of patients who have undergone other SOT. PTDM increases mortality, which is best documented in patients who have received kidney and heart transplants. PTDM results from predisposing factors (similar to type 2 diabetes mellitus) but also as a result of specific post-transplant risk factors. Although PTDM has many characteristics in common with type 2 diabetes mellitus, the prevention and treatment of the two disorders are often different. Over the past 20 years, the lifespan of patients who have undergone SOT has increased, and PTDM becomes more common over the lifespan of these patients. Accordingly, PTDM becomes an important condition not only to be aware of but also to treat. This Review presents the current knowledge on PTDM in patients receiving kidney, heart, liver and lung transplants. This information is not only for transplant health providers but also for endocrinologists and others who will meet these patients in their clinics.

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Post-transplant diabetes mellitus in patients with solid organ transplants

Developmental origins of type 2 diabetes: Focus on epigenetics.

Diabetes mellitus is an incurable progressive disease, characterized by elevated blood glucose levels, which lead to the development of micro- and macrovascular complications. Although the etiopathology of the disease remains unclear, it seems to be multifactorial, with an important interaction between genetics and environmental causes. Currently, the genetics of type 2 diabetes (T2D) is poorly understood. The recent advance of the genetic technologies and with a better understanding of genetics, more than 120 distinct genetic loci, with more than 150 variants, have been identified that may be involved in the pathogenesis of T2D. However, as these variants can account for only approximately 20% of the heritability of T2D, there is an obvious need for additional approaches to identify susceptibility genes or genetic mechanisms involved in the development of this disease. There is a growing number of genes found to be related to T2D; however, their individual impact on the pathogenesis of the disease appears to be low, while silencing of protective genes may also contribute to the development of this disease. The present review attempts to summarize our current knowledge in the field of genetics of T2D, highlighting the possible practical applications for each approach.

Genetic Approaches to the Study of Gene Variants and Their Impact on the Pathophysiology of Type 2 Diabetes

With the pandemic of type 2 diabetes (T2D), there is an ever-increasing need to fully understand the underlying mechanisms of the disease. Type 2 diabetes shows a high heritability risk (25-80%); however, genes account only for 10% of this risk. From all the risk factors for diabetes, epigenetic mechanisms have the highest statistical scoring in explaining the disease. A multitude of organ-specific epigenomic changes have been linked to type 2 diabetes. Nutritional influences, mainly in the early life, physical activity level, environmental toxins act as epigenetic factors and the recognized epigenetic changes can represent a therapeutical target, new drugs being currently in development for this application. Our current review focuses on the most common epigenetic modifications linked to type 2 diabetes or insulin resistance, the potentially emerging epigenetic-related interventions and pharmacoepigenetic knowledge.

Epigenetic Modifications Linked to T2D, the Heritability Gap, and Potential Therapeutic Targets.

Kidney Dysfunction in Central Obesity Associated Metabolic Disorders

Background: Often described as a novel anthropometric parameter, the conicity index (CI) was developed in 1991 by Valdez to assess central obesity associated with an increased risk of cardiovascular disease (CVD). 

Katalin Csép

Papers

Genetic Approaches to the Study of Gene Variants and Their Impact on the Pathophysiology of Type 2 Diabetes

Epigenetic Modifications Linked to T2D, the Heritability Gap, and Potential Therapeutic Targets.

Kidney Dysfunction in Central Obesity Associated Metabolic Disorders

The Conicity Index in Identification of Cardiorenal Metabolic Syndrome Patients at Increased Risk for Complications