Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder.

OBJECTIVE: The genome-wide association studies (GWAS) analysis, the most successful technique for discovering disease-related genetic variation, has some statistical concerns, including multiple testing, the correlation among variants (single-nucleotide polymorphisms) based on linkage disequilibrium and omitting the important variants when fitting the model with just one variant. To eliminate these problems in a small sample-size study, we used a sparse Bayesian learning model for finding bipolar disorder (BD) genetic variants. METHODS: This study used the Wellcome Trust Case Control Consortium data set, including 1998 BD cases and 1500 control samples, and after quality control, 380,628 variants were analysed. In this GWAS, a Bayesian logistic model with hierarchical shrinkage spike and slab priors was used, with all variants considered simultaneously in one model. In order to decrease the computational burden, an alternative inferential method, Bayesian variational inference, has been used. RESULTS: Thirteen variants were selected as associated with BD. The three of them (rs7572953, rs1378850 and rs4148944) were reported in previous GWAS. Eight of which were related to hemogram parameters, such as lymphocyte percentage, plateletcrit and haemoglobin concentration. Among selected related genes, GABPA, ELF3 and JAM2 were enriched in the platelet-derived growth factor pathway. These three genes, along with APP, ARL8A, CDH23 and GPR37L1, could be differential diagnostic variants for BD. CONCLUSIONS: By reducing the statistical restrictions of GWAS analysis, the application of the Bayesian variational spike and slab models can offer insight into the genetic link with BD even with a small sample size. To uncover related variations with other traits, this model needs to be further examined.

Predictive Factors for Length of Stay in Patients Undergoing Total Hip Arthroplasty: A Cross-Sectional Study.

Background: Total hip arthroplasty (THA) is an effective surgery for patients with end-stage hip joint degenerative arthritis. This study aimed to determine peri-operative factors that impact the length of stay (LOS) and design a formula to predict LOS in patients undergoing THA. Methods: This cross-sectional study was performed from September 2019 to January 2020. For this study, all patients who underwent THA over a period of 12 years since 2005 were included in the study. Data about the LOS and several variables including demographic variables, surgery-related variables, transfusion, intensive care unit (ICU) admission, past drug history, comorbidities, and laboratory data, were gathered. Qualitative variables are presented as numbers (%), and quantitative variables are presented as mean Mann± standard deviation. Mann Whitney test , Kruskal-Wallis test, and Spearman's rank correlation test were also used. Results: A total of 524 patients were included in the study; 12 were excluded .261 (51%) were female and 251(49%) male. The mean age was 56.13±17.04 years. In the univariate analysis, the day of admission, surgery indication, transfusion, diabetes mellitus, oral anti-diabetic drugs, American Society of Anesthesiology (ASA) score, preoperative hemoglobin (Hb) level, and type of prosthesis showed significant relation with LOS. Significant variables entered to zero truncated negative binomial regression. Among them, the day of admission, ASA score, preoperative Hb level, and type of prosthesis showed significant relation with LOS (P < 0.05) and were used for model design. Conclusion: Preoperative Hb level, ASA score, day of admission, and prosthesis type have an impact on LOS and can predict LOS in patients who are candidates for THA.

Comparison of dental and skeletal indices between patients under haemodialysis and peritoneal dialysis with healthy individuals in digital panoramic radiography.

OBJECTIVE: The aim was to compare dental and skeletal indices in panoramic radiography between patients undergoing haemodialysis, peritoneal dialysis and age- and sex-matched control group. METHODS: In this comparative cross-sectional study, quantitative Indices including Antegonial Index (AI), Mental Index (MI), Panoramic Mandibular Index (PMI) and qualitative indices including Mandibular Cortical Index (MCI) and Trabecular Pattern (TP) were evaluated in panoramic images of 32 haemodialysis patients, 14 patients under peritoneal dialysis and 52 healthy individuals. The images were also investigated for pulp canal calcification, pulp stones, soft tissue calcification, changes in or loss of lamina dura, radiolucencies associated with brown tumour and ridge resorption. The indices were compared between the three groups and were investigated for association with the patients' blood test parameters and their diseases causing chronic renal failure (CRF). Intraobserver agreement for the 2-week interval of assessment was calculated for the indices. RESULTS: MI (p = 0.574) and PMI (p = 0.100) were not significantly different, but AI (p = 0.01), MCI (p < 0.001) and TP (p = 0.002) were significantly different between the two case groups and the control group. The prevalence of pulp calcification (p = 0.03) and ridge resorption (p = 0.005) was higher in the haemodialysis group. Soft tissue calcification (p = 0.85) and lamina dura changes (p = 0.9) showed no significant difference. Brown tumours were observed in only one case in the haemodialysis group. CONCLUSIONS: AI, MCI and TP showed a reduction in mineral density of the cortical and trabecular bone in CRF patients and more severely in patients under haemodialysis than those under peritoneal dialysis.