Results: BIO RAD Variant II analyzer was used. Sickle cell syndromes including double heterozygous states accounted for 56.13% of total cases. HbSS, HbS/β0-th, HbS/β+-th β-thal trait comprises 29%, 6.5%, 5.1%& 10% of total cases respectively with mean MCV (fl) = 84, 68,71,64 respectively. The Mean HbA2 for β-thal trait, HbE trait &HbE-β thal showed 5.1 ± 1.1, 19 ± 9 & 24 ± 8 respectively. HbF is increased in 8.6% case (excluding SC syndromes & β-thal disorders), of these 5.5% were infants & 12 cases of Aplastic Anemias. Peak P2 >7% (2.4% cases) was seen in uncontrolled diabetes mellitus which on quantification showed HbA1C = 8 ± 2.1 mmol/L.
Discussion: : HPLC in correlation with CBC parameters & family studies can aid in the diagnosis of majority of Hemoglobinopathies and thalassemic syndrome. The CBC & HPLC parameters of the present study are in good correlation with the research conducted by Tejinder Sing, RiouJ & Alla Joutovsky. Present study showed HPLC comprehensively characterizing HbS, A, A2, F, S, C, D from each other & was also applicable for the quantification of HbA1c for the monitoring of Diabetes Mellitus.
Conclusion: : The merits of HPLC are small quantity of sample required, economical, less TAT, accurate categorization of HbS, HbA2 & F. But one has to be aware of the limitations and problems associated with this method due to variant hemoglobin within the same retention windows. The present findings show HPLC as an excellent & powerful diagnostic tool for the direct identification of hemoglobin variants with a high degree of precision in the quantification of normal and abnormal hemoglobin fractions.
RESULTS: The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.
CONCLUSION: Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.
Method: In this study, the potential targets of miR-145 were identified bio-informatically using different target prediction tools. The identified target genes were validated in vitro by dual luciferase assay. Wound healing and soft agar colony assay assessed cell proliferation and migration. miR-145 expression level was measured quantitatively by RT-PCR at different stages of breast tumor. Western blot was used to verify the role of miR-145 in EMT transition using key marker proteins.
Result: Wound healing and soft agar colony assays, using miR-145 over-expressing stably transfected MCF7 cells, unraveled its role as a pro-proliferation candidate in cancerous cells. The association between miR-145 over-expression and differential methylation patterns in representative target genes (DR5, BCL2, TP53, RNF8, TIP60, CHK2, and DCR2) supported the inference drawn. These in vitro observations were validated in a representative set of nodal positive tumors of stage 3 and 4 depicting higher miR-145 expression as compared to early stages. Further, the role of miR-145 in epithelial-mesenchymal (EMT) transition found support through the observation of two key markers, Vimentin and ALDL, where a positive correlation with Vimentin protein and a negative correlation with ALDL mRNA expression were observed.
Conclusion: Our results demonstrate miR-145 as a pro-cancerous candidate, evident from the phenotypes of aggressive cellular proliferation, epithelial to mesenchymal transition, hypermethylation of CpG sites in DDR and apoptotic genes and upregulation of miR-145 in later stages of tumor tissues.
OBJECTIVE: To compare the cancer spectrum and frequencies between male BRCA1 and BRCA2 PV carriers.
DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study of 6902 men, including 3651 BRCA1 and 3251 BRCA2 PV carriers, older than 18 years recruited from cancer genetics clinics from 1966 to 2017 by 53 study groups in 33 countries worldwide collaborating through the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Clinical data and pathologic characteristics were collected.
MAIN OUTCOMES AND MEASURES: BRCA1/2 status was the outcome in a logistic regression, and cancer diagnoses were the independent predictors. All odds ratios (ORs) were adjusted for age, country of origin, and calendar year of the first interview.
RESULTS: Among the 6902 men in the study (median [range] age, 51.6 [18-100] years), 1634 cancers were diagnosed in 1376 men (19.9%), the majority (922 of 1,376 [67%]) being BRCA2 PV carriers. Being affected by any cancer was associated with a higher probability of being a BRCA2, rather than a BRCA1, PV carrier (OR, 3.23; 95% CI, 2.81-3.70; P
METHODS: We did a genome-wide association study of NKTCL in multiple populations from east Asia. We recruited a discovery cohort of 700 cases with NKTCL and 7752 controls without NKTCL of Han Chinese ancestry from 19 centres in southern, central, and northern regions of China, and four independent replication samples including 717 cases and 12 650 controls. Three of these independent samples (451 cases and 5301 controls) were from eight centres in the same regions of southern, central, and northern China, and the fourth (266 cases and 7349 controls) was from 11 centres in Hong Kong, Taiwan, Singapore, and South Korea. All cases had primary NKTCL that was confirmed histopathologically, and matching with controls was based on geographical region and self-reported ancestry. Logistic regression analysis was done independently by geographical regions, followed by fixed-effect meta-analyses, to identify susceptibility loci. Bioinformatic approaches, including expression quantitative trait loci, binding motif and transcriptome analyses, and biological experiments were done to fine-map and explore the functional relevance of genome-wide association loci to the development of NKTCL.
FINDINGS: Genetic data were gathered between Jan 1, 2008, and Jan 23, 2019. Meta-analysis of all samples (a total of 1417 cases and 20 402 controls) identified two novel loci significantly associated with NKTCL: IL18RAP on 2q12.1 (rs13015714; p=2·83 × 10-16; odds ratio 1·39 [95% CI 1·28-1·50]) and HLA-DRB1 on 6p21.3 (rs9271588; 9·35 × 10-26 1·53 [1·41-1·65]). Fine-mapping and experimental analyses showed that rs1420106 at the promoter of IL18RAP was highly correlated with rs13015714, and the rs1420106-A risk variant had an upregulatory effect on IL18RAP expression. Cell growth assays in two NKTCL cell lines (YT and SNK-6 cells) showed that knockdown of IL18RAP inhibited cell proliferation by cell cycle arrest in NKTCL cells. Haplotype association analysis showed that haplotype 47F-67I was associated with reduced risk of NKTCL, whereas 47Y-67L was associated with increased risk of NKTCL. These two positions are component parts of the peptide-binding pocket 7 (P7) of the HLA-DR heterodimer, suggesting that these alterations might account for the association at HLA-DRB1, independent of the previously reported HLA-DPB1 variants.
INTERPRETATION: Our findings provide new insights into the development of NKTCL by showing the importance of inflammation and immune regulation through the IL18-IL18RAP axis and antigen presentation involving HLA-DRB1, which might help to identify potential therapeutic targets. Taken in combination with additional genetic and other risk factors, our results could potentially be used to stratify people at high risk of NKTCL for targeted prevention.
FUNDING: Guangdong Innovative and Entrepreneurial Research Team Program, National Natural Science Foundation of China, National Program for Support of Top-Notch Young Professionals, Chang Jiang Scholars Program, Singapore Ministry of Health's National Medical Research Council, Tanoto Foundation, National Research Foundation Singapore, Chang Gung Memorial Hospital, Recruitment Program for Young Professionals of China, First Affiliated Hospital and Army Medical University, US National Institutes of Health, and US National Cancer Institute.