Genome-wide interaction and pathway-based identification of key regulators in multiple myeloma.
ABSTRACT: Inherited genetic susceptibility to multiple myeloma has been investigated in a number of studies. Although 23 individual risk loci have been identified, much of the genetic heritability remains unknown. Here we carried out genome-wide interaction analyses on two European cohorts accounting for 3,999 cases and 7,266 controls and characterized genetic susceptibility to multiple myeloma with subsequent meta-analysis that discovered 16 unique interacting loci. These risk loci along with previously known variants explain 17% of the heritability in liability scale. The genes associated with the interacting loci were found to be enriched in transforming growth factor beta signaling and circadian rhythm regulation pathways suggesting immunoglobulin trait modulation, TH17 cell differentiation and bone morphogenesis as mechanistic links between the predisposition markers and intrinsic multiple myeloma biology. Further tissue/cell-type enrichment analysis associated the discovered genes with hemic-immune system tissue types and immune-related cell types indicating overall involvement in immune response.
Project description:The last decade has seen enormous progress in understanding genetic associations of systemic sclerosis to explain the observed heritability. This review highlights the most recent findings and places them in the context of proposed functional roles.Over 30 genes and gene regions have now been identified as scleroderma susceptibility loci. These include both human leukocyte antigen (HLA) and non-HLA genes, most of which involve immune-related pathways and modifiers of immune function. Many of these associations have also been reported in other systemic autoimmune diseases and suggest that there are multiple autoimmunity genes resulting in disease occurrence.In spite of these advances, only a small proportion of the heritability of systemic sclerosis has been explained. Ongoing studies include fine mapping and sequencing studies to identify causal variants, whereas other studies focus on functional consequences of these variants in order to identify the link between these genetic variants and disease susceptibility. Such knowledge should lead to more targeted and effective treatment in this disease.
Project description:Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.
Project description:So far, 23 germline susceptibility loci have been associated with multiple myeloma (MM) risk. It is unclear whether the genetic variation associated with MM susceptibility also predisposes to its precursor, monoclonal gammopathy of undetermined significance (MGUS). Leveraging 2434 MM cases, 754 MGUS cases, and 2 independent sets of controls (2567/879), we investigated potential shared genetic susceptibility of MM and MGUS by (1) performing MM and MGUS genome-wide association studies (GWAS); (2) validating the association of a polygenic risk score (PRS) based on 23 established MM loci (MM-PRS) with risk of MM, and for the first time with MGUS; and (3) examining genetic correlation of MM and MGUS. Heritability and genetic estimates yielded 17% (standard error [SE] ±0.04) and 15% (SE ±0.11) for MM and MGUS risk, respectively, and a 55% (SE ±0.30) genetic correlation. The MM-PRS was associated with risk of MM when assessed continuously (odds ratio [OR], 1.17 per SD; 95% confidence interval [CI], 1.13-1.21) or categorically (OR, 1.70; 95% CI, 1.38-2.09 for highest; OR, 0.71; 95% CI, 0.55-0.90 for lowest compared with middle quintile). The MM-PRS was similarly associated with MGUS (OR, 1.19 per SD; 95% CI, 1.14-1.26 as a continuous measure, OR, 1.77, 95%CI: 1.29-2.43 for highest and OR, 0.70, 95%CI: 0.50-0.98 for lowest compared with middle quintile). MM and MGUS associations did not differ by age, sex, or MM immunoglobulin isotype. We validated a 23-SNP MM-PRS in an independent series of MM cases and provide evidence for its association with MGUS. Our results suggest shared common genetic susceptibility to MM and MGUS.
Project description:This review looks back at five decades of research into genetic susceptibility to colorectal cancer (CRC) and the insights these studies have provided. Initial evidence of a genetic basis of CRC stems from epidemiological studies in the 1950s and is further provided by the existence of multiple dominant predisposition syndromes. Genetic linkage and positional cloning studies identified the first high-penetrance genes for CRC in the 1980s and 1990s. More recent genome-wide association studies have identified common low-penetrance susceptibility loci and provide support for a polygenic model of disease susceptibility. These observations suggest a high proportion of CRC may arise in a group of susceptible individuals as a consequence of the combined effects of common low-penetrance risk alleles and rare variants conferring moderate CRC risks. Despite these advances, however, currently identified loci explain only a small fraction of the estimated heritability to CRC. It is hoped that a new generation of sequencing projects will help explain this missing heritability.
Project description:BACKGROUND:Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS:In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p?=?1.4×10-6) and 14 (IGHV1-67 p?=?7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE:The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Project description:Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Several AIS susceptibility loci have been identified; however, they could explain only a small proportion of AIS heritability. To identify additional AIS susceptibility loci, we conduct a meta-analysis of the three genome-wide association studies consisting of 79,211 Japanese individuals. We identify 20 loci significantly associated with AIS, including 14 previously not reported loci. These loci explain 4.6% of the phenotypic variance of AIS. We find 21 cis-expression quantitative trait loci-associated genes in seven of the fourteen loci. By a female meta-analysis, we identify additional three significant loci. We also find significant genetic correlations of AIS with body mass index and uric acid. The cell-type specificity analyses show the significant heritability enrichment for AIS in multiple cell-type groups, suggesting the heterogeneity of etiology and pathogenesis of AIS. Our findings provide insights into etiology and pathogenesis of AIS.
Project description:Genome-wide association studies have identified several risk loci for multiple myeloma (MM); however, the mechanisms by which they influence MM are unknown. Here by using genetic association data and functional characterization, we demonstrate that rs4487645 G>T, the most highly associated variant (P?=?5.30 × 10-25), resides in an enhancer element 47?kb upstream of the transcription start site of c-Myc-interacting CDCA7L. The G-risk allele, associated with increased CDCA7L expression (P=1.95 × 10-36), increases IRF4 binding and the enhancer interacts with the CDCA7L promoter. We show that suppression of CDCA7L limits MM proliferation through apoptosis, and increased CDCA7L expression is associated with adverse patient survival. These findings implicate IRF4-mediated CDCA7L expression in MM biology and indicate how germline variation might confer susceptibility to MM.
Project description:Genome-wide association studies (GWASs) have identified several single-nucleotide polymorphisms (SNPs) influencing the risk of Hodgkin's lymphoma (HL) and demonstrated the association of common genetic variation for this type of cancer. Such evidence for inherited genetic risk is also provided by the family history and the very high concordance between monozygotic twins. However, little is known about the genetic and environmental contributions. A common measure for describing the phenotypic variation due to genetics is the heritability. Using GWAS data on 906 HL cases by considering all typed SNPs simultaneously, we have calculated that the common variance explained by SNPs accounts for >35% of the total variation on the liability scale in HL (95% confidence interval 6-62%). These findings are consistent with similar heritability estimates of ∼ 0.40 (95% confidence interval 0.17-0.58) based on Swedish population data. Our estimates support the underlying polygenic basis for susceptibility to HL, and show that heritability based on the population data is somehow larger than heritability based on the genomic data because of the possibility of some missing heritability in the GWAS data. Besides that there is still major evidence for multiple loci causing HL on chromosomes other than chromosome 6 that need to be detected. Because of limited findings in prior GWASs, it seems worth checking for more loci causing susceptibility to HL.
Project description:The genetic contribution to interindividual variation in common obesity has been estimated at 40-70%. Yet, despite a relatively high heritability, the search for obesity susceptibility genes has been an arduous task. This paper reviews recent progress made in the obesity genetics field with an emphasis on established obesity susceptibility loci identified through candidate gene as well as genome-wide studies. For the last 15 years, candidate gene and genome-wide linkage studies have been the two main genetic epidemiological approaches to identify genetic loci for common traits, yet progress has been slow and success limited. Only recently have candidate gene studies started to succeed; by means of large-scale studies and meta-analyses at least five variants in four candidate genes have been found to be robustly associated with obesity-related traits. Genome-wide linkage studies, however, have so far not been able to pinpoint genetic loci for common obesity. The genome-wide association approach, which has become available in recent years, has dramatically changed the pace of gene discoveries for common disease, including obesity. Three waves of large-scale high-density genome-wide association studies have already discovered at least 15 previously unanticipated genetic loci incontrovertibly associated with body mass index and extreme obesity risk. Although the combined contribution of these loci to the variation in obesity risk at the population level is small and their predictive value is typically low, these recently discovered loci are set to improve fundamentally our insights into the pathophysiology of obesity.
Project description:BACKGROUND:Genome-wide association studies have identified many susceptibility loci for obesity. However, missing heritability problem is still challenging and ignorance of genetic interactions is believed to be an important cause. Current methods for detecting interactions usually do not consider regulatory elements in non-coding regions. Interaction analyses within chromatin regulatory circuitry may identify new susceptibility loci. METHODS:We developed a pipeline named interaction analyses within chromatin regulatory circuitry (IACRC), to identify genetic interactions impacting body mass index (BMI). Potential interacting SNP pairs were obtained based on Hi-C datasets, PreSTIGE (Predicting Specific Tissue Interactions of Genes and Enhancers) algorithm, and super enhancer regions. SNP?×?SNP analyses were next performed in three GWAS datasets, including 2286 unrelated Caucasians from Kansas City, 3062 healthy Caucasians from the Gene Environment Association Studies initiative, and 3164 Hispanic subjects from the Women's Health Initiative. RESULTS:A total of 16,643,227 SNP?×?SNP analyses were performed. Meta-analyses showed that two SNP pairs, rs6808450-rs9813534 (combined P?=?2.39?×?10-9) and rs6808450-rs3773306 (combined P?=?2.89?×?10-9) were associated with BMI after multiple testing corrections. Single-SNP analyses did not detect significant association signals for these three SNPs. In obesity relevant cells, rs6808450 is located in intergenic enhancers, while rs9813534 and rs3773306 are located in the region of strong transcription regions of CAND2 and RPL32, respectively. The expression of CAND2 was significantly downregulated after the differentiation of human Simpson-Golabi-Behmel syndrome (SGBS) preadipocyte cells (P?=?0.0241). Functional validation in the International Mouse Phenotyping Consortium database showed that CAND2 was associated with increased lean body mass and decreased total body fat amount. CONCLUSIONS:Detecting epistasis within chromatin regulatory circuitry identified CAND2 as a novel obesity susceptibility gene. We hope IACRC could facilitate the interaction analyses for complex diseases and offer new insights into solving the missing heritability problem.