Multiparameter spectral CT-based radiomics in predicting the expression of programmed death ligand 1 in non-small-cell lung cancer

AIM

To explore the value of radiomics for predicting the expression of programmed death ligand 1 (PD-L1) in non-small-cell lung cancer (NSCLC) based on multiparameter spectral computed tomography (CT) images.

MATERIALS AND METHODS

A total of 220 patients with NSCLC were enrolled retrospectively and divided into the training (n=176) and testing (n=44) cohorts. The radiomics features were extracted from the conventional CT images, mono-energy 40 keV images, iodine density (ID) maps, Z-effective maps, and electron density maps. The logistic regression (LR) and support vector machine (SVM) algorithms were employed to build models based on radiomics signatures. The prediction abilities were qualified by the area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve. Internal validation was performed on the independent testing dataset.

RESULTS

The combined model for PD-L1 ≥1%, which consisted of the radiomics score (rad-score; p<0.0001), white blood cell (WBC; p=0.027) counts, and air bronchogram (p=0.003), reached the highest performance with the AUCs of 0.873 and 0.917 in the training and testing dataset, respectively, which was better than the radiomics model with the AUCs of 0.842 and 0.886. The combined model for PD-L1 ≥50%, which consisted of rad-score (p<0.0001) and WBC counts (p=0.027), achieved the highest performance in the training and testing dataset with AUCs of 0.932 and 0.903, respectively, which was better than the radiomics model with AUCs of 0.920 and 0.892, respectively.

CONCLUSION

The radiomics model based on the multiparameter images of spectral CT can predict the expression level of PD-L1 in NSCLC. The combined model can obtain higher prediction efficiency and serves as a promising method for immunotherapy selection.

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.

The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis

BACKGROUND

Growing evidence indicates that dynamic changes in gut microbiome can affect intelligence; however, whether these relationships are causal remains elusive. We aimed to disentangle the poorly understood causal relationship between gut microbiota and intelligence.

METHODS

We performed a 2-sample Mendelian randomization (MR) analysis using genetic variants from the largest available genome-wide association studies of gut microbiota (N = 18,340) and intelligence (N = 269,867). The inverse-variance weighted method was used to conduct the MR analyses complemented by a range of sensitivity analyses to validate the robustness of the results. Considering the close relationship between brain volume and intelligence, we applied 2-step MR to evaluate whether the identified effect was mediated by regulating brain volume (N = 47,316).

RESULTS

We found a risk effect of the genus Oxalobacter on intelligence (odds ratio = 0.968 change in intelligence per standard deviation increase in taxa; 95% CI, 0.952-0.985; p = 1.88 × 10-4) and a protective effect of the genus Fusicatenibacter on intelligence (odds ratio = 1.053; 95% CI, 1.024-1.082; p = 3.03 × 10-4). The 2-step MR analysis further showed that the effect of genus Fusicatenibacter on intelligence was partially mediated by regulating brain volume, with a mediated proportion of 33.6% (95% CI, 6.8%-60.4%; p = .014).

CONCLUSIONS

Our results provide causal evidence indicating the role of the microbiome in intelligence. Our findings may help reshape our understanding of the microbiota-gut-brain axis and development of novel intervention approaches for preventing cognitive impairment.

Mechanism of Efferocytosis in Determining Ischaemic Stroke Resolution-Diving into Microglia/Macrophage Functions and Therapeutic Modality

After ischaemic cerebral vascular injury, efferocytosis-a process known as the efficient clearance of apoptotic cells (ACs) by various phagocytes in both physiological and pathological states-is crucial for maintaining central nervous system (CNS) homeostasis and regaining prognosis. The mechanisms of efferocytosis in ischaemic stroke and its influence on preventing inflammation progression from secondary injury were still not fully understood, despite the fact that the fundamental process of efferocytosis has been described in a series of phases, including AC recognition, phagocyte engulfment, and subsequent degradation. The genetic reprogramming of macrophages and brain-resident microglia after an ischaemic stroke has been equated by some researchers to that of the peripheral blood and brain. Based on previous studies, some molecules, such as signal transducer and activator of transcription 6 (STAT6), peroxisome proliferator-activated receptor γ (PPARG), CD300A, and sigma non-opioid intracellular receptor 1 (SIGMAR1), were discovered to be largely associated with aspects of apoptotic cell elimination and accompanying neuroinflammation, such as inflammatory cytokine release, phenotype transformation, and suppressing of antigen presentation. Exacerbated stroke outcomes are brought on by defective efferocytosis and improper modulation of pertinent signalling pathways in blood-borne macrophages and brain microglia, which also results in subsequent tissue inflammatory damage. This review focuses on recent researches which contain a number of recently discovered mechanisms, such as studies on the relationship between benign efferocytosis and the regulation of inflammation in ischaemic stroke, the roles of some risk factors in disease progression, and current immune approaches that aim to promote efferocytosis to treat some autoimmune diseases. Understanding these pathways provides insight into novel pathophysiological processes and fresh characteristics, which can be used to build cerebral ischaemia targeting techniques.

A landscape of gene expression regulation for synovium in arthritis

The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Assessment of bidirectional relationships between brain imaging-derived phenotypes and stroke: a Mendelian randomization study

BACKGROUND

Stroke is a major cause of mortality and long-term disability worldwide. Whether the associations between brain imaging-derived phenotypes (IDPs) and stroke are causal is uncertain.

METHODS

We performed two-sample bidirectional Mendelian randomization (MR) analyses to explore the causal associations between IDPs and stroke. Summary data of 587 brain IDPs (up to 33,224 individuals) from the UK Biobank and five stroke types (sample size range from 301,663 to 446,696, case number range from 5,386 to 40,585) from the MEGASTROKE consortium were used.

RESULTS

Forward MR indicated 14 IDPs belong to projection fibers or association fibers were associated with stroke. For example, higher genetically determined mean diffusivity (MD) in the right external capsule was causally associated with an increased risk of small vessel stroke (IVW OR = 2.76, 95% CI 2.07 to 3.68, P = 5.87 × 10^-12). Reverse MR indicated that genetically determined higher risk of any ischemic stroke was associated with increased isotropic or free water volume fraction (ISOVF) in body of corpus callosum (IVW β = 0.23, 95% CI 0.14 to 0.33, P = 3.22 × 10^-7). This IDP is a commissural fiber and it is not included in the IDPs identified by forward MR.

CONCLUSIONS

We identified 14 IDPs with statistically significant evidence of causal effects on stroke or stroke subtypes. We also identified potential causal effects of stroke on one IDP of commissural fiber. These findings might guide further work toward identifying preventative strategies at the brain imaging levels.

Mitochondrial RNA editing sites affect the phylogenetic reconstruction of gymnosperms

•RNA editing sites may contain homoplasious signals that cause artifactual inferences in phylogenetic analyses.•Excluding RNA editing sites from gymnosperm mitochondrial genes restored the sister relationship of gnetophytes and Pinaceae.•Phylogenetic analysis based on mitochondrial genomic data should carefully evaluate the impact of RNA editing sites.

Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis

Genome-wide association studies (GWASs) have repeatedly reported multiple non-coding single-nucleotide polymorphisms (SNPs) at 2p14 associated with rheumatoid arthritis (RA), but their functional roles in the pathological mechanisms of RA remain to be explored. In this study, we integrated a series of bioinformatics and functional experiments and identified three intronic RA SNPs (rs1876518, rs268131, and rs2576923) within active enhancers that can regulate the expression of SPRED2 directly. At the same time, SPRED2 and ACTR2 influence each other as a positive feedback signal amplifier to strengthen the protective role in RA by inhibiting the migration and invasion of rheumatoid fibroblast-like synoviocytes (FLSs). In particular, the transcription factor CEBPB preferentially binds to the rs1876518-T allele to increase the expression of SPRED2 in FLSs. Our findings decipher the molecular mechanisms behind the GWAS signals at 2p14 for RA and emphasize SPRED2 as a potential candidate gene for RA, providing a potential target and direction for precise treatment of RA.

Multitissue Integrative Analysis Identifies Susceptibility Genes for Atopic Dermatitis

Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease with multiple environmental and genetic factors involved in its etiology. Although lots of genetic loci associated with AD have been reported by GWASs, only a small part of phenotypic variations can be explained. To identify additional susceptibility genes on AD, we conducted a large-scale transcriptome-wide association study using a joint-tissue imputation approach in ∼840,000 European individuals combined with six precomputed gene expression weights of four AD-relevant tissues, including skin fibroblast, lymphocyte, and whole blood. The Mendelian randomization causal inference analysis was performed to estimate the causal effect of transcriptome-wide association study‒identified genes. We identified 51 genes significantly associated with AD after Bonferroni corrections, and 19 genes showed putatively causal associations such as an established gene FLG (P = 3.98 × 10^‒10) and seven genes that have not been implicated in previous transcriptome-wide association studies, such as AQP3 (P = 4.43 × 10^‒7) and PDCD1 (P = 7.66 × 10^‒7). Among them, four genes (AQP3, PDCD1, ADCY3, and DOLPP1) were further supported in differential expression analyses or the Mouse Genome Informatics database. Overall, our study identified susceptibility genes associated with AD, providing, to our knowledge, previously unreported clues in revealing the genetic mechanisms in AD.

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.

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).

ExsgRNA: reduce off-target efficiency by on-target mismatched sgRNA

Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing technology has been widely used to facilitate efficient genome editing. Current popular sgRNA design tools only consider the sgRNA perfectly matched to the target site and provide the results without any on-target mismatch. We suppose taking on-target gRNA-DNA mismatches into consideration might provide better sgRNA with similar binding activity and reduced off-target sites. Here, we trained a seq2seq-attention model with feedback-loop architecture, to automatically generate sgRNAs with on-target mismatches. Dual-luciferase reporter experiment showed that multiple sgRNAs with three mismatches could achieve the 80% of the relative activity of the perfect matched sgRNA. Meanwhile, it could reduce the number of off-target sites using sgRNAs with on-target mismatches. Finally, we provided a freely accessible web server sgRNA design tool named ExsgRNA. Users could submit their target sequence to this server and get optimal sgRNAs with less off-targets and similar on-target activity compared with the perfect-matched sgRNA.

Individualized pathway activity algorithm identifies oncogenic pathways in pan-cancer analysis

Background

Accumulative evidences have shown that dysregulation of biological pathways contributed to the initiation and progression of malignant tumours. Several methods for pathway activity measurement have been proposed, but they are restricted to making comparisons between groups or sensitive to experimental batch effects.

Methods

We introduced a novel method for individualized pathway activity measurement (IPAM) that is based on the ranking of gene expression levels in individual sample. Taking advantage of IPAM, we calculated the pathway activity of 318 pathways from KEGG database in the 10528 tumour/normal samples of 33 cancer types from TCGA to identify characteristic dysregulated pathways among different cancer types.

Findings

IPAM precisely quantified the level of activity of each pathway in pan-cancer analysis and exhibited better performance in cancer classification and prognosis prediction over five widely used tools. The average ROC-AUC of cancer diagnostic model using tumour-educated platelets (TEPs) reached 92.84%, suggesting the potential of our algorithm in early diagnosis of cancer. We identified several pathways significantly deregulated and associated with patient survival in a large fraction of cancer types, such as tyrosine metabolism, fatty acid degradation, cell cycle, p53 signalling pathway and DNA replication. We also confirmed the dominant role of metabolic pathways in cancer pathway dysregulation and identified the driving factors of specific pathway dysregulation, such as PPARA for branched-chain amino acid metabolism and NR1I2, NR1I3 for fatty acid metabolism.

Interpretation

Our study will provide novel clues for understanding the pathological mechanisms of cancer, ultimately paving the way for personalized medicine of cancer.

Funding

A full list of funding can be found in the Acknowledgements section.

MetaDecoder: a novel method for clustering metagenomic contigs

BACKGROUND

Clustering the metagenomic contigs into potential genomes is a key step to investigate the functional roles of microbial populations. Existing algorithms have achieved considerable success with simulated or real sequencing datasets. However, accurately classifying contigs from complex metagenomes is still a challenge.

RESULTS

We introduced a novel clustering algorithm, MetaDecoder, which can classify metagenomic contigs based on the frequencies of k-mers and coverages. MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. The second layer comprises a semi-supervised k-mer frequency probabilistic model and a modified Gaussian mixture model for modeling the coverage based on single copy marker genes. Benchmarks on simulated and real-world datasets demonstrated that MetaDecoder can be served as a promising approach for effectively clustering metagenomic contigs.

CONCLUSIONS

In conclusion, we developed the GPU-based MetaDecoder for effectively clustering metagenomic contigs and reconstructing microbial communities from microbial data. Applying MetaDecoder on both simulated and real-world datasets demonstrated that it could generate more complete clusters with lower contamination. Using MetaDecoder, we identified novel high-quality genomes and expanded the existing catalog of bacterial genomes. Video Abstract.

Transcriptome-wide association study identifies multiple genes and pathways associated with thyroid function

Thyroid dysfunction is a common endocrine disease measured by thyroid-stimulating hormone (TSH) level. Although more than 70 genetic loci associated with TSH have been reported through genome-wide association studies (GWASs), the variants can only explain a small fraction of the thyroid function heritability. To identify novel candidate genes for thyroid function, we conducted the first large-scale transcriptome-wide association study (TWAS) for thyroid function using GWAS-summary data for TSH levels in up to 119 715 individuals combined with pre-computed gene expression weights of six panels from four tissue types. The candidate genes identified by TWAS were further validated by TWAS replication and gene expression profiles. We identified 74 conditionally independent genes significantly associated with thyroid function, such as PDE8B (P = 1.67 × 10-282), PDE10A (P = 7.61 × 10-119), NR3C2 (P = 1.50 × 10-92), and CAPZB (P = 3.13 × 10-79). After TWAS replication using UKBB datasets, 26 genes were replicated for significant associations with thyroid-relevant diseases/traits. Among them, 16 gene were causal for their associations to thyroid-relevant diseases/traits and further validated in differential expression analyses, including two novel genes (MFSD6 and RBM47) that did not implicate in previous GWASs. Enrichment analyses detected several pathways associated with thyroid function, such as the cAMP signaling pathway (P = 7.27 × 10-4), hemostasis (P = 3.74 × 10-4), and platelet activation, signaling, and aggregation (P = 9.98 × 10-4). Our study identified multiple candidate genes and pathways associated with thyroid function, providing novel clues for revealing the genetic mechanisms of thyroid function and disease.

Phosphorus Co-Existing in Water: A New Mechanism to Boost Boron Removal by Calcined Oyster Shell Powder

The removal of boron (B) from water by co-precipitation with hydroxyapatite (HAP) has been extensively studied due to its low cost, ease of use and high efficiency. However, there is no explicit mechanism to express how resolved B was trapped by HAP. Thus, in this work, the process of removing B from water was studied using a low-cost calcium (Ca) precipitation agent derived from used waste oyster shells. The results showed that the removal rate of B in the simulated wastewater by calcined oyster shell (COS) in the presence of phosphorus (P) is up to more than 90%, as opposed to virtually no removal without phosphate. For B removal, the treated water needs to be an alkaline solution with a high pH above 12, where B is removed as [CaB(OH)4]+ but is not molecular. Finally, the synergistic mechanism of co-precipitation between HAP and dissolved B, occlusion co-precipitation, was explained in detail. The proposed method discovered the relationship between Ca, P and B, and was aimed at removing B without secondary pollution through co-precipitation.

Causal Associations Between Blood Lipids and COVID-19 Risk: A Two-Sample Mendelian Randomization Study

Supplemental Digital Content is available in the text.

Objective:

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2. It has been reported that dyslipidemia is correlated with COVID-19, and blood lipids levels, including total cholesterol, HDL-C (high-density lipoprotein cholesterol), and LDL-C (low-density lipoprotein cholesterol) levels, were significantly associated with disease severity. However, the causalities of blood lipids on COVID-19 are not clear.

Approach and Results:

We performed 2-sample Mendelian randomization (MR) analyses to explore the causal effects of blood lipids on COVID-19 susceptibility and severity. Using the outcome data from the UK Biobank (1221 cases and 4117 controls), we observed potential positive causal effects of dyslipidemia (odds ratio [OR], 1.27 [95% CI, 1.08–1.49], P=3.18×10⁻³), total cholesterol (OR, 1.19 [95% CI, 1.07–1.32], P=8.54×10⁻⁴), and ApoB (apolipoprotein B; OR, 1.18 [95% CI, 1.07–1.29], P=1.01×10⁻³) on COVID-19 susceptibility after Bonferroni correction. In addition, the effects of total cholesterol (OR, 1.01 [95% CI, 1.00–1.02], P=2.29×10⁻²) and ApoB (OR, 1.01 [95% CI, 1.00–1.02], P=2.22×10⁻²) on COVID-19 susceptibility were also identified using outcome data from the host genetics initiative (14 134 cases and 1 284 876 controls).

Conclusions:

In conclusion, we found that higher total cholesterol and ApoB levels might increase the risk of COVID-19 infection.

An Intronic Risk SNP rs12454712 for Central Obesity Acts As an Allele-Specific Enhancer To Regulate BCL2 Expression

Genome-wide association studies (GWAS) have reproducibly associated the single nucleotide polymorphism (SNP) rs12454712 with waist-to-hip ratio adjusted for BMI (WHRadjBMI), but the functional role underlying this intronic variant is unknown. Integrative genomic and epigenomic analyses supported rs12454712 as a functional independent variant. We further demonstrated that rs12454712 acted as an allele-specific enhancer regulating expression of its located gene BCL2 by using dual-luciferase reporter assays and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9. Specifically, the rs12454712-C allele can bind transcription factor ZNF329, which efficiently elevates the enhancer activity and increases BCL2 expression. Knocking down Bcl2 in 3T3-L1 cells led to the downregulation of adipogenic differentiation marker genes and increased cell apoptosis. A significant negative correlation between BCL2 expression in subcutaneous adipose tissues and obesity was observed. Our findings illustrate the molecular mechanisms behind the intronic SNP rs12454712 for central obesity, which would be a potential and promising target for developing appropriate therapies.

DDRS: Detection of drug response SNPs specifically in patients receiving drug treatment

Detecting SNPs associated with drug efficacy or toxicity is helpful to facilitate personalized medicine. Previous studies usually find SNPs associated with clinical outcome only in patients received a specific treatment. However, without information from patients without drug treatment, it is possible that the detected SNPs are associated with patients' clinical outcome even without drug treatment. Here we aimed to detect drug response SNPs based on data from patients with and without drug treatment through combing the cox proportional-hazards model and pairwise Kaplan-Meier survival analysis. A pipeline named Detection of Drug Response SNPs (DDRS) was built and applied to TCGA breast cancer data including 363 patients with doxorubicin treatment and 321 patients without any drug treatment. We identified 548 doxorubicin associated SNPs. Drug response score derived from these SNPs were associated with drug-resistant level (indicated by IC₅₀) of breast cancer cell lines. Enrichment analyses showed that these SNPs were enriched in active epigenetic regulation markers (e.g., H3K27ac). Compared with random genes, the cis-eQTL genes of these SNPs had a shorter protein-protein interaction distance to doxorubicin associated genes. In addition, linear discriminant analysis showed that the eQTL gene expression levels could be used to predict clinical outcome for patients with doxorubicin treatment (AUC = 0.738). Specifically, we identified rs2817101 as a drug response SNP for doxorubicin treatment. Higher expression level of its cis-eQTL gene GSTA1 is associated with poorer survival. This approach can also be applied to identify new drug associated SNPs in other cancers.

Transcriptome-wide association study identifies multiple genes associated with childhood body mass index

BACKGROUND

Childhood obesity is one of the most common and costly nutritional problems with high heritability. The genetic mechanism of childhood obesity remains unclear. Here, we conducted a transcriptome-wide association study (TWAS) to identify novel genes for childhood obesity.

METHODS

By integrating the GWAS summary of childhood body mass index (BMI), we conducted TWAS analyses with pre-computed gene expression weights in 39 obesity priority tissues. The GWAS summary statistics of childhood BMI were derived from the early growth genetics consortium with 35,668 children from 20 studies.

RESULTS

We identified 15 candidate genes for childhood BMI after Bonferroni corrections. The most significant gene, ADCY3, was identified in 13 tissues, including adipose, brain, and blood. Interestingly, eight genes were only identified in the specific tissue, such as FAIM2 in the brain (P = 2.04 × 10^-7) and fat mass and obesity-associated gene (FTO) in the muscle (P = 1.93 × 10^-8). Compared with the TWAS results of adult BMI, we found that one gene TUBA1B with predominant influence only on childhood BMI in the muscle (P = 1.12 × 10^-7). We evaluated the candidate genes by querying public databases and identified 12 genes functionally related to obesity phenotypes, including nine differentially expressed genes during the differentiation of human preadipocyte cells. The remaining genes (FAM150B, KNOP1, and LMBR1L) were regarded as novel candidate genes for childhood BMI.

CONCLUSIONS

Our study identified multiple candidate genes for childhood BMI, providing novel clues for understanding the genetic mechanism of childhood obesity.

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.

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.

Clinical characteristics of adult-type annular pancreas: A case report

BACKGROUND

Annular pancreas (AP) is a rare congenital abnormal rotation of the pancreas. AP rarely occurs in adults. Pancreatic tumors and ampullary tumors are related to AP, so the discovery and treatment of AP are essential.

CASE SUMMARY

This study investigated the clinical manifestations, imaging features, complications, and treatment of six patients diagnosed with AP at the Department of Hepatobiliary and Pancreatic Surgery, First Hospital of Jilin University from January 2010 to June 2020. There were four males and two females, with an average age of 56.00 ± 9.86 years old. In this study, abdominal pain and jaundice were the main clinical manifestations. Imaging can show the “crocodile jaw sign” or “double bubble sign”.

CONCLUSION

For patients with duodenal or biliary obstruction, physicians should give priority to AP when imaging examinations suggest that the duodenum is wrapped with tissue similar to the density of the pancreas. Symptomatic patients should actively undergo surgical treatment.

An integrative multi-omics network-based approach identifies key regulators for breast cancer

Although genome-wide association studies (GWASs) have successfully identified thousands of risk variants for human complex diseases, understanding the biological function and molecular mechanisms of the associated SNPs involved in complex diseases is challenging. Here we developed a framework named integrative multi-omics network-based approach (IMNA), aiming to identify potential key genes in regulatory networks by integrating molecular interactions across multiple biological scales, including GWAS signals, gene expression-based signatures, chromatin interactions and protein interactions from the network topology. We applied this approach to breast cancer, and prioritized key genes involved in regulatory networks. We also developed an abnormal gene expression score (AGES) signature based on the gene expression deviation of the top 20 rank-ordered genes in breast cancer. The AGES values are associated with genetic variants, tumor properties and patient survival outcomes. Among the top 20 genes, RNASEH2A was identified as a new candidate gene for breast cancer. Thus, our integrative network-based approach provides a genetic-driven framework to unveil tissue-specific interactions from multiple biological scales and reveal potential key regulatory genes for breast cancer. This approach can also be applied in other complex diseases such as ovarian cancer to unravel underlying mechanisms and help for developing therapeutic targets.

LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files

The triangular correlation heatmap aiming to visualize the linkage disequilibrium (LD) pattern and haplotype block structure of SNPs is ubiquitous component of population-based genetic studies. However, current tools suffered from the problem of time and memory consuming. Here, we developed LDBlockShow, an open source software, for visualizing LD and haplotype blocks from variant call format files. It is time and memory saving. In a test dataset with 100 SNPs from 60 000 subjects, it was at least 10.60 times faster and used only 0.03-13.33% of physical memory as compared with other tools. In addition, it could generate figures that simultaneously display additional statistical context (e.g. association P-values) and genomic region annotations. It can also compress the SVG files with a large number of SNPs and support subgroup analysis. This fast and convenient tool will facilitate the visualization of LD and haplotype blocks for geneticists.

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.

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.

PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files

MOTIVATION

Linkage disequilibrium (LD) decay is of great interest in population genetic studies. However, no tool is available now to do LD decay analysis from variant call format (VCF) files directly. In addition, generation of pair-wise LD measurements for whole genome SNPs usually resulting in large storage wasting files.

RESULTS

We developed PopLDdecay, an open source software, for LD decay analysis from VCF files. It is fast and is able to handle large number of variants from sequencing data. It is also storage saving by avoiding exporting pair-wise results of LD measurements. Subgroup analyses are also supported.

AVAILABILITY AND IMPLEMENTATION

PopLDdecay is freely available at https://github.com/BGI-shenzhen/PopLDdecay.

Transcription Factor Enrichment Analysis in Enhancers Identifies EZH2 as a Susceptibility Gene for Osteoporosis

PURPOSE

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with osteoporosis. Most of these SNPs are noncoding variants and could be mapped to enhancers. Transcription factors (TFs) play important roles in gene regulation via enhancers harboring these SNPs; thus, we aimed to identify common regulatory TFs binding to enhancers associated with osteoporosis.

METHODS

We first annotated all the osteoporosis-related SNPs identified by GWASs to enhancers and conducted TF enrichment analyses to identify common TFs binding to osteoporosis-associated enhancers. We further conducted genetic association analyses between the identified TFs and bone mineral density (BMD) in a Han Chinese population.

RESULTS

After functional annotation, a total of 5081 osteoporosis-related SNPs were mapped to enhancers. TF enrichment analyses identified 2 significant TFs after multiple testing adjustments, which are EZH2 (Padj = .028) and NRSF (Padj = .038). We also found 1 SNP, rs111851041, in EZH2 was significantly associated with BMD both at the hip and spine after multiple testing adjustments (hip BMD: P = 4.32 × 10-4; spine BMD: P = 2.72 × 10-3). The expression of EZH2 decreased significantly from 12 to 48 hours of osteogenic differentiation. And functional validation showed that EZH2 was associated with osteoporosis-related phenotypes in knockout mice.

CONCLUSIONS

By conducting TF enrichment analyses, we identified EZH2 as a common TF binding to osteoporosis-associated enhancers, and EZH2 was also associated with BMD in a Chinese population. EZH2 is functionally related to bone phenotypes. The identified gene could provide new insight into osteoporosis pathophysiology and highlight opportunities for future clinical and pharmacological research on osteoporosis.

The hornwort genome and early land plant evolution

Hornworts, liverworts and mosses are three early diverging clades of land plants, and together comprise the bryophytes. Here, we report the draft genome sequence of the hornwort Anthoceros angustus. Phylogenomic inferences confirm the monophyly of bryophytes, with hornworts sister to liverworts and mosses. The simple morphology of hornworts correlates with low genetic redundancy in plant body plan, while the basic transcriptional regulation toolkit for plant development has already been established in this early land plant lineage. Although the Anthoceros genome is small and characterized by minimal redundancy, expansions are observed in gene families related to RNA editing, UV protection and desiccation tolerance. The genome of A. angustus bears the signatures of horizontally transferred genes from bacteria and fungi, in particular of genes operating in stress-response and metabolic pathways. Our study provides insight into the unique features of hornworts and their molecular adaptations to live on land.

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.

An Allele-Specific Functional SNP Associated with Two Systemic Autoimmune Diseases Modulates IRF5 Expression by Long-Range Chromatin Loop Formation

Both systemic lupus erythematosus (SLE) and systemic sclerosis (SSc) are autoimmune diseases sharing similar genetic backgrounds. Genome-wide association studies have constantly disclosed numerous genetic variants conferring to both disease risks at 7q32.1, but the functional mechanisms underlying them are still largely unknown. Through a series of bioinformatics and functional analyses, we prioritized a potential independent functional single-nucleotide polymorphism (rs13239597) within TNPO3 promoter region, residing in a putative enhancer element and validated that IRF5 is the distal target gene (∼118 kb) of rs13239597, which is a key regulator involved in pathogenic autoantibody dysregulation, increasing risk of both SLE and SSc. We experimentally validated the long-range chromatin interactions between rs13239597 and IRF5 using chromosome conformation capture assay. We further demonstrated that rs13239597-A acted as an allele-specific enhancer regulating IRF5 expression, independently of TNPO3 by using dual-luciferase reporter assays and CRISPR-Cas9. Particularly, the transcription factor EVI1 could preferentially bind to rs13239597-A allele and increase the enhancer activity to regulate IRF5 expression. Taken together, our results uncovered a mechanistic insight of a noncoding functional variant acting as an allele-specific distal enhancer to directly modulate IRF5 expression, which might obligate in understanding of complex genetic architectures of SLE and SSc pathogenesis.

Addressing the Missing Heritability Problem With the Help of Regulatory Features

Genome-wide association studies (GWASs) have successfully identified thousands of susceptibility loci for human complex diseases. However, missing heritability is still a challenging problem. Considering most GWAS loci are located in regulatory elements, we recently developed a pipeline named functional disease-associated single-nucleotide polymorphisms (SNPs) prediction (FDSP), to predict novel susceptibility loci for complex diseases based on the interpretation of regulatory features and published GWAS results with machine learning. When applied to type 2 diabetes and hypertension, the predicted susceptibility loci by FDSP were proved to be capable of explaining additional heritability. In addition, potential target genes of the predicted positive SNPs were significantly enriched in disease-related pathways. Our results suggested that taking regulatory features into consideration might be a useful way to address the missing heritability problem. We hope FDSP could offer help for the identification of novel susceptibility loci for complex diseases.

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.

Runs of homozygosity associate with decreased risks of lung cancer in never-smoking East Asian females

Although genome-wide association studies (GWASs) have identified some risk single-nucleotide polymorphisms in East Asian never-smoking females, the unexplained missing heritability is still required to be investigated. Runs of homozygosity (ROHs) are thought to be a type of genetic variation acting on human complex traits and diseases. We detected ROHs in 8,881 East Asian never-smoking women. The summed ROHs were used to fit a logistic regression model which noteworthily revealed a significant association between ROHs and the decreased risk of lung cancer (P < 0.05). We identified 4 common ROHs regions located at 2p22.1, which were significantly associated with decreased risk of lung cancer (P = 2.00 × 10^-4 - 1.35 × 10^-4). Functional annotation was conducted to investigate the regulatory function of ROHs. The common ROHs were overlapped with potential regulatory elements, such as active epigenome elements and chromatin states in lung-derived cell lines. SOS1 and ARHGEF33 were significantly up-regulated as the putative target genes of the identified ROHs in lung cancer samples according to the analysis of differently expressed genes. Our results suggest that ROHs could act as recessive contributing factors and regulatory elements to influence the risk of lung cancer in never-smoking East Asian females.

The complete chloroplast genome of Magnolia sinostellata (Magnoliaceae), a rare and endangered species of China

Magnolia sinostellata Chiu & Chen is a rare and endangered species endemic to subtropical China. Here we assembled and annotated the complete chloroplast (cp) genome of M. sinostellata. The chloroplast genome of M. sinostellata is 160,076 bp in length and encodes 79 protein-coding genes, 30 transfer RNA (tRNA) genes and four ribosomal RNA (rRNA) genes. The maximum-likelihood (ML) phylogenetic analysis result reveals that M. sinostellata is most closely related to M. biondii.

Multiple Functional Variants at 13q14 Risk Locus for Osteoporosis Regulate RANKL Expression Through Long-Range Super-Enhancer

RANKL is a key regulator involved in bone metabolism, and a drug target for osteoporosis. The clinical diagnosis and assessment of osteoporosis are mainly based on bone mineral density (BMD). Previous powerful genomewide association studies (GWASs) have identified multiple intergenic single-nucleotide polymorphisms (SNPs) located over 100 kb upstream of RANKL and 65 kb downstream of AKAP11 at 13q14.11 for osteoporosis. Whether these SNPs exert their roles on osteoporosis through RANKL is unknown. In this study, we conducted integrative analyses combining expression quantitative trait locus (eQTL), genomic chromatin interaction (high-throughput chromosome conformation capture [Hi-C]), epigenetic annotation, and a series of functional assays. The eQTL analysis identified six potential functional SNPs (rs9533090, rs9594738, r8001611, rs9533094, rs9533095, and rs9594759) exclusively correlated with RANKL gene expression (p < 0.001) at 13q14.11. Co-localization analyses suggested that eQTL signal for RANKL and BMD-GWAS signal shared the same causal variants. Hi-C analysis and functional annotation further validated that the first five osteoporosis SNPs are located in a super-enhancer region to regulate the expression of RANKL via long-range chromosomal interaction. Particularly, dual-luciferase assay showed that the region harboring rs9533090 in the super-enhancer has the strongest enhancer activity, and rs9533090 is an allele-specific regulatory SNP. Furthermore, deletion of the region harboring rs9533090 using CRISPR/Cas9 genome editing significantly reduced RANKL expression in both mRNA level and protein level. Finally, we found that the rs9533090-C robustly recruits transcription factor NFIC, which efficiently elevates the enhancer activity and increases the RANKL expression. In summary, we provided a feasible method to identify regulatory noncoding SNPs to distally regulate their target gene underlying the pathogenesis of osteoporosis by using bioinformatics data analyses and experimental validation. Our findings would be a potential and promising therapeutic target for precision medicine in osteoporosis. © 2018 American Society for Bone and Mineral Research.

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.

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.

Importance of the plasma soluble HLA-G levels for prognostic stratification with traditional prognosticators in colorectal cancer

An increased peripheral soluble HLA-G (sHLA-G) expression has been observed in various malignancies while its prognostic significance was rather limited. In this study, the prognostic value of plasma sHLA-G in 178 colorectal cancer (CRC) patients was investigated. sHLA-G levels were analyzed by specific enzyme-linked immunosorbent assay. Data showed sHLA-G levels were significantly increased in CRC patients compared with normal controls (36.8 U/ml vs 25.4 U/ml, p = 0.009). sHLA-G in the died were obviously higher than that of alive CRC patients (46.8 U/ml vs 27.4 U/ml, p = 0.012). Patients with sHLA-G above median levels (≥ 36.8 U/ml, sHLA-Ghigh) had a significantly shorter survival time than those with sHLA-Glow (< 36.8 U/ml, p < 0.001), and sHLA-G could be an independent prognostic factor for CRC patients. With stratification of clinical parameters in survival by sHLA-Glow and sHLA-Ghigh, sHLA-G exhibited a significant predictive value for CRC patients of the female (p = 0.036), the elder (p = 0.009), advanced tumor burden (T3 + 4, p = 0.038), regional lymph node status (N0, p = 0.041), both metastasis status (M0, p = 0.014) and (M1, p=0.018), and clinical stage (I + II, p = 0.018), respectively. Summary, our data demonstrated for the first time that sHLA-G levels is an independent prognosis factor and improves the prognostic stratification offered by traditional prognosticators in CRC patients.

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.

Acupuncture through Baihui (DU20) to Qubin (GB7) mitigates neurological impairment after intracerebral hemorrhage

Inflammation plays an important role in nerve defects caused by intracerebral hemorrhage. Repairing brain damage by inhibiting the macrophage-inducible C-type lectin/spleen tyrosine kinase (Mincle/Syk) signaling pathway is a potential new target for treating cerebral hemorrhage. In this study, we aimed to determine whether acupuncture through Baihui (DU20) to Qubin (GB7) is an effective treatment for intracerebral hemorrhage through the Mincle/Syk signaling pathway. An intracerebral hemorrhage rat model was established by autologous blood infusion into the caudate nucleus. Acupuncture through Baihui to Qubin was performed for 30 minutes, once every 12 hours, for a total of three times. Piceatannol (34.62 mg/kg), a Syk inhibitor, was intraperitoneally injected as a control. Modified neurological severity score was used to assess neurological function. Brain water content was measured. Immunohistochemistry and western blot assay were used to detect immunoreactivity and protein expression levels of Mincle, Syk, and CARD9. Real-time polymerase chain reaction was used to determine interleukin-1β mRNA levels. Hematoxylin-eosin staining was performed to observe histopathological changes. Our results showed that acupuncture through Baihui to Qubin remarkably improved neurological function and brain water content, and inhibited immunoreactivity and expression of Mincle, Syk, CARD9, and interkeukin-1β. Moreover, this effect was similar to piceatannol. These findings suggest that acupuncture through Baihui to Qubin can improve neurological impairment after cerebral hemorrhage by inhibiting the Mincle/Syk signaling pathway.

Surface characterization and degradation behavior of polyimide films induced by coupling irradiation treatment

Schematic of irradiation-load-heating coupling treatment and degradation process of polyimide film.

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.