Genetic Basis of Common Human Disease: Insight into the Role of Missense SNPs from Genome-Wide Association Studies

The gasdermins: a pore-forming protein family expressed in the epidermis

Gasdermins comprise a family of pore-forming proteins, which play critical roles in (auto)inflammatory diseases and cancer. They are expressed as self-inhibited precursor proteins consisting of an aminoterminal cytotoxic effector domain (NT-GSDM) and a carboxyterminal inhibitor domain (GSDM-CT) separated by an unstructured linker region. Proteolytic processing in the linker region liberates NT-GSDM, which translocates to membranes, forms oligomers, and induces membrane permeabilization, which can disturb the cellular equilibrium that can lead to cell death. Gasdermin activation and pore formation are associated with inflammation, particularly when induced by the inflammatory protease caspase-1 upon inflammasome activation. These gasdermin pores allow the release of the pro-inflammatory cytokines interleukin(IL)-1β and IL-18 and induce a lytic type of cell death, termed pyroptosis that supports inflammation, immunity, and tissue repair. However, even at the cellular level, the consequences of gasdermin activation are diverse and range from induction of programmed cell death - pyroptosis or apoptosis - to poorly characterized protective mechanisms. The specific effects of gasdermin activation can vary between species, cell types, the membrane that is being permeabilized (plasma membrane, mitochondrial membrane, etc.), and the overall biological state of the local tissue/cells. In epithelia, gasdermins seem to play crucial roles. Keratinocytes represent the main cell type of the epidermis, which is the outermost skin layer with an essential barrier function. Compared to other tissues, keratinocytes express all members of the gasdermin family, in part in a differentiation-specific manner. That raises questions regarding the specific roles of individual GSDM family members in the skin, the mechanisms and consequences of their activation, and the potential crosstalk between them. In this review, we summarize the current knowledge about gasdermins with a focus on keratinocytes and the skin and discuss the possible roles of the different family members in immunity and disease.

Novel start codons introduce novel coding sequences in the human genomes

Start-gain mutations can introduce novel start codons and generate novel coding sequences that may affect the function of genes. In this study, we systematically investigated the novel start codons that were either polymorphic or fixed in the human genomes. 829 polymorphic start-gain SNVs were identified in the human populations, and the novel start codons introduced by these SNVs have significantly higher activity in translation initiation. Some of these start-gain SNVs were reported to be associated with phenotypes and diseases in previous studies. By comparative genomic analysis, we found 26 human-specific start codons that were fixed after the divergence between the human and chimpanzee, and high-level translation initiation activity was observed on them. The negative selection signal was detected in the novel coding sequences introduced by these human-specific start codons, indicating the important function of these novel coding sequences.

Gasdermins assemble; recent developments in bacteriology and pharmacology

The discovery of gasdermin D (GSDMD) as the terminal executioner of pyroptosis provided a large piece of the cell death puzzle, whilst simultaneously and firmly putting the gasdermin family into the limelight. In its purest form, GSDMD provides a connection between the innate alarm systems to an explosive, inflammatory form of cell death to jolt the local environment into immunological action. However, the gasdermin field has moved rapidly and significantly since the original seminal work and novel functions and mechanisms have been recently uncovered, particularly in response to infection. Gasdermins regulate and are regulated by mechanisms such as autophagy, metabolism and NETosis in fighting pathogen and protecting host. Importantly, activators and interactors of the other gasdermins, not just GSDMD, have been recently elucidated and have opened new avenues for gasdermin-based discovery. Key to this is the development of potent and specific tool molecules, so far a challenge for the field. Here we will cover some of these recently discovered areas in relation to bacterial infection before providing an overview of the pharmacological landscape and the challenges associated with targeting gasdermins.

Facial Skin Microbiome: Aging-Related Changes and Exploratory Functional Associations with Host Genetic Factors, a Pilot Study

In this exploratory study, we investigate the variation in the facial skin microbiome architecture through aging and their functional association with host genetic factors in a cohort of healthy women, living in the same area and without cutaneous diseases. Notably, facial skin microbiota (SM) samples were collected from a cohort of 15 healthy Caucasian females, firstly divided into three age groups (younger women aged 20–35 years old; middle aged women of 36–52 years old; and older women aged 53–68 years old). Then, the recruited cohort was divided into two groups based on their facial hydration level (dry and normal skin). The facial SM revealed a different composition in the three analyzed aging groups and between normal and dry skins. The middle-aged women also revealed functional variations associated with collagen biosynthesis and oxidative stress damage repair. Otherwise, the association between selected host SNPs (single nucleotide polymorphisms) and the facial SM profile showed significant associations, suggesting a negative correlation with collagen metabolism and ROS damage protection. Finally, the composition and functionality of the facial SM seemed to affect the aging process through the two aging-correlated pathways of host ROS damage repair and collagen metabolism. Our exploratory data could be useful for future studies characterizing the structure, function, and dynamics of the SM in the aging process to design personalized therapeutic agents focusing on potential genomic targets, microbes, and their metabolites.

The enigmatic roles of epithelial gasdermin B: Recent discoveries and controversies

Gasdermin B (GSDMB) belongs to a family of structurally related proteins [(i.e., gasdermins (GSDMs)]. It distinguishes itself from other members by the lack of autoinhibition but clear bioactivity of its full-length form, its preference to bind to phosphatidylinositol phosphates and sulfatides, and the ability to promote both lytic and nonlytic cellular functions. It is the only gasdermin that lacks a mouse ortholog, making in vivo mechanistic studies challenging to perform. GSDMB is abundantly expressed in epithelial cells lining organs that directly interface with the external environment, such as the gastrointestinal tract, with emerging evidence supporting its role in enteric infections, inflammatory bowel disease (IBD), and colorectal cancer. This review discusses the unique features of GSDMB among other gasdermin family members and controversies surrounding GSDMB-dependent mammalian inflammatory cell death (i.e., pyroptosis), including recent discoveries revealing both lytic and nonlytic functions of epithelial-derived GSDMB, particularly during gut health and disease.

Dynamic insights into the effects of nonsynonymous polymorphisms (nsSNPs) on loss of TREM2 function

Single nucleotide variations in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) are associated with many neurodegenerative diseases, including Nasu-Hakola disease (NHD), frontotemporal dementia (FTD), and late-onset Alzheimer's disease because they disrupt ligand binding to the extracellular domain of TREM2. However, the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) in TREM2 on disease progression remain unknown. In this study, we identified several high-risk nsSNPs in the TREM2 gene using various deleterious SNP predicting algorithms and analyzed their destabilizing effects on the ligand recognizing region of the TREM2 immunoglobulin (Ig) domain by molecular dynamics (MD) simulation. Cumulative prediction by all tools employed suggested the three most deleterious nsSNPs involved in loss of TREM2 function are rs549402254 (W50S), rs749358844 (R52C), and rs1409131974 (D104G). MD simulation showed that these three variants cause substantial structural alterations and conformational remodeling of the apical loops of the TREM2 Ig domain, which is responsible for ligand recognition. Detailed analysis revealed that these variants substantially increased distances between apical loops and induced conformation remodeling by changing inter-loop nonbonded contacts. Moreover, all nsSNPs changed the electrostatic potentials near the putative ligand-interacting region (PLIR), which suggested they might reduce specificity or loss of binding affinity for TREM2 ligands. Overall, this study identifies three potential high-risk nsSNPs in the TREM2 gene. We propose further studies on the molecular mechanisms responsible for loss of TREM2 function and the associations between TREM2 nsSNPs and neurodegenerative diseases.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

Incorporating regulatory interactions into gene-set analyses for GWAS data: A controlled analysis with the MAGMA tool

To date, genome-wide association studies have identified thousands of statistically-significant associations between genetic variants, and phenotypes related to a myriad of traits and diseases. A key goal for human-genetics research is to translate these associations into functional mechanisms. Popular gene-set analysis tools, like MAGMA, map variants to genes they might affect, and then integrate genome-wide association study data (that is, variant-level associations for a phenotype) to score genes for association with a phenotype. Gene scores are subsequently used in competitive gene-set analyses to identify biological processes that are enriched for phenotype association. By default, variants are mapped to genes in their proximity. However, many variants that affect phenotypes are thought to act at regulatory elements, which can be hundreds of kilobases away from their target genes. Thus, we explored the idea of augmenting a proximity-based mapping scheme with publicly-available datasets of regulatory interactions. We used MAGMA to analyze genome-wide association study data for ten different phenotypes, and evaluated the effects of augmentation by comparing numbers, and identities, of genes and gene sets detected as statistically significant between mappings. We detected several pitfalls and confounders of such “augmented analyses”, and introduced ways to control for them. Using these controls, we demonstrated that augmentation with datasets of regulatory interactions only occasionally strengthened the enrichment for phenotype association amongst (biologically-relevant) gene sets for different phenotypes. Still, in such cases, genes and regulatory elements responsible for the improvement could be pinpointed. For instance, using brain regulatory-interactions for augmentation, we were able to implicate two acetylcholine receptor subunits involved in post-synaptic chemical transmission, namely CHRNB2 and CHRNE, in schizophrenia. Collectively, our study presents a critical approach for integrating regulatory interactions into gene-set analyses for genome-wide association study data, by introducing various controls to distinguish genuine results from spurious discoveries.

Enzyme Inhibitors: The Best Strategy to Tackle Superbug NDM-1 and Its Variants

Multidrug bacterial resistance endangers clinically effective antimicrobial therapy and continues to cause major public health problems, which have been upgraded to unprecedented levels in recent years, worldwide. β-Lactam antibiotics have become an important weapon to fight against pathogen infections due to their broad spectrum. Unfortunately, the emergence of antibiotic resistance genes (ARGs) has severely astricted the application of β-lactam antibiotics. Of these, New Delhi metallo-β-lactamase-1 (NDM-1) represents the most disturbing development due to its substrate promiscuity, the appearance of variants, and transferability. Given the clinical correlation of β-lactam antibiotics and NDM-1-mediated resistance, the discovery, and development of combination drugs, including NDM-1 inhibitors, for NDM-1 bacterial infections, seems particularly attractive and urgent. This review summarizes the research related to the development and optimization of effective NDM-1 inhibitors. The detailed generalization of crystal structure, enzyme activity center and catalytic mechanism, variants and global distribution, mechanism of action of existing inhibitors, and the development of scaffolds provides a reference for finding potential clinically effective NDM-1 inhibitors against drug-resistant bacteria.

Deep structure of DNA for genomic analysis

Recent advances in next generation sequencing, deep networks and other bioinformatic tools have enabled us to mine huge amount of genomic information about living organisms in the post-microarray era. However, these tools do not explicitly factor in the role of the underlying DNA biochemistry (particularly, DNA hybridization) essential to life processes. Here, we focus more precisely on the role that DNA hybridization plays in determining properties of biological organisms at the macro-level. We illustrate its role with solutions to challenging problems in human disease. These solutions are made possible by novel structural properties of DNA hybridization landscapes revealed by a metric model of oligonucleotides of a common length that makes them reminiscent of some planets in our solar system, particularly earth and saturn. They allow a judicious selection of so-called noncrosshybridizing (nxh) bases that offer substantial reduction of DNA sequences of arbitrary length into a few informative features. The quality assessment of the information extracted by them is high because of their very low Shannon Entropy, i.e. they minimize the degree of uncertainty in hybridization that makes results on standard microarrays irreproducible. For example, SNP classification (pathogenic/nonpathogenic) and pathogen identification can be solved with high sensitivity (~77%/100%) and specificity (~92%/100%, respectively) for combined taxa on a sample of over 264 fully coding sequences in whole bacterial genomes and fungal mitochondrial genomes using machine learning (ML) models. These methods can be applied to several other interesting research questions that could be addressed with similar genomic analyses.

Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein-protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein-protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.

Computational analysis of deleterious single nucleotide polymorphisms in catechol O-Methyltransferase conferring risk to post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is one of the prevalent neurological disorder which is drawing increased attention over the past few decades. Major risk factors for PTSD can be categorized into environmental and genetic factors. Among the genetic risk factors, polymorphisms in the catechol-O-methyltransferase (COMT) gene is known to be associated with the risk for PTSD. In the present study, we analysed the impact of deleterious single nucleotide polymorphisms (SNPs) in the COMT gene conferring risk to PTSD using computational based approaches followed by molecular dynamic simulations. The data on COMT gene associated with PTSD were collected from several databases including Online Mendelian Inheritance in Man (OMIM) search. Datasets related to SNP were downloaded from the dbSNP database. To study the structural and dynamic effects of COMT wild type and mutant forms, we performed molecular dynamics simulations (MD simulations) at a time scale of 300 ns. Results from screening the SNPs using the computational tools SIFT and Polyphen-2 demonstrated that the SNP rs4680 (V158M) in COMT has a deleterious effect with phenotype in PTSD. Results from the MD simulations showed that there is some major fluctuations in the structural features including root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuation (RMSF) and secondary structural elements including α-helices, sheets and turns between wild-type (WT) and mutant forms of COMT protein. In conclusion, our study provides novel insights into the deleterious effects and impact of V158M mutation on COMT protein structure which plays a key role in PTSD.

MIF promoter polymorphism increases peripheral blood expression levels, contributing to increased susceptibility and poor prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world. The etiology and pathogenesis of HCC remain unclear. Macrophage migration inhibitory factor (MIF) plays a critical role in the pathogenesis of hepatocellular carcinoma. The association between MIF polymorphisms and its expression level in HCC has rarely been demonstrated. In the present study, the peripheral blood of 202 patients with HCC (HCC group), 242 patients with chronic hepatitis B (CHB group), 215 patients with liver cirrhosis (LC group) and 227 healthy volunteers (normal group) were collected, DNA was extracted and the target fragment of MIF gene was amplified using PCR. The products were then sequenced, and the expression levels of MIF protein were tested using ELISA. The results showed that the MIF rs755622 polymorphism was associated with an increased susceptibility and metastasis of HCC, and that the genotypes GC and CC were associated with poor prognosis of HCC. Compared with the normal, CHB and LC groups, the expression of MIF in the peripheral blood of the HCC group was significantly increased, and the high expression was associated with to poor prognosis. In the HCC group, MIF protein levels for genotypes GC and CC were increased compared with those of genotype GG. The current study indicated that the MIF rs755622 polymorphism is associated with susceptibility and metastasis of HCC, and that the GC and CC genotypes may be indicators of poor prognosis, which may be ascribed to the MIF rs755622 polymorphism leading to elevated MIF protein expression in peripheral blood.

Mapping the degradation pathway of a disease-linked aspartoacylase variant

Canavan disease is a severe progressive neurodegenerative disorder that is characterized by swelling and spongy degeneration of brain white matter. The disease is genetically linked to polymorphisms in the aspartoacylase (ASPA) gene, including the substitution C152W. ASPA C152W is associated with greatly reduced protein levels in cells, yet biophysical experiments suggest a wild-type like thermal stability. Here, we use ASPA C152W as a model to investigate the degradation pathway of a disease-causing protein variant. When we expressed ASPA C152W in Saccharomyces cerevisiae, we found a decreased steady state compared to wild-type ASPA as a result of increased proteasomal degradation. However, molecular dynamics simulations of ASPA C152W did not substantially deviate from wild-type ASPA, indicating that the native state is structurally preserved. Instead, we suggest that the C152W substitution interferes with the de novo folding pathway resulting in increased proteasomal degradation before reaching its stable conformation. Systematic mapping of the protein quality control components acting on misfolded and aggregation-prone species of C152W, revealed that the degradation is highly dependent on the molecular chaperone Hsp70, its co-chaperone Hsp110 as well as several quality control E3 ubiquitin-protein ligases, including Ubr1. In addition, the disaggregase Hsp104 facilitated refolding of aggregated ASPA C152W, while Cdc48 mediated degradation of insoluble ASPA protein. In human cells, ASPA C152W displayed increased proteasomal turnover that was similarly dependent on Hsp70 and Hsp110. Our findings underscore the use of yeast to determine the protein quality control components involved in the degradation of human pathogenic variants in order to identify potential therapeutic targets.

Folliculin variants linked to Birt-Hogg-Dubé syndrome are targeted for proteasomal degradation

Germline mutations in the folliculin (FLCN) tumor suppressor gene are linked to Birt-Hogg-Dubé (BHD) syndrome, a dominantly inherited genetic disease characterized by predisposition to fibrofolliculomas, lung cysts, and renal cancer. Most BHD-linked FLCN variants include large deletions and splice site aberrations predicted to cause loss of function. The mechanisms by which missense variants and short in-frame deletions in FLCN trigger disease are unknown. Here, we present an integrated computational and experimental study that reveals that the majority of such disease-causing FLCN variants cause loss of function due to proteasomal degradation of the encoded FLCN protein, rather than directly ablating FLCN function. Accordingly, several different single-site FLCN variants are present at strongly reduced levels in cells. In line with our finding that FLCN variants are protein quality control targets, several are also highly insoluble and fail to associate with the FLCN-binding partners FNIP1 and FNIP2. The lack of FLCN binding leads to rapid proteasomal degradation of FNIP1 and FNIP2. Half of the tested FLCN variants are mislocalized in cells, and one variant (ΔE510) forms perinuclear protein aggregates. A yeast-based stability screen revealed that the deubiquitylating enzyme Ubp15/USP7 and molecular chaperones regulate the turnover of the FLCN variants. Lowering the temperature led to a stabilization of two FLCN missense proteins, and for one (R362C), function was re-established at low temperature. In conclusion, we propose that most BHD-linked FLCN missense variants and small in-frame deletions operate by causing misfolding and degradation of the FLCN protein, and that stabilization and resulting restoration of function may hold therapeutic potential of certain disease-linked variants. Our computational saturation scan encompassing both missense variants and single site deletions in FLCN may allow classification of rare FLCN variants of uncertain clinical significance.

GSDMB promotes non-canonical pyroptosis by enhancing caspase-4 activity

Gasdermin B (GSDMB) has been reported to be associated with immune diseases in humans, but the detailed molecular mechanisms remain unsolved. The N-terminus of GSDMB by itself, unlike other gasdermin family proteins, does not induce cell death. Here, we show that GSDMB is highly expressed in the leukocytes of septic shock patients, which is associated with increased release of the gasdermin D (GSDMD) N-terminus. GSDMB expression and the accumulation of the N-terminal fragment of GSDMD are induced by the activation of the non-canonical pyroptosis pathway in a human monocyte cell line. The downregulation of GSDMB alleviates the cleavage of GSDMD and cell death. Consistently, the overexpression of GSDMB promotes GSDMD cleavage, accompanied by increased LDH release. We further found that GSDMB promotes caspase-4 activity, which is required for the cleavage of GSDMD in non-canonical pyroptosis, by directly binding to the CARD domain of caspase-4. Our study reveals a GSDMB-mediated novel regulatory mechanism for non-canonical pyroptosis and suggests a potential new strategy for the treatment of inflammatory diseases.

Recommendations on Collecting and Storing Samples for Genetic Studies in Hearing and Tinnitus Research

Objectives:

Research on the genetic basis of tinnitus is still in its first steps. A group of scientists dedicated to tinnitus genetics within European Tinnitus Network (TINNET) network recognize that further progress requires multicenter collaborative efforts for defining contributing genes. The purpose of the present work is to provide instructions regarding collection, processing, storage, and shipment of samples intended for genetic studies in auditory research.

Design:

One part of the recommendations has a general character; another part is of particular importance for auditory healthcare practitioners such as otolaryngology physicians, audiologists, and general practitioners.

Results:

We provide a set of instructions and various options for obtaining samples. We give advice regarding sample processing, storage, and shipment and define the minimal and essential clinical information that should accompany the samples collected for genetic processing.

Conclusions:

These recommendations offer a basis to standardize and optimize collaborations between geneticists and healthcare practitioners specialized in tinnitus and hearing disorders.

Biophysical and Mechanistic Models for Disease-Causing Protein Variants

The rapid decrease in DNA sequencing cost is revolutionizing medicine and science. In medicine, genome sequencing has revealed millions of missense variants that change protein sequences, yet we only understand the molecular and phenotypic consequences of a small fraction. Within protein science, high-throughput deep mutational scanning experiments enable us to probe thousands of variants in a single, multiplexed experiment. We review efforts that bring together these topics via experimental and computational approaches to determine the consequences of missense variants in proteins. We focus on the role of changes in protein stability as a driver for disease, and how experiments, biophysical models, and computation are providing a framework for understanding and predicting how changes in protein sequence affect cellular protein stability.

CXCL12 and CXCR4 polymorphisms and expressions in peripheral blood from patients of hepatocellular carcinoma

AIM

To determine if CXCL12 (rs1801157) and CXCR4 (rs2228014) polymorphisms are associated with hepatocellular carcinoma (HCC) susceptibility, and detect their expressions in peripheral blood.

METHODS

206 HCC patients, 252 chronic hepatitis B patients, 221 liver cirrhosis patients and 275 healthy volunteers were recruited. Genes CXCL12 and CXCR4 were amplified and genotyped. Their expression in peripheral blood were detected.

RESULTS

CXCL12 rs1801157 and CXCR4 rs2228014 polymorphisms were associated with increased susceptibility of HCC, and genotypes GA/AA and CT/TT may be risk factors of HCC (all p < 0.05). Expressions of CXCL12 and CXCR4 in peripheral blood from HCC patients increased significantly (p < 0.05).

CONCLUSION

CXCL12 and CXCR4 polymorphisms may be risk factors for HCC, and they may be potential HCC markers.

Absence of specific alternatively spliced exon of CD44 in macrophages prevents colitis

CD44 is a transmembrane molecule appearing in numerous isoforms generated by insertions of alternatively spliced variant exons (CD44v) and having various binding partners. CD44v7 on T cells was proposed to promote colitis by preventing T-cell apoptosis. Here we demonstrate that Cd44v7-deficient T cells - like Cd44 wild-type (Cd44^WT) T cells - provoked disease in two different colitis models: the model induced by CD4⁺CD45RB^high T-cell transfer into Rag2-deficient mice and a new model based on ovalbumin (OVA)-specific T-cell transfer into Rag-sufficient, OVA-challenged mice. In contrast, CD44v7 absence on macrophages in recipient mice prevented colitis. Prevention was associated with the downregulation of signal transducer and activator of transcription 3 (STAT3)-activating and Foxp3-counteracting interleukin-6 (IL-6), lower numbers of phospho-STAT3-containing lymphocytes, and higher Foxp3⁺ T-cell counts in the colon. Consequently, the protected colons showed lower IL-12, IL-1β expression, and decreased interferon-γ levels. Importantly, stimulation of T cells by Cd44v7-deficient macrophages induced upregulation of Foxp3 in vitro, while cotransfer of Cd44^WT macrophages into Cd44v7-deficient mice reduced Foxp3⁺ T-cell counts and caused colitis. Accordingly, the CD44v7 ligand osteopontin, whose levels were elevated in Crohn's disease, specifically induced IL-6 in human monocytes, a cytokine also increased in these patients. We suggest macrophage-specific targeting of the CD44v7 pathway as a novel therapeutic option for Crohn's disease.

Target highlights from the first post-PSI CASP experiment (CASP12, May-August 2016)

The functional and biological significance of the selected CASP12 targets are described by the authors of the structures. The crystallographers discuss the most interesting structural features of the target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP12 experiment.

A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.

Consensus Genome-Wide Expression Quantitative Trait Loci and Their Relationship with Human Complex Trait Disease

Most of the risk loci identified from genome-wide association (GWA) studies do not provide direct information on the biological basis of a disease or on the underlying mechanisms. Recent expression quantitative trait locus (eQTL) association studies have provided information on genetic factors associated with gene expression variation. These eQTLs might contribute to phenotype diversity and disease susceptibility, but interpretation is handicapped by low reproducibility of the expression results. To address this issue, we have generated a set of consensus eQTLs by integrating publicly available data for specific human populations and cell types. Overall, we find over 4000 genes that are involved in high-confidence eQTL relationships. To elucidate the role that eQTLs play in human common diseases, we matched the high-confidence eQTLs to a set of 335 disease risk loci identified from the Wellcome Trust Case Control Consortium GWA study and follow-up studies for 7 human complex trait diseases-bipolar disorder (BD), coronary artery disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type 1 diabetes (T1D), and type 2 diabetes (T2D). The results show that the data are consistent with ∼50% of these disease loci arising from an underlying expression change mechanism.

Spatial distribution of disease-associated variants in three-dimensional structures of protein complexes

Next-generation sequencing enables simultaneous analysis of hundreds of human genomes associated with a particular phenotype, for example, a disease. These genomes naturally contain a lot of sequence variation that ranges from single-nucleotide variants (SNVs) to large-scale structural rearrangements. In order to establish a functional connection between genotype and disease-associated phenotypes, one needs to distinguish disease drivers from neutral passenger variants. Functional annotation based on experimental assays is feasible only for a limited number of candidate mutations. Thus alternative computational tools are needed. A possible approach to annotating mutations functionally is to consider their spatial location relative to functionally relevant sites in three-dimensional (3D) structures of the harboring proteins. This is impeded by the lack of available protein 3D structures. Complementing experimentally resolved structures with reliable computational models is an attractive alternative. We developed a structure-based approach to characterizing comprehensive sets of non-synonymous single-nucleotide variants (nsSNVs): associated with cancer, non-cancer diseases and putatively functionally neutral. We searched experimentally resolved protein 3D structures for potential homology-modeling templates for proteins harboring corresponding mutations. We found such templates for all proteins with disease-associated nsSNVs, and 51 and 66% of proteins carrying common polymorphisms and annotated benign variants. Many mutations caused by nsSNVs can be found in protein–protein, protein–nucleic acid or protein–ligand complexes. Correction for the number of available templates per protein reveals that protein–protein interaction interfaces are not enriched in either cancer nsSNVs, or nsSNVs associated with non-cancer diseases. Whereas cancer-associated mutations are enriched in DNA-binding proteins, they are rarely located directly in DNA-interacting interfaces. In contrast, mutations associated with non-cancer diseases are in general rare in DNA-binding proteins, but enriched in DNA-interacting interfaces in these proteins. All disease-associated nsSNVs are overrepresented in ligand-binding pockets, and nsSNVs associated with non-cancer diseases are additionally enriched in protein core, where they probably affect overall protein stability.

CAGI4 Crohn's exome challenge: Marker SNP versus exome variant models for assigning risk of Crohn disease

Understanding the basis of complex trait disease is a fundamental problem in human genetics. The CAGI Crohn's Exome challenges are providing insight into the adequacy of current disease models by requiring participants to identify which of a set of individuals has been diagnosed with the disease, given exome data. For the CAGI4 round, we developed a method that used the genotypes from exome sequencing data only to impute the status of genome wide association studies marker SNPs. We then used the imputed genotypes as input to several machine learning methods that had been trained to predict disease status from marker SNP information. We achieved the best performance using Naïve Bayes and with a consensus machine learning method, obtaining an area under the curve of 0.72, larger than other methods used in CAGI4. We also developed a model that incorporated the contribution from rare missense variants in the exome data, but this performed less well. Future progress is expected to come from the use of whole genome data rather than exomes.

Ensemble variant interpretation methods to predict enzyme activity and assign pathogenicity in the CAGI4 NAGLU (Human N-acetyl-glucosaminidase) and UBE2I (Human SUMO-ligase) challenges

CAGI (Critical Assessment of Genome Interpretation) conducts community experiments to determine the state of the art in relating genotype to phenotype. Here, we report results obtained using newly developed ensemble methods to address two CAGI4 challenges: enzyme activity for population missense variants found in NAGLU (Human N-acetyl-glucosaminidase) and random missense mutations in Human UBE2I (Human SUMO E2 ligase), assayed in a high-throughput competitive yeast complementation procedure. The ensemble methods are effective, ranked second for SUMO-ligase and third for NAGLU, according to the CAGI independent assessors. However, in common with other methods used in CAGI, there are large discrepancies between predicted and experimental activities for a subset of variants. Analysis of the structural context provides some insight into these. Post-challenge analysis shows that the ensemble methods are also effective at assigning pathogenicity for the NAGLU variants. In the clinic, providing an estimate of the reliability of pathogenic assignments is the key. We have also used the NAGLU dataset to show that ensemble methods have considerable potential for this task, and are already reliable enough for use with a subset of mutations.

Gene polymorphism linked to increased asthma and IBD risk alters gasdermin-B structure, a sulfatide and phosphoinositide binding protein

The exact function of human gasdermin-B (GSDMB), which regulates differentiation and growth of epithelial cells, is yet to be elucidated. In human epidermal growth factor receptor 2 (HER2)-positive breast cancer, GSDMB gene amplification and protein overexpression indicate a poor response to HER2-targeted therapy. Genome-wide association studies revealed a correlation between GSDMB SNPs and an increased susceptibility to Crohn's disease, ulcerative colitis, and asthma. The N- and C-terminal domains of all gasdermins possess lipid-binding and regulatory activities, respectively. Inflammatory caspases cleave gasdermin-D in the interdomain linker but not GSDMB. The cleaved N-terminal domain binds phosphoinositides and cardiolipin, forms membrane-disrupting pores, and executes pyroptosis. We show that both full-length GSDMB and the N-terminal domain bind to nitrocellulose membranes immobilized with phosphoinositides or sulfatide, but not with cardiolipin. In addition, the GSDMB N-terminal domain binds liposomes containing sulfatide. The crystal structure of the GSDMB C-terminal domain reveals the structural impact of the amino acids encoded by SNPs that are linked to asthma and inflammatory bowel disease (IBD). A loop that carries the polymorphism amino acids corresponding to healthy individuals (Gly299:Pro306) exhibits high conformational flexibility, whereas the loop carrying amino acids found in individuals with increased disease risk (Arg299:Ser306) exhibits a well-defined conformation and higher positive surface charge. Apoptotic executioner caspase-3, -6, and -7, but not the inflammatory caspases, cleave GSDMB at 88DNVD91 within the N-terminal domain. Selective sulfatide binding may indicate possible function for GSDMB in the cellular sulfatide transport.

The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)

The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (www.ebi.ac.uk/gwas/), ontology supported search functionality and an improved curation interface. These developments have improved the data release frequency by increasing automation of curation and providing scaling improvements. The range of available Catalog data has also been extended with structured ancestry and recruitment information added for all studies. The infrastructure improvements also support scaling for larger arrays, exome and sequencing studies, allowing the Catalog to adapt to the needs of evolving study design, genotyping technologies and user needs in the future.

Large scale analysis of protein stability in OMIM disease related human protein variants

Background

Modern genomic techniques allow to associate several Mendelian human diseases to single residue variations in different proteins. Molecular mechanisms explaining the relationship among genotype and phenotype are still under debate. Change of protein stability upon variation appears to assume a particular relevance in annotating whether a single residue substitution can or cannot be associated to a given disease. Thermodynamic properties of human proteins and of their disease related variants are lacking. In the present work, we take advantage of the available three dimensional structure of human proteins for predicting the role of disease related variations on the perturbation of protein stability.

Results

We develop INPS3D, a new predictor based on protein structure for computing the effect of single residue variations on protein stability (ΔΔG), scoring at the state-of-the-art (Pearson’s correlation value of the regression is equal to 0.72 with mean standard error of 1.15 kcal/mol on a blind test set comprising 351 variations in 60 proteins). We then filter 368 OMIM disease related proteins known with atomic resolution (where the three dimensional structure covers at least 70 % of the sequence) with 4717 disease related single residue variations and 685 polymorphisms without clinical consequence. We find that the effect on protein stability of disease related variations is larger than the effect of polymorphisms: in particular, by setting to |1 kcal/mol| the threshold between perturbing and not perturbing variations of the protein stability, about 44 % of disease related variations and 20 % of polymorphisms are predicted with |ΔΔG| > 1 kcal/mol, respectively. A consistent fraction of OMIM disease related variations is however predicted to promote |ΔΔG| ≤ 1 kcal/mol and we focus here on detecting features that can be associated to the thermodynamic property of the protein variant. Our analysis reveals that some 47 % of disease related variations promoting |ΔΔG| ≤ 1 are located in solvent exposed sites of the protein structure. We also find that the increase of the fraction of variations that in proteins are predicted with |ΔΔG| ≤ 1 kcal/mol, partially relates with the increasing number of the protein interacting partners, corroborating the notion that disease related, non-perturbing variations are likely to impair protein-protein interaction (70 % of the disease causing variations, with high accessible surface are indeed predicted in interacting sites). The set of OMIM surface accessible variations with |ΔΔG| ≤ 1 kcal/mol and located in interaction sites are 23 % of the total in 161 proteins. Among these, 43 proteins with some 327 disease causing variations are involved in signalling, structural biological processes, development and differentiation.

Conclusions

We compute the effect of disease causing variations on protein stability with INPS3D, a new state-of-the-art tool for predicting the change in ΔΔG value associated to single residue substitution in protein structures.  The analysis indicates that OMIM disease related variations in proteins promote a much larger effect on protein stability than polymorphisms non-associated to diseases. Disease related variations with a slight effect on protein stability (|ΔΔG| < 1 kcal/mol) frequently occur at the protein accessible surface suggesting that they are located in protein-protein interactions patches in putative human biological functional networks. The hypothesis is corroborated by proving that proteins with many disease related variations that slightly perturb protein stability are on average more connected in the human physical interactome (IntAct) than proteins with variations predicted with |ΔΔG| > 1 kcal/mol. 

Inference of domain-disease associations from domain-protein, protein-disease and disease-disease relationships

Background

Protein domains can be viewed as portable units of biological function that defines the functional properties of proteins. Therefore, if a protein is associated with a disease, protein domains might also be associated and define disease endophenotypes. However, knowledge about such domain-disease relationships is rarely available. Thus, identification of domains associated with human diseases would greatly improve our understandingof the mechanism of human complex diseases and further improve the prevention, diagnosis and treatment of these diseases.

Methods

Based on phenotypic similarities among diseases, we first group diseases into overlapping modules. We then develop a framework to infer associations between domains and diseases through known relationships between diseases and modules, domains and proteins, as well as proteins and disease modules. Different methods including Association, Maximum likelihood estimation (MLE), Domain-disease pair exclusion analysis (DPEA), Bayesian, and Parsimonious explanation (PE) approaches are developed to predict domain-disease associations.

Results

We demonstrate the effectiveness of all the five approaches via a series of validation experiments, and show the robustness of the MLE, Bayesian and PE approaches to the involved parameters. We also study the effects of disease modularization in inferring novel domain-disease associations. Through validation, the AUC (Area Under the operating characteristic Curve) scores for Bayesian, MLE, DPEA, PE, and Association approaches are 0.86, 0.84, 0.83, 0.83 and 0.79, respectively, indicating the usefulness of these approaches for predicting domain-disease relationships. Finally, we choose the Bayesian approach to infer domains associated with two common diseases, Crohn’s disease and type 2 diabetes.

Conclusions

The Bayesian approach has the best performance for the inference of domain-disease relationships. The predicted landscape between domains and diseases provides a more detailed view about the disease mechanisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0247-y) contains supplementary material, which is available to authorized users.

Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease

BACKGROUND

There are now over 2000 loci in the human genome where genome wide association studies (GWAS) have found one or more SNPs to be associated with altered risk of a complex trait disease. At each of these loci, there must be some molecular level mechanism relevant to the disease. What are these mechanisms and how do they contribute to disease?

RESULTS

Here we consider the roles of three primary mechanism classes: changes that directly alter protein function (missense SNPs), changes that alter transcript abundance as a consequence of variants close-by in sequence, and changes that affect splicing. Missense SNPs are divided into those predicted to have a high impact on in vivo protein function, and those with a low impact. Splicing is divided into SNPs with a direct impact on splice sites, and those with a predicted effect on auxiliary splicing signals. The analysis was based on associations found for seven complex trait diseases in the classic Wellcome Trust Case Control Consortium (WTCCC1) GWA study and subsequent studies and meta-analyses, collected from the GWAS catalog. Linkage disequilibrium information was used to identify possible candidate SNPs for involvement in disease mechanism in each of the 356 loci associated with these seven diseases. With the parameters used, we find that 76% of loci have at least of these mechanisms. Overall, except for the low incidence of direct impact on splice sites, the mechanisms are found at similar frequencies, with changes in transcript abundance the most common. But the distribution of mechanisms over diseases varies markedly, as does the fraction of loci with assigned mechanisms. Many of the implicated proteins have previously been suggested as relevant, but the specific mechanism assignments are new. In addition, a number of new disease relevant proteins are proposed.

CONCLUSIONS

The high fraction of GWAS loci with proposed mechanisms suggests that these classes of mechanism play a major role. Other mechanism types, such as variants affecting expression of genes remote in the DNA sequence, will contribute in other loci. Each of the identified putative mechanisms provides a hypothesis for further investigation.