Objective: To provide updated prevalence estimates of asthma and asthma medication use for women of childbearing age in the United States.Methods: Using data from 11,383 women aged 18-44, including a subset of 1,245 pregnant women, enrolled in the National Health and Nutrition Examination Survey (2001-2016), we assessed the age-adjusted prevalence of self-reported diagnosed asthma. For women aged 18-44, we stratified by year, demographics, and other characteristics. Furthermore, we assessed asthma medication use among women aged 18-44 with asthma.Results: After age-adjustment, 9.9% (95% confidence interval (CI) 9.2%, 10.7%) of women aged 18-44 and 10.9% (95% CI 7.2%, 14.6%) of pregnant women reported having asthma. Asthma prevalence was highest in 2015-2016 (12.0% 95% CI 9.8%, 14.3%) and lowest in 2003-2004 (8.6% 95% CI 6.4%, 10.8%). Women aged 18-44 with Medicaid or State Children's Health Insurance Program insurance coverage (16.8% 95% CI 14.5%, 19.2%), obesity (14.4% 95% CI 12.9%, 15.8%), diabetes (18.7% 95% CI 12.1%, 25.2%), hypertension (16.6% 95% CI 14.2%, 19.0%), and current smokers (12.8% 95% CI 11.4%, 14.2%) had the highest asthma prevalence. Of women with asthma, 38.3% (95% CI 34.5%, 42.1%) reported using asthma medications in the past 30 days.Conclusions: Among women of childbearing ages, asthma burden varies across demographic and clinical characteristics and has increased in recent years.

Background

Suboptimal asthma control during pregnancy may affect perinatal outcomes. US guidelines recommend questionnaires to assess asthma control including the Asthma Control Test (ACT).

Objective

To validate telephone administration of a modified version of ACT during pregnancy.

Methods

MotherToBaby Pregnancy Studies (2011-2013) enrolled 159 pregnant women with asthma. Participants were interviewed by telephone at intake, at approximately gestational weeks 20 and 32, and postpartum. The ACT was modified to address dyspnea specifically due to asthma; the modified version is the Pregnancy Asthma Control Test (p-ACT). Women answered the p-ACT and guideline-based asthma impairment questions and reported asthma course changes and exacerbations. Possible p-ACT scores ranged from 5 to 25; higher score indicated better control. Reliability, criterion validity, construct validity, prospective validity, and responsiveness were assessed.

Results

Cronbach's alpha for internal consistency was similar across time points (0.84-0.90). The p-ACT score varied by impairment; for example, at intake, the mean score was 23.2 for well-controlled versus 13.7 for very poorly controlled asthma. The p-ACT score change between interviews differed by asthma course; for example, women reporting that their asthma was much better at week 20 than at intake had a mean score increase of 4.7; women reporting that their asthma was a little worse had a mean score decrease of 1.3. Lower p-ACT score was associated with previous exacerbations, whereas intake p-ACT score was not associated with future exacerbations during pregnancy.

Conclusions

The p-ACT demonstrated good internal consistency, varied in the expected direction by impairment level, and was responsive to changes in asthma course. Telephone administration of the p-ACT is reliable and valid for assessing asthma control during pregnancy.

Purpose

To characterize prednisone use in pregnant women with rheumatoid arthritis using individual-level heat-maps and clustering individual trajectories of prednisone dose, and to evaluate the association between prednisone dose trajectory groups and gestational length.

Methods

This study included pregnant women with rheumatoid arthritis who enrolled in the MotherToBaby Autoimmune Diseases in Pregnancy Study (2003-2014) before gestational week 20 and reported prednisone use without another oral glucocorticoid during pregnancy (n = 254). Information on medication use and pregnancy outcomes was collected by telephone interview plus by medical record review. Prednisone daily dose and cumulative dose were plotted by gestational day using a heat map for each individual. K-means clustering was used to cluster individual trajectories of prednisone dose into groups. The associations between trajectory group and demographics, disease severity measured by the Health Assessment Questionnaire at enrollment, and gestational length were evaluated.

Results

Women used prednisone 3 to 292 days during pregnancy, with daily doses ranging from <1 to 60 mg. Total cumulative dose ranged from 8 to 6225 mg. Disease severity, non-biologic disease modifying anti-rheumatic drug use, and gestational length varied significantly by trajectory group. After adjusting for disease severity, non-biologic disease modifying anti-rheumatic drug use, and other covariates, the highest vs lowest daily dose trajectory group was associated with reduced gestational age at delivery (β: -2.3 weeks (95%: -3.4, -1.3)), as was the highest vs lowest cumulative dose trajectory group (β: -2.6 weeks (95%: -3.6, -1.5)).

Conclusions

In pregnant women with rheumatoid arthritis, patterns of higher prednisone dose were associated with shorter gestational length compared with lower dose.

Single-molecule sequencing instruments can generate multikilobase sequences with the potential to greatly improve genome and transcriptome assembly. However, the error rates of single-molecule reads are high, which has limited their use thus far to resequencing bacteria. To address this limitation, we introduce a correction algorithm and assembly strategy that uses short, high-fidelity sequences to correct the error in single-molecule sequences. We demonstrate the utility of this approach on reads generated by a PacBio RS instrument from phage, prokaryotic and eukaryotic whole genomes, including the previously unsequenced genome of the parrot Melopsittacus undulatus, as well as for RNA-Seq reads of the corn (Zea mays) transcriptome. Our long-read correction achieves >99.9% base-call accuracy, leading to substantially better assemblies than current sequencing strategies: in the best example, the median contig size was quintupled relative to high-coverage, second-generation assemblies. Greater gains are predicted if read lengths continue to increase, including the prospect of single-contig bacterial chromosome assembly.

Linked-Read sequencing technology has recently been employed successfully for de novo assembly of human genomes, however, the utility of this technology for complex plant genomes is unproven. We evaluated the technology for this purpose by sequencing the 3.5-gigabase (Gb) diploid pepper (Capsicum annuum) genome with a single Linked-Read library. Plant genomes, including pepper, are characterized by long, highly similar repetitive sequences. Accordingly, significant effort is used to ensure that the sequenced plant is highly homozygous and the resulting assembly is a haploid consensus. With a phased assembly approach, we targeted a heterozygous F1 derived from a wide cross to assess the ability to derive both haplotypes and characterize a pungency gene with a large insertion/deletion. The Supernova software generated a highly ordered, more contiguous sequence assembly than all currently available C. annuum reference genomes. Over 83% of the final assembly was anchored and oriented using four publicly available de novo linkage maps. A comparison of the annotation of conserved eukaryotic genes indicated the completeness of assembly. The validity of the phased assembly is further demonstrated with the complete recovery of both 2.5-Kb insertion/deletion haplotypes of the PUN1 locus in the F1 sample that represents pungent and nonpungent peppers, as well as nearly full recovery of the BUSCO2 gene set within each of the two haplotypes. The most contiguous pepper genome assembly to date has been generated which demonstrates that Linked-Read library technology provides a tool to de novo assemble complex highly repetitive heterozygous plant genomes. This technology can provide an opportunity to cost-effectively develop high-quality genome assemblies for other complex plants and compare structural and gene differences through accurate haplotype reconstruction.

The contributions of coding mutations to tumorigenesis are relatively well known; however, little is known about somatic alterations in noncoding DNA. Here we describe GECCO (Genomic Enrichment Computational Clustering Operation) to analyze somatic noncoding alterations in 308 pancreatic ductal adenocarcinomas (PDAs) and identify commonly mutated regulatory regions. We find recurrent noncoding mutations to be enriched in PDA pathways, including axon guidance and cell adhesion, and newly identified processes, including transcription and homeobox genes. We identified mutations in protein binding sites correlating with differential expression of proximal genes and experimentally validated effects of mutations on expression. We developed an expression modulation score that quantifies the strength of gene regulation imposed by each class of regulatory elements, and found the strongest elements were most frequently mutated, suggesting a selective advantage. Our detailed single-cancer analysis of noncoding alterations identifies regulatory mutations as candidates for diagnostic and prognostic markers, and suggests new mechanisms for tumor evolution.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

While genome assembly projects have been successful in many haploid and inbred species, the assembly of noninbred or rearranged heterozygous genomes remains a major challenge. To address this challenge, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble long-read sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We generate new reference sequences for heterozygous samples including an F1 hybrid of Arabidopsis thaliana, the widely cultivated Vitis vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata, samples that have challenged short-read assembly approaches. The FALCON-based assemblies are substantially more contiguous and complete than alternate short- or long-read approaches. The phased diploid assembly enabled the study of haplotype structure and heterozygosities between homologous chromosomes, including the identification of widespread heterozygous structural variation within coding sequences.

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

The completion of a telomere-to-telomere human reference genome, T2T-CHM13, has resolved complex regions of the genome, including repetitive and homologous regions. Here, we present a high-resolution epigenetic study of previously unresolved sequences, representing entire acrocentric chromosome short arms, gene family expansions, and a diverse collection of repeat classes. This resource precisely maps CpG methylation (32.28 million CpGs), DNA accessibility, and short-read datasets (166,058 previously unresolved chromatin immunoprecipitation sequencing peaks) to provide evidence of activity across previously unidentified or corrected genes and reveals clinically relevant paralog-specific regulation. Probing CpG methylation across human centromeres from six diverse individuals generated an estimate of variability in kinetochore localization. This analysis provides a framework with which to investigate the most elusive regions of the human genome, granting insights into epigenetic regulation.