Post-natal gestational age assessment using targeted metabolites of neonatal heel prick and umbilical cord blood: A GARBH-Ini cohort study from North India.

Background: Accurate assessment of gestational age (GA) and identification of preterm birth (PTB) at delivery is essential to guide appropriate post-natal clinical care. Undoubtedly, dating ultrasound sonography (USG) is the gold standard to ascertain GA, but is not accessible to the majority of pregnant women in low- and middle-income countries (LMICs), particularly in rural areas and small secondary care hospitals. Conventional methods of post-natal GA assessment are not reliable at delivery and are further compounded by a lack of trained personnel to conduct them. We aimed to develop a population-specific GA model using integrated clinical and biochemical variables measured at delivery. Methods: We acquired metabolic profiles on paired neonatal heel prick (nHP) and umbilical cord blood (uCB) dried blood spot (DBS) samples (n = 1278). The master data set consists of 31 predictors from nHP and 24 from uCB after feature selection. These selected predictors including biochemical analytes, birth weight, and placental weight were considered for the development of population-specific GA estimation and birth outcome classification models using eXtreme Gradient Boosting (XGBoost) algorithm. Results: The nHP and uCB full model revealed root mean square error (RMSE) of 1.14 (95% confidence interval (CI) = 0.82-1.18) and of 1.26 (95% CI = 0.88-1.32) to estimate the GA as compared to actual GA, respectively. In addition, these models correctly estimated 87.9 to 92.5% of the infants within ±2 weeks of the actual GA. The classification models also performed as the best fit to discriminate the PTB from term birth (TB) infants with an area under curve (AUC) of 0.89 (95% CI = 0.84-0.94) for nHP and an AUC of 0.89 (95% CI = 0.85-0.95) for uCB. Conclusion: The biochemical analytes along with clinical variables in the nHP and uCB data sets provide higher accuracy in predicting GA. These models also performed as the best fit to identify PTB infants at delivery.

Association of HLA-DRB1 Alleles with Rheumatic Fever and Rheumatic Heart Disease: A Meta-analysis.

BACKGROUND: Rheumatic fever (RF) and its sequel rheumatic heart disease (RHD) is an autoimmune disease caused by an abnormal host immune response to group A streptococcus (GAS) infection. The HLA class II molecules are entailed in immune-mediated infectious, inflammatory, and autoimmune diseases including RHD. However, HLA class II genes are reported to be associated with RF/RHD across different populations with a very little consistency. OBJECTIVE: The aim of the study is to investigate the association between HLA class II genes and RF/RHD by meta-analysis. METHODS: A comprehensive literature search was conducted to identify all relevant case-control studies published before December 31, 2019. The data were extracted using standardized form and pooled odds ratio (OR) with 95% confidence interval (CI) are calculated to assess the strength of the association between HLA class II genes and RF/RHD. RESULTS: Thirteen studies for HLA-DRB1 alleles (1065 patients and 1691 controls) and eight studies for HLA-DQB1 alleles (644 patients and 1088 controls) were finally included. The meta-analysis showed a significantly higher frequency of HLA-DRB1*07 allele (OR = 1.68, P < .0001) in RF/RHD patients when compared to controls, while the frequency of HLA-DRB1*15 allele (OR = 0.60, P = .03) was significantly lower in RF/RHD patients than in controls. However, there were no significant differences in the frequency of HLA-DQB1 alleles between RF/RHD patients and controls. CONCLUSIONS: The results of the meta-analysis suggest that the differential presentation of autoimmune peptides by HLA-DRB1*07 (susceptible) and HLA-DRB1*15 (protective) alleles with different affinities may play a crucial role in the pathogenesis of RF/RHD.

Association of HLA-G 3'UTR 14-bp Ins/Del polymorphism with breast cancer among South Indian women.

AIM: Human leucocyte antigen-G (HLA-G) and tumour necrosis factor-alpha (TNF-α) are potent immune mediators implicated in the pathogenesis of breast cancer. The polymorphisms in the 3' untranslated region (3'UTR) of HLA-G and promoter region of TNF-α are well known to influence their expression levels and may consequently contribute to varied disease predisposition. Therefore, in the present study, we explored the effect of HLA-G 3'UTR (14-bp Ins/Del and +3142 C/G) and TNF-α promoter (-238 G/A and -308 G/A) polymorphisms on breast cancer risk among South Indian women. METHODS: A total of 342 women (100 patients with breast cancer, 142 patients with benign breast disorder and 100 healthy women volunteers) were enrolled for this study. Genotyping of HLA-G and TNF-α polymorphisms were performed by direct PCR DNA amplification and amplification refractory mutation system PCR methods, respectively. RESULTS: Significantly higher frequencies of HLA-G 14-bp Ins allele and Ins/+3142G haplotype were observed in patients with breast cancer than healthy controls (OR=1.56, Pc=0.036) and patients with benign breast disorder (OR=1.47, Pc=0.046). Similarly, subgroup analysis based on age at diagnosis (age≤50 years and >50 years) of breast cancer revealed higher frequencies of 14-bp Ins allele and Ins/+3142G haplotype in the patients of age >50 years than healthy controls (OR=1.77, Pc=0.03). Additionally, the extended haplotypes and multifactor dimensionality reduction analysis of the studied polymorphisms revealed significant contribution of HLA-G 14-bp Ins/Del polymorphism towards breast cancer risk. CONCLUSION: The findings of the present study suggest that the HLA-G 14-bp Ins/Del polymorphism could influence breast cancer pathogenesis among South Indian women.