An Osteoporosis Risk SNP at 1p36.12 Acts as an Allele-Specific Enhancer to Modulate LINC00339 Expression via Long-Range Loop Formation

Genome-wide association studies (GWASs) have reproducibly associated variants within intergenic regions of 1p36.12 locus with osteoporosis, but the functional roles underlying these noncoding variants are unknown. Through an integrative functional genomic and epigenomic analyses, we prioritized rs6426749 as a potential causal SNP for osteoporosis at 1p36.12. Dual-luciferase assay and CRISPR/Cas9 experiments demonstrate that rs6426749 acts as a distal allele-specific enhancer regulating expression of a lncRNA (LINC00339) (∼360 kb) via long-range chromatin loop formation and that this loop is mediated by CTCF occupied near rs6426749 and LINC00339 promoter region. Specifically, rs6426749-G allele can bind transcription factor TFAP2A, which efficiently elevates the enhancer activity and increases LINC00339 expression. Downregulation of LINC00339 significantly increases the expression of CDC42 in osteoblast cells, which is a pivotal regulator involved in bone metabolism. Our study provides mechanistic insight into how a noncoding SNP affects osteoporosis by long-range interaction, a finding that could indicate promising therapeutic targets for osteoporosis.

Phenome-wide investigation of the causal associations between childhood BMI and adult trait outcomes: a two-sample Mendelian randomization study

Background

Childhood obesity is reported to be associated with the risk of many diseases in adulthood. However, observational studies cannot fully account for confounding factors. We aimed to systematically assess the causal associations between childhood body mass index (BMI) and various adult traits/diseases using two-sample Mendelian randomization (MR).

Methods

After data filtering, 263 adult traits genetically correlated with childhood BMI (P < 0.05) were subjected to MR analyses. Inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods were used to estimate the causal effects. Multivariable MR analysis was performed to test whether the effects of childhood BMI on adult traits are independent from adult BMI.

Results

We identified potential causal effects of childhood obesity on 60 adult traits (27 disease-related traits, 27 lifestyle factors, and 6 other traits). Higher childhood BMI was associated with a reduced overall health rating (β = − 0.10, 95% CI − 0.13 to − 0.07, P = 6.26 × 10⁻¹¹). Specifically, higher childhood BMI was associated with increased odds of coronary artery disease (OR = 1.09, 95% CI 1.06 to 1.11, P = 4.28 × 10⁻¹¹), essential hypertension (OR = 1.12, 95% CI 1.08 to 1.16, P = 1.27 × 10⁻¹¹), type 2 diabetes (OR = 1.36, 95% CI 1.30 to 1.43, P = 1.57 × 10⁻³⁴), and arthrosis (OR = 1.09, 95% CI 1.06 to 1.12, P = 8.80 × 10⁻⁹). However, after accounting for adult BMI, the detrimental effects of childhood BMI on disease-related traits were no longer present (P > 0.05). For dietary habits, different from conventional understanding, we found that higher childhood BMI was associated with low calorie density food intake. However, this association might be specific to the UK Biobank population.

Conclusions

In summary, we provided a phenome-wide view of the effects of childhood BMI on adult traits. Multivariable MR analysis suggested that the associations between childhood BMI and increased risks of diseases in adulthood are likely attributed to individuals remaining obese in later life. Therefore, ensuring that childhood obesity does not persist into later life might be useful for reducing the detrimental effects of childhood obesity on adult diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00865-3.

Naringenin regulates production of matrix metalloproteinases in the knee-joint and primary cultured articular chondrocytes and alleviates pain in rat osteoarthritis model

Inflammation of cartilage is a primary symptom for knee-joint osteoarthritis. Matrix metalloproteinases (MMPs) are known to play an important role in the articular cartilage destruction related to osteoarthritis. Naringenin is a plant-derived flavonoid known for its anti-inflammatory properties. We studied the effect of naringenin on the transcriptional expression, secretion and enzymatic activity of MMP-3 in vivo in the murine monosodium iodoacetate (MIA) osteoarthritis model. The assessment of pain behavior was also performed in the MIA rats. The destruction of knee-joint tissues was analyzed microscopically. Moreover, the effect of naringenin was also studied in vitro in IL-1β activated articular chondrocytes. The transcriptional expression of MMP-3, MMP-1, MMP-13, thrombospondin motifs (ADAMTS-4) and ADAMTS-5 was also studied in primary cultured chondrocytes of rats. Naringenin caused significant reduction in pain behavior and showed marked improvement in the tissue morphology of MIA rats. Moreover, a significant inhibition of MMP-3 expression in MIA rats was observed upon treatment with naringenin. In the in vitro tests, naringenin caused a significant reduction in the transcriptional expression, secretion and enzymatic activity of the studied degradative enzymes. The NF-κB pathway was also found to be inhibited upon treatment with naringenin in vitro. Overall, the study suggests that naringenin alleviated pain and regulated the production of matrix-metalloproteinases via regulation of NF-κB pathway. Thus, naringenin could be a potent therapeutic option for the treatment of osteoarthritis.

Associations of Plasma FGF2 Levels and Polymorphisms in the FGF2 Gene with Obesity Phenotypes in Han Chinese Population

Obesity is highly heritable, but the specific genes influencing obesity related traits are largely unknown. Fibroblast growth factor 2 (FGF2) could influence adipocyte differentiation. However, the association of FGF2 polymorphisms and obesity remains unclear. This study aimed to investigate the associations of both the plasma FGF2 levels and SNPs in FGF2 gene with obesity phenotypes in Han Chinese populations. Plasma FGF2 levels were measured and subjected to association analyses in 62 subjects. Eleven SNPs in FGF2 were genotyped and tested for associations in a discovery sample of 1,300 subjects. SNPs significantly associated with obesity were subjected to replication in another independent sample of 1,035 subjects. We found that plasma FGF2 levels were positively correlated with fat mass (P = 0.010). Association analyses in the discovery sample identified three SNPs (rs1449683, rs167428, rs308442) significantly associated with fat mass after multiple testing adjustments (P < 0.0045). Subsequent replication study successfully validated one SNP (rs167428) associated with fat mass (P_combine = 3.46 × 10⁻⁵). eQTL analyses revealed that SNPs associated with obesity also affected FGF2 expression. Our findings suggested that high plasma FGF2 level correlated with increased risk of obesity, and FGF2 gene polymorphisms could affect individual variances of obesity in Han Chinese population.

Association between fibroblast growth factor 21 and bone mineral density in adults

PURPOSE

Animal-based studies have reported a decrease in bone mass resulting from high level of fibroblast growth factor 21 (FGF21). However, the correlation between plasma FGF21 levels and bone mineral density (BMD) is paradoxical in previous human-based studies, and the associations between FGF21 gene polymorphisms and BMD haven't been reported yet. Therefore, here, we evaluated plasma FGF21 levels with sufficient study samples, and performed genetic association test to reveal the physiological and genetic role of FGF21 on BMD in adults.

METHODS

Plasma and genetic samples containing 168 and 569 Han Chinese subjects, respectively, were employed in this study. Fasting plasma FGF21 levels were determined using enzyme-linked immunosorbent assay (ELISA). Regional BMD values were measured by dual energy X-ray absorptiometry (DXA). Five variants of FGF21 gene were successfully genotyped.

RESULTS

Physiological association suggested that plasma FGF21 levels were inversely correlated with BMD in femoral neck (Neck-BMD: P = 0.039) and Ward's triangle (Ward's-BMD: P = 0.002) of hip region. A FGF21 gene variant, rs490942, was significantly associated with the increase of Ward's-BMD in total (P = 0.027) and female (P = 0.016) cohorts, as well as Neck-BMD in female cohort (P = 7.45 × 10^-3). Meanwhile, eQTL results indicated that this SNP was related to the decreased level of FGF21 gene expression.

CONCLUSIONS

Taking together from both physiological and genetic levels, we suggest that FGF21 is inversely associated with regional BMD. And we haven't observed sex-specific effect in this study.

Comprehensive functional annotation of susceptibility SNPs prioritized 10 genes for schizophrenia

Nearly 95% of susceptibility SNPs identified by genome-wide association studies (GWASs) are located in non-coding regions, which causes a lot of difficulty in deciphering their biological functions on disease pathogenesis. Here, we aimed to conduct a comprehensive functional annotation for all the schizophrenia susceptibility loci obtained from GWASs. Considering varieties of epigenomic regulatory elements, we annotated all 22,688 acquired susceptibility SNPs according to their genomic positions to obtain functional SNPs. The comprehensive annotation indicated that these functional SNPs are broadly involved in diverse biological processes. Histone modification enrichment showed that H3K27ac, H3K36me3, H3K4me1, and H3K4me3 were related to the development of schizophrenia. Transcription factors (TFs) prediction, methylation quantitative trait loci (meQTL) analyses, expression quantitative trait loci (eQTL) analyses, and proteomic quantitative trait loci analyses (pQTL) identified 447 target protein-coding genes. Subsequently, differential expression analyses between schizophrenia cases and controls, nervous system phenotypes from mouse models, and protein-protein interaction with known schizophrenia-related pathways and genes were carried out with our target genes. We finaly prioritized 10 target genes for schizophrenia (CACNA1C, CLU, CSNK2B, GABBR1, GRIN2A, MAPK3, NOTCH4, SRR, TNF, and SYNGAP1). Our results may serve as an encyclopedia of schizophrenia susceptibility SNPs and offer holistic guides for post-GWAS functional experiments.

Lineage-specific rearrangement of chromatin loops and epigenomic features during adipocytes and osteoblasts commitment

Human mesenchymal stem cells (hMSCs) can be differentiated into adipocytes and osteoblasts. The processes are driven by the rewiring of chromatin architectures and transcriptomic/epigenomic changes. Here, we induced hMSCs to adipogenic and osteogenic differentiation, and performed 2 kb resolution Hi-C experiments for chromatin loops detection. We also generated matched RNA-seq, ChIP-seq and ATAC-seq data for integrative analysis. After comprehensively comparing adipogenesis and osteogenesis, we quantitatively identified lineage-specific loops and screened out lineage-specific enhancers and open chromatin. We reveal that lineage-specific loops can activate gene expression and facilitate cell commitment through combining enhancers and accessible chromatin in a lineage-specific manner. We finally proposed loop-mediated regulatory networks and identified the controlling factors for adipocytes and osteoblasts determination. Functional experiments validated the lineage-specific regulation networks towards IRS2 and RUNX2 that are associated with adipogenesis and osteogenesis, respectively. These results are expected to help better understand the chromatin conformation determinants of hMSCs fate commitment.

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

Despite genome-wide association studies (GWASs) have identified many susceptibility genes for osteoporosis, it still leaves a large part of missing heritability to be discovered. Integrating regulatory information and GWASs could offer new insights into the biological link between the susceptibility SNPs and osteoporosis. We generated five machine learning classifiers with osteoporosis-associated variants and regulatory features data. We gained the optimal classifier and predicted genome-wide SNPs to discover susceptibility regulatory variants. We further utilized Genetic Factors for Osteoporosis Consortium (GEFOS) and three in-house GWASs samples to validate the associations for predicted positive SNPs. The random forest classifier performed best among all machine learning methods with the F1 score of 0.8871. Using the optimized model, we predicted 37,584 candidate SNPs for osteoporosis. According to the meta-analysis results, a list of regulatory variants was significantly associated with osteoporosis after multiple testing corrections and contributed to the expression of known osteoporosis-associated protein-coding genes. In summary, combining GWASs and regulatory elements through machine learning could provide additional information for understanding the mechanism of osteoporosis. The regulatory variants we predicted will provide novel targets for etiology research and treatment of osteoporosis.

Epigenetic Element-Based Transcriptome-Wide Association Study Identifies Novel Genes for Bipolar Disorder

Since the bipolar disorder (BD) signals identified by genome-wide association study (GWAS) often reside in the non-coding regions, understanding the biological relevance of these genetic loci has proven to be complicated. Transcriptome-wide association studies (TWAS) providing a powerful approach to identify novel disease risk genes and uncover possible causal genes at loci identified previously by GWAS. However, these methods did not consider the importance of epigenetic regulation in gene expression. Here, we developed a novel epigenetic element-based transcriptome-wide association study (ETWAS) that tested the effects of genetic variants on gene expression levels with the epigenetic features as prior and further mediated the association between predicted expression and BD. We conducted an ETWAS consisting of 20 352 cases and 31 358 controls and identified 44 transcriptome-wide significant hits. We found 14 conditionally independent genes, and 10 genes that did not previously implicate with BD were regarded as novel candidate genes, such as ASB16 in the cerebellar hemisphere (P = 9.29 × 10-8). We demonstrated that several genome-wide significant signals from the BD GWAS driven by genetically regulated expression, and NEK4 explained 90.1% of the GWAS signal. Additionally, ETWAS identified genes could explain heritability beyond that explained by GWAS-associated SNPs (P = 5.60 × 10-66). By querying the SNPs in the final models of identified genes in phenome databases, we identified several phenotypes previously associated with BD, such as schizophrenia and depression. In conclusion, ETWAS is a powerful method, and we identified several novel candidate genes associated with BD.

Genetic analysis identifies DDR2 as a novel gene affecting bone mineral density and osteoporotic fractures in Chinese population

DDR2 gene, playing an essential role in regulating osteoblast differentiation and chondrocyte maturation, may influence bone mineral density (BMD) and osteoporosis, but the genetic variations actually leading to the association remain to be elucidated. Therefore, the aim of this study was to investigate whether the genetic variants in DDR2 are associated with BMD and fracture risk. This study was performed in three samples from two ethnicities, including 1,300 Chinese Han subjects, 700 Chinese Han subjects (350 with osteoporotic hip fractures and 350 healthy controls) and 2,286 US white subjects. Twenty-eight SNPs in DDR2 were genotyped and tested for associations with hip BMD and fractures. We identified 3 SNPs in DDR2 significantly associated with hip BMD in the Chinese population after multiple testing adjustments, which were rs7521233 (P = 1.06×10-4, β: -0.018 for allele C), rs7553831 (P = 1.30×10-4, β: -0.018 for allele T), and rs6697469 (P = 1.59×10-3, β: -0.015 for allele C), separately. These three SNPs were in high linkage disequilibrium. Haplotype analyses detected two significantly associated haplotypes, including one haplotype in block 2 (P = 9.54×10-4, β: -0.016) where these three SNPs located. SNP rs6697469 was also associated with hip fractures (P = 0.043, OR: 1.42) in the Chinese population. The effect on fracture risk was consistent with its association with lower BMD. However, in the white population, we didn't observe significant associations with hip BMD. eQTL analyses revealed that SNPs associated with BMD also affected DDR2 mRNA expression levels in Chinese. Our findings, together with the prior biological evidence, suggest that DDR2 could be a new candidate for osteoporosis in Chinese population. Our results also reveal an ethnic difference, which highlights the need for further genetic studies in each ethnic group.

Association analyses of FGFR2 gene polymorphisms with femoral neck bone mineral density in Chinese Han population

Femoral neck (FN) bone mineral density (BMD) is the most important risk phenotype for osteoporosis and has been used as a reference standard for describing osteoporosis. Identification of genetic variations associated with FN BMD may provide potential targets for therapeutic studies. Given the important biological role of FGFR2 gene involved in bone, we tested the associations between FGFR2 polymorphisms and FN BMD in 1,300 Chinese Han subjects. Of the 28 total SNPs, 2 SNPs, namely rs11200014 and rs1078806, were significantly associated with FN BMD under dominant model (P = 0.0014 and 0.0012, respectively) after conservative Bonferroni correction. The two SNPs were in complete linkage disequilibrium. In addition, haplotype-based association tests identified two haplotypes significantly associated with FN BMD, including one haplotype in block 4 where the two SNPs located. However, different from previous studies in white older men, we did not detect any significant association in sex-stratified analyses. In summary, our findings suggest that the FGFR2 gene may play an important role in variation in FN BMD in Chinese Han population, independent of gender effects. Further studies performed in multiple and large samples are needed to elucidate the underlying molecular mechanism and pathophysiology of osteoporosis.

An Osteoporosis Susceptibility Allele at 11p15 Regulates SOX6 Expression by Modulating TCF4 Chromatin Binding

Osteoporosis is an age-related complex disease clinically diagnosed with bone mineral density (BMD). Although several genomewide association studies (GWASs) have discovered multiple noncoding genetic variants at 11p15 influencing osteoporosis risk, the functional mechanisms of these variants remain unknown. Through integrating bioinformatics and functional experiments, a potential functional single-nucleotide polymorphism (SNP; rs1440702) located in an enhancer element was identified and the A allele of rs1440702 acted as an allelic specificities enhancer to increase its distal target gene SOX6 (~600 Kb upstream) expression, which plays a key role in bone formation. We also validated this long-range regulation via conducting chromosome conformation capture (3C) assay. Furthermore, we demonstrated that SNP rs1440702 with a risk allele (rs1440702-A) could increase the activity of the enhancer element by altering the binding affinity of the transcription factor TCF4, resulting in the upregulation expression of SOX6 gene. Collectively, our integrated analyses revealed how the noncoding genetic variants (rs1440702) affect osteoporosis predisposition via long-range gene regulatory mechanisms and identified its target gene SOX6 for downstream biomarker and drug development. © 2022 American Society for Bone and Mineral Research (ASBMR).

Detecting epistasis within chromatin regulatory circuitry reveals CAND2 as a novel susceptibility gene for obesity

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.

Modeling circRNA expression pattern with integrated sequence and epigenetic features demonstrates the potential involvement of H3K79me2 in circRNA expression

MOTIVATION

CircRNAs are an abundant class of non-coding RNAs with widespread, cell-/tissue-specific patterns. Previous work suggested that epigenetic features might be related to circRNA expression. However, the contribution of epigenetic changes to circRNA expression has not been investigated systematically. Here, we built a machine learning framework named CIRCScan, to predict circRNA expression in various cell lines based on the sequence and epigenetic features.

RESULTS

The predicted accuracy of the expression status models was high with area under the curve of receiver operating characteristic (ROC) values of 0.89-0.92 and the false-positive rates of 0.17-0.25. Predicted expressed circRNAs were further validated by RNA-seq data. The performance of expression-level prediction models was also good with normalized root-mean-square errors of 0.28-0.30 and Pearson's correlation coefficient r over 0.4 in all cell lines, along with Spearman's correlation coefficient ρ of 0.33-0.46. Noteworthy, H3K79me2 was highly ranked in modeling both circRNA expression status and levels across different cells. Further analysis in additional nine cell lines demonstrated a significant enrichment of H3K79me2 in circRNA flanking intron regions, supporting the potential involvement of H3K79me2 in circRNA expression regulation.

AVAILABILITY AND IMPLEMENTATION

The CIRCScan assembler is freely available online for academic use at https://github.com/johnlcd/CIRCScan.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression

The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.

Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis

The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.

Systematic functional characterization of non-coding regulatory SNPs associated with central obesity

Central obesity is associated with higher risk of developing a wide range of diseases independent of overall obesity. Genome-wide association studies (GWASs) have identified more than 300 susceptibility loci associated with central obesity. However, the functional understanding of these loci is limited by the fact that most loci are in non-coding regions. To address this issue, our study first prioritized 2,034 single-nucleotide polymorphisms (SNPs) based on fine-mapping and epigenomic annotation analysis. Subsequently, we employed self-transcribing active regulatory region sequencing (STARR-seq) to systematically evaluate the enhancer activity of these prioritized SNPs. The resulting data analysis identified 141 SNPs with allelic enhancer activity. Further analysis of allelic transcription factor (TF) binding prioritized 20 key TFs mediating the central-obesity-relevant genetic regulatory network. Finally, as an example, we illustrate the molecular mechanisms of how rs8079062 acts as an allele-specific enhancer to regulate the expression of its targeted RNF157. We also evaluated the role of RNF157 in the adipogenic differentiation process. In conclusion, our results provide an important resource for understanding the genetic regulatory mechanisms underlying central obesity.