Regulatory element-based prediction identifies new susceptibility regulatory variants for osteoporosis

Enhancer-Gene Interaction Analyses Identified the Epidermal Growth Factor Receptor as a Susceptibility Gene for Type 2 Diabetes Mellitus

Background

Genetic interactions are known to play an important role in the missing heritability problem for type 2 diabetes mellitus (T2DM). Interactions between enhancers and their target genes play important roles in gene regulation and disease pathogenesis. In the present study, we aimed to identify genetic interactions between enhancers and their target genes associated with T2DM.

Methods

We performed genetic interaction analyses of enhancers and protein-coding genes for T2DM in 2,696 T2DM patients and 3,548 controls of European ancestry. A linear regression model was used to identify single nucleotide polymorphism (SNP) pairs that could affect the expression of the protein-coding genes. Differential expression analyses were used to identify differentially expressed susceptibility genes in diabetic and nondiabetic subjects.

Results

We identified one SNP pair, rs4947941×rs7785013, significantly associated with T2DM (combined P=4.84×10-10). The SNP rs4947941 was annotated as an enhancer, and rs7785013 was located in the epidermal growth factor receptor (EGFR) gene. This SNP pair was significantly associated with EGFR expression in the pancreas (P=0.033), and the minor allele "A" of rs7785013 decreased EGFR gene expression and the risk of T2DM with an increase in the dosage of "T" of rs4947941. EGFR expression was significantly upregulated in T2DM patients, which was consistent with the effect of rs4947941×rs7785013 on T2DM and EGFR expression. A functional validation study using the Mouse Genome Informatics (MGI) database showed that EGFR was associated with diabetes-relevant phenotypes.

Conclusion

Genetic interaction analyses of enhancers and protein-coding genes suggested that EGFR may be a novel susceptibility gene for T2DM.

A promising biomarker of elevated galanin level in hypothalamus for osteoporosis risk in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) and osteoporosis are two major healthcare problems worldwide. T2DM is considered to be a risk factor for osteoporosis. Interestingly, several epidemiological studies suggest that bone abnormalities associated with diabetes may differ, at least in part, from those associated with senile or post-menopausal osteoporosis. The growing prevalence that patients with T2DM simultaneously suffer from osteoporosis, puts forward the importance to discuss the relationship between both diseases, as well as to investigate correlative agents to treat them. Emerging evidences demonstrate that neuropeptide galanin is involved in the pathogenesis of T2DM and osteoporosis. Galanin via activation of central GALR2 increases insulin sensitivity as well as bone density and mass in animal models. The disorder of galanin function plays major role in development of both diseases. Importantly, galanin signaling is indispensable for ΔFosB, an AP1 antagonist, to play the bone mass-accruing effects in the ventral hypothalamic neurons of diabetic models. This review summarizes our and other recent studies to provide a new insight into the multivariate relationship among galanin, T2DM and osteoporosis, highlighting the beneficial effect of galanin on the comorbid state of both diseases. These may help us better understanding the pathogenesis of osteoporosis and T2DM and provide useful clues for further inquiry if elevated galanin level may be taken as a biomarker for both conjoint diseases, and GALR2 agonist may be taken as a novel therapeutic strategy to treat both diseases concurrently.

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell-specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes (NFKB1 and SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.

A road map for understanding molecular and genetic determinants of osteoporosis

Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and genomics'. In this Review, we highlight findings from genome-wide association studies and studies using various omics technologies individually to identify mechanisms of osteoporosis. Furthermore, we summarize current studies of data integration to understand, diagnose and inform the treatment of osteoporosis. The integration of multiple technologies will provide a road map to illuminate the complex pathogenesis of osteoporosis, especially from molecular functional aspects, in vivo in humans.

Sex-specific SNP-SNP interaction analyses within topologically associated domains reveals ANGPT1 as a novel tumor suppressor gene for lung cancer

Genetic interaction has been recognized to be an important cause of the missing heritability. The topologically associating domain (TAD) is a self-interacting genomic region, and the DNA sequences within a TAD physically interact with each other more frequently. Sex differences influence cancer susceptibility at the genetic level. Here, we performed both regular and sex-specific genetic interaction analyses within TAD to identify susceptibility genes for lung cancer in 5204 lung cancer patients and 7389 controls. We found that one SNP pair, rs4262299-rs1654701, was associated with lung cancer in women after multiple testing corrections (combined P = 8.52 × 10^-9 ). Single-SNP analyses did not detect significant association signals for these two SNPs. Both identified SNPs are located in the intron region of ANGPT1. We further found that 5% of nonsmall cell lung cancer patients have an alteration in ANGPT1, indicated the potential role of ANGPT1 in the neoplastic progression in lung cancer. The expression of ANGPT1 was significantly down-regulated in patients in lung squamous cell carcinoma and lung adenocarcinoma. We checked the interaction effect on the ANGPT1 expression and lung cancer and found that the minor allele "G" of rs1654701 increased ANGPT1 gene expression and decreased lung cancer risk with the increased dosage of "A" of rs4262299, which consistent with the tumor suppressor function of ANGPT1. Survival analyses found that the high expression of ANGPT1 was individually associated with a higher survival probability in lung cancer patients. In summary, our results suggest that ANGPT1 may be a novel tumor suppressor gene for lung cancer.

Postmenopausal Osteoporosis reference genes for qPCR expression assays

Osteoporosis (OP) is a multifactorial disease influenced by genetic factors in more than half of the cases. In spite of the efforts to clarify the relationship among genetic factors and susceptibility to develop OP, many genetic associations need to be further functionally validated. Besides, some limitations as the choice of stably expressed reference genes (RG) should be overcome to ensure the quality and reproducibility of gene expression assays. To our knowledge, a validation study for RG in OP is still missing. We compared the expression levels, using polymerase chain reaction quantitative real time (qPCR) of 10 RG (G6PD, B2M, GUSB, HSP90, EF1A, RPLP0, GAPDH, ACTB, 18 S and HPRT1) to assess their suitability in OP analysis by using GeNorm, Normfinder, BestKeeper and RefFinder programs. A minimal number of two RG was recommended by GeNorm to obtain a reliable normalization. RPLP0 and B2M were identified as the most stable genes in OP studies while ACTB, 18 S and HPRT1 were inadequate for normalization in our data set. Moreover, we showed the dramatic effects of suboptimal RG choice on the quantification of a target gene, highlighting the importance in the identification of the most appropriate reference gene to specific diseases. We suggest the use of RPLP0 and B2M as the most stable reference genes while we do not recommend the use of the least stable reference genes HPRT1, 18 S and ACTB in OP expression assays using PBMC as biological source. Additionally, we emphasize the importance of individualized and careful choice in software and reference genes selection.

Functional characterization of the C7ORF76 genomic region, a prominent GWAS signal for osteoporosis in 7q21.3

Genome-wide association studies (GWAS) have repeatedly identified genetic variants associated with bone mineral density (BMD) and osteoporotic fracture in non-coding regions of C7ORF76, a poorly studied gene of unknown function. The aim of the present study was to elucidate the causality and molecular mechanisms underlying the association. We re-sequenced the genomic region in two extreme BMD groups from the BARCOS cohort of postmenopausal women to search for functionally relevant variants. Eight selected variants were tested for association in the complete cohort and 2 of them (rs4342521 and rs10085588) were found significantly associated with lumbar spine BMD and nominally associated with osteoporotic fracture. cis-eQTL analyses of these 2 SNPs, together with SNP rs4727338 (GWAS lead SNP in Estrada et al., Nat Genet. 44:491-501, 2012), performed in human primary osteoblasts, disclosed a statistically significant influence on the expression of the proximal neighbouring gene SLC25A13 and a tendency on the distal SHFM1. We then studied the functionality of a putative upstream regulatory element (UPE), containing rs10085588. Luciferase reporter assays showed transactivation capability with a strong allele-dependent effect. Finally, 4C-seq experiments in osteoblastic cell lines showed that the UPE interacted with different tissue-specific enhancers and a lncRNA (LOC100506136) in the region. In summary, this study is the first one to analyse in depth the functionality of C7ORF76 genomic region. We provide functional regulatory evidence for the rs10085588, which may be a causal SNP within the 7q21.3 GWAS signal for osteoporosis.

Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine

Elucidation of the systems biology foundation underlying the effect of Fangji, which are multi-herbal traditional Chinese medicine (TCM) formulas, is one of the major aims in the field. The numerous bioactive ingredients of a Fangji deal with the multiple targets of a complex disease, which is influenced by a number of genes and their interactions with the environment. Genome-wide association study (GWAS) is an unbiased approach for dissecting the genetic variants underlying complex diseases and individual response to a given treatment. GWAS has great potential for the study of systems biology from the point of view of genomics, but the capacity using current analysis models is largely handicapped, as evidenced by missing heritability. Recent development of a full genetic model, in which gene-gene interactions (dominance and epistasis) and gene-environment interactions are all considered, has addressed these problems. This approach has been demonstrated to substantially increase model power, remarkably improving the detection of association of GWAS and the construction of the molecular architecture. This analysis does not require a very large sample size, which is often difficult to meet for a GWAS of treatment response. Furthermore, this analysis can integrate other omic information and allow for variations of Fangji, which is very promising for Fangjiomic study and detection of the sophisticated molecular architecture of the function of Fangji, as well as for the delineation of the systems biology of personalized medicine in TCM in an unbiased and comprehensive manner.