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Background: Premenstrual dysphoric disorder is a mood disorder that has been recognized in the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition (DSM-5) as a subcategory of depressive disorders. The disorder has a high prevalence rate, and yet no uniform measure is standardized on the Indian population. Aim: This study aimed to develop a scale to assess premenstrual dysphoric disorder that can be used for screening and for clinical use and that is standardized on the Indian population. Methods: This study used cross-sectional research design and collected data through social media platforms from a sample of 300 females, out of which 38 were excluded for pregnancy, mental health conditions, substance use, and oral contraceptive use. Results: The scale was analyzed using SPSS 21.0 for descriptive statistics, internal consistency, and convergent, content (factor analysis), and divergent validity. Results showed a high reliability of 0.90 and a concurrent validity of 0.76 and 0.64 against PSTT and BDI. Factor analysis revealed four factors, namely, affective and cognitive functioning, daily life and occupational functioning, somatic symptoms, and interpersonal anger. The sensitivity and specificity of the scale were found to be 86 (86%) and 66 (66%), respectively. Conclusion: The scale developed in this study was found reliable and valid for use on the Indian population. It has high sensitivity and can be used as a screening measure for premenstrual dysphoric disorder. [ABSTRACT FROM AUTHOR]

Background: Premenstrual dysphoric disorder (PMDD) is a condition that affects nearly 3--9% of the women in the reproductive age during the luteal phase of each menstrual cycle characterized by symptoms varying in severity and affecting the quality of life. Earlier research studies conducted have reported independent relationships between PvuII-ESR1-polymorphism and psychological traits in PMDD and risk for cognitive, behavioral, and affective symptoms. However, as the studies are few in number and the results are not consistent, there is a need for our study to link between the PvuII-ESR1gene and PMDD. Methodology: All nonpregnant women aged between 18 and 45 years and attending the OBG or Medicine or Psychiatry OPD for a routine health checkup were recruited into the study. The cross-sectional study recruited 35 samples each in the control and PMDD groups using a validated screening PMDD Assessment Scale Questionnaire (PMDDASQ). Mann--Whitney's U test and Chi-square test were used to calculate P values for the continuous and categorical variables. Tetra-primer--amplification refractory mutation system--polymerase chain reaction was used to identify the PvuII-ESR1gene polymorphism after isolation of genomic DNA from the whole blood. Results: Data-Analysis Pak tool and Med-Calc software were used for data analysis. The PvuII-ESR1 genotype distribution was in Hardy--Weinberg equilibrium in both PMDD and controls. The PMDDASQ scoring showed a significance with P ≤ 0.05. Pearson's Chi-Squared test performed for genotypes and alleles did not show any significant association with the phenotype. Conclusion: PvuII-ESR1 SNP (T/C rs2234693) does not show any association with phenotype between the control and PMDD. However, PMDDAS questionnaire can be used to differentiate the women who are controls from PMDD. [ABSTRACT FROM AUTHOR]

Precision oncology relies on advanced sequencing technologies to guide treatment strategies, yet effectively translating genomic data into actionable insights remains a critical challenge. The Personalized OncoGenomics (POG) program at BC Cancer utilizes whole genome and transcriptome analysis (WGTA), providing a comprehensive view of the molecular biology of advanced cancer patient tumours, with over 1200 patients enrolled to-date. This analysis relies on curated clinical knowledgebases linking cancer variants and their clinical relevance, but the breadth and utility of these can be limited by access restrictions or missing information. CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is an open-access, expert moderated, crowd-sourced knowledgebase of clinically relevant cancer variants that aims to address these limitations and is one of several sources used for variant interpretation in POG. Based on a retrospective cohort of POG cases, we evaluated the knowledgebase coverage of genes and variants involved in treatment recommendations from the molecular tumour board (MTB) as well as those suggested by genome analysts. We also considered the impact of quality of evidence on MTB recommendations and patient treatments. We found more than 95% of patients had an alteration considered clinically actionable by the MTB, demonstrating the benefit of WGTA paired with open-source automated variant matching and reporting software. Clinical interpretations derived from CIViC represented nearly 50% of therapeutic evidence reported at the MTB, emphasizing the role of open-access knowledge in precision oncology. Additionally, we identified genome signatures as a critical area with clinical implications requiring further curation efforts and evidence model development. [ABSTRACT FROM AUTHOR]