Integrating deep phenotyping with genetic analysis: a comprehensive workflow for diagnosis and management of rare bone diseases.

Phenotypes play a fundamental role in medical genetics, serving as external manifestations of underlying genotypes. Deep phenotyping, a cornerstone of precision medicine, involves precise multi-system phenotype assessments, facilitating disease subtyping and genetic understanding. Despite their significance, the field lacks standardized protocols for accurate phenotype evaluation, hindering clinical comprehension and research comparability. We present a comprehensive workflow of deep phenotyping for rare bone diseases from the Genetics Clinic of Skeletal Deformity at Peking Union Medical College Hospital. Our workflow integrates referral, informed consent, and detailed phenotype evaluation through HPO standards, capturing nuanced phenotypic characteristics using clinical examinations, questionnaires, and multimedia documentation. Genetic testing and counseling follow, based on deep phenotyping results, ensuring personalized interventions. Multidisciplinary team consultations facilitate comprehensive patient care and clinical guideline development. Regular follow-up visits emphasize dynamic phenotype reassessment, ensuring treatment strategies remain responsive to evolving patient needs. In conclusion, this study highlights the importance of deep phenotyping in rare bone diseases, offering a standardized framework for phenotype evaluation, genetic analysis, and multidisciplinary intervention. By enhancing clinical care and research outcomes, this approach contributes to the advancement of precision medicine in the field of medical genetics.

ATF3 as a potential diagnostic marker of early-stage osteoarthritis and its correlation with immune infiltration through bioinformatics analysis.

AIMS: This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. METHODS: The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed. RESULTS: A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018). CONCLUSION: ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression.Cite this article: Bone Joint Res 2022;11(9):679-689.

Efficacy of hybrid minimally invasive esophagectomy vs open esophagectomy for esophageal cancer: A meta-analysis.

BACKGROUND: The first line treatment regimen for esophageal cancer is still surgical resection and the choice of surgical scheme depends on surgeon. Now the efficacy comparison of hybrid minimally invasive esophagectomy (HMIE) and open esophagectomy (OE) is still controversial. AIM: To compare the perioperative and postoperative outcomes of HMIE and OE in patients with esophageal cancer. METHODS: PubMed, EMBASE, and Cochrane Library databases were searched for related articles. The odds ratio (OR) or standard mean difference (SMD) with a 95% confidence interval (CI) was used to evaluate the effectiveness of HMIE and OE. RESULTS: Seventeen studies including a total of 2397 patients were selected. HMIE was significantly associated with less blood loss (SMD = -0.43, 95%CI: -0.66, -0.20; P = 0.0002) and lower incidence of pulmonary complications (OR = 0.72, 95%CI: 0.57, 0.90; P = 0.004). No significant differences were seen in the lymph node yield (SMD = 0.11, 95%CI: -0.08, 0.30; P = 0.26), operation time (SMD = 0.24, 95%CI: -0.14, 0.61; P = 0.22), total complications rate (OR = 0.68, 95%CI: 0.46, 0.99; P = 0.05), cardiac complication rate (OR = 0.91, 95%CI: 0.62, 1.34; P = 0.64), anastomotic leak rate (OR = 0.95, 95%CI: 0.67, 1.35; P = 0.78), duration of intensive care unit stay (SMD = -0.01, 95%CI: -0.21, 0.19; P = 0.93), duration of hospital stay (SMD = -0.13, 95%CI: -0.28, 0.01; P = 0.08), and total mortality rates (OR = 0.70, 95%CI: 0.47, 1.06; P = 0.09) between the two treatment groups. CONCLUSION: Compared with the OE, HMIE shows less blood loss and pulmonary complications. However, further studies are necessary to evaluate the long-term oncologic outcomes of HMIE.

The efficacy comparison of carvedilol plus endoscopic variceal ligation and traditional, nonselective ß-blockers plus endoscopic variceal ligation in cirrhosis patients for the prevention of variceal rebleeding: a meta-analysis.

BACKGROUND: Currently, the first-line treatment regimen in cirrhotic patients for variceal rebleeding prophylaxis is still under debate. AIM: This study aimed to compare the efficacy and safety of carvedilol plus endoscopic variceal ligation (EVL) and traditional, nonselective ß-blockers (NSBBs) plus EVL in preventing variceal rebleeding. PATIENTS AND METHODS: Studies were found in PubMed, the Cochrane Library, China National Knowledge Infrastructure, Wanfang Med Online, and Wiper Database. Review Manager 5.3 was used to analyze the relevant data. RESULTS: Nine trials including 802 patients were identified (402 for carvedilol and 400 for traditional NSBBs). Carvedilol was more efficacious than traditional NSBBs in decreasing the variceal rebleeding rate [odds ratio (OR): 0.53; 95% confidence interval (CI): 0.38-0.75; P = 0.0003], lowering the degree of esophageal varices (OR: 4.40; 95% CI: 2.64-7.34; P < 0.00001), decreasing the mean arterial pressure (standard mean difference: - 0.35; 95% CI: - 0.56 to - 0.14; P = 0.0009), reducing the total adverse events occurrence (OR: 0.39; 95% CI: 0.28-0.53; P < 0.00001), and decreasing drug-related adverse events (OR: 0.37; 95% CI: 0.25-0.56; P < 0.00001). No difference was noted between carvedilol and traditional NSBBs with respect to mortality and heart rate (OR: 0.72; 95% CI: 0.43; 1.22; P = 0.22 and standard mean difference: 0.09; 95% CI: - 0.12 to 0.30; P = 0.40, respectively). CONCLUSION: Combined with variceal ligation, carvedilol was more effective and safer than traditional NSBBs in the prevention of rebleeding in cirrhotic patients.

Efficacy and Safety of Tenofovir Disoproxil Treatment for Chronic Hepatitis B Patients with Genotypic Resistance to Other Nucleoside Analogues: A Prospective Study.

BACKGROUND: Tenofovir disoproxil (TDF) is a promising salvage therapy for patients with chronic hepatitis B (CHB) who failed regimens of other nucleoside analogues (NAs). In this study, we aimed to investigate the clinical efficacy and safety of TDF monotherapy in Chinese CHB patients with genotypic resistance. METHODS: A total of 33 CHB patients who had failed treatment with other NAs and had genotypic resistance were switched to TDF monotherapy for 48 weeks. Patients' demographic data (age, sex, history of hepatitis B virus [HBV] therapy), laboratory testing results (hepatitis B e antigen [HBeAg] status, HBV DNA levels, alanine aminotransferase [ALT] levels, serum creatinine, urinary protein, genotypic assay), clinical symptoms, and liver color ultrasound examinations were collected for evaluation at day 0 (baseline) and the 12th, 24th, 36th, and 48th weeks after initiating treatment. Statistical analyses were carried out using rank sum test or rank correlation. RESULTS: With regard to efficacy, the study found that all patients who switched to TDF monotherapy had undetectable HBV DNA levels after 48 weeks. In addition, patients with lower baseline HBV DNA levels realized earlier virological undetectability (rs = 0.39, P = 0.030). ALT levels were normal in 30 of 33 patients (91%). HBeAg negative conversion occurred in 7 of 25 patients (28%), among whom HBeAg seroconversion (12%) and HBeAg seroclearance (16%) occurred. The time of complete virological response was significantly affected by the number of resistance loci (rs = 0.36, P = 0.040). Concerning safety, the study found that no adverse events were observed during the 48 weeks. CONCLUSION: TDF monotherapy is an effective and safe salvage treatment for CHB patients who are resistant to other NAs.

Metabolite variations between acute-on-chronic liver failure and chronic liver failure caused by hepatitis B virus based on ultra-performance liquid chromatography mass spectrometry.

OBJECTIVE: The present study aims to compare serum metabolite alterations between acute-on-chronic liver failure (ACLF) and chronic liver failure (CLF), and find the specific biomarkers associated with the diseases. METHODS: Serum samples were collected from patients with ACLF (n=76) and CLF (n=56) as well as healthy individuals (n=20) and assayed by ultra-performance liquid chromatography mass spectrometry (UPLC-MS). The acquired data was analyzed using principal components analysis (PCA) and partial least squares discriminate analysis (PLS-DA). RESULTS: The PLS-DA model with satisfactory explanatory and predictive ability (R2=0.979, Q2=0.918) is capable of discriminate ACLF patients from CLF patients. Significant difference in the metabolomics among the three groups was observed, metabolites that decreased significantly in the serum of ACLF and CLF included phosphatidylcholines (PCs) and lysophosphatidylcholines (LPCs), whereas conjugated bile acids (GCDCA, GUDCA) increased significantly, these metabolites considered as common biomarkers of liver failure. Linoleyl carnitine showed significant increase in CLF compared with controls while no significant change was observed in ACLF, it could be special biomarkers of ACLF and CLF. CONCLUSION: Metabolomics based on ultra-performance liquid chromatography mass spectrometry provide a new way to diagnose and reveal the pathogenesis of ACLF and CLF.

A serum metabolomic analysis for diagnosis and biomarker discovery of primary biliary cirrhosis and autoimmune hepatitis.

BACKGROUND: Because of the diversity of the clinical and laboratory manifestations, the diagnosis of autoimmune liver disease (AILD) remains a challenge in clinical practice. The value of metabolomics has been studied in the diagnosis of many diseases. The present study aimed to determine whether the metabolic profiles, based on ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), differed between autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), to identify specific metabolomic markers, and to establish a model for the diagnosis of AIH and PBC. METHODS: Serum samples were collected from 20 patients with PBC, 19 patients with AIH, and 25 healthy individuals. UPLC-MS data of the samples were analyzed using principal component analysis, partial least squares discrimination analysis and orthogonal partial least squares discrimination analysis. RESULTS: The partial least squares discrimination analysis model (R2Y=0.991, Q2=0.943) was established between the AIH and PBC groups and exhibited both sensitivity and specificity of 100%. Five groups of biomarkers were identified, including bile acids, free fatty acids, phosphatidylcholines, lysolecithins and sphingomyelin. Bile acids significantly increased in the AIH and PBC groups compared with the healthy control group. The other biomarkers decreased in the AIH and PBC groups compared with those in the healthy control group. In addition, the biomarkers were downregulated in the AIH group compared with the PBC group. CONCLUSIONS: The biomarkers identified revealed the pathophysiological changes in AILD and helped to discriminate between AIH and PBC. The predictability of this method suggests its potential application in the diagnosis of AILD.