Bedside Back to Bench: Building Bridges between Basic and Clinical Genomic Research.

Genome sequencing has revolutionized the diagnosis of genetic diseases. Close collaborations between basic scientists and clinical genomicists are now needed to link genetic variants with disease causation. To facilitate such collaborations, we recommend prioritizing clinically relevant genes for functional studies, developing reference variant-phenotype databases, adopting phenotype description standards, and promoting data sharing.

Probabilistic association of differentially expressed genes with cis-regulatory elements.

Differential gene expression in response to perturbations is mediated at least in part by changes in binding of transcription factors (TFs) and other proteins at specific genomic regions. Association of these cis-regulatory elements (CREs) with their target genes is a challenging task that is essential to address many biological and mechanistic questions. Many current approaches rely on chromatin conformation capture techniques or single-cell correlational methods to establish CRE-to-gene associations. These methods can be effective but have limitations, including resolution, gaps in detectable association distances, and cost. As an alternative, we have developed DegCre, a nonparametric method that evaluates correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations. It has several unique features, including the ability to use any type of CRE activity measurement, yield probabilistic scores for CRE-to-gene pairs, and assess CRE-to-gene pairings across a wide range of sequence distances. We apply DegCre to six data sets, each using different perturbations and containing a variety of regulatory signal measurements, including chromatin openness, histone modifications, and TF occupancy. To test their efficacy, we compare DegCre associations to Hi-C loop calls and CRISPR-validated CRE-to-gene associations, establishing good performance by DegCre that is comparable or superior to competing methods. DegCre is a novel approach to the association of CREs to genes from a perturbation-differential perspective, with strengths that are complementary to existing approaches and allow for new insights into gene regulation.

Long-read genome sequencing and variant reanalysis increase diagnostic yield in neurodevelopmental disorders.

Variant detection from long-read genome sequencing (lrGS) has proven to be more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences HiFi technology on 96 short-read-negative probands with rare diseases that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, nine of which (8/96, ~9.4%) harbored pathogenic or likely pathogenic variants. Nine probands (~9.4%) had variants that were accurately called in both srGS and lrGS and represent changes to clinical interpretation, mostly from recently published gene-disease associations. Seven cases included variants that were only correctly interpreted in lrGS, including copy-number variants, an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality-control and filtration. Thus, while reanalysis of older srGS data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS datasets grow allowing for better variant frequency annotation, the additional lrGS-only rare disease yield will grow over time.

Allele-specific transcription factor binding across human brain regions offers mechanistic insight into eQTLs.

Transcription factors (TFs) regulate gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because TF occupancy is driven in part by recognition of DNA sequence, genetic variation can influence TF-DNA associations and gene regulation. To identify variants that impact TF binding in human brain tissues, we assessed allele-specific binding (ASB) at heterozygous variants for 94 TFs in nine brain regions from two donors. Leveraging graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signals between alleles at heterozygous variants within each brain region and identified thousands of variants exhibiting ASB for at least one TF. ASB reproducibility was measured by comparisons between independent experiments both within and between donors. We found that rare alleles in the general population more frequently led to reduced TF binding, whereas common alleles had an equal likelihood of increasing or decreasing binding. Further, for ASB variants in predicted binding motifs, the favored allele tended to be the one with the stronger expected motif match, but this concordance was not observed within highly occupied sites. We also found that neuron-specific cis-regulatory elements (cCREs), in contrast with oligodendrocyte-specific cCREs, showed depletion of ASB variants. We identified 2670 ASB variants associated with evidence for allele-specific gene expression in the brain from GTEx data and observed increasing eQTL effect direction concordance as ASB significance increases. These results provide a valuable and unique resource for mechanistic analysis of cis-regulatory variation in human brain tissue.

Variants in the degron of AFF3 are associated with intellectual disability, mesomelic dysplasia, horseshoe kidney, and epileptic encephalopathy.

The ALF transcription factor paralogs, AFF1, AFF2, AFF3, and AFF4, are components of the transcriptional super elongation complex that regulates expression of genes involved in neurogenesis and development. We describe an autosomal dominant disorder associated with de novo missense variants in the degron of AFF3, a nine amino acid sequence important for its binding to ubiquitin ligase, or with de novo deletions of this region. The sixteen affected individuals we identified, along with two previously reported individuals, present with a recognizable pattern of anomalies, which we named KINSSHIP syndrome (KI for horseshoe kidney, NS for Nievergelt/Savarirayan type of mesomelic dysplasia, S for seizures, H for hypertrichosis, I for intellectual disability, and P for pulmonary involvement), partially overlapping the AFF4-associated CHOPS syndrome. Whereas homozygous Aff3 knockout mice display skeletal anomalies, kidney defects, brain malformations, and neurological anomalies, knockin animals modeling one of the microdeletions and the most common of the missense variants identified in affected individuals presented with lower mesomelic limb deformities like KINSSHIP-affected individuals and early lethality, respectively. Overexpression of AFF3 in zebrafish resulted in body axis anomalies, providing some support for the pathological effect of increased amount of AFF3. The only partial phenotypic overlap of AFF3- and AFF4-associated syndromes and the previously published transcriptome analyses of ALF transcription factors suggest that these factors are not redundant and each contributes uniquely to proper development.

Genome-wide strand asymmetry in massively parallel reporter activity favors genic strands.

Massively parallel reporter assays (MPRAs) are useful tools to characterize regulatory elements in human genomes. An aspect of MPRAs that is not typically the focus of analysis is their intrinsic ability to differentiate activity levels for a given sequence element when placed in both of its possible orientations relative to the reporter construct. Here, we describe pervasive strand asymmetry of MPRA signals in data sets from multiple reporter configurations in both published and newly reported data. These effects are reproducible across different cell types and in different treatments within a cell type and are observed both within and outside of annotated regulatory elements. From elements in gene bodies, MPRA strand asymmetry favors the sense strand, suggesting that function related to endogenous transcription is driving the phenomenon. Similarly, we find that within Alu mobile element insertions, strand asymmetry favors the transcribed strand of the ancestral retrotransposon. The effect is consistent across the multiplicity of Alu elements in human genomes and is more pronounced in less diverged Alu elements. We find sequence features driving MPRA strand asymmetry and show its prediction from sequence alone. We see some evidence for RNA stabilization and transcriptional activation mechanisms and hypothesize that the effect is driven by natural selection favoring efficient transcription. Our results indicate that strand asymmetry is a pervasive and reproducible feature in MPRA data. More importantly, the fact that MPRA asymmetry favors naturally transcribed strands suggests that it stems from preserved biological functions that have a substantial, global impact on gene and genome evolution.

Errors in genome sequencing result disclosures: A randomized controlled trial comparing neonatology non-genetics healthcare professionals and genetic counselors.

PURPOSE: We compared the rate of errors in genome sequencing (GS) result disclosures by genetic counselors (GC) and trained non-genetics healthcare professionals (NGHPs) in SouthSeq, a randomized trial utilizing GS in critically ill infants. METHODS: Over 400 recorded GS result disclosures were analyzed for major and minor errors. We used Fisher's exact test to compare error rates between GCs and NGHPs and performed a qualitative content analysis to characterize error themes. RESULTS: Major errors were identified in 7.5% of disclosures by NGHPs and in no disclosures by GCs. Minor errors were identified in 32.1% of disclosures by NGHPs and in 11.4% of disclosures by GCs. Although most disclosures lacked errors, NGHPs were significantly more likely to make any error than GCs for all result types (positive, negative, or uncertain). Common major error themes include omission of critical information, overstating a negative result, and overinterpreting an uncertain result. The most common minor error was failing to disclose negative secondary findings. CONCLUSION: Trained NGHPs made clinically significant errors in GS result disclosures. Characterizing common errors in result disclosure can illuminate gaps in education to inform the development of future genomics training and alternative service delivery models.

Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion.

BACKGROUND: The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies. METHODS: Using 2011-2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women's timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics. RESULTS: Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06-1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04-1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80-1.26]). CONCLUSIONS: Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

NCCN Guidelines® Insights: Colorectal Cancer Screening, Version 1.2024.

The NCCN Guidelines for Colorectal Cancer (CRC) Screening describe various colorectal screening modalities as well as recommended screening schedules for patients at average or increased risk of developing sporadic CRC. They are intended to aid physicians with clinical decision-making regarding CRC screening for patients without defined genetic syndromes. These NCCN Guidelines Insights focus on select recent updates to the NCCN Guidelines, including a section on primary and secondary CRC prevention, and provide context for the panel's recommendations regarding the age at which to initiate screening in average-risk individuals and those with increased risk based on personal history of childhood, adolescent, and young adult cancer.

Aberrant regulation of a poison exon caused by a non-coding variant in a mouse model of Scn1a-associated epileptic encephalopathy.

Dravet syndrome (DS) is a developmental and epileptic encephalopathy that results from mutations in the Nav1.1 sodium channel encoded by SCN1A. Most known DS-causing mutations are in coding regions of SCN1A, but we recently identified several disease-associated SCN1A mutations in intron 20 that are within or near to a cryptic and evolutionarily conserved "poison" exon, 20N, whose inclusion is predicted to lead to transcript degradation. However, it is not clear how these intron 20 variants alter SCN1A expression or DS pathophysiology in an organismal context, nor is it clear how exon 20N is regulated in a tissue-specific and developmental context. We address those questions here by generating an animal model of our index case, NM_006920.4(SCN1A):c.3969+2451G>C, using gene editing to create the orthologous mutation in laboratory mice. Scn1a heterozygous knock-in (+/KI) mice exhibited an ~50% reduction in brain Scn1a mRNA and Nav1.1 protein levels, together with characteristics observed in other DS mouse models, including premature mortality, seizures, and hyperactivity. In brain tissue from adult Scn1a +/+ animals, quantitative RT-PCR assays indicated that ~1% of Scn1a mRNA included exon 20N, while brain tissue from Scn1a +/KI mice exhibited an ~5-fold increase in the extent of exon 20N inclusion. We investigated the extent of exon 20N inclusion in brain during normal fetal development in RNA-seq data and discovered that levels of inclusion were ~70% at E14.5, declining progressively to ~10% postnatally. A similar pattern exists for the homologous sodium channel Nav1.6, encoded by Scn8a. For both genes, there is an inverse relationship between the level of functional transcript and the extent of poison exon inclusion. Taken together, our findings suggest that poison exon usage by Scn1a and Scn8a is a strategy to regulate channel expression during normal brain development, and that mutations recapitulating a fetal-like pattern of splicing cause reduced channel expression and epileptic encephalopathy.

An individualized Bayesian method for estimating genomic variants of hypertension.

BACKGROUND: Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual. RESULTS: We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve. CONCLUSIONS: The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Accounting for Medicaid expansion and regional policy and programs to advance equity in cancer prevention in the United States.

BACKGROUND: Many studies compare state-level outcomes to estimate changes attributable to Medicaid expansion. However, it is imperative to conduct more granular, demographic-level analyses to inform current efforts on cancer prevention among low-income adults. Therefore, the authors compared the volume of patients with cancer and disease stage at diagnosis in Ohio, which expanded its Medicaid coverage in 2014, with those in Georgia, a nonexpansion state, by cancer site and health insurance status. METHODS: The authors used state cancer registries from 2010 to 2017 to identify adults younger than 64 years who had incident female breast cancer, cervical cancer, or colorectal cancer. Multivariable Poisson regression was conducted by cancer type, health insurance, and state to examine the risk of late-stage disease, adjusting for individual-level and area-level covariates. A difference-in-differences framework was then used to estimate the differences in risks of late-stage diagnosis in Ohio versus Georgia. RESULTS: In Ohio, the largest increase in all three cancer types was observed in the Medicaid group after Medicaid expansion. In addition, significantly reduced risks of late-stage disease were observed among patients with breast cancer on Medicaid in Ohio by approximately 7% and among patients with colorectal cancer on Medicaid in Ohio and Georgia after expansion by approximately 6%. Notably, the authors observed significantly reduced risks of late-stage diagnosis among all patients with colorectal cancer in Georgia after expansion. CONCLUSIONS: More early stage cancers in the Medicaid-insured and/or uninsured groups after expansion suggest that the reduced cancer burden in these vulnerable population subgroups may be attributed to Medicaid expansion. Heterogeneous risks of late-stage disease by cancer type highlight the need for comprehensive evaluation frameworks, including local cancer prevention efforts and federal health policy reforms. PLAIN LANGUAGE SUMMARY: This study looked at how Medicaid expansion affected cancer diagnosis and treatment in two states, Ohio and Georgia. The researchers found that, after Ohio expanded their Medicaid program, there were more patients with cancer among low-income adults on Medicaid. The study also found that, among people on Medicaid, there were lower rates of advanced cancer at the time of diagnosis for breast cancer and colon cancer in Ohio and for colon cancer in Georgia. These findings suggest that Medicaid expansion may be effective in reducing the cancer burden among low-income adults.

Non-coding and Loss-of-Function Coding Variants in TET2 are Associated with Multiple Neurodegenerative Diseases.

We conducted genome sequencing to search for rare variation contributing to early-onset Alzheimer's disease (EOAD) and frontotemporal dementia (FTD). Discovery analysis was conducted on 435 cases and 671 controls of European ancestry. Burden testing for rare variation associated with disease was conducted using filters based on variant rarity (less than one in 10,000 or private), computational prediction of deleteriousness (CADD) (10 or 15 thresholds), and molecular function (protein loss-of-function [LoF] only, coding alteration only, or coding plus non-coding variants in experimentally predicted regulatory regions). Replication analysis was conducted on 16,434 independent cases and 15,587 independent controls. Rare variants in TET2 were enriched in the discovery combined EOAD and FTD cohort (p = 4.6 × 10-8, genome-wide corrected p = 0.0026). Most of these variants were canonical LoF or non-coding in predicted regulatory regions. This enrichment replicated across several cohorts of Alzheimer's disease (AD) and FTD (replication only p = 0.0029). The combined analysis odds ratio was 2.3 (95% confidence interval [CI] 1.6-3.4) for AD and FTD. The odds ratio for qualifying non-coding variants considered independently from coding variants was 3.7 (95% CI 1.7-9.4). For LoF variants, the combined odds ratio (for AD, FTD, and amyotrophic lateral sclerosis, which shares clinicopathological overlap with FTD) was 3.1 (95% CI 1.9-5.2). TET2 catalyzes DNA demethylation. Given well-defined changes in DNA methylation that occur during aging, rare variation in TET2 may confer risk for neurodegeneration by altering the homeostasis of key aging-related processes. Additionally, our study emphasizes the relevance of non-coding variation in genetic studies of complex disease.

Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing.

PURPOSE: Neurodevelopmental disorders (NDDs) often result from rare genetic variation, but genomic testing yield for NDDs remains below 50%, suggesting that clinically relevant variants may be missed by standard analyses. Here, we analyze "poison exons" (PEs), which are evolutionarily conserved alternative exons often absent from standard gene annotations. Variants that alter PE inclusion can lead to loss of function and may be highly penetrant contributors to disease. METHODS: We curated published RNA sequencing data from developing mouse cortex to define 1937 conserved PE regions potentially relevant to NDDs, and we analyzed variants found by genome sequencing in multiple NDD cohorts. RESULTS: Across 2999 probands, we found 6 novel clinically relevant variants in PE regions. Five of these variants are in genes that are part of the sodium voltage-gated channel alpha subunit family (SCN1A, SCN2A, and SCN8A), which is associated with epilepsies. One variant is in SNRPB, associated with cerebrocostomandibular syndrome. These variants have moderate to high computational impact assessments, are absent from population variant databases, and in genes with gene-phenotype associations consistent with each probands reported features. CONCLUSION: With a very minimal increase in variant analysis burden (average of 0.77 variants per proband), annotation of PEs can improve diagnostic yield for NDDs and likely other congenital conditions.

An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors.

Cells within a tumor microenvironment (TME) dynamically communicate and influence each other's cellular states through an intercellular communication network (ICN). In cancers, intercellular communications underlie immune evasion mechanisms of individual tumors. We developed an individualized causal analysis framework for discovering tumor specific ICNs. Using head and neck squamous cell carcinoma (HNSCC) tumors as a testbed, we first mined single-cell RNA-sequencing data to discover gene expression modules (GEMs) that reflect the states of transcriptomic processes within tumor and stromal single cells. By deconvoluting bulk transcriptomes of HNSCC tumors profiled by The Cancer Genome Atlas (TCGA), we estimated the activation states of these transcriptomic processes in individual tumors. Finally, we applied individualized causal network learning to discover an ICN within each tumor. Our results show that cellular states of cells in TMEs are coordinated through ICNs that enable multi-way communications among epithelial, fibroblast, endothelial, and immune cells. Further analyses of individual ICNs revealed structural patterns that were shared across subsets of tumors, leading to the discovery of 4 different subtypes of networks that underlie disparate TMEs of HNSCC. Patients with distinct TMEs exhibited significantly different clinical outcomes. Our results show that the capability of estimating individual ICNs reveals heterogeneity of ICNs and sheds light on the importance of intercellular communication in impacting disease development and progression.

Osteopontin is associated with dementia in the presence of cerebral small vessel disease.

BACKGROUND: Osteopontin (OPN) is a proinflammatory cytokine that has been recently implicated in neuroinflammation and neurodegeneration. We hypothesized that an increase in plasma osteopontin is a deleterious neuroinflammatory marker in people with dementia and cerebral small vessel disease (CSVD). METHODS: A pilot study was conducted on participants in the Northern Manhattan Study (NOMAS). Three groups were selected based on their dementia status and evidence of subclinical CSVD and chosen to be similar in age, sex, and education attainment: No dementia/No CSVD (n=19), Dementia/No CSVD (n=22), and Dementia+CSVD (n=21). Dementia (any type) was diagnosed by consensus adjudication following a series of comprehensive neuropsychological assessments and a review of the medical history. CSVD was indicated by silent brain infarcts, enlarged perivascular spaces, cerebral microbleeds, and white matter hyperintensity volumes (WMHV) on MRI. Multinomial logistic regression was used to examine the difference in OPN levels across groups, adjusting for key determinants of CSVD and neurodegeneration. RESULTS: Plasma osteopontin levels were elevated in the Dementia+CSVD group (mean=70.69±39.00 ng/ml) but not in the Dementia/No CSVD group (mean=45.46±19.11 ng/ml) compared to the No dementia/No CSVD group (mean=36.43±15.72 ng/ml). Osteopontin was associated with Dementia+CSVD (Odds Ratio (OR) per ng/ml=1.06, 95%CI 1.02-1.11) after adjusting for covariates, including brain volume. OPN was strongly correlated with WMHV (Spearman's rank correlation =0.46, p=0.0001), but not with other components of CSVD. CONCLUSION: In this pilot, greater levels of plasma osteopontin were associated with dementia with evidence of CSVD. This link was predominately driven by the contribution of OPN to dementia through the burden of white matter lesions.

Shorter Time to Treatment Is Associated With Improved Survival in Rural Patients With Breast Cancer Despite Other Adverse Socioeconomic Factors.

BACKGROUND: Cancer care in rural areas poses unique challenges, including access and proximity to care. This study examined differences in time to treatment initiation (TTI), a potential surrogate for access, and predictors of overall survival (OS) between rural and nonrural patients with breast cancer. METHODS: Women with stage I to III breast cancer diagnosed between 2004 and 2012 in facilities accredited by the National Cancer Database of Commission on Cancer (CoC) were included. Differences between rural and nonrural patients in demographics, disease and treatment characteristics, socioeconomic factors, and TTI were assessed by χ2 test. The effects on OS of age, insurance status, cancer center type, community median income, percentage of the community who had not graduated from high school, and TTI were assessed using Cox models. RESULTS: The study population was composed of 1,205,031 patients, 18,417 (2%) of whom were rural. Compared with nonrural patients, rural patients were more likely to be older, to be White, to receive care at nonacademic centers, to have government insurance or annual income less than $38,000, and to be less educated (P < .0001). Rural patients also had shorter median TTI (3 vs 4 weeks; P < .0001), which was associated with improved OS (P < .0001), and were more likely to have TTI less than 4 weeks and less than 8 weeks (P < .0001 for both). Shorter TTI (both <4 weeks vs 8 weeks and 4-8 weeks vs >8 weeks) was also associated with improved OS (P < .0001 for both). After adjusting for disease stage and demographic-, socioeconomic-, and treatment-related factors, rural status was associated with improved OS compared with nonrural status (HR, 0.92; 95% CI, 0.89-0.96; P < .0001). CONCLUSIONS: Despite several adverse demographic and socioeconomic factors, rural patients with breast cancer with access to CoC-accredited facilities had significantly shorter TTI and better OS compared with nonrural patients. The clinical significance of this is undetermined; however, these data suggest that improving TTI can mitigate disparities in rural cancer care.

A voice-based digital assistant for intelligent prompting of evidence-based practices during ICU rounds.

OBJECTIVE: To evaluate the technical feasibility and potential value of a digital assistant that prompts intensive care unit (ICU) rounding teams to use evidence-based practices based on analysis of their real-time discussions. METHODS: We evaluated a novel voice-based digital assistant which audio records and processes the ICU care team's rounding discussions to determine which evidence-based practices are applicable to the patient but have yet to be addressed by the team. The system would then prompt the team to consider indicated but not yet delivered practices, thereby reducing cognitive burden compared to traditional rigid rounding checklists. In a retrospective analysis, we applied automatic transcription, natural language processing, and a rule-based expert system to generate personalized prompts for each patient in 106 audio-recorded ICU rounding discussions. To assess technical feasibility, we compared the system's prompts to those created by experienced critical care nurses who directly observed rounds. To assess potential value, we also compared the system's prompts to a hypothetical paper checklist containing all evidence-based practices. RESULTS: The positive predictive value, negative predictive value, true positive rate, and true negative rate of the system's prompts were 0.45 ± 0.06, 0.83 ± 0.04, 0.68 ± 0.07, and 0.66 ± 0.04, respectively. If implemented in lieu of a paper checklist, the system would generate 56% fewer prompts per patient, with 50%±17% greater precision. CONCLUSION: A voice-based digital assistant can reduce prompts per patient compared to traditional approaches for improving evidence uptake on ICU rounds. Additional work is needed to evaluate field performance and team acceptance.

Patient Decisions Regarding Rescheduling Colonoscopies Postponed Due to the COVID-19 Pandemic.

BACKGROUND: Due to the COVID-19 pandemic, elective colonoscopies were postponed in Ohio from 3/17/2020 to 5/1/2020. When the ban was lifted, canceled patients determined whether to reschedule their colonoscopy in the midst of the ongoing pandemic. AIMS: We aim to determine whether demographic, colorectal cancer (CRC) risk, and COVID-19 morbidity and mortality risk factors are associated with rescheduling of colonoscopies canceled by the COVID-19 pandemic. METHODS: A medical record review of 420 participants ages 40-74 at a midwestern academic health system with elective colonoscopies canceled from 3/17/2020 to 5/1/2020 due to the COVID-19 pandemic was performed. RESULTS: More than half of participants (71.0%) rescheduled their colonoscopy within the next 8 months. Indication for colonoscopy being 'surveillance following adenoma', colonoscopy ordered by primary care provider rather than gastroenterologist, and dyslipidemia were independently associated with rescheduling colonoscopy. Higher body mass index, indication for colonoscopy being simply 'screening for CRC,' and stool testing were associated with not rescheduling. Diagnoses associated with colorectal cancer risk such as adenomas, personal or family history of colorectal cancer, and inflammatory bowel disease were not associated with rescheduling, nor were other comorbidities associated with increased COVID-19 severity. 4.5% (19/420) opted for stool fecal immunochemical test or Cologuard testing. CONCLUSIONS: Most patients rescheduled their colonoscopy despite the risk of virus exposure, suggesting that concern of missed colorectal cancer diagnosis outweighed coronavirus concerns. Patient trust in referring providers may be important for rescheduling, and colonoscopy indications were independently associated with rescheduling status.

Fecal Microbiome Associated with Both Colon Adenomas and Lifetime Colorectal Cancer Risk.

BACKGROUND: Increasing data indicates the gut flora including bacteria and fungi combined with environmental factors are important in the pathogenesis of colorectal cancer (CRC). Understanding differences in the microbiome in patients with colon neoplasia will foster the development of biomarkers for early detection. AIMS: Determine the association of microbiome with presence of adenomas and predicted CRC risk. METHODS: In subjects referred for colonoscopy, the NCI CRC risk assessment tool was completed and stool for microbiome analysis as well as fecal immunochemical test (FIT) were collected. We calculated the microbiome alpha diversity using the Shannon index as well as individual bacterial and fungal species. RESULTS: Among 34 patients, we identified 10 with one or more adenomas. Only 2 patients were FIT positive. The median predicted lifetime CRC risk was 2.75% and the prevalence of adenoma was higher in the fourth quartile (P < 0.001). The measured alpha diversity was somewhat higher in patients with adenomas (P = 0.07). We identified 4 bacterial species with an increased relative abundance among patients with adenomas [P < 0.5]. Lifetime CRC risk was associated with 2 specific bacterial species, P. distasonis & E. hermannii [P = 0.05 & 0.09, respectively]. No associations were seen with fungal species and adenoma prevalence or lifetime CRC risk. CONCLUSIONS: In addition to a strong correlation of predicted CRC risk and adenoma prevalence, we also found important differences in specific bacterial species and both adenoma prevalence and CRC risk. Larger trials are needed to potentially implement further data in the clinical setting.