Approaches for establishing the function of regulatory genetic variants involved in disease

Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study

Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Targeted Integration of Transgenes at the Mouse Gt(ROSA)26Sor Locus

The targeting of transgenic constructs at single copy into neutral genomic loci avoids the unpredictable outcomes associated with conventional random integration approaches. The Gt(ROSA)26Sor locus on chromosome 6 has been used many times for the integration of transgenic constructs and is known to be permissive for transgene expression and disruption of the gene is not associated with a known phenotype. Furthermore, the transcript made from the Gt(ROSA)26Sor locus is ubiquitously expressed and subsequently the locus can be used to drive the ubiquitous expression of transgenes.Here we report a protocol for the generation of targeted transgenic alleles at Gt(ROSA)26Sor, taking as an example a conditional overexpression allele, by PhiC31 integrase/recombinase-mediated cassette exchange of an engineered Gt(ROSA)26Sor locus in mouse embryonic stem cells. The overexpression allele is initially silenced by the presence of a loxP flanked stop sequence but can be strongly activated through the action of Cre recombinase.

Joint disease-specificity at the regulatory base-pair level

Given the pleiotropic nature of coding sequences and that many loci exhibit multiple disease associations, it is within non-coding sequence that disease-specificity likely exists. Here, we focus on joint disorders, finding among replicated loci, that GDF5 exhibits over twenty distinct associations, and we identify causal variants for two of its strongest associations, hip dysplasia and knee osteoarthritis. By mapping regulatory regions in joint chondrocytes, we pinpoint two variants (rs4911178; rs6060369), on the same risk haplotype, which reside in anatomical site-specific enhancers. We show that both variants have clinical relevance, impacting disease by altering morphology. By modeling each variant in humanized mice, we observe joint-specific response, correlating with GDF5 expression. Thus, we uncouple separate regulatory variants on a common risk haplotype that cause joint-specific disease. By broadening our perspective, we finally find that patterns of modularity at GDF5 are also found at over three-quarters of loci with multiple GWAS disease associations.

Role of Non-Coding Variants in Brugada Syndrome

Brugada syndrome (BrS) is an inherited electrical heart disease associated with a high risk of sudden cardiac death (SCD). The genetic characterization of BrS has always been challenging. Although several cardiac ion channel genes have been associated with BrS, SCN5A is the only gene that presents definitive evidence for causality to be used for clinical diagnosis of BrS. However, more than 65% of diagnosed cases cannot be explained by variants in SCN5A or other genes. Therefore, in an important number of BrS cases, the underlying mechanisms are still elusive. Common variants, mostly located in non-coding regions, have emerged as potential modulators of the disease by affecting different regulatory mechanisms, including transcription factors (TFs), three-dimensional organization of the genome, or non-coding RNAs (ncRNAs). These common variants have been hypothesized to modulate the interindividual susceptibility of the disease, which could explain incomplete penetrance of BrS observed within families. Altogether, the study of both common and rare variants in parallel is becoming increasingly important to better understand the genetic basis underlying BrS. In this review, we aim to describe the challenges of studying non-coding variants associated with disease, re-examine the studies that have linked non-coding variants with BrS, and provide further evidence for the relevance of regulatory elements in understanding this cardiac disorder.

Genetics of rheumatic fever and rheumatic heart disease

Rheumatic heart disease (RHD) is a complication of group A streptococcal infection that results from a complex interaction between the genetic make-up of the host, the infection itself and several other environmental factors, largely reflecting poverty. RHD is estimated to affect 33.4 million people and results in 10.5 million disability-adjusted life-years lost globally. The disease has long been considered heritable but still little is known about the host genetic factors that increase or reduce the risk of developing RHD. In the 1980s and 1990s, several reports linked the disease to the human leukocyte antigen (HLA) locus on chromosome 6, followed in the 2000s by reports implicating additional candidate regions elsewhere in the genome. Subsequently, the search for susceptibility loci has been reinvigorated by the use of genome-wide association studies (GWAS) through which millions of variants can be tested for association in thousands of individuals. Early findings implicate not only HLA, particularly the HLA-DQA1 to HLA-DQB1 region, but also the immunoglobulin heavy chain locus, including the IGHV4-61 gene segment, on chromosome 14. In this Review, we assess the emerging role of GWAS in assessing RHD, outlining both the advantages and disadvantages of this approach. We also highlight the potential use of large-scale, publicly available data and the value of international collaboration to facilitate comprehensive studies that produce findings that have implications for clinical practice.

AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes

Motivation

Reliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex.

Results

We present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes.

Availability and implementation

Source code freely available at https://github.com/jknightlab/AltHapAlignR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification and characterization of GLDC as host susceptibility gene to severe influenza

Glycine decarboxylase (GLDC) was prioritized as a candidate susceptibility gene to severe influenza in humans. The higher expression of GLDC derived from genetic variations may confer a higher risk to H7N9 and severe H1N1 infection. We sought to characterize GLDC as functional susceptibility gene that GLDC may intrinsically regulate antiviral response, thereby impacting viral replication and disease outcome. We demonstrated that GLDC inhibitor AOAA and siRNA depletion boosted IFNβ‐ and IFN‐stimulated genes (ISGs) in combination with PolyI:C stimulation. GLDC inhibition and depletion significantly amplified antiviral response of type I IFNs and ISGs upon viral infection and suppressed the replication of H1N1 and H7N9 viruses. Consistently, GLDC overexpression significantly promoted viral replication due to the attenuated antiviral responses. Moreover, GLDC inhibition in H1N1‐infected BALB/c mice recapitulated the amplified antiviral response and suppressed viral growth. AOAA provided potent protection to the infected mice from lethal infection, comparable to a standard antiviral against influenza viruses. Collectively, GLDC regulates cellular antiviral response and orchestrates viral growth. GLDC is a functional susceptibility gene to severe influenza in humans.

The IL-23/IL-17 pathway in human chronic inflammatory diseases-new insight from genetics and targeted therapies

Chronic inflammatory diseases such as rheumatoid arthritis, inflammatory bowel disease, spondyloarthritis, and psoriasis cause significant morbidity and are a considerable burden for the patients in terms of pain, impaired function, and diminished quality of life, as well as for society, because of the associated high health-care costs and loss of productivity. Our limited understanding of the pathogenic mechanisms involved in these diseases currently hinders early diagnosis and the development of more specific and effective therapies. The past years have been marked by considerable progress in our insight of the genetic basis of many diseases. In particular, genome-wide association studies (GWAS) performed with thousands of patients have provided detailed information about the genetic variants associated with a large number of chronic inflammatory diseases. These studies have brought to the forefront many genes linked to signaling pathways that were not previously known to be involved in pathogenesis, pointing to new directions in the study of disease mechanisms. GWAS also provided fundamental evidence for a key role of the immune system in the pathogenesis of these diseases, because many of the identified loci map to genes involved in different immune processes. However, the mechanisms by which disease-associated genetic variants act on disease development and the targeted cell populations remain poorly understood. The challenge of the post-GWAS era is to understand how these variants affect pathogenesis, to allow translation of genetic data into better diagnostics and innovative treatment strategies. Here, we review recent results that document the importance of the IL-23/IL-17 pathway for the pathogenesis of several chronic inflammatory diseases and summarize data that demonstrate how therapeutic targeting of this pathway can benefit affected patients.

Anti-TNF Therapy in Spondyloarthritis and Related Diseases, Impact on the Immune System and Prediction of Treatment Responses

Immune-mediated inflammatory diseases (IMIDs), such as spondyloarthritis (SpA), psoriasis, Crohn's disease (CD), and rheumatoid arthritis (RA) remain challenging illnesses. They often strike at a young age and cause lifelong morbidity, representing a considerable burden for the affected individuals and society. Pioneering studies have revealed the presence of a TNF-dependent proinflammatory cytokine cascade in several IMIDs, and the introduction of anti-TNF therapy 20 years ago has proven effective to reduce inflammation and clinical symptoms in RA, SpA, and other IMID, providing unprecedented clinical benefits and a valid alternative in case of failure or intolerable adverse effects of conventional disease-modifying antirheumatic drugs (DMARDs, for RA) or non-steroidal anti-inflammatory drugs (NSAIDs, for SpA). However, our understanding of how TNF inhibitors (TNFi) affect the immune system in patients is limited. This question is relevant because anti-TNF therapy has been associated with infectious complications. Furthermore, clinical efficacy of TNFi is limited by a high rate of non-responsiveness (30–40%) in RA, SpA, and other IMID, exposing a substantial fraction of patients to side-effects without clinical benefit. Despite the extensive use of TNFi, it is still not possible to determine which patients will respond to TNFi before treatment initiation. The recent introduction of antibodies blocking IL-17 has expanded the therapeutic options for SpA, as well as psoriasis and psoriatic arthritis. It is therefore essential to develop tools to guide treatment decisions for patients affected by SpA and other IMID, both to optimize clinical care and contain health care costs. After a brief overview of the biology of TNF, its receptors and currently used TNFi in the clinics, we summarize the progress that has been made to increase our understanding of the action of TNFi on the immune system in patients. We then summarize efforts dedicated to identify biomarkers that can predict treatment responses to TNFi and we conclude with a section dedicated to the recently introduced inhibitors of IL-17A and IL-23 in SpA and related diseases. The focus of this review is on SpA, however, we also refer to RA on topics for which only limited information is available on SpA in the literature.

Prediction of drug response and adverse drug reactions: From twin studies to Next Generation Sequencing

Understanding and predicting inter-individual differences related to the success of drug therapy is of tremendous importance, both during drug development and for clinical applications. Importantly, while seminal twin studies indicate that the majority of inter-individual differences in drug disposition are driven by hereditary factors, common genetic polymorphisms explain only less than half of this genetically encoded variability. Recent progress in Next Generation Sequencing (NGS) technologies has for the first time allowed to comprehensively map the genetic landscape of human pharmacogenes. Importantly, these projects have unveiled vast numbers of rare genetic variants, which are estimated to contribute substantially to the missing heritability of drug metabolism phenotypes. However, functional interpretation of these rare variants remains challenging and constitutes one of the important frontiers of contemporary pharmacogenomics. Furthermore, NGS technologies face challenges in the interrogation of genes residing in complex genomic regions, such as CYP2D6 and HLA genes. We here provide an update of the implementation of pharmacogenomic variations in the clinical setting and present emerging strategies that facilitate the translation of NGS data into clinically useful information. Importantly, we anticipate that these developments will soon result in a paradigm shift of pre-emptive genotyping away from the interrogation to candidate variants and towards the comprehensive profiling of an individuals genotype, thus allowing for a true individualization of patient drug treatment regimens.

ANRIL regulates production of extracellular matrix proteins and vasoactive factors in diabetic complications

noncoding RNAs (lncRNAs) have gained widespread interest due to their prevailing presence in various diseases. lncRNA ANRIL (a. k. a. CDKN2B-AS1) is located on human chromosome 9 (p21.3) and transcribed in opposite direction to the INK4b-ARF-INK4a gene cluster. It has been identified as a highly susceptible region for diseases such as coronary artery diseases and type 2 diabetes. Here, we explored its regulatory role in diabetic nephropathy (DN) and diabetic cardiomyopathy (DCM) in association with epigenetic modifiers p300 and polycomb repressive complex 2 (PRC2) complex. We used an ANRIL-knockout (ANRILKO) mouse model for this study. The wild-type and ANRILKO animals with or without streptozotocin-induced diabetes were monitored for 2 min. At the end of the time point, urine and tissues were collected. The tissues were measured for fibronectin (FN), type IV collagen (Col1α4), and VEGF mRNA and protein expressions. Renal function was determined by the measurement of 24-h urine volume and albumin/creatinine ratio at euthanasia. Renal and cardiac structures were investigated using periodic acid-Schiff stain and/or immunohistochemical analysis. Elevated expressions of extracellular matrix (ECM) proteins were prevented in ANRILKO diabetic animals. Furthermore, ANRILKO had a protective effect on diabetic mouse kidneys, as evidenced by lowering of urine volume and urine albumin levels in comparison with the wild-type diabetic animals. These alterations regulated by ANRIL may be mediated by p300 and enhancer of zeste 2 (EZH2) of the PRC2 complex. Our study concludes that ANRIL regulates functional and structural alterations in the kidneys and hearts in diabetes through controlling the expressions of ECM proteins and VEGF.

The human noncoding genome defined by genetic diversity

Understanding the significance of genetic variants in the noncoding genome is emerging as the next challenge in human genomics. We used the power of 11,257 whole-genome sequences and 16,384 heptamers (7-nt motifs) to build a map of sequence constraint for the human species. This build differed substantially from traditional maps of interspecies conservation and identified regulatory elements among the most constrained regions of the genome. Using new Hi-C experimental data, we describe a strong pattern of coordination over 2 Mb where the most constrained regulatory elements associate with the most essential genes. Constrained regions of the noncoding genome are up to 52-fold enriched for known pathogenic variants as compared to unconstrained regions (21-fold when compared to the genome average). This map of sequence constraint across thousands of individuals is an asset to help interpret noncoding elements in the human genome, prioritize variants and reconsider gene units at a larger scale.

Novel tools for primary immunodeficiency diagnosis: making a case for deep profiling

PURPOSE OF REVIEW

This review gives an overview of the systems-immunology single-cell proteomic and transcriptomic approaches that can be applied to study primary immunodeficiency. It also introduces recent advances in multiparameter tissue imaging, which allows extensive immune phenotyping in disease-affected tissue.

RECENT FINDINGS

Mass cytometry is a variation of flow cytometry that uses rare earth metal isotopes instead of fluorophores as tags bound to antibodies, allowing simultaneous measurement of over 40 parameters per single-cell. Mass cytomety enables comprehensive single-cell immunophenotyping and functional assessments, capturing the complexity of the immune system, and the molecularly heterogeneous consequences of primary immunodeficiency defects. Protein epitopes and transcripts can be simultaneously detected allowing immunophenotype and gene expression evaluation in mixed cell populations. Multiplexed epitope imaging has the potential to provide extensive phenotypic characterization at the subcellular level, in the context of 3D tissue microenvironment.

SUMMARY

Mass cytometry and multiplexed epitope imaging can complement genetic methods in diagnosis and study of the pathogenesis of primary immunodeficiencies. The ability to understand the effect of a specific defect across multiple immune cell types and pathways, and in affected tissues, may provide new insight into tissue-specific disease pathogenesis and evaluate effects of therapeutic interventions.

Integrating Next-Generation Genomic Sequencing and Mass Spectrometry To Estimate Allele-Specific Protein Abundance in Human Brain

Gene expression contributes to phenotypic traits and human disease. To date, comparatively less is known about regulators of protein abundance, which is also under genetic control and likely influences clinical phenotypes. However, identifying and quantifying allele-specific protein abundance by bottom-up proteomics is challenging since single nucleotide variants (SNVs) that alter protein sequence are not considered in standard human protein databases. To address this, we developed the GenPro software and used it to create personalized protein databases (PPDs) to identify single amino acid variants (SAAVs) at the protein level from whole exome sequencing. In silico assessment of PPDs generated by GenPro revealed only a 1% increase in tryptic search space compared to a direct translation of all human transcripts and an equivalent search space compared to the UniProtKB reference database. To identify a large unbiased number of SAAV peptides, we performed high-resolution mass spectrometry-based proteomics for two human post-mortem brain samples and searched the collected MS/MS spectra against their respective PPD. We found an average of ∼117 000 unique peptides mapping to ∼9300 protein groups for each sample, and of these, 977 were unique variant peptides. We found that over 400 reference and SAAV peptide pairs were, on average, equally abundant in human brain by label-free ion intensity measurements and confirmed the absolute levels of three reference and SAAV peptide pairs using heavy labeled peptides standards coupled with parallel reaction monitoring (PRM). Our results highlight the utility of integrating genomic and proteomic sequencing data to identify sample-specific SAAV peptides and support the hypothesis that most alleles are equally expressed in human brain.

Using GWAS to identify novel therapeutic targets for osteoporosis

Osteoporosis is a common, increasingly prevalent, global health burden characterized by low bone mineral density (BMD) and increased risk of fracture. Despite its significant impact on human health, there is currently a lack of highly effective treatments free of side effects for osteoporosis. Therefore, a major goal in the field is to identify new drug targets. Genetic discovery has been shown to be effective in the unbiased identification of novel drug targets and genome-wide association studies (GWASs) have begun to provide insight into genetic basis of osteoporosis. Over the last decade, GWASs have led to the identification of ∼100 loci associated with BMD and other bone traits related to risk of fracture. However, there have been limited efforts to identify the causal genes underlying the GWAS loci or the mechanisms by which GWAS loci alter bone physiology. In this review, we summarize the current state of the field and discuss strategies for causal gene discovery and the evidence that the novel genes underlying GWAS loci are likely to be a new source of drug targets.

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits

Background

Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem.

Results

We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants.

Conclusions

XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0384-y) contains supplementary material, which is available to authorized users.

Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context.

Coronary heart disease is the leading cause of death worldwide with multiple environmental and genetic risk factors. Here the authors integrate genomic, epigenomic and transcriptomic mapping to elucidate causal variation and mechanisms of known genetic associations.

Characterisation of non-coding genetic variation in histamine receptors using AnNCR-SNP

Almost 90 % of disease-associated genetic variants found using genome wide association studies (GWAS) are located in non-coding regions of the genome. Such variants can affect phenotype by altering important regulatory elements such as promoters, enhancers or repressors, leading to changes in gene expression and consequently disease, such as thyroid cancer and allergic diseases. A number of allergy and atopy related diseases such as asthma and atopic dermatitis are related to histamine receptors; however, these diseases are not fully characterized at the molecular level. Moreover, candidate gene based studies of common variants known as single nucleotide polymorphism (SNPs) located in the coding regions of these receptors have given mixed results. It is important to complement these approaches by identifying and characterising non-coding variants in order to further elucidate the role of these receptors in disease. Here we present an analysis of histamine receptor genes using the tool AnNCR-SNP to characterise variants in non-coding genomic regions. AnNCR-SNP combines bioinformatics and experimental data sets from various sources to predict the effects of genetic variation on gene expression regulation. We find many SNPs located in areas of open chromatin, overlapping with transcription factor binding sites and associated with changes in gene expression in expression quantitative trait loci (eQTL) experiments. Here we present the results as a catalogue of non-coding variation in histamine receptor genes to aid histamine researchers in identifying putative functional SNPs found in GWAS for further validation, and to help select variants for candidate gene studies.

The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits

The Hybrid Mouse Diversity Panel (HMDP) is a collection of approximately 100 well-characterized inbred strains of mice that can be used to analyze the genetic and environmental factors underlying complex traits. While not nearly as powerful for mapping genetic loci contributing to the traits as human genome-wide association studies, it has some important advantages. First, environmental factors can be controlled. Second, relevant tissues are accessible for global molecular phenotyping. Finally, because inbred strains are renewable, results from separate studies can be integrated. Thus far, the HMDP has been studied for traits relevant to obesity, diabetes, atherosclerosis, osteoporosis, heart failure, immune regulation, fatty liver disease, and host-gut microbiota interactions. High-throughput technologies have been used to examine the genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes of the mice under various environmental conditions. All of the published data are available and can be readily used to formulate hypotheses about genes, pathways and interactions.

Genetic polymorphisms associated with overweight and obesity in uncontrolled Type 2 diabetes mellitus

Generally, obese and overweight individuals display higher free fatty acid levels, which stimulate insulin resistance. The combination of overweight or obesity with insulin resistance can trigger Type 2 diabetes mellitus (T2DM) and are primary contributing factors to the development of uncontrolled T2DM. Genetic polymorphisms also play an important role as they can impact a population's susceptibility to becoming overweight or obese and developing related chronic complications, such as uncontrolled T2DM. This review specifically examines the genetic polymorphisms associated with overweight and obesity in patients with uncontrolled T2DM. Particularly, gene polymorphisms in ADIPOQ (rs1501299 and rs17300539), LepR (rs1137101 and rs1045895), IRS2 (rs1805092), GRB14 (rs10195252 and rs3923113) and PPARG (rs1801282) have been associated with overweight and obesity in uncontrolled T2DM.

From GWAS to function: lessons from blood cells

Haematopoiesis, or the process of formation of mature blood cells from committed progenitors, represents an accessible and well-studied paradigm of cell differentiation and lineage specification. Genetic association studies provide a powerful approach to discover new genes, biological pathways and mechanisms underlying haematopoietic development. Here, we highlight recent findings of genomewide association studies (GWAS) linking 145 genomic loci to traits affecting the formation of red and white cells and platelets in European and other ancestries. We present strategies to address the main challenges in GWAS discoveries, particularly to find functional and regulatory effects of genetic variants, and to identify genes through which these genetic variants affect haematological phenotypes. We argue that studies of haematological trait variation provide an ideal paradigm for understanding the function of GWAS-associated variants owing to the accessible nature of cells, simple cellular phenotype and focused efforts to characterize the genetic and epigenetic factors influencing the regulatory landscape in highly pure mature cell populations.

The African-387 C>T TGFB1 variant is functional and associates with the ophthalmoplegic complication in juvenile myasthenia gravis

Although extraocular muscles are commonly affected by myasthenia gravis (MG) at presentation, a treatment-resistant ophthalmoplegic complication of MG (OP-MG) occurs in younger patients with African-genetic ancestry. In MG, pathogenic antibodies activate complement-mediated muscle damage and this may be potentiated in some OP-MG cases because of relative deficiency of decay-accelerating factor/CD55. Extending this argument, we hypothesized that OP-MG individuals may harbor African-specific polymorphisms in key genes influencing extraocular muscle remodeling. We screened the regulatory region of the transforming growth factor beta-1 (TGFB1) gene encoding the cytokine pivotal in muscle healing responses. We show the frequency of an African-specific polymorphism TGFB1 c.-387 T (rs11466316) among South Africans with African-genetic ancestry is higher than 1000 Genomes African controls (17.2% vs 4.8%; P<1 × 10(-7)), and associates with juvenile OP-MG (28%; P=0.043). Further, TGFB1 -387 C>T is functional because it represses the TGFB1 promoter construct basal activity by fivefold, and OP-MG fibroblasts (-387 C/T or T/T) have lower basal TGFB1 mRNA transcripts compared with controls (-387 C/C)(P=0.001). Co-transfections with Sp1 show less responsiveness of the -387 T promoter compared with wild-type -387 C (P=0.015). Our findings suggest that population-specific alleles may lower TGFB1 expression, thereby influencing OP-MG susceptibility by inhibiting extraocular muscle CD55 upregulation and/or altered endplate remodeling.

CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants

The vast majority of disease-associated single nucleotide polymorphisms (SNPs) mapped by genome-wide association studies (GWAS) are located in the non-protein coding genome, but establishing the functional and mechanistic roles of these sequence variants has proven challenging. Here, we describe a general pipeline in which candidate functional SNPs are first evaluated by fine-mapping, epigenomic profiling, and epigenome editing and then interrogated for causal function by using genome editing to create isogenic cell lines. To validate this approach, we analyzed the 6q22.1 prostate cancer risk locus and identified rs339331 as the top scoring SNP. Epigenome editing confirmed that rs339331 possessed regulatory potential. Using transcription activator-like effector nuclease (TALEN)-mediated genome-editing, we created a panel of isogenic 22Rv1 prostate cancer cell lines representing all three genotypes (TT, TC, CC) at rs339331. Introduction of the “T” risk allele increased transcription of the RFX6 gene, increased HOXB13 binding at the rs339331 region, and increased deposition of the enhancer-associated H3K4me2 histone mark at the rs339331 region. The cell lines also differed in cellular morphology and adhesion, and pathway analysis of differentially expressed genes suggested an influence of androgens. In summary, we have developed and validated a widely accessible approach to establish functional causality for non-coding sequence variants identified by GWAS.

Allele-Selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-Coding and Noncoding RNAs, and RNA Isoforms

mRNA translation into proteins is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants remains poorly understood. mRNA levels on polysomes have been shown to correlate well with expressed protein levels, pointing to polysomal loading as a critical factor. To study regulation and genetic factors of protein translation we measured levels and allelic ratios of mRNAs and ncRNAs (including microRNAs) in lymphoblast cell lines (LCL) and in polysomal fractions. We first used targeted assays to measure polysomal loading of mRNA alleles, confirming reported genetic effects on translation of OPRM1 and NAT1, and detecting no effect of rs1045642 (3435C>T) in ABCB1 (MDR1) on polysomal loading while supporting previous results showing increased mRNA turnover of the 3435T allele. Use of high-throughput sequencing of complete transcript profiles (RNA-Seq) in three LCLs revealed significant differences in polysomal loading of individual RNA classes and isoforms. Correlated polysomal distribution between protein-coding and non-coding RNAs suggests interactions between them. Allele-selective polysome recruitment revealed strong genetic influence for multiple RNAs, attributable either to differential expression of RNA isoforms or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Genes identified by different allelic RNA ratios between cytosol and polysomes were enriched with published expression quantitative trait loci (eQTLs) affecting RNA functions, and associations with clinical phenotypes. Polysomal RNA-Seq combined with allelic ratio analysis provides a powerful approach to study polysomal RNA recruitment and regulatory variants affecting protein translation.

Expression quantitative trait locus analysis for translational medicine

Expression quantitative trait locus analysis has emerged as an important component of efforts to understand how genetic polymorphisms influence disease risk and is poised to make contributions to translational medicine. Here we review how expression quantitative trait locus analysis is aiding the identification of which gene(s) within regions of association are causal for a disease or phenotypic trait; the narrowing down of the cell types or regulators involved in the etiology of disease; the characterization of drivers and modifiers of cancer; and our understanding of how different environments and cellular contexts can modify gene expression. We also introduce the concept of transcriptional risk scores as a means of refining estimates of individual liability to disease based on targeted profiling of the transcripts that are regulated by polymorphisms jointly associated with disease and gene expression.