The paradoxical influence of the COVID-19 lockdown period on different types of preterm births in Alberta: a provincial study.

Objectives: The objective of this study was to determine if the COVID-19 pandemic impacted different types of preterm birth rates in Alberta, Canada. Methods: A population-based, retrospective, cohort study was conducted from March 15, 2015 to December 31, 2020 using provincial data. The primary exposure was the COVID-19 lockdown period, and the primary outcome was the incidence of preterm birth (<37 weeks gestational age). Multivariable analyses in the complete lockdown and overall lockdown (partial and complete lockdown) periods were performed to test the association between the year of birth and preterm birth status and were adjusted for various independent variables. Preterm birth status was adjusted for various confounding factors. Results: Following the analysis of n = 41,187 mothers and their singleton infants, we found that the lockdown due to COVID-19 had no impact in reducing the overall preterm birth rate. However, a paradoxical influence was observed with an increase of extremely low preterm births in the overall lockdown period, and a decrease in moderate preterm births during the complete lockdown period. Conclusions: The results of this study demonstrated that there was a decrease in moderate and increase in extremely low preterm birth rates as a result of the COVID-19 lockdown. However, the COVID-19 lockdown did not impact the very preterm and late preterm birth rate in Alberta.

Fine-mapping of a novel premenopausal breast cancer susceptibility locus at Chr4q31.22 in Caucasian women and validation in African and Chinese women.

We previously identified a novel breast cancer susceptibility variant on chromosome 4q31.22 locus (rs1429142) conferring risk among women of European ancestry. Here, we report replication of findings, validation of the variant in diverse populations and fine-mapping of the associated locus in Caucasian population. The SNP rs1429142 (C/T, minor allele frequency 18%) showed association for the overall breast cancer risk in Stages 1-4 (n = 4,331 cases/4271 controls; p = 4.35 × 10-8 ; odds ratio, ORC-allele ,1.25), and an elevated risk among premenopausal women (n = 1,503 cases/4271 controls; p = 5.81 × 10-10 ; ORC-allele 1.40) in European populations. SNP rs1429142 was associated with premenopausal breast cancer risk in women of African (T/C; p-value 1.45 × 10-02 ; ORC-allele 1.2) but not from Chinese ancestry. Fine-mapping of the locus revealed several potential causal variants which are present within a single association signal, revealed from the conditional regression analysis. Functional annotation of the potential causal variants revealed three putative SNPs rs1366691, rs1429139 and rs7667633 with active enhancer functions inferred based on histone marks, DNase hypersensitive sites in breast cell line data. These putative variants were bound by transcription factors (C-FOS, STAT1/3 and POL2/3) with known roles in inflammatory pathways. Furthermore, Hi-C data revealed several short-range interactions in the fine-mapped locus harboring the putative variants. The fine mapped locus was predicted to be within a single topologically associated domain, potentially facilitating enhancer-promoter interactions possibly leading to the regulation of nearby genes.

A Genome-Wide Association Study to Identify Potential Germline Copy Number Variants for Sporadic Breast Cancer Susceptibility.

Breast cancer (BC) predisposition in populations arises from both genetic and nongenetic risk factors. Structural variations such as copy number variations (CNVs) are heritable determinants for disease susceptibility. The primary objectives of this study are (1) to identify CNVs associated with sporadic BC using a genome-wide association study (GWAS) design; (2) to utilize 2 distinct CNV calling algorithms to identify concordant CNVs as a strategy to reduce false positive associations in the hypothesis-generating GWAS discovery phase, and (3) to identify potential candidate CNVs for follow-up replication studies. We used Affymetrix SNP Array 6.0 data profiled on Caucasian subjects (422 cases/348 controls) to call CNVs using algorithms implemented in Nexus Copy Number and Partek Genomics Suite software. Nexus algorithm identified CNVs associated with BC (731 autosomal CNVs with >5% frequency in the total sample and Q < 0.05). Thirteen CNVs were identified when Partek algorithm-called CNVs were overlapped with Nexus-identified CNVs; these CNVs showed concordances for frequency, effect size, and direction. Coding genes present within BC-associated CNVs were known to play a role in disease etiology and prognosis. Long noncoding RNAs identified within CNVs showed tissue-specific expression, indicating potential functional relevance of the findings. The identified candidate CNVs warrant independent replication.

Predicting the Risk Factors Associated With Severe Outcomes Among COVID-19 Patients-Decision Tree Modeling Approach.

Background: The COVID-19 pandemic has seen a large surge in case numbers over several waves, and has critically strained the health care system, with a significant number of cases requiring hospitalization and ICU admission. This study used a decision tree modeling approach to identify the most important predictors of severe outcomes among COVID-19 patients. Methods: We identified a retrospective population-based cohort (n = 140,182) of adults who tested positive for COVID-19 between 5th March 2020 and 31st May 2021. Demographic information, symptoms and co-morbidities were extracted from a communicable disease and outbreak management information system and electronic medical records. Decision tree modeling involving conditional inference tree and random forest models were used to analyze and identify the key factors(s) associated with severe outcomes (hospitalization, ICU admission and death) following COVID-19 infection. Results: In the study cohort, nearly 6.37% were hospitalized, 1.39% were admitted to ICU and 1.57% died due to COVID-19. Older age (>71Y) and breathing difficulties were the top two factors associated with a poor prognosis, predicting about 50% of severe outcomes in both models. Neurological conditions, diabetes, cardiovascular disease, hypertension, and renal disease were the top five pre-existing conditions that altogether predicted 29% of outcomes. 79% of the cases with poor prognosis were predicted based on the combination of variables. Age stratified models revealed that among younger adults (18-40 Y), obesity was among the top risk factors associated with adverse outcomes. Conclusion: Decision tree modeling has identified key factors associated with a significant proportion of severe outcomes in COVID-19. Knowledge about these variables will aid in identifying high-risk groups and allocating health care resources.

Single-Nucleotide Polymorphisms in TAOK3 Are Associated With High Opioid Requirement for Pain Management in Patients With Advanced Cancer Admitted to a Tertiary Palliative Care Unit.

PURPOSE: Different amounts of opioid are required for the relief of cancer pain in different individuals, raising the possibility that genetic factors play a role. We tested the hypothesis that genetic variations in the TAOK3 (TAO kinase 3, encoding serine/threonine-protein kinase) explain some of the interindividual variations related to the morphine-equivalent daily dose (MEDD) in patients with cancer. EXPERIMENTAL DESIGN: We selected two single-nucleotide polymorphisms (SNPs) in the TAOK3, reported earlier to associate with higher MEDD in postoperative pain based on genome-wide association study. We investigated their association with MEDD in Canadian patients with cancer (n = 110) admitted to a tertiary palliative care unit. SNPs analyzed were rs1277441 (C/T, C = minor allele) and rs795484 (A/G, A = minor allele). RESULTS: Minor allele frequencies in our population were 0.29 (rs1277441) and 0.28 (rs795484). These SNPs were in perfect linkage disequilibrium (r2 = 0.97). SNPs in TAOK3 showed a significant association with mean MEDD ≥800 mg. For rs795484, MEDD values ≥800 mg occurred in patients who were GG (7%), GA (18%), and AA (57%) (P = 0.004; Fisher's exact test); similar results were obtained for rs1277441. Homozygous variants for either SNP had received higher numbers of different opioids (P = 0.021). CONCLUSION: In this cohort of patients with advanced cancer pain, TAOK3 SNPs were associated with opioid doses. This result supports the original findings from a GWAS in postoperative patients. The proportions of variant homozygotes (8.2% of patients) and their requirement for higher doses of opioids would appear potentially clinically important and should be validated in further studies.

Breast cancer associated germline structural variants harboring small noncoding RNAs impact post-transcriptional gene regulation.

Copy Number Variants (CNVs) are a class of structural variations of DNA. Germline CNVs are known to confer disease susceptibility, but their role in breast cancer warrants further investigations. We hypothesized that breast cancer associated germline CNVs contribute to disease risk through gene dosage or other post-transcriptional regulatory mechanisms, possibly through tissue specific expression of CNV-embedded small-noncoding RNAs (CNV-sncRNAs). Our objectives are to identify breast cancer associated CNVs using a genome wide association study (GWAS), identify sncRNA genes embedded within CNVs, confirm breast tissue (tumor and normal) expression of the sncRNAs, correlate their expression with germline copy status and identify pathways influenced by the genes regulated by sncRNAs. We used an association study design and accessed germline CNV data generated on Affymetrix Human SNP 6.0 array in 686 (in-house data) and 495 (TCGA data) subjects served as discovery and validation cohorts. We identified 1812 breast cancer associated CNVs harboring miRNAs (n = 38), piRNAs (n = 9865), snoRNAs (n = 71) and tRNAs (n = 12) genes. A subset of CNV-sncRNAs expressed in breast tissue, also showed correlation with germline copy status. We identified targets potentially regulated by miRNAs and snoRNAs. In summary, we demonstrate the potential impact of embedded CNV-sncRNAs on expression and regulation of down-stream targets.

Germline copy number variations are associated with breast cancer risk and prognosis.

Breast cancer is one of the most common cancers among women, and susceptibility is explained by genetic, lifestyle and environmental components. Copy Number Variants (CNVs) are structural DNA variations that contribute to diverse phenotypes via gene-dosage effects or cis-regulation. In this study, we aimed to identify germline CNVs associated with breast cancer susceptibility and their relevance to prognosis. We performed whole genome CNV genotyping in 422 cases and 348 controls using Human Affymetrix SNP 6 array. Principal component analysis for population stratification revealed 84 outliers leaving 366 cases and 320 controls of Caucasian ancestry for association analysis; CNVs with frequency > 10% and overlapping with protein coding genes were considered for breast cancer risk and prognostic relevance. Coding genes within the CNVs identified were interrogated for gene- dosage effects by correlating copy number status with gene expression profiles in breast tumor tissue. We identified 200 CNVs associated with breast cancer (q-value < 0.05). Of these, 21 CNV regions (overlapping with 22 genes) also showed association with prognosis. We validated representative CNVs overlapping with APOBEC3B and GSTM1 genes using the TaqMan assay. Germline CNVs conferred dosage effects on gene expression in breast tissue. The candidate CNVs identified in this study warrant independent replication.