Reverse Plasticity Underlies Rapid Evolution by Clonal Selection within Populations of Fibroblasts Propagated on a Novel Soft Substrate.

Mechanical properties such as substrate stiffness are a ubiquitous feature of a cell's environment. Many types of animal cells exhibit canonical phenotypic plasticity when grown on substrates of differing stiffness, in vitro and in vivo. Whether such plasticity is a multivariate optimum due to hundreds of millions of years of animal evolution, or instead is a compromise between conflicting selective demands, is unknown. We addressed these questions by means of experimental evolution of populations of mouse fibroblasts propagated for approximately 90 cell generations on soft or stiff substrates. The ancestral cells grow twice as fast on stiff substrate as on soft substrate and exhibit the canonical phenotypic plasticity. Soft-selected lines derived from a genetically diverse ancestral population increased growth rate on soft substrate to the ancestral level on stiff substrate and evolved the same multivariate phenotype. The pattern of plasticity in the soft-selected lines was opposite of the ancestral pattern, suggesting that reverse plasticity underlies the observed rapid evolution. Conversely, growth rate and phenotypes did not change in selected lines derived from clonal cells. Overall, our results suggest that the changes were the result of genetic evolution and not phenotypic plasticity per se. Whole-transcriptome analysis revealed consistent differentiation between ancestral and soft-selected populations, and that both emergent phenotypes and gene expression tended to revert in the soft-selected lines. However, the selected populations appear to have achieved the same phenotypic outcome by means of at least two distinct transcriptional architectures related to mechanotransduction and proliferation.

The avocado genome informs deep angiosperm phylogeny, highlights introgressive hybridization, and reveals pathogen-influenced gene space adaptation.

The avocado, Persea americana, is a fruit crop of immense importance to Mexican agriculture with an increasing demand worldwide. Avocado lies in the anciently diverged magnoliid clade of angiosperms, which has a controversial phylogenetic position relative to eudicots and monocots. We sequenced the nuclear genomes of the Mexican avocado race, P. americana var. drymifolia, and the most commercially popular hybrid cultivar, Hass, and anchored the latter to chromosomes using a genetic map. Resequencing of Guatemalan and West Indian varieties revealed that ∼39% of the Hass genome represents Guatemalan source regions introgressed into a Mexican race background. Some introgressed blocks are extremely large, consistent with the recent origin of the cultivar. The avocado lineage experienced 2 lineage-specific polyploidy events during its evolutionary history. Although gene-tree/species-tree phylogenomic results are inconclusive, syntenic ortholog distances to other species place avocado as sister to the enormous monocot and eudicot lineages combined. Duplicate genes descending from polyploidy augmented the transcription factor diversity of avocado, while tandem duplicates enhanced the secondary metabolism of the species. Phenylpropanoid biosynthesis, known to be elicited by Colletotrichum (anthracnose) pathogen infection in avocado, is one enriched function among tandems. Furthermore, transcriptome data show that tandem duplicates are significantly up- and down-regulated in response to anthracnose infection, whereas polyploid duplicates are not, supporting the general view that collections of tandem duplicates contribute evolutionarily recent "tuning knobs" in the genome adaptive landscapes of given species.

vcf2fhir: a utility to convert VCF files into HL7 FHIR format for genomics-EHR integration.

BACKGROUND: VCF formatted files are the lingua franca of next-generation sequencing, whereas HL7 FHIR is emerging as a standard language for electronic health record interoperability. A growing number of FHIR-based clinical genomics applications are emerging. Here, we describe an open source utility for converting variants from VCF format into HL7 FHIR format. RESULTS: vcf2fhir converts VCF variants into a FHIR Genomics Diagnostic Report. Conversion translates each VCF row into a corresponding FHIR-formatted variant in the generated report. In scope are simple variants (SNVs, MNVs, Indels), along with zygosity and phase relationships, for autosomes, sex chromosomes, and mitochondrial DNA. Input parameters include VCF file and genome build ('GRCh37' or 'GRCh38'); and optionally a conversion region that indicates the region(s) to convert, a studied region that lists genomic regions studied by the lab, and a non-callable region that lists studied regions deemed uncallable by the lab. Conversion can be limited to a subset of VCF by supplying genomic coordinates of the conversion region(s). If studied and non-callable regions are also supplied, the output FHIR report will include 'region-studied' observations that detail which portions of the conversion region were studied, and of those studied regions, which portions were deemed uncallable. We illustrate the vcf2fhir utility via two case studies. The first, 'SMART Cancer Navigator', is a web application that offers clinical decision support by linking patient EHR information to cancerous gene variants. The second, 'Precision Genomics Integration Platform', intersects a patient's FHIR-formatted clinical and genomic data with knowledge bases in order to provide on-demand delivery of contextually relevant genomic findings and recommendations to the EHR. CONCLUSIONS: Experience to date shows that the vcf2fhir utility can be effectively woven into clinically useful genomic-EHR integration pipelines. Additional testing will be a critical step towards the clinical validation of this utility, enabling it to be integrated in a variety of real world data flow scenarios. For now, we propose the use of this utility primarily to accelerate FHIR Genomics understanding and to facilitate experimentation with further integration of genomics data into the EHR.

The Hologic Aptima SARS-CoV-2 assay enables high ratio pooling saving reagents and improving turnaround time.

BACKGROUND: The Hologic Aptima™ TMA SARS-CoV-2 assay was employed to test pooled nasopharyngeal (NP) samples to evaluate the performance of pooled sample testing and characterize variables influencing results. METHODS: Results on 1033 previously tested NP samples were retrieved to characterize the relative light units (RLU) of SARS-CoV-2-positive samples in the tested population. The pooling strategy of combining 10 SARS-CoV-2 samples into one pool (10/1) was used in this study. The results were compared with neat sample testing using the same Aptima™ TMA SARS-CoV-2 assay and also the CDC RT-PCR and the Cepheid SARS-CoV-2 assays. RESULTS: The Aptima assay compares favorably with both CDC RT-PCR and the Cepheid SARS-CoV-2 assays. Once samples are pooled 10 to 1 as in our experiments, the resulting signal strength of the assay suffers. A divide opens between pools assembled from strong-positive versus only weak-positive samples. Pools of the former can be reliably detected with positive percent agreement (PPA) of 95.2%, while pools of the latter are frequently misclassified as negative with PPA of 40%. When the weak-positive samples with kRLU value lower than 1012 constitute 3.4% of the total sample profile, the assay PPA approaches 93.4% suggesting that 10/1 pooled sample testing by the Aptima assay is an effective screening tool for SARS-CoV-2. CONCLUSION: Performing pooled testing, one should monitor the weak positives with kRLU lower than 1012 or quantification cycle (Cq) value higher than 35 on an ongoing basis and adjust pooling approaches to avoid reporting false negatives.

Building a precision oncology workforce by multidisciplinary and case-based learning.

BACKGROUND: Participants in two recent National Academy of Medicine workshops identified a need for more multi-disciplinary professionals on teams to assist oncology clinicians in precision oncology. METHODS: We developed a graduate school course to prepare biomedical students and pharmacy students to work within a multidisciplinary team of oncology clinicians, pathologists, radiologists, clinical pharmacists, and genetic counselors. Students learned precision oncology skills via case-based learning, hands-on data analyses, and presentations to peers. After the course, a focus group session was conducted to gain an in-depth student perspective on their interprofessional training experience, achievement of the course learning outcomes, ways to improve the course design in future offerings, and how the course could improve future career outcomes. A convenience sampling strategy was used for recruitment into the focus group session. A thematic content analysis was then conducted using the constant comparative method. RESULTS: Major themes arising from student feedback were (1) appreciation of a customized patient case-based teaching approach, (2) more emphasis on using data analysis tools, (3) valuing interdisciplinary inclusion, and (4) request for more student discussion with advanced preparation materials. CONCLUSIONS: Feedback was generally positive and supports the continuation and expansion of the precision oncology course to include more hands-on instruction on the use of clinical bioinformatic tools.

Deep reticulation and incomplete lineage sorting obscure the diploid phylogeny of rain-lilies and allies (Amaryllidaceae tribe Hippeastreae).

Hybridization is a frequent and important force in plant evolution. Next-generation sequencing (NGS) methods offer new possibilities for clade resolution and ambitious sampling of gene genealogies, yet difficulty remains in detecting deep reticulation events using currently available methods. We reconstructed the phylogeny of diploid representatives of Amaryllidaceae tribe Hippeastreae to test the hypothesis of ancient hybridizations preceding the radiation of its major subclade, Hippeastrinae. Through hybrid enrichment of DNA libraries and NGS, we obtained data for 18 nuclear loci through a curated assembly approach and nearly complete plastid genomes for 35 ingroup taxa plus 5 outgroups. Additionally, we obtained alignments for 39 loci through an automated assembly algorithm. These data were analyzed with diverse phylogenetic methods, including concatenation, coalescence-based species tree estimation, Bayesian concordance analysis, and network reconstructions, to provide insights into the evolutionary relationships of Hippeastreae. Causes for gene tree heterogeneity and cytonuclear discordance were examined through a Bayesian posterior predictive approach (JML) and coalescent simulations. Two major clades were found, Hippeastrinae and Traubiinae, as previously reported. Our results suggest the presence of two major nuclear lineages in Hippeastrinae characterized by different chromosome numbers: (1) Tocantinia and Hippeastrum with 2n=22, and (2) Eithea, Habranthus, Rhodophiala, and Zephyranthes mostly with 2n=12, 14, and 18. Strong cytonuclear discordance was confirmed in Hippeastrinae, and a network scenario with at least six hybridization events is proposed to reconcile nuclear and plastid signals, along a backbone that may also have been affected by incomplete lineage sorting at the base of each major subclade.

Endometrial Thickness as Measured by Transvaginal Ultrasound and the Corresponding Histopathologic Diagnosis in Women With Postmenopausal Bleeding.

Endometrial thickness as measured by transvaginal ultrasound (TVUS) is being increasingly used as a first-line method to evaluate patients with vaginal bleeding. Our study aims to examine correlation between the histopathologic diagnosis and the results of TVUS and find a threshold that could reliably exclude carcinoma. We included women, age 55 years and above, who presented with postmenopausal bleeding and had a TVUS within 30 days of their endometrial biopsy. Total of 304 patients met our criteria and were divided into 4 groups. Patients in group A (n=198) had benign/atrophic endometrium, group B (n=44) had polyps, group C (n=30) had hyperplasia, and group D (n=32) had carcinoma. The endometrial thickness obtained by TVUS was compared with the histopathologic finding of the endometrial biopsy. The mean endometrial thickness was 7.5, 12.1, 14.8, and 16.9 mm for groups A to D, respectively. Statistical analysis showed that very low endometrial thickness (3 to 4 mm) would be ideal to use as a threshold to maximize sensitivity. Three of 32 patients in group D had an endometrial thickness ≤4 mm. At a threshold of 4 mm, the sensitivity is 90.6% and increases to 96.9% when decreasing the threshold to 3 mm. However, other parameters such as test accuracy, specificity, and positive predictive values are very low at these thresholds. Sensitivity can be maximized to 96.9% using a threshold of 3 mm. However, this would call into question the cost-effectiveness of this method. Postmenopausal bleeding remains the most reliable indicator of endometrial pathology.

Potential use of low-copy nuclear genes in DNA barcoding: a comparison with plastid genes in two Hawaiian plant radiations.

BACKGROUND: DNA barcoding of land plants has relied traditionally on a small number of markers from the plastid genome. In contrast, low-copy nuclear genes have received little attention as DNA barcodes because of the absence of universal primers for PCR amplification. RESULTS: From pooled-species 454 transcriptome data we identified two variable intron-less nuclear loci for each of two species-rich genera of the Hawaiian flora: Clermontia (Campanulaceae) and Cyrtandra (Gesneriaceae) and compared their utility as DNA barcodes with that of plastid genes. We found that nuclear genes showed an overall greater variability, but also displayed a high level of heterozygosity, intraspecific variation, and retention of ancient alleles. Thus, nuclear genes displayed fewer species-diagnostic haplotypes compared to plastid genes and no interspecies gaps. CONCLUSIONS: The apparently greater coalescence times of nuclear genes are likely to limit their utility as barcodes, as only a small proportion of their alleles were fixed and unique to individual species. In both groups, species-diagnostic markers from either genome were scarce on the youngest island; a minimum age of ca. two million years may be needed for a species flock to be barcoded. For young plant groups, nuclear genes may not be a superior alternative to slowly evolving plastid genes.

Validation of reference transcripts in strawberry (Fragaria spp.).

Contemporary methods to assay gene expression depend on a stable set of reference transcripts for accurate quantitation. A lack of well-tested reference genes slows progress in characterizing gene expression in high-value specialty crops. In this study, a set of strawberry (Fragaria spp.) constitutively expressed reference genes has been identified by merging digital gene expression data with expression profiling. Constitutive reference candidates were validated using quantitative PCR and hybridization. Several transcripts have been identified that show improved stability across tissues relative to traditional reference transcripts. Results are similar between commercial octoploid strawberry and the diploid model. Our findings also show that while some never-before-used references are appropriate for most applications, even the most stable reference transcripts require careful assessment across the diverse tissues and fruit developmental states before being adopted as controls.

Maintaining informatics training learning outcomes with a COVID-19 era shift to a fully online flipped course.

The emergence of the coronavirus disease 2019 pandemic forced us to adapt our recently developed informatics training serving a variety of students as well as faculty and staff. The successful flipped classroom course series (a hybrid-format with both asynchronous online learning and in-person synchronous components) was shifted to a fully online format with the synchronous portion now held via web-based video conference. We repeated our participant survey at the end of each of the 3 one-credit courses to compare student satisfaction and learning outcomes achievement to the original offering. The responses were overall very positive again with a slight response distribution improvement in some measures of satisfaction. Likewise, students reported similar achievement of the learning outcomes across all courses with some Unix coourse objectives receiving higher competency agreement in the new, fully online version. Overall, the fully online version of the course series was equally successful, if not more so, than the original version with a physical classroom session each week. Given that participants also had strong agreement with a new question that they would prefer online class meetings instead of in a classroom, even if there wasn't a global pandemic (citing a variety of logistical reasons such as "convenience of screen sharing," parking issues, and job-related time constraints), the fully online version of the informatics training will be retained.

Automated HL7v2 LRI informatics framework for streamlining genomics-EHR data integration.

While VCF formatted files are the lingua franca of next-generation sequencing, most EHRs do not provide native VCF support. As a result, labs often must send non-structured PDF reports to the EHR. On the other hand, while FHIR adoption is growing, most EHRs support HL7 interoperability standards, particularly those based on the HL7 Version 2 (HL7v2) standard. The HL7 Version 2 genomics component of the HL7 Laboratory Results Interface (HL7v2 LRI) standard specifies a formalism for the structured communication of genomic data from lab to EHR. We previously described an open-source tool (vcf2fhir) that converts VCF files into HL7 FHIR format. In this report, we describe how the utility has been extended to output HL7v2 LRI data that contains both variants and variant annotations (e.g., predicted phenotypes and therapeutic implications). Using this HL7v2 converter, we implemented an automated pipeline for moving structured genomic data from the clinical laboratory to EHR. We developed an open source hl7v2GenomicsExtractor that converts genomic interpretation report files into a series of HL7v2 observations conformant to HL7v2 LRI. We further enhanced the converter to produce output conformant to Epic's genomic import specification and to support alternative input formats. An automated pipeline for pushing standards-based structured genomic data directly into the EHR was successfully implemented, where genetic variant data and the clinical annotations are now both available to be viewed in the EHR through Epic's genomics module. Issues encountered in the development and deployment of the HL7v2 converter primarily revolved around data variability issues, primarily lack of a standardized representation of data elements within various genomic interpretation report files. The technical implementation of a HL7v2 message transformation to feed genomic variant and clinical annotation data into an EHR has been successful. In addition to genetic variant data, the implementation described here releases the valuable asset of clinically relevant genomic annotations provided by labs from static PDFs to calculable, structured data in EHR systems.

Transcriptional Profile of Human Pancreatic Acinar Ductal Metaplasia.

BACKGROUND AND AIMS: Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from genetically engineered mouse models. METHODS: We used primary, human pancreatic acinar cells from organ donors to evaluate the transcriptional and pathway profiles during the course of ADM. RESULTS: Following 6 days of three-dimensional culture on Matrigel, acinar cells underwent morphological and molecular changes indicative of ADM. mRNA from 14 donors' paired cells (day 0, acinar phenotype and day 6, ductal phenotype) was subjected to whole transcriptome sequencing. Acinar cell specific genes were significantly downregulated in the samples from the day 6 cultures while ductal cell-specific genes were upregulated. Several regulons of ADM were identified including transcription factors with reduced activity (PTF1A, RBPJL, and BHLHA15) and those ductal and progenitor transcription factors with increased activity (HNF1B, SOX11, and SOX4). Cells with the ductal phenotype contained higher expression of genes increased in pancreatic cancer while cells with an acinar phenotype had lower expression of cancer-associated genes. CONCLUSION: Our findings support the relevancy of human in vitro models to study pancreas cancer pathogenesis and exocrine cell plasticity.

Development and application of a computable genotype model in the GA4GH Variation Representation Specification.

As the diversity of genomic variation data increases with our growing understanding of the role of variation in health and disease, it is critical to develop standards for precise inter-system exchange of these data for research and clinical applications. The Global Alliance for Genomics and Health (GA4GH) Variation Representation Specification (VRS) meets this need through a technical terminology and information model for disambiguating and concisely representing variation concepts. Here we discuss the recent Genotype model in VRS, which may be used to represent the allelic composition of a genetic locus. We demonstrate the use of the Genotype model and the constituent Haplotype model for the precise and interoperable representation of pharmacogenomic diplotypes, HGVS variants, and VCF records using VRS and discuss how this can be leveraged to enable interoperable exchange and search operations between assayed variation and genomic knowledgebases.

Sync for Genes Phase 5: Computable artifacts for sharing dynamically annotated FHIR-formatted genomic variants.

Introduction: Variant annotation is a critical component in next-generation sequencing, enabling a sequencing lab to comb through a sea of variants in order to hone in on those likely to be most significant, and providing clinicians with necessary context for decision-making. But with the rapid evolution of genomics knowledge, reported annotations can quickly become out-of-date. Under the ONC Sync for Genes program, our team sought to standardize the sharing of dynamically annotated variants (e.g., variants annotated on demand, based on current knowledge). The computable biomedical knowledge artifacts that were developed enable a clinical decision support (CDS) application to surface up-to-date annotations to clinicians. Methods: The work reported in this article relies on the Health Level 7 Fast Healthcare Interoperability Resources (FHIR) Genomics and Global Alliance for Genomics and Health (GA4GH) Variant Annotation (VA) standards. We developed a CDS pipeline that dynamically annotates patient's variants through an intersection with current knowledge and serves up the FHIR-encoded variants and annotations (diagnostic and therapeutic implications, molecular consequences, population allele frequencies) via FHIR Genomics Operations. ClinVar, CIViC, and PharmGKB were used as knowledge sources, encoded as per the GA4GH VA specification. Results: Primary public artifacts from this project include a GitHub repository with all source code, a Swagger interface that allows anyone to visualize and interact with the code using only a web browser, and a backend database where all (synthetic and anonymized) patient data and knowledge are housed. Conclusions: We found that variant annotation varies in complexity based on the variant type, and that various bioinformatics strategies can greatly improve automated annotation fidelity. More importantly, we demonstrated the feasibility of an ecosystem where genomic knowledge bases have standardized knowledge (e.g., based on the GA4GH VA spec), and CDS applications can dynamically leverage that knowledge to provide real-time decision support, based on current knowledge, to clinicians at the point of care.

Introducing HL7 FHIR Genomics Operations: a developer-friendly approach to genomics-EHR integration.

OBJECTIVE: Enabling clinicians to formulate individualized clinical management strategies from the sea of molecular data remains a fundamentally important but daunting task. Here, we describe efforts towards a new paradigm in genomics-electronic health record (HER) integration, using a standardized suite of FHIR Genomics Operations that encapsulates the complexity of molecular data so that precision medicine solution developers can focus on building applications. MATERIALS AND METHODS: FHIR Genomics Operations essentially "wrap" a genomics data repository, presenting a uniform interface to applications. More importantly, operations encapsulate the complexity of data within a repository and normalize redundant data representations-particularly relevant in genomics, where a tremendous amount of raw data exists in often-complex non-FHIR formats. RESULTS: Fifteen FHIR Genomics Operations have been developed, designed to support a wide range of clinical scenarios, such as variant discovery; clinical trial matching; hereditary condition and pharmacogenomic screening; and variant reanalysis. Operations are being matured through the HL7 balloting process, connectathons, pilots, and the HL7 FHIR Accelerator program. DISCUSSION: Next-generation sequencing can identify thousands to millions of variants, whose clinical significance can change over time as our knowledge evolves. To manage such a large volume of dynamic and complex data, new models of genomics-EHR integration are needed. Qualitative observations to date suggest that freeing application developers from the need to understand the nuances of genomic data, and instead base applications on standardized APIs can not only accelerate integration but also dramatically expand the applications of Omic data in driving precision care at scale for all.

A genomic data archive from the Network for Pancreatic Organ donors with Diabetes.

The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

Next-generation sequencing and genome evolution in allopolyploids.

PREMISE OF THE STUDY: Hybridization and polyploidization (allopolyploidy) are ubiquitous in the evolution of plants, but tracing the origins and subsequent evolution of the constituent genomes of allopolyploids has been challenging. Genome doubling greatly complicates genetic analyses, and this has long hindered investigation in that most allopolyploid species are "nonmodel" organisms. However, recent advances in sequencing and genomics technologies now provide unprecedented opportunities to analyze numerous genetic markers in multiple individuals in any organism. METHODS: Here we review the application of next-generation sequencing technologies to the study of three aspects of allopolyploid genome evolution: duplicated gene loss and expression in two recently formed Tragopogon allopolyploids, intergenomic interactions and chromosomal evolution in Tragopogon miscellus, and repetitive DNA evolution in Nicotiana allopolyploids. KEY RESULTS: For the first time, we can explore on a genomic scale the evolutionary processes that are ongoing in natural allopolyploids and not be restricted to well-studied crops and genetic models. CONCLUSIONS: These approaches can be easily and inexpensively applied to many other plant species-making any evolutionarily provocative system a new "model" system.

HUMAN STUDY COMT and DRD3 haplotype-associated pain intensity and acute care utilization in adult sickle cell disease.

A previous exploratory analysis of a COMT gene single-nucleotide polymorphism (SNP) and a DRD3 SNP by our group suggested possible contributions to pain-related acute care utilization in people with sickle cell disease (SCD). Our aim was to extend the analysis to gene-spanning haplotypes of COMT SNPs and DRD3 SNPs to investigate possible associations with pain intensity and pain-related acute care utilization in an SCD cohort. Genotyping was conducted, and clinical data were collected, including self-reported pain intensity using PAINReportIt® (average of current pain and least and worst in past 24 hours, average pain intensity [API]) and medical record-extracted, pain-related acute care utilization data of 130 adults with SCD. Haplotype blocks were identified based on linkage disequilibria (COMT = 7 haploblocks; DRD3 = 8 haploblocks). Regression analyses were tested for association between haplotypes and API and utilization, yielding several significant findings. For COMT block 1 (rs2075507, rs4646310, rs737865), the A-G-G haplotype was associated with higher API compared to the reference A-G-A (p = 0.02), whereas the A-A-A haplotype was associated with higher utilization (p = 0.02). For DRD3 block 2 (rs9817063, rs2134655, rs963468, and rs3773679), relative to reference T-C-G-C, the T-T-G-C haplotype was associated with higher utilization (p = 0.01). For DRD3 block 4 (rs167770, rs324029, and rs324023), the A-G-T haplotype was associated with higher API (p = 0.04) and utilization (p < 0.001) relative to reference G-A-T, whereas the A-A-T haplotype was associated with higher utilization (p = 0.01). We found COMT and DRD3 haplotypes associated with pain-related SCD features, suggesting that in future studies more emphasis be placed on cis effects of SNP alleles in evaluating genetic contributions to SCD pain and acute care utilization for pain.

The vaginal microbiome is associated with endometrial cancer grade and histology.

The human microbiome has been strongly correlated with disease pathology and outcomes, yet remains relatively underexplored in patients with malignant endometrial disease. In this study, vaginal microbiome samples were prospectively collected at the time of hysterectomy from 61 racially and ethnically diverse patients from three disease conditions: 1) benign gynecologic disease (controls, n=11), 2) low-grade endometrial carcinoma (n=30), and 3) high-grade endometrial carcinoma (n=20). Extracted DNA underwent shotgun metagenomics sequencing, and microbial α and ß diversities were calculated. Hierarchical clustering was used to describe community state types (CST), which were then compared by microbial diversity and grade. Differential abundance was calculated, and machine learning utilized to assess the predictive value of bacterial abundance to distinguish grade and histology. Both α- and ß-diversity were associated with patient tumor grade. Four vaginal CST were identified that associated with grade of disease. Different histologies also demonstrated variation in CST within tumor grades. Using supervised clustering algorithms, critical microbiome markers at the species level were used to build models that predicted benign vs carcinoma, high-grade carcinoma versus benign, and high-grade versus low-grade carcinoma with high accuracy. These results confirm that the vaginal microbiome segregates not just benign disease from endometrial cancer, but is predictive of histology and grade. Further characterization of these findings in large, prospective studies is needed to elucidate their potential clinical applications.

Analysis of AVPR1A, thermal and pressure pain thresholds, and stress in sickle cell disease.

Aim: In patients with sickle cell disease (SCD), negative physical and emotional experiences result from intense chronic and acute pain episodes, but factors underlying these, and their interactions, are not well understood. The arginine vasopressin receptor 1a gene (AVPR1A) single nucleotide polymorphism rs10877969 has been previously associated with aspects of acute pain and stress related pain. In this study, we tested for associations between this SNP, thermal and pressure pain thresholds, clinical pain, and stress in people with SCD. Methods: 150 adults enrolled with SCD completed pain intensity measures (Average Pain Intensity, API) and the Perceived Stress Questionnaire (PSQ). Thermal and pressure pain threshold data were available from quantitative sensory testing (QST), and rs10877969 genotypes were obtained. Results: In models adjusted for age and gender, between rs10877969 genotypes, we observed no significant differences in thermal (cold, p = 0.66; heat, p = 0.91) and mechanical (pressure, p = 0.33) pain thresholds. The association of rs10877969 with API (p = 0.09) was borderline, but non-significant with PSQ (p = 0.51). The correlation between clinical pain and environmental stress was significant, r = 0.18, p = 0.024, however, the interaction of genotype and PSQ was not significant (p = 0.63). Conclusion: Clinical and experimental pain were not significantly associated with the rs10877969 genotype. The rs10877969 genotype did not moderate the correlation between environmental stress and clinical pain in this population. However, a trend toward a protective T allele effect on average pain rating in SCD warrants future exploration of this SNP/gene in SCD.