Immune-related gene IL17RA as a diagnostic marker in osteoporosis.

Objectives: Bone immune disorders are major contributors to osteoporosis development. This study aims to identify potential diagnostic markers and molecular targets for osteoporosis treatment from an immunological perspective. Method: We downloaded dataset GSE56116 from the Gene Expression Omnibus database, and identified differentially expressed genes (DEGs) between normal and osteoporosis groups. Subsequently, differentially expressed immune-related genes (DEIRGs) were identified, and a functional enrichment analysis was performed. A protein-protein interaction network was also constructed based on data from STRING database to identify hub genes. Following external validation using an additional dataset (GSE35959), effective biomarkers were confirmed using RT-qPCR and immunohistochemical (IHC) staining. ROC curves were constructed to validate the diagnostic values of the identified biomarkers. Finally, a ceRNA and a transcription factor network was constructed, and a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed to explore the biological functions of these diagnostic markers. Results: In total, 307 and 31 DEGs and DEIRGs were identified, respectively. The enrichment analysis revealed that the DEIRGs are mainly associated with Gene Ontology terms of positive regulation of MAPK cascade, granulocyte chemotaxis, and cytokine receptor. protein-protein interaction network analysis revealed 10 hub genes: FGF8, KL, CCL3, FGF4, IL9, FGF9, BMP7, IL17RA, IL12RB2, CD40LG. The expression level of IL17RA was also found to be significantly high. RT-qPCR and immunohistochemical results showed that the expression of IL17RA was significantly higher in osteoporosis patients compared to the normal group, as evidenced by the area under the curve Area Under Curve of 0.802. Then, we constructed NEAT1-hsa-miR-128-3p-IL17RA, and SNHG1-hsa-miR-128-3p-IL17RA ceRNA networks in addition to ERF-IL17RA, IRF8-IL17RA, POLR2A-IL17RA and ERG-IL17RA transcriptional networks. Finally, functional enrichment analysis revealed that IL17RA was involved in the development and progression of osteoporosis by regulating local immune and inflammatory processes in bone tissue. Conclusion: This study identifies the immune-related gene IL17RA as a diagnostic marker of osteoporosis from an immunological perspective, and provides insight into its biological function.

Comprehensive analysis of senescence-related genes and immune infiltration in intervertebral disc degeneration: a meta-data approach utilizing bulk and single-cell RNA sequencing data.

Objectives: This study aims to identify the key senescence genes and potential regulatory mechanisms that contribute to the etiology of intervertebral disc degeneration (IDD). Method: We analyzed GSE34095 and GSE70362 datasets, identifying key senescence-related differentially expressed genes (DEGs) in IDD using lasso regression. Risk scores classified patients into high- and low-risk groups. We compared pathways, functions, and immune infiltration between these groups. Diagnostic ability was assessed using ROC curves and a nomogram predicted IDD incidence. In single-cell dataset GSE165722, we evaluated expression of key senescence-related DEGs. Results: We identified 12 key senescence-related DEGs distinguishing high- and low-risk IDD patients. Enrichment analysis revealed cellular stress response, apoptotic signaling pathway, and protein kinase activation differences. Immune cell analysis showed elevated eosinophils in low-risk group and increased effector memory CD8 T, central memory CD4 T, myeloid-derived suppressor, natural killer, monocyte, Type 1 T helper, plasmacytoid dendritic, and natural killer T cells in high-risk group. A nomogram using AUC >0.75 genes (CXCL8, MAP4K4, MINK1, and TNIK) predicted IDD incidence with good diagnostic power. High senescence scores were observed in neutrophils. Conclusion: Our diagnostic model, based on key senescence-related DEGs and immune cell infiltration, offers new insights into IDD pathogenesis and immunotherapy strategies.

BRD4 Inhibition Suppresses Senescence and Apoptosis of Nucleus Pulposus Cells by Inducing Autophagy during Intervertebral Disc Degeneration: An In Vitro and In Vivo Study.

Intervertebral disc degeneration (IDD) is the most common chronic skeletal muscle degeneration disease. Although the underlying mechanisms remain unclear, nucleus pulposus (NP) autophagy, senescence, and apoptosis are known to play a critical role in this process. Previous studies suggest that bromodomain-containing protein 4 (BRD4) promotes senescent and apoptotic effects in several age-related degenerative diseases. It is not known, however, if BRD4 inhibition is protective in IDD. In this study, we explored whether BRD4 influenced IDD. In human clinical specimens, the BRD4 level was markedly increased with the increasing Pfirrmann grade. At the cellular level, BRD4 inhibition prevented IL-1ß-induced senescence and apoptosis of NP cells and activated autophagy via the AMPK/mTOR/ULK1 signaling pathway. Inhibition of autophagy by 3-methyladenine (3-MA) partially reversed the antisenescence and antiapoptotic effects of BRD4. In vivo, BRD4 inhibition attenuated IDD. Taken together, the results of this study showed that BRD4 inhibition reduced NP cell senescence and apoptosis by induced autophagy, which ultimately alleviated IDD. Therefore, BRD4 may serve as a novel potential therapeutic target for the treatment of IDD.

An Immune-Related Long Non-Coding RNA Signature to Predict the Prognosis of Ewing's Sarcoma Based on a Machine Learning Iterative Lasso Regression.

The aim of this study was to construct a new immune-associated long non-coding RNA (lncRNA) signature to predict the prognosis of Ewing sarcoma (ES) and explore its molecular mechanisms. We downloaded transcriptome and clinical prognosis data from the Gene Expression Omnibus (GSE17679, which included 88 ES samples and 18 matched normal skeletal muscle samples), and used it as a training set to identify immune-related lncRNAs with different expression levels in ES. Univariable Cox regression was used to screen immune-related lncRNAs related to ES prognosis, and an immune-related lncRNA signature was constructed based on machine learning iterative lasso regression. An external verification set was used to confirm the predictive ability of the signature. Clinical feature subgroup analysis was used to explore whether the signature was an independent prognostic factor. In addition, CIBERSORT was used to explore immune cell infiltration in the high- and low-risk groups, and to analyze the correlations between the lncRNA signature and immune cell levels. Gene set enrichment and variation analyses were used to explore the possible regulatory mechanisms of the immune-related lncRNAs in ES. We also analyzed the expression of 17 common immunotherapy targets in the high- and low-risk groups to identify any that may be regulated by immune-related lncRNAs. We screened 35 immune-related lncRNAs by univariate Cox regression. Based on this, an immune-related 11-lncRNA signature was generated by machine learning iterative lasso regression. Analysis of the external validation set confirmed its high predictive ability. DPP10 antisense RNA 3 was negatively correlated with resting dendritic cell, neutrophil, and γδ T cell infiltration, and long intergenic non-protein coding RNA 1398 was positively correlated with resting dendritic cells and M2 macrophages. These lncRNAs may affect ES prognosis by regulating GSE17721_CTRL_VS_PAM3CSK4_12H_BMDC_UP, GSE2770_IL4_ACT_VS_ACT_CD4_TCELL_48H_UP, GSE29615_CTRL_VS_DAY3_ LAIV_IFLU_VACCINE_PBMC_UP, complement signaling, interleukin 2-signal transducer and activator of transcription 5 signaling, and protein secretion. The immune-related 11-lncRNA signature may also have regulatory effects on the immunotherapy targets CD40 molecule, CD70 molecule, and CD276 molecule. In conclusion, we constructed a new immune-related 11-lncRNA signature that can stratify the prognoses of patients with ES.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients.

BACKGROUND: Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients. METHODS: We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration. RESULTS: We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells. CONCLUSION: The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration.

Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.

Different Types of Double-Level Degenerative Lumber Spondylolisthesis: What Is Different in the Sagittal Plane?

BACKGROUND: Degenerative lumber spondylolisthesis (DLS) is a common orthopedic condition, described as a condition that compared with the lower vertebra, the superior vertebra slides forward or backward in the sagittal plane without accompanying isthmic spondylolisthesis. Information pertaining to different types of double-level DLS is scarce. This study aims to analyze parameters of patients with different types of double-level DLS to provide a reference for guiding surgical treatment and restoring sagittal balance of patients with DLS. METHODS: From January 2014 to January 2020, records of patients with double-level DLS were retrospectively reviewed. Patients with double-level DLS were divided into 3 types: anterior, posterior, and combined; the anterior and combined types were studied. The sagittal spinopelvic parameters included C7 tilt, maximal thoracic kyphosis, maximal lumbar lordosis (LLmax), pelvic incidence (PI), pelvic tilt (PT), and sacral slope (SS). After descriptive analysis, demographic and radiographic data were compared. RESULTS: Forty and 18 patients were included in the anterior and combined type groups, respectively. Both groups had different levels of chronic low back pain, but the incidence of radiating leg pain and neurogenic claudication was significantly higher in the anterior type. Oswestry Disability Index and visual analog scale low back scores were also higher in the anterior type. In the anterior type, C7 tilt (7.14 ± 2.15 vs. 5.41 ± 2.28, P = 0.007), LLmax (50.02 ± 14.76 vs. 36.96 ± 14.56, P = 0.003), PI (68.28 ± 9.16 vs. 55.53 ± 14.19, P < 0.001), PT (28.68 ± 7.31 vs. 19.38 ± 4.70, P < 0.001), and PT/PI (42.45 ± 11.22 vs. 36.04 ± 9.87, P = 0.041) were significantly higher. In the anterior type, PI correlated positively with LLmax (r = 0.59) and SS (r = 0.71). LLmax and SS (r = 0.65) had a positive correlation. PT/PI and SS (r = -0.77) had a negative correlation. In the combined type, PI correlated positively with LLmax (r = 0.61) and SS (r = 0.88), and PT/PI correlated negatively with SS (r = -0.81). CONCLUSIONS: In patients with double-level DLS, the sagittal spinopelvic parameters differed between the anterior and combined types. Overall, spinal surgeons should focus on correcting sagittal deformities, relieving postoperative clinical symptoms, and improving quality of life during fusion surgery.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs). METHODS: We analyzed the ES gene expression profile dataset, GSE17679, from the GEO database and extracted differential expressed IRGs (DEIRGs). Then, we conducted functional correlation and protein-protein interaction (PPI) analyses of the DEIRGs and used the machine learning algorithm-iterative Lasso Cox regression analysis to build an optimal DEIRG signature. In addition, we applied ES samples from the ICGC database to test the optimal gene signature. We performed univariate and multivariate Cox regressions on clinicopathological characteristics and optimal gene signature to evaluate whether signature is an important prognostic factor. Finally, we calculated the infiltration of 24 immune cells in ES using the ssGSEA algorithm, and analyzed the correlation between the DEIRGs in the optimal gene signature and immune cells. RESULTS: A total of 249 DEIRGs were screened and an 11-gene signature with the strongest correlation with patient prognoses was analyzed using a machine learning algorithm. The 11-gene signature also had a high prognostic value in the ES external verification set. Univariate and multivariate Cox regression analyses showed that 11-gene signature is an independent prognostic factor. We found that macrophages and cytotoxic, CD8 T, NK, mast, B, NK CD56bright, TEM, TCM, and Th2 cells were significantly related to patient prognoses; the infiltration of cytotoxic and CD8 T cells in ES was significantly different. By correlating prognostic biomarkers with immune cell infiltration, we found that FABP4 and macrophages, and NDRG1 and Th2 cells had the strongest correlation. CONCLUSION: Overall, the IRG-related 11-gene signature can be used as a reliable ES prognostic biomarker and can provide guidance for personalized ES therapy.

Development of a novel immune-related genes prognostic signature for osteosarcoma.

Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature's prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients.

Sirtuins and intervertebral disc degeneration: Roles in inflammation, oxidative stress, and mitochondrial function.

Intervertebral disc degeneration (IDD) is one of the main causes of low back pain, which seriously reduces the quality of life of patients and places a heavy economic burden on their families. Cellular senescence is considered to be an important factor leading to IDD, and inflammatory response, oxidative stress, and mitochondrial dysfunction are closely related to intervertebral disc (IVD) senescence. Therefore, inhibition of the inflammatory response and oxidative stress, along with maintaining mitochondrial function, may be useful in treating IDD. The sirtuins are a family of evolutionarily conserved nicotinamide adenine dinucleotide (NAD+)-dependent histone deacetylases, which are the major molecules mediating life extension or delay of aging-related diseases. The sirtuin protein family consist of seven members (SIRT1 - 7), which are mainly involved in various aging-related diseases by regulating inflammation, oxidative stress, and mitochondrial function. Among them, SIRT1, SIRT2, SIRT3, and SIRT6 are closely related to IDD. In addition, some activators of sirtuin proteins, such as resveratrol, melatonin, magnolol, 1,4-dihydropyridine (DHP), SRT1720, and nicotinamide mononucleotide (NMN), have been evaluated in preclinical studies for their effects in preventing IDD. This review described the biological functions of sirtuins and the important roles of SIRT1, SIRT2, SIRT3, and SIRT6 in IDD by regulating oxidative stress, inflammatory response, and mitochondrial function. In addition, we introduce the status of some sirtuin activators in IDD preclinical studies. This review will provide a background for further clarification of the molecular mechanism underlying IDD and the development of potential therapeutic drugs.

GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration.

This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

[Anterior versus posterior decompression for the treatment of thoracolumbar fractures with spinal cord injury:a Meta-analysis].

OBJECTIVE: To systematically evaluate the efficacy and safety of anterior decompression and posterior decompression in the treatment of thoracolumbar fractures with spinal cord injury, so as to provide a good scientific basis for more effective treatment of thoracolumbar fractures with spinal cord injury. METHODS: A clinical data about comparative study of anterior decompression and posterior decompression in the treatment of thoracolumbar fractures with spinal cord injury was searched and collected. The databases of Pubmed, Embase, Cochrane Library, CNKI, CBM, Wanfang Medical Network were searched by computer. Artificially collected journals included Spine, European Spine Journal, The Journal of Bone and Joint Surgery. Two spine surgeons independently screened the literature according to established inclusion and exclusion criteria and assessed the quality of the included studies. Meta-analysis was performed on the data using Review Manager 5.3 software, the indicators included operative time, intraoperative blood loss, postoperative tactile score, postoperative motor score, postoperative vertebral height, hospitalization time, neurological function recovery, efficiency of treatment, postoperative complications. RESULTS: Fifteen randomized controlled trials (RCTs) were enrolled in a total of 1 360 patients, including 680 anterior decompression and 680 posterior decompression. The results of Meta-analysis showed that the anterior decompression group had longer operation time [MD=80.09, 95% CI(36.83, 123.34), P=0.000 3], more intraoperative blood loss [MD=225.21, 95%CI(171.07, 279.35), P<0.000 01], longer hospitalization time [MD=2.31, 95% CI(0.32, 4.31), P=0.02]. And the postoperative tactile score [MD=13.39, 95% CI(9.86, 16.92), P<0.000 01], postoperative motor score [MD=13.15, 95% CI(7.02, 19.29), P<0.000 1], vertebral height [MD=1.36, 95% CI(0.79, 1.92), P<0.000 01] in anterior decompression were higher than that in posterior decompression. There was no statistically significant differences in the efficacy of treatment [OR=1.14, 95% CI(0.56, 2.31), P=0.72], neurological recovery [OR=0.87, 95% CI(0.57, 1.33), P=0.52] between two groups. CONCLUSIONS: Compared with posterior decompression, the anterior decompression has the advantages of longer operating time, more intraoperative blood loss, longer hospitalization time, higher postoperative tactile score, higher postoperative motor score, and higher injury vertebral height, But there was no significant difference in the treatment efficiency and nerve function recovery between two groups.

Polymorphism analyses of 19 STRs in Labrador Retriever population from China and its heterozygosity comparisons with other retriever breeds.

Pure breed dogs of Western origin are increasingly more popular in China as is a need to differentiate breeds and individual dogs for personal and forensic reasons. Research on genetic diversities of the canine population in China is rarely conducted. In this study, genetic distributions and forensic efficiencies of 19 canine STR loci in Labrador Retriever population from China were evaluated by using one available commercial canine kit in China. This panel was used to genetically define 214 Labrador Retrievers in China, as an example of one of the most important Western breeds and to compare them with Labrador Retrievers from America based on three overlapping STR loci. Moreover, genetic relationship analyses between Labrador Retriever population and two reference populations in America were performed. All 19 STR loci were polymorphic and conformed to Hardy-Weinberg equilibrium in the studied population. The STR panel was able to discern individual dogs with a high degree of accuracy. Breed-wide genetic heterozygosity comparisons based on present and published allele frequencies revealed that the studied population had the lower genetic heterozygosity than canine populations in America. Principal component analysis among Labrador Retriever population and other reference populations showed that the studied Labrador Retrievers were genetically close to the retriever breeds in America. Population genetic structure analyses among these canine breeds further revealed genetic differentiations between the studied Labrador Retriever population and other compared breeds. In conclusion, these STR loci had relatively high forensic values in Labrador Retriever population in China, which could be employed for individual identification and kinship testing.

Evaluation of the MiSeq FGx system for use in forensic casework.

Capillary electrophoresis (CE) is widely used in forensic genetics to study short tandem repeats (STRs). Recently, next-generation sequencing (NGS) platforms have facilitated the development of new strategies for forensic DNA typing. Several studies have shown that NGS successfully analyzes challenging samples. However, because NGS is complicated and time-consuming, it remains unclear whether NGS platforms offer significant advantages over CE for all forensic cases. Here, the MiSeq FGx system was used to test some cases that had previously been analyzed using CE. These cases included paternity test cases in which some samples exhibited locus inconsistencies; samples with off-ladder (OL) alleles; samples with triallelic patterns; and samples with amelogenin test abnormalities. The results generated by MiSeq FGx were compared to those previously generated by CE. The MiSeq FGx and CE results were consistent with the exception of three samples, where inconsistencies were observed at the Penta D locus. For all three incongruent samples, the MiSeq FGx results were correct. Sequence analysis indicated that, in two cases, mismatches were due to undetected alleles rather than mutations. In two additional cases, mutation sources were identified, and in a fifth case, mutation step size was reconsidered. MiSeq FGx was used to identify OL alleles and samples with amelogenin test abnormalities. For cases where verification was required via CE analysis, the simultaneous NGS amplification of several types of multiple genetic markers improved testing efficiency. In addition, we identified additional sequence variants at autosomal, Y chromosomal, and X chromosomal STR loci in the Han Chinese population from northern China. Our results will be useful for future forensic analyses of STR genotypes in Chinese populations. It is likely that NGS would be more widely used in forensic genetics if costs and procedure complexity were reduced.

Single nucleotide polymorphisms of mitochondrial DNA HVS-I and HVS-II in Chinese Bai ethnic group.

For forensic and population genetic purposes, a total of 125 unrelated volunteers' blood samples were collected from Chinese Bai ethnic minority group to analyze sequence variation of two hypervariable segments (HVS-I and HVS-II) in the mitochondrial DNA control region. Comparing the HVS-I and HVS-II sequences of the 125 Chinese Bais to the Anderson reference sequence, we found 86 polymorphic loci in HVS-I and 40 in HVS-II in mitochondrial DNA sequences of the Chinese Bai ethnic minority group, which defined 93 and 53 different haplotypes, respectively. Haplotype diversity and the mean pairwise differences were 0.992 ± 0.003 and 6.553 in HVS-I, and 0.877 ± 0.027 and 2.407 in HVS-II, respectively. We defined four macrohaplogroups R, M, N and D with the proportions ranging from 9.6% to 40.0%. With the analysis of the hypervariable domain from nucleotide 16 180-16 193 in HVS-I, our study revealed new haplotypes of sequence variations. In addition, the Fst metric, phylogenetic tree, and principal component analysis demonstrated a close genetic relationship between the Bai group and Chinese Han populations from South China, Changsha, and Guangdong. The results support that the Bai group is a multiorigin ethnic minority that has merged with the Chinese Han population.

[Genetic polymorphisms of 16 STR loci in Tibetan Mastiff].

OBJECTIVE: To explore the genetic polymorphisms of 16 STR loci from 449 Tibetan Mastiffs in order to set up gene polymorphism database of Tibetan Mastiff. METHODS: The PCR amplification was performed using the 16 STR loci fluorescent multiple amplification kit for dog. The amplified products were detected and statistically analyzed. RESULTS: In the 16 STR loci from 449 Tibetan Mastiffs, CDP was 0.999 999 999 999 999 and CEP was 0.999 997 795. Except FH2010 (10 alleles), PEZ21 (12 alleles), and PEZ05 (13 alleles), the other STR loci had more than 15 alleles. In the 16 STR loci, H was > 0.5 and PIC was > 0.7. CONCLUSION: The 16 STR loci have high polymorphism to be suitable for individual identification and paternity testing of Tibetan Mastiff. The data obtained through this study can be used to establish DNA polymorphism database of Tibetan Mastiff.

Identification of a novel human leukocyte antigen allele B∗46:34.

A new human leukocyte antigen (HLA) B allele was found in a healthy male Chinese Kazak individual. Sequencing-based typing (SBT) was used to identify and analyze the difference between the new allele and the closest matching HLA-B allele. HLA-B(∗)46 new allele has 1nt change from B(∗)46:01:01 at nt 853 where G->C (condon 260 GTA->CTA), resulting in a coding change: 260 Val is changed to Leu. The new HLA-B(∗)46:34 allele was identified, and was named officially by the World Health Organization (WHO) Nomenclature Committee in June 2012. The GenBank sequence accession number is JX035785.

Genetic polymorphism analysis of 15 STR loci in Chinese Hui ethnic group residing in Qinghai province of China.

In the present study, we investigated the diversity distributions of allelic frequencies of 15 short tandem repeats (STRs) loci in a sample of Chinese Hui ethnic group in the Ningxia Hui Autonomous Region. The allelic frequencies of the 15 STR loci (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, vWA, TPOX, D18S51, D5S818 and FGA) were obtained from 2975 unrelated healthy Hui individuals. The STR genotyping data of all the samples were generated by DNA extraction, multiple amplification, GeneScan and genotype analysis. The genetic distances among different populations were calculated by using Nei's method and a phylogenetic tree was constructed based on the allelic frequencies of the same 15 STR loci using the neighbor-joining method. A total of 185 alleles were observed in the Hui population, with the corresponding allelic frequencies ranging from 0.0002 to 0.5322. Chi-Square tests showed that all STR loci were in Hardy-Weinberg equilibrium. The forensic statistical parameters of all the loci showed high values. The population data in this study were compared with the previously published population data from other ethnics or areas. The Hui population showed significant differences from the Minnan Han, Uigur, Ewenki, Yi, Tibetan, Maonan and Malay ethnic minority groups in some loci, and from the South Morocco population and the Moroccan population in all the loci. Our results are valuable for human individual identification and paternity testing in the Chinese Hui population and are expected to enrich the genetic information resources of Chinese populations.

Allele polymorphism and haplotype diversity of HLA-A, -B and -DRB1 loci in sequence-based typing for Chinese Uyghur ethnic group.

BACKGROUND: Previous studies indicate that the frequency distributions of HLA alleles and haplotypes vary from one ethnic group to another or between the members of the same ethnic group living in different geographic areas. It is necessary and meaningful to study the high-resolution allelic and haplotypic distributions of HLA loci in different groups. METHODOLOGY/PRINCIPAL FINDINGS: High-resolution HLA typing for the Uyghur ethnic minority group using polymerase chain reaction-sequence-based-typing method was first reported. HLA-A, -B and -DRB1 allelic distributions were determined in 104 unrelated healthy Uyghur individuals and haplotypic frequencies and linkage disequilibrium parameters for HLA loci were estimated using the maximum-likelihood method. A total of 35 HLA-A, 51 HLA-B and 33 HLA-DRB1 alleles were identified at the four-digit level in the population. High frequency alleles were HLA-A*1101 (13.46%), A*0201 (12.50%), A*0301 (10.10%); HLA-B*5101(8.17%), B*3501(6.73%), B*5001 (6.25%); HLA-DRB1*0701 (16.35%), DRB1*1501 (8.65%) and DRB1*0301 (7.69%). The two-locus haplotypes at the highest frequency were HLA-A*3001-B*1302 (2.88%), A*2402-B*5101 (2.86%); HLA-B*5001-DRB1*0701 (4.14%) and B*0702-DRB1*1501 (3.37%). The three-locus haplotype at the highest frequency was HLA-A*3001-B*1302-DRB1*0701(2.40%). Significantly high linkage disequilibrium was observed in six two-locus haplotypes, with their corresponding relative linkage disequilibrium parameters equal to 1. Neighbor-joining phylogenetic tree between the Uyghur group and other previously reported populations was constructed on the basis of standard genetic distances among the populations calculated using the four-digit sequence-level allelic frequencies at HLA-A, HLA-B and HLA-DRB1 loci. The phylogenetic analyses reveal that the Uyghur group belongs to the northwestern Chinese populations and is most closely related to the Xibe group, and then to Kirgiz, Hui, Mongolian and Northern Han. CONCLUSIONS/SIGNIFICANCE: The present findings could be useful to elucidate the genetic background of the population and to provide valuable data for HLA matching in clinical bone marrow transplantation, HLA-linked disease-association studies, population genetics, human identification and paternity tests in forensic sciences.