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Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p-value < 5x10-8), which validated 12 previously reported loci for proinsulin and 10 additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher vs. lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait loci (eQTL) data, suggesting candidate genes including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal, but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms predisposing to disease.

Integrative genetic association methods have shown great promise in post-GWAS (genome-wide association study) analyses, in which one of the most challenging tasks is identifying putative causal genes and uncovering molecular mechanisms of complex traits. Recent studies suggest that prevailing computational approaches, including transcriptome-wide association studies (TWASs) and colocalization analysis, are individually imperfect, but their joint usage can yield robust and powerful inference results. This paper presents INTACT, a computational framework to integrate probabilistic evidence from these distinct types of analyses and implicate putative causal genes. This procedure is flexible and can work with a wide range of existing integrative analysis approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly desirable feature, we further propose an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated probabilistic evidence. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. We apply the proposed methods to analyze the multi-tissue eQTL data from the GTEx project and eight large-scale complex- and molecular-trait GWAS datasets from multiple consortia and the UK Biobank. Overall, we find that the proposed methods markedly improve the existing putative gene implication methods and are particularly advantageous in evaluating and identifying key gene sets and biological pathways underlying complex traits.

Aims/hypothesis Determining how high BMI at different time points influences the risk of developing type 2 diabetes and affects insulin secretion and insulin sensitivity is critical. Methods By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from those of high adulthood BMI on the risk of type 2 diabetes and insulin-related phenotypes using Mendelian randomisation. We performed two-sample MR using external studies of type 2 diabetes, and oral and intravenous measures of insulin secretion and sensitivity. Results We found that a childhood BMI that was one standard deviation (1.97 kg/m2) higher than the mean, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including increased insulin sensitivity index (β=0.15; 95% CI 0.067, 0.225; p=2.79Å~10−4) and reduced fasting glucose levels (β=−0.053; 95% CI −0.089, −0.017; p=4.31Å~10−3). However, there was little to no evidence of a direct protective effect on type 2 diabetes (OR 0.94; 95% CI 0.85, 1.04; p=0.228) independently of genetic liability to adulthood BMI. Conclusions/interpretation Our results provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty regarding the biological pathway of these effects and the limitations of this type of study

ObjectiveGenome-wide association studies (GWAS) have identified >100 risk loci for systemic lupus erythematosus (SLE), but the disease genes at most loci remain unclear, hampering translation of these genetic discoveries. We aimed to prioritise genes underlying the 110 SLE loci that were identified in the latest East Asian GWAS meta-analysis.MethodsWe built gene expression predictive models in blood B cells, CD4+and CD8+T cells, monocytes, natural killer cells and peripheral blood cells of 105 Japanese individuals. We performed a transcriptome-wide association study (TWAS) using data from the latest genome-wide association meta-analysis of 208 370 East Asians and searched for candidate genes using TWAS and three data-driven computational approaches.ResultsTWAS identified 171 genes for SLE (p–5); 114 (66.7%) showed significance only in a single cell type; 127 (74.3%) were in SLE GWAS loci. TWAS identified a strong association betweenCD83and SLE (p–8). Meta-analysis of genetic associations in the existing 208 370 East Asian and additional 1498 cases and 3330 controls found a novel single-variant association at rs72836542 (OR=1.11, p=4.5×10–9) aroundCD83. For the 110 SLE loci, we identified 276 gene candidates, including 104 genes at recently-identified SLE novel loci. We demonstrated in vitro that putative causal variant rs61759532 exhibited an allele-specific regulatory effect onACAP1, and that presence of the SLE risk allele decreasedACAP1expression.ConclusionsCell-level TWAS in six types of immune cells complemented SLE gene discovery and guided the identification of novel genetic associations. The gene findings shed biological insights into SLE genetic associations.

Abstract Ischemic stroke is one of the most severe neurological disorders with limited therapeutic strategies. The utilization of nanoparticle drug delivery systems is a burgeoning field and has been widely investigated. Among these, biomimetic drug delivery systems composed of biogenic membrane components and synthetic nanoparticles have been extensively highlighted in recent years. Biomimetic membrane camouflage presents an effective strategy to prolong circulation, reduce immunogenicity and enhance targeting. For one thing, biomimetic nanoparticles reserve the physical and chemical properties of intrinsic nanoparticle. For another, the biological functions of original source cells are completely inherited. Compared to conventional surface modification methods, this approach is more convenient and biocompatible. In this review, membrane-based nanoparticles derived from different donor cells were exemplified. The prospect of future biomimetic nanoparticles in ischemic stroke therapy was discussed. Graphic abstract

Determining how high body-mass index (BMI) at different time points influences the risk of developing type two diabetes (T2D), and affects insulin secretion and insulin sensitivity, is critical. By estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice-versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from high adulthood BMI on the risk of T2D and insulin related phenotypes using Mendelian randomisation and studies of T2D, and oral and intravenous measures of insulin secretion and sensitivity. We found that a 1.s.d. (= 1.97kg/m2) higher childhood BMI, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including an increased insulin sensitivity index (β = 0.15 [0.067, 0.225], p = 2.79×10−4), and reduced fasting glucose (β = -0.053 [-0.089, -0.017], p = 4.31×10−3). There was however little to no evidence of a direct protective effect on T2D (OR = 0.94 [0.85 - 1.04], p = 0.228), independently of genetic liability to adulthood BMI. Our results thus cumulatively provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty in biological pathway of these effects, and the limitations of this type of study.Research in ContextHigh BMI in adulthood is associated with higher risk of type two diabetes, coupled with lower insulin sensitivity and secretion.Richardson et al [2020] used genetics to show that high BMI in childhood does not appear to increase the risk of type diabetes independently from its effect on adult BMI.We asked: does high childhood BMI affect insulin related traits such as fasting glucose and insulin sensitivity, independently of adulthood BMI?We used genetics to show that high childhood BMI has a protective effect on seven insulin sensitivity and secretion traits, including fasting glucose and measures of insulin sensitivity and secretion, independently of adulthood BMI.Our work has the potential to turn conventional understanding on its head – high BMI in childhood improves insulin sensitivity (when adjusting for knock on effects to high adult BMI) and opens up important questions about plasticity in childhood and compensatory mechanisms.

Background: Vitamin D level has been reported to be associated with psoriasis, atopic dermatitis, and vitiligo. However, its causal relationship with the risk of these three diseases remains unclear. Methods: We obtained genome-wide association statistics for three measures of circulating vitamin D levels (25(OH)D in 120,618 individuals, and 25(OH)D3 and epimeric form C3-epi-25(OH)D3 in 40,562 individuals) and for the diseases psoriasis (3871 cases and 333,288 controls), atopic dermatitis (21,399 cases and 95,464 controls), and vitiligo (4680 cases and 39,586 controls). We performed Mendelian randomization using inverse-variance weighted, weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier methods. We carried out sensitivity analyses to evaluate the robustness of the results. Results: We showed that elevated vitamin D levels protected individuals from developing psoriasis (OR = 0.995, p = 8.84 × 10−4 for 25(OH)D; OR = 0.997, p = 1.81 × 10−3 for 25(OH)D3; and OR = 0.998, p = 0.044 for C3-epi-25(OH)D3). Genetically predicted risk of atopic dermatitis increased the levels of 25(OH)D (OR = 1.040, p = 7.14 × 10−4) and 25(OH)D3 (OR = 1.208, p = 0.048). A sensitivity analysis suggested the robustness of these causal associations. Conclusions: This study reported causal relationships between circulating vitamin D levels and the risk of psoriasis, atopic dermatitis, and vitiligo. These findings provide potential disease intervention and monitoring targets.

Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.

Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impact on health. Psoriasis patients have higher risk of type 2 diabetes (~1.5 Odds Ratio) and vice versa, controlling for body mass index (BMI), yet there has been limited study comparing their genetic architecture. We hypothesized there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis (TDMA) was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D adjusted for BMI (74,124 cases and 824,006 controls). We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multi-variable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (p=1.6x10(−4), OR=1.01), and highlighted the impact of BMI. TDMA further revealed 4 genome-wide significant loci (p

Background:. The prevalence of skin diseases and diabetes mellitus (DM) are prominent around the world. The current scope of knowledge regarding the prevalence of skin diseases and comorbidities with type 2 DM (T2DM) is limited, leading to limited recognition of the correlations between skin diseases and T2DM. Methods:. We collected 383 subjects from the Da Qing Diabetes Study during the period from July 9th to September 1st, 2016. The subjects were categorized into three groups: Normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and T2DM. The prevalence and clinical characteristics of skin diseases were recorded and investigated. Results:. In this cross-sectional study, 383 individuals with ages ranging from 53 to 89-year-old were recruited. The overall prevalence of skin diseases was 93.5%, and 75.7% of individuals had two or more kinds of skin diseases. Additionally, there were 47 kinds of comorbid skin diseases in patients with T2DM, of which eight kinds of skin diseases had a prevalence >10%. The prevalence of skin diseases in NGT, IGT, and T2DM groups were 93.3%, 91.5%, and 96.6%, respectively; stratified analysis by categories showed a statistically significant difference in “disturbances of pigmentation” and “neurological and psychogenic dermatoses”. The duration of T2DM also significantly associated with the prevalence of “disturbances of pigmentation” and “neurological and psychogenic dermatoses”. Subsequently, the prevalence of “disturbances of pigmentation” was higher in males than females in NGT (P

Transcriptome-wide association studies (TWAS) and colocalization analysis are complementary integrative genetic association approaches routinely used to identify functional units underlying complex traits in post-genome-wide association study (post-GWAS) analyses. Recent studies suggest that both approaches are individually imperfect, but joint usage can yield robust and powerful inference results. This paper introduces a new statistical framework, INTACT, to perform probabilistic integration of TWAS and colocalization evidence for implicating putative causal genes. This procedure is flexible and can work with a wide range of existing TWAS and colocalization approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly-desirable feature, we describe an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated TWAS and colocalization analysis results. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. Finally, we apply the proposed methods to the GTEx data and a variety of GWAS summary statistics derived from complex and molecular traits previously analyzed by Hukku et al. and Sinnott-Armstrong et al. We find empirical evidence that the proposed methods improve and complement existing putative gene implication methods and are advantageous in evaluating and identifying key gene sets and biological pathways.

ObjectiveSystemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.MethodsWe newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations.ResultsWe identified 113 genetic regions including 46 novel loci at genome-wide significance (p−8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=−0.242) and non-albumin protein (rg=0.238).ConclusionThis study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Systemic lupus erythematosus (SLE) is a complex and heterogeneous autoimmune disease involving multiple immune cells. A major hurdle to the elucidation of SLE pathogenesis is our limited understanding of dysregulated gene expression linked to various clinical statuses with a high cellular resolution. Here, we conducted a large-scale transcriptome study with 6,386 RNA sequencing data covering 27 immune cell types from 159 SLE and 89 healthy donors. We first profiled two distinct cell-type-specific transcriptomic signatures: disease-state and disease-activity signatures, reflecting disease establishment and exacerbation, respectively. We next identified candidate biological processes unique to each signature. This study suggested the clinical value of disease-activity signatures, which were associated with organ involvement and responses to therapeutic agents such as belimumab. However, disease-activity signatures were less enriched around SLE risk variants than disease-state signatures, suggesting that the genetic studies to date may not well capture clinically vital biology in SLE. Together, we identified comprehensive gene signatures of SLE, which will provide essential foundations for future genomic, genetic, and clinical studies.

Few studies have explored the impact of rare variants (minor allele frequency, MAF

Aim: A genomic region on 5q33.3 lies between and encompasses the IL12B and PTTG1 genes, and contains many potential psoriasis causal variants. We aimed to further examine the influence of variants in and around this region. Materials & methods: We used least absolute shrinkage and selection operator (LASSO)-based regression analysis to assess independent contributions of 2171 variants to psoriasis susceptibility and tested them for association with different clinical psoriasis subtypes. Results: We found that ADRA1B gene variants contribute to psoriasis in Chinese population. ADRA1B gene variants have a stronger association with moderate-to-severe disease group and an earlier age at onset of psoriasis than IL-12B and PTTG1 variants. Conclusion: The association of variants in the ADRA1B gene with psoriasis could explain why variants in the IL-12B, ADRA1B and PTTG1 gene regions are associated with psoriasis.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease involving multiple immune cells. To elucidate SLE pathogenesis, it is essential to understand the dysregulated gene expression pattern linked to various clinical statuses with a high cellular resolution. Here, we conducted a large-scale transcriptome study with 6,386 RNA sequencing data covering 27 immune cell types from 136 SLE and 89 healthy donors. We profiled two distinct cell-type-specific transcriptomic signatures: disease-state and disease-activity signatures, reflecting disease establishment and exacerbation, respectively. We then identified candidate biological processes unique to each signature. This study suggested the clinical value of disease-activity signatures, which were associated with organ involvement and therapeutic responses. However, disease-activity signatures were less enriched around SLE risk variants than disease-state signatures, suggesting that current genetic studies may not well capture clinically vital biology. Together, we identified comprehensive gene signatures of SLE, which will provide essential foundations for future genomic and genetic studies.

Glioblastoma multiforme (GBM) is acknowledged as the most aggressive primary brain tumor in adults. It is typically characterized by the high heterogeneity which corresponds to extensive genetic mutations and complex alternative splicing (AS) profiles. Known as a major repressive splicing factor in AS, polypyrimidine tract-binding protein 1 (PTBP1) is involved in the exon skipping events of multiple precursor mRNAs (pre-mRNAs) in GBM. However, precise mechanisms that modulate the expression and activity of PTBP1 remain to be elucidated. In present study, we provided evidences for the role of a long intergenic noncoding RNA (LINREP) implicated in the regulation of PTBP1-induced AS. LINREP interacted with PTBP1 and human antigen R (HuR, ELAVL1) protein complex and protected PTBP1 from the ubiquitin-proteasome degradation. Consequently, a broad spectrum of PTBP1-induced spliced variants was generated by exon skipping, especially for the skipping of reticulon 4 (RTN4) exon 3. Interestingly, LINREP also promoted the dissociation of nuclear UPF1 from PTBP1, which increased the binding of PTBP1 to RTN4 transcripts, thus enhancing the skipping of RTN4 exon 3 to some extent. Besides, HuR recruitment was essential for the stabilization of LINREP via a manner dependent on N

Few studies have explored the impact of rare variants (minor allele frequency 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.

Type 2 diabetes is increasing in all ancestry groups1. Part of its genetic basis may reside among the rare (minor allele frequency 2. We analyzed high-coverage (mean depth 38.2x) whole genome sequencing from 9,639 individuals with T2D and 34,994 controls in the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program2 to show that rare, non-coding variants that are poorly captured by genotyping arrays or imputation panels contribute h2=53% (P=4.2×10−5) to the genetic component of risk in the largest (European) ancestry subset. We coupled sequence variation with islet epigenomic signatures3 to annotate and group rare variants with respect to gene expression4, chromatin state5 and three-dimensional chromatin architecture6, and show that pancreatic islet regulatory elements contribute to T2D genetic risk (h2=8%, P=2.4×10−3). We used islet annotation to create a non-coding framework for rare variant aggregation testing. This approach identified five loci containing rare alleles in islet regulatory elements that suggest novel biological mechanisms readily linked to hypotheses about variant-to-function. Large scale whole genome sequence analysis reveals the substantial contribution of rare, non-coding variation to the genetic architecture of T2D and highlights the value of tissue-specific regulatory annotation for variant-to-function discovery.

Systemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci1-8. Nevertheless, these loci only partially explain SLE heritability and provide limited biological insight. We report the largest study of SLE in East Asians (13,377 cases and 194,993 controls), identifying 233 association signals within 113 (46 novel) genetic loci. We detect six new lead missense variants and prioritize ten most likely putative causal variants, one of which we demonstrate exhibits allele-specific regulatory effect on ACAP1 in vitro. We suggest 677 effector genes with potential for drug repurposing, and provide evidence that two distinct association signals at a single locus act on different genes (NCF2 and SMG7). We demonstrate that SLE-risk variants overlap with cell-specific active regulatory elements, notably EBNA2-mediated super-enhancers in Epstein-Barr Virus-transformed B cells, and implicate the role for non-immune cells in SLE biology. These findings shed light on genetic and biological understandings of SLE.

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underly the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertook a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture were identified. Nine disease loci showed clear ancestral group heterogeneity and implicated antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores performed significantly better when trained on matched ancestral data sets. These analyses help to reveal the genetic bases for disparities in SLE among ancestral groups.

Nanomaterials based on hybrid scaffolds have shown a high potential to promote osteointegration and bone regeneration. In this study, a novel nanocomposite scaffold was synthesized via a cross-linking/hydrothermal/freeze-drying method, resulting in layer-by-layer structures with functional and structural properties mimicking the natural bone. The hierarchical structures of the scaffold were reinforced with nitrogen-doped multiwalled carbon nanotubes (N-MWCNTs), cellulose, and nanohydroxyapatite. The N-MWCNT/Cel/nHA scaffolds were characterized and evaluated in terms of structure, morphology, biocompatibility, cellular responses, and bone repair efficiency in vivo. The resulting scaffolds showed that incorporation of 1 wt % N-MWCNTs into the hybrid scaffold with micropores (∼5 μm) significantly improved its mechanical properties, although the surface morphology of the scaffold tended to be rough and porous. Importantly, the resulting scaffolds supported in vitro cellular attachment, proliferation, viability, and mineralization of bone mesenchymal stem cells (BMSCs). On the other hand, incorporation of N-MWCNTs into the scaffold induced preferential differentiation of BMSCs to osteogenic lineage accompanied by increased alkaline phosphatase activity and expression of key osteogenic genes. Furthermore, 12 weeks after implantation, the 1%N-MWCNT/Cel/nHA porous scaffolds successfully cicatrized a distal femoral condyle critical size defect in rabbit without obvious inflammatory responses, as indicated by the results of the Micro-CT and histological analyses. In vitro and in vivo experiments confirmed that the scaffolds not only improved the interface bonding with bone tissue but also accelerated the new bone formation and regeneration by up-regulating signaling molecules that are involved in cell proliferation and differentiation. These results indicated that the novel N-MWCNT/Cel/nHA scaffold is an efficient platform for osteogenesis research and bone regeneration medicine.

This study was aimed to investigate whether NFKB1 participates in the pathogenesis of psoriasis by mediating Th1/Th17 cells. In this study, expression of NFKB1 was assessed in skin tissues from psoriasis patients and the healthy controls through Western blot and Immunohistochemistry. Enzyme-linked immunosorbent assay (ELISA) was used to analyze the serum levels of IFN-γ, IL-17 (IL-17A) and IL-17RA. The imiquimod-induced psoriasis mouse model was employed to examine the role of NFKB1 in psoriasis via the assessment of psoriasis area and severity index (PASI), including erythema, thickness and scales. The effects of NFKB1 on Th1/Th17 cells in were examined by flow cytometry. In vitro co-culture of Th1/Th17 cells isolated from different mice with HaCat cells was conducted to elucidate the effect of Th1/Th17 cells-mediated by NFKB1 on HaCat cells by MTT, wound healing and transwell invasion assay, respectively. The results showed that NF-κB p105/p50 expression in skin tissues was significantly increased in psoriasis (n = 21) compared to the healthy controls (n = 16), as well as levels of serum INF-γ and IL-17. Additionally, NF-κB p105/p50 expression in lesional skin tissues was much higher than that in non-lesional skin tissues of the same patients. In the psoriasis mouse model, NFKB1 overexpression significantly elevated the scores of erythema, thickness and scales. Besides, NFKB1 up-regulated the level of NF-κB p105/p50, INF-γ, T-bet, IL-17 and RORγt, as well as Th1/Th17 cells in skin tissues of psoriasis mice. Finally, in vitro assay confirmed that the activation of Th1 and Th17 mediated by NFKB1 in psoriasis promoted the proliferation, migration and invasion of keratinocytes. These findings suggest a critical role for NFKB1 in the regulation of Th1 and Th17 in psoriasis.

Genotype imputation is now routinely performed in genomic analysis. Reference panel size, that is, the number of haplotypes in the reference panel, has been well established to be one major driving factor of imputation accuracy. For that reason, huge efforts have been made worldwide to provide large reference panels, with the Haplotype Reference Consortium (HRC) being currently the largest available in the public domain. The imputation performance of HRC, whose major samples are Europeans, has been mainly evaluated in Europeans. We conducted whole-genome genotype imputation on two independent genome-wide genotyping datasets, one with 1000 European samples and the other with 1000 Han Chinese samples. We compared the results obtained using HRC with those using Phase III of the 1000 Genomes Project (1000G) reference panel. For the European dataset, using HRC improved imputation quality, especially for rare variants with minor allele-frequency (MAF)

Objective This study was aimed to explore the effect of Bach2 on B cells in systemic lupus erythematosus (SLE), as well as the underlying mechanisms. Methods Expression of Bach2, phosphorylated-Bach2 (p-Bach2), Akt, p-Akt and BCR-ABL (p210) in B cells isolated from SLE patients and the healthy persons were assessed by Western blot. Immunofluorescence staining was performed to assess the localization of Bach2 in B cells. Enzyme-linked immunosorbent assay (ELISA) was employed to detect IgG produced by B cells. Cell counting kit-8 (CCK-8) and Annexin-V FITC/PI double staining assay were adopted to evaluate cell proliferation and apoptosis in B cells, respectively. Results Compared to the healthy controls, Bach2, p-Akt and p210 were significantly decreased, while nuclear translocation of Bach2, IgG, CD40 and CD86 obviously up-regulated in B cells from SLE patients. Bach2 significantly inhibited the proliferation, promoted apoptosis of B cells from SLE patients, whereas BCR-ABL dramatically reversed cell changes induced by Bach2. Besides, BCR-ABL also inhibited nuclear translocation of Bach2 in B cells from SLE patients. Further, LY294002 treatment had no effect on decreased expression of Bach2 induced by BCR-ABL, but significantly eliminated BCR-ABL-induced phosphorylation of Bach2 and restored reduced nuclear translocation of Bach2 induced by BCR-ABL in B cells from SLE. Conclusions Bach2 may play a suppressive role in B cells from SLE, and BCR-ABL may inhibit the nuclear translocation of Bach2 via serine phosphorylation through the PI3K pathway.

Background Psoriasis is a complex disease that is influenced by both genetic and environmental factors with abnormal gene expression in lesional skin. However, no studies are available on genome-scale gene expression of psoriatic lesions in the Chinese population. In addition, systematic studies on the biological pathways, pathogenicity and interaction networks of psoriasis-related genes with abnormal expression profiles require further investigation. Objectives To further explore the associated pathways in psoriasis by functional analysis and to identify the key genes by gene pathogenicity analysis. Methods We performed RNA sequencing on 60 skin biopsy samples from psoriasis patients and healthy controls to identify the primary differentially expressed genes in psoriatic lesional skin. We retrieved all reported psoriasis-associated genes and performed integrative analyses covering gene expression profiling, pathway analysis, gene pathogenicities and protein-protein interaction networks. Results We found that internal and external stimuli may activate immuno-inflammatory responses to promote the development of psoriasis. Pathways associated with infectious diseases and cancers were identified by functional and pathway analyses. The gene pathogenicity analysis revealed five key genes in psoriasis, including PPARD, GATA3, TIMP3, WNT5A and PTTG1. Conclusions Our analyses showed that genes contributed to the pathogenesis of psoriasis by activating risk pathways with components abnormality in expression. We identified five potentially pathogenic genes for psoriasis that may serve as important biomarkers for the diagnosis and treatment. This article is protected by copyright. All rights reserved.

Background Atopic dermatitis (AD) is a chronic inflammatory skin disease. The 5q22.1 region was found to have an association with AD in our previous genome-wide association study (GWAS). Objective To identify the AD susceptibility gene in 5q22.1 and observe its expression in AD tissues. Methods Suggestive indels from the GWAS data were genotyped in 3013 AD patients and 5075 controls from the Chinese Han population with the SequenomMassArray system. Association, Bayesian and bioinformatics analyses were used to identify possible causal indels and genes in the 5q22.1 region. Immunohistochemistry (IHC) was performed to observe protein expression in the tissues. PLINK 1.07 software was used for all statistical analyses. Results The genotyping and association analysis showed that six deletions and four SNPs were associated with AD (P Conclusions The study indicates that TMEM232 in the 5q22.1 region is the causal gene for AD in the Chinese Han population.

Objective Genome-wide association studies have identified many susceptibility loci for systemic lupus erythematosus (SLE). However, most of these loci are located in noncoding regions of the genome. Long noncoding RNAs (lncRNAs) are pervasively expressed and have been reported to be involved in various diseases. This study aimed to explore the genetic significance of lncRNAs in SLE. Methods A genome-wide survey of SLE risk variants in lncRNA gene loci was performed in Han Chinese subjects (4,556 with SLE and 9,451 healthy controls). The functional relevance of an SLE risk variant in one of the lncRNA genes was explored using biochemical and molecular cell biology analyses. In vitro loss-of-function and gain-of-function strategies were used to clarify the functional and phenotypic relevance of this SLE susceptibility lncRNA. Moreover, correlation of this lncRNA with the degree of apoptosis in the peripheral blood of SLE patients was evaluated. Results A novel SLE susceptibility locus in a lncRNA gene, designated SLEAR (for SLE-associated RNA), was identified at the single-nucleotide polymorphism rs13259960 (odds ratio 1.35, Pcombined = 1.03 × 10-11 ). The A>G variation at rs13259960, located in an intronic enhancer, was found to impair STAT1 recruitment to the enhancer that loops to the SLEAR promoter, resulting in decreased SLEAR production in peripheral blood mononuclear cells from patients with SLE (3 with the G/G genotype, 22 with A/G, and 103 with A/A at rs13259960; P = 0.0241). Moreover, SLEAR interacted with the RNA binding proteins interleukin enhancer binding factor 2, heterogeneous nuclear RNP F, and TATA-binding protein-associated factor 15, to form a complex for transcriptional activation of the downstream antiapoptotic genes. In addition, SLEAR regulated apoptosis of Jurkat cells in vitro, and its expression level was correlated with the degree of cell death in the peripheral blood of patients with SLE (r = 0.824, P = 2.15 × 10-8 ; n = 30). Conclusion These findings suggest a mechanism by which the risk variant at rs13259960 modulates SLEAR expression and confers a predisposition to SLE. Taken together, these results may give insights into the etiology of SLE.

The human major histocompatibility complex (MHC) region has been shown to be associated with numerous diseases. However, it remains a challenge to pinpoint the causal variants for these associations because of the extreme complexity of the region. We thus sequenced the entire 5-Mb MHC region in 20,635 individuals of Han Chinese ancestry (10,689 controls and 9,946 patients with psoriasis) and constructed a Han-MHC database that includes both variants and HLA gene typing results of high accuracy. We further identified multiple independent new susceptibility loci in HLA-C, HLA-B, HLA-DPB1 and BTNL2 and an intergenic variant, rs118179173, associated with psoriasis and confirmed the well-established risk allele HLA-C*06:02. We anticipate that our Han-MHC reference panel built by deep sequencing of a large number of samples will serve as a useful tool for investigating the role of the MHC region in a variety of diseases and thus advance understanding of the pathogenesis of these disorders.