Maternal and perinatal outcomes of pregnant women with SARS-CoV-2 infection

Objectives To evaluate the maternal and perinatal outcomes of pregnancies affected by SARS-CoV-2 infection. Methods This was a multinational retrospective cohort study including women with a singleton pregnancy and laboratory-confirmed SARS-CoV-2 infection, conducted in 72 centers in 22 different countries in Europe, the USA, South America, Asia and Australia, between 1 February 2020 and 30 April 2020. Confirmed SARS-CoV-2 infection was defined as a positive result on real-time reverse-transcription polymerase chain reaction (RT-PCR) assay of nasopharyngeal swab specimens. The primary outcome was a composite measure of maternal mortality and morbidity, including admission to the intensive care unit (ICU), use of mechanical ventilation and death. Results In total, 388 women with a singleton pregnancy tested positive for SARS-CoV-2 on RT-PCR of a nasopharyngeal swab and were included in the study. Composite adverse maternal outcome was observed in 47/388 (12.1%) women; 43 (11.1%) women were admitted to the ICU, 36 (9.3%) required mechanical ventilation and three (0.8%) died. Of the 388 women included in the study, 122 (31.4%) were still pregnant at the time of data analysis. Among the other 266 women, six (19.4% of the 31 women with first-trimester infection) had miscarriage, three (1.1%) had termination of pregnancy, six (2.3%) had stillbirth and 251 (94.4%) delivered a liveborn infant. The rate of preterm birth before 37 weeks' gestation was 26.3% (70/266). Of the 251 liveborn infants, 69/251(27.5%) were admitted to the neonatal ICU, and there were five (2.0%) neonatal deaths. The overall rate of perinatal death was 4.1% (11/266). Only one (1/251, 0.4%) infant, born to a mother who tested positive during the third trimester, was found to be positive for SARS-CoV-2 on RT-PCR. Conclusions SARS-CoV-2 infection in pregnant women is associated with a 0.8% rate of maternal mortality, but an 11.1% rate of admission to the ICU. The risk of vertical transmission seems to be negligible. (C) 2020 International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

IMPORTANCE: Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN). OBJECTIVE: We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort. DESIGN/SETTING/PARTICIPANTS: Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM. EXPOSURE: Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%. MAIN OUTCOMES AND MEASURES: Total retinal, mRNFL and GC-IPL thickness. RESULTS: 74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p<0.001), GC-IPL thickness (-1.73 μm, 95% CI: -1.86, -1.59; p<0.001) and mRNFL thickness (-0.68 μm, 95% CI: -0.81, -0.54; p<0.001) compared to those without DM. After adjusting for co-variates, in the GLMM, total retinal thickness was 1.99 um lower (95% CI: -2.47, -1.50; p<0.001) and GC-IPL was 1.02 μm lower (95% CI: -1.18, -0.87; p<0.001) among those with DM compared to without. mRNFL was no longer significantly different (p = 0.369). GC-IPL remained significantly lower, after adjusting for co-variates, among those with DM compared to those without DM when including only participants with no/mild DR (-0.80 μm, 95% CI: -0.98, -0.62; p<0.001). Total retinal thickness decreased 0.40 μm (95% CI: -0.61, -0.20; p<0.001), mRNFL thickness increased 0.20 μm (95% CI: 0.14, 0.27; p<0.001) and GC-IPL decreased 0.26 μm (95% CI: -0.33, -0.20; p<0.001) per unit increase in A1c after adjusting for co-variates. Among participants with diabetes, age, DR grade, ethnicity, body mass index, glaucoma, spherical equivalent, and visual acuity were significantly associated with GC-IPL thickness. CONCLUSION: GC-IPL was thinner among participants with DM, compared to without DM. This difference persisted after adjusting for confounding variables and when considering only those with no/mild DR. This confirms that GC-IPL thinning occurs early in DM and can serve as a useful marker of DRN

Oil palm (Elaeis guineensis Jacq.) tissue culture ESTs: identifying genes associated with callogenesis and embryogenesis

Background: Oil palm (Elaeis guineensis Jacq.) is one of the most important oil bearing crops in the world. However, genetic improvement of oil palm through conventional breeding is extremely slow and costly, as the breeding cycle can take up to 10 years. This has brought about interest in vegetative propagation of oil palm. Since the introduction of oil palm tissue culture in the 1970s, clonal propagation has proven to be useful, not only in producing uniform planting materials, but also in the development of the genetic engineering programme. Despite considerable progress in improving the tissue culture techniques, the callusing and embryogenesis rates from proliferating callus cultures remain very low. Thus, understanding the gene diversity and expression profiles in oil palm tissue culture is critical in increasing the efficiency of these processes. Results: A total of 12 standard cDNA libraries, representing three main developmental stages in oil palm tissue culture, were generated in this study. Random sequencing of clones from these cDNA libraries generated 17,599 expressed sequence tags (ESTs). The ESTs were analysed, annotated and assembled to generate 9,584 putative unigenes distributed in 3,268 consensi and 6,316 singletons. These unigenes were assigned putative functions based on similarity and gene ontology annotations. Cluster analysis, which surveyed the relatedness of each library based on the abundance of ESTs in each consensus, revealed that lipid transfer proteins were highly expressed in embryogenic tissues. A glutathione S-transferase was found to be highly expressed in non-embryogenic callus. Further analysis of the unigenes identified 648 non-redundant simple sequence repeats and 211 putative full-length open reading frames. Conclusion: This study has provided an overview of genes expressed during oil palm tissue culture. Candidate genes with expression that are modulated during tissue culture were identified. However, in order to confirm whether these genes are suitable as early markers for embryogenesis, the genes need to be tested on earlier stages of tissue culture and a wider range of genotypes. This collection of ESTs is an important resource for genetic and genome analyses of the oil palm, particularly during tissue culture development

Formation of regulatory modules by local sequence duplication

Turnover of regulatory sequence and function is an important part of molecular evolution. But what are the modes of sequence evolution leading to rapid formation and loss of regulatory sites? Here, we show that a large fraction of neighboring transcription factor binding sites in the fly genome have formed from a common sequence origin by local duplications. This mode of evolution is found to produce regulatory information: duplications can seed new sites in the neighborhood of existing sites. Duplicate seeds evolve subsequently by point mutations, often towards binding a different factor than their ancestral neighbor sites. These results are based on a statistical analysis of 346 cis-regulatory modules in the Drosophila melanogaster genome, and a comparison set of intergenic regulatory sequence in Saccharomyces cerevisiae. In fly regulatory modules, pairs of binding sites show significantly enhanced sequence similarity up to distances of about 50 bp. We analyze these data in terms of an evolutionary model with two distinct modes of site formation: (i) evolution from independent sequence origin and (ii) divergent evolution following duplication of a common ancestor sequence. Our results suggest that pervasive formation of binding sites by local sequence duplications distinguishes the complex regulatory architecture of higher eukaryotes from the simpler architecture of unicellular organisms

GWAS Meets Microarray: Are the Results of Genome-Wide Association Studies and Gene-Expression Profiling Consistent? Prostate Cancer as an Example

Genome-wide association studies (GWASs) and global profiling of gene expression (microarrays) are two major technological breakthroughs that allow hypothesis-free identification of candidate genes associated with tumorigenesis. It is not obvious whether there is a consistency between the candidate genes identified by GWAS (GWAS genes) and those identified by profiling gene expression (microarray genes).We used the Cancer Genetic Markers Susceptibility database to retrieve single nucleotide polymorphisms from candidate genes for prostate cancer. In addition, we conducted a large meta-analysis of gene expression data in normal prostate and prostate tumor tissue. We identified 13,905 genes that were interrogated by both GWASs and microarrays. On the basis of P values from GWASs, we selected 1,649 most significantly associated genes for functional annotation by the Database for Annotation, Visualization and Integrated Discovery. We also conducted functional annotation analysis using same number of the top genes identified in the meta-analysis of the gene expression data. We found that genes involved in cell adhesion were overrepresented among both the GWAS and microarray genes.We conclude that the results of these analyses suggest that combining GWAS and microarray data would be a more effective approach than analyzing individual datasets and can help to refine the identification of candidate genes and functions associated with tumor development

Associations of Variants in CHRNA5/A3/B4 Gene Cluster with Smoking Behaviors in a Korean Population

Multiple genome-wide and targeted association studies reveal a significant association of variants in the CHRNA5-CHRNA3-CHRNB4 (CHRNA5/A3/B4) gene cluster on chromosome 15 with nicotine dependence. The subjects examined in most of these studies had a European origin. However, considering the distinct linkage disequilibrium patterns in European and other ethnic populations, it would be of tremendous interest to determine whether such associations could be replicated in populations of other ethnicities, such as Asians. In this study, we performed comprehensive association and interaction analyses for 32 single-nucleotide polymorphisms (SNPs) in CHRNA5/A3/B4 with smoking initiation (SI), smoking quantity (SQ), and smoking cessation (SC) in a Korean sample (N = 8,842). We found nominally significant associations of 7 SNPs with at least one smoking-related phenotype in the total sample (SI: P = 0.015∼0.023; SQ: P = 0.008∼0.028; SC: P = 0.018∼0.047) and the male sample (SI: P = 0.001∼0.023; SQ: P = 0.001∼0.046; SC: P = 0.01). A spectrum of haplotypes formed by three consecutive SNPs located between rs16969948 in CHRNA5 and rs6495316 in the intergenic region downstream from the 5′ end of CHRNB4 was associated with these three smoking-related phenotypes in both the total and the male sample. Notably, associations of these variants and haplotypes with SC appear to be much weaker than those with SI and SQ. In addition, we performed an interaction analysis of SNPs within the cluster using the generalized multifactor dimensionality reduction method and found a significant interaction of SNPs rs7163730 in LOC123688, rs6495308 in CHRNA3, and rs7166158, rs8043123, and rs11072793 in the intergenic region downstream from the 5′ end of CHRNB4 to be influencing SI in the male sample. Considering that fewer than 5% of the female participants were smokers, we did not perform any analysis on female subjects specifically. Together, our detected associations of variants in the CHRNA5/A3/B4 cluster with SI, SQ, and SC in the Korean smoker samples provide strong evidence for the contribution of this cluster to the etiology of SI, ND, and SC in this Asian population

Practical and Theoretical Considerations in Study Design for Detecting Gene-Gene Interactions Using MDR and GMDR Approaches

Detection of interacting risk factors for complex traits is challenging. The choice of an appropriate method, sample size, and allocation of cases and controls are serious concerns. To provide empirical guidelines for planning such studies and data analyses, we investigated the performance of the multifactor dimensionality reduction (MDR) and generalized MDR (GMDR) methods under various experimental scenarios. We developed the mathematical expectation of accuracy and used it as an indicator parameter to perform a gene-gene interaction study. We then examined the statistical power of GMDR and MDR within the plausible range of accuracy (0.50∼0.65) reported in the literature. The GMDR with covariate adjustment had a power of>80% in a case-control design with a sample size of≥2000, with theoretical accuracy ranging from 0.56 to 0.62. However, when the accuracy was<0.56, a sample size of≥4000 was required to have sufficient power. In our simulations, the GMDR outperformed the MDR under all models with accuracy ranging from 0.56∼0.62 for a sample size of 1000–2000. However, the two methods performed similarly when the accuracy was outside this range or the sample was significantly larger. We conclude that with adjustment of a covariate, GMDR performs better than MDR and a sample size of 1000∼2000 is reasonably large for detecting gene-gene interactions in the range of effect size reported by the current literature; whereas larger sample size is required for more subtle interactions with accuracy<0.56