Association of operative time and approach on postoperative complications for esophagectomy.

BACKGROUND: Minimally invasive esophagectomy is associated with decreased postoperative complications compared with open esophagectomy. However, the risks of complications for minimally invasive esophagectomy compared with open esophagectomy may be affected by operative time. The objectives of this study are to (1) compare the incidence of postoperative complications for minimally invasive esophagectomy and open esophagectomy and (2) evaluate the association of postoperative complications on operative approach and operative time. METHODS: A retrospective cohort analysis of patients who underwent an esophagectomy in the American College of Surgeons National Surgical Quality Improvement Program Procedure-Targeted Data File was performed from 2016 to 2020. For analysis, minimally invasive esophagectomy and open esophagectomy were stratified into tertiles of operative time. A bivariate analysis of postoperative complications comparing minimally invasive esophagectomy with open esophagectomy was performed. Multivariable Poisson regression models were estimated evaluating the association of the likelihood of postoperative complications with operative approach and operative time. RESULTS: In total, 8,574 patients who underwent esophagectomy were included: 5,369 patients underwent minimally invasive esophagectomy, and 3,205 patients underwent open esophagectomy. Median operative time was 402 minutes for minimally invasive esophagectomy and 321 minutes for open esophagectomy. The incidence of postoperative complications and 30-day mortality was lower in the minimally invasive esophagectomy group than the open esophagectomy group within the same tertiles of operative time. When we compared patients who underwent short open esophagectomy with those who underwent long minimally invasive esophagectomy, there were no significant differences in complications. CONCLUSION: There is no significant association of postoperative complications for short open esophagectomy compared with long minimally invasive esophagectomy. Patients should be selected for minimally invasive esophagectomy when there is appropriate surgeon experience and hospital resources.

Robotic Surgery in Thoracic Training Programs: A National Needs Assessment.

BACKGROUND: The cardiothoracic surgical trainees perceive a need for more instruction and exposure to robotic-assisted thoracoscopic surgery (RATS) during their training. We sought to assess utilization and trainee exposure to robotic surgery in thoracic residency programs to identify areas for improvement. METHODS: A voluntary electronic survey of 10 questions was distributed to surgeons working in all thoracic surgery residency programs in the United States. The survey asked to provide the size of the residency, the availability and utilization of robots, and the trainee's adoption of robotic surgery in their practice after graduation. Multivariable logistic regression was performed with Stata MP version 17.0 (College Station, TX). RESULTS: Of a total of 76 cardiothoracic surgery training programs, surgeons from 69 training programs completed the survey (90.8%). The majority of pulmonary lobectomy was performed using robotic surgery (55%). About half of the training programs (35/69) have a formal robotic curriculum for the residents. Of 121 thoracic-track trainees, 118 trainees (97.5%) performed robotic surgery as part of their practice, while 62 of 110 (56.4%) cardiothoracic (CT) track and 16 of 158 (10.1%) cardiac-track trainees performed robotic surgery. In a multivariate analysis, the adoption of robotic surgery was associated with having an established robotic training curriculum (OR 5.82, 95% CI 1.32 - 35.7), and a larger training program (OR 3.78, 95% CI 1.34 - 10.6). CONCLUSIONS: A disparity exists in robotic surgical training among the training programs. A standardized curriculum and formal case requirements may be needed to ensure optimal preparation for future graduates.

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.

Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Leveraging gene co-regulation to identify gene sets enriched for disease heritability.

Identifying gene sets that are associated to disease can provide valuable biological knowledge, but a fundamental challenge of gene set analyses of GWAS data is linking disease-associated SNPs to genes. Transcriptome-wide association studies (TWASs) detect associations between the genetically predicted expression of a gene and disease risk, thus implicating candidate disease genes. However, causal disease genes at TWAS-associated loci generally remain unknown due to gene co-regulation, which leads to correlations across genes in predicted expression. We developed a method, gene co-regulation score (GCSC) regression, to identify gene sets that are enriched for disease heritability explained by predicted expression. GCSC regresses TWAS chi-square statistics on gene co-regulation scores reflecting correlations in predicted gene expression; a gene set is enriched for heritability if genes with high co-regulation to the set have higher TWAS chi-square statistics than genes with low co-regulation to the set, beyond what is expected based on co-regulation to all genes. We verified via simulations that GCSC is well calibrated and well powered. We applied GCSC to gene expression data from GTEx (48 tissues) and GWAS summary statistics for 43 independent diseases and complex traits analyzing a broad set of biological pathways and specifically expressed gene sets. We identified many enriched sets, recapitulating known biology. For Alzheimer disease, we detected evidence of an immune basis, and specifically a role for antigen presentation, in analyses of both biological pathways and specifically expressed gene sets. Our results highlight the advantages of leveraging gene co-regulation within the TWAS framework to identify enriched gene sets.

Indwelling Central Venous Catheters Drive Bloodstream Infection During Veno-venous Extracorporeal Membrane Oxygenation Support.

Blood stream infection (BSI) is a potentially lethal complication in patients receiving extracorporeal membrane oxygenation (ECMO). It may be particularly common in patients with veno-venous ECMO due to their long hospitalization in the intensive care unit. Given that these patients have concurrent indwelling central venous catheters (CVC), it is unclear whether the ECMO circuit, CVC, or both, contribute to BSI. This study evaluated the risk factors associated with BSI in patients receiving veno-venous ECMO in a single institution study of 61 patients from 2016 through 2019. All ECMO catheters and the circuit oxygenator fluid were aseptically collected and analyzed for microorganisms at the time of decannulation. New BSI was diagnosed in 15 (24.6%) patients and increased mortality by threefold. None of the ECMO catheters or oxygenator fluid were culture positive. BSI increased with CVC use of over 8 days and was significantly lowered when CVC were exchanged by day 8 compared with patients with exchanges at later points (15.0% vs. 42.8%, p = 0.02). Median length of CVC use in the BSI-negative and BSI-positive group were 6.3 ± 5.0 and 9.4 ± 5.1, respectively (p = 0.04). In summary, BSI is a potentially lethal complication in patients receiving ECMO. Indwelling CVC, not the ECMO circuitry, is the likely contributor for BSI, and exchanging CVC by day 8 can reduce the incidence of BSI.

Outcomes after extracorporeal membrane oxygenation support in COVID-19 and non-COVID-19 patients.

BACKGROUND: Veno-venous extracorporeal membrane oxygenation (V-V ECMO) support is increasingly used in the management of COVID-19-related acute respiratory distress syndrome (ARDS). However, the clinical decision-making to initiate V-V ECMO for severe COVID-19 still remains unclear. In order to determine the optimal timing and patient selection, we investigated the outcomes of both COVID-19 and non-COVID-19 patients undergoing V-V ECMO support. METHODS: Overall, 138 patients were included in this study. Patients were stratified into two cohorts: those with COVID-19 and non-COVID-19 ARDS. RESULTS: The survival in patients with COVID-19 was statistically similar to non-COVID-19 patients (p = .16). However, the COVID-19 group demonstrated higher rates of bleeding (p = .03) and thrombotic complications (p < .001). The duration of V-V ECMO support was longer in COVID-19 patients compared to non-COVID-19 patients (29.0 ± 27.5 vs 15.9 ± 19.6 days, p < .01). Most notably, in contrast to the non-COVID-19 group, we found that COVID-19 patients who had been on a ventilator for longer than 7 days prior to ECMO had 100% mortality without a lung transplant. CONCLUSIONS: These findings suggest that COVID-19-associated ARDS was not associated with a higher post-ECMO mortality than non-COVID-19-associated ARDS patients, despite longer duration of extracorporeal support. Early initiation of V-V ECMO is important for improved ECMO outcomes in COVID-19 ARDS patients. Since late initiation of ECMO was associated with extremely high mortality related to lack of pulmonary recovery, it should be used judiciously or as a bridge to lung transplantation.

Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.

Polygenic risk prediction is a widely investigated topic because of its promising clinical applications. Genetic variants in functional regions of the genome are enriched for complex trait heritability. Here, we introduce a method for polygenic prediction, LDpred-funct, that leverages trait-specific functional priors to increase prediction accuracy. We fit priors using the recently developed baseline-LD model, including coding, conserved, regulatory, and LD-related annotations. We analytically estimate posterior mean causal effect sizes and then use cross-validation to regularize these estimates, improving prediction accuracy for sparse architectures. We applied LDpred-funct to predict 21 highly heritable traits in the UK Biobank (avg N = 373 K as training data). LDpred-funct attained a +4.6% relative improvement in average prediction accuracy (avg prediction R2 = 0.144; highest R2 = 0.413 for height) compared to SBayesR (the best method that does not incorporate functional information). For height, meta-analyzing training data from UK Biobank and 23andMe cohorts (N = 1107 K) increased prediction R2 to 0.431. Our results show that incorporating functional priors improves polygenic prediction accuracy, consistent with the functional architecture of complex traits.

Population-specific causal disease effect sizes in functionally important regions impacted by selection.

Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.

Improving the informativeness of Mendelian disease-derived pathogenicity scores for common disease.

Despite considerable progress on pathogenicity scores prioritizing variants for Mendelian disease, little is known about the utility of these scores for common disease. Here, we assess the informativeness of Mendelian disease-derived pathogenicity scores for common disease and improve upon existing scores. We first apply stratified linkage disequilibrium (LD) score regression to evaluate published pathogenicity scores across 41 common diseases and complex traits (average N = 320K). Several of the resulting annotations are informative for common disease, even after conditioning on a broad set of functional annotations. We then improve upon published pathogenicity scores by developing AnnotBoost, a machine learning framework to impute and denoise pathogenicity scores using a broad set of functional annotations. AnnotBoost substantially increases the informativeness for common disease of both previously uninformative and previously informative pathogenicity scores, implying that Mendelian and common disease variants share similar properties. The boosted scores also produce improvements in heritability model fit and in classifying disease-associated, fine-mapped SNPs. Our boosted scores may improve fine-mapping and candidate gene discovery for common disease.

Malignant melanoma arising in a primary mediastinal germ cell tumor.

Primary mediastinal germ cell tumors with somatic malignancies are rare. We report a case of a 34-year old man with melanoma arising in a primary mediastinal mixed germ cell tumor. On initial biopsy, the patient was found to have a germ cell tumor containing yolk sac and embryonal components only. After chemotherapy, histopathological evaluation of the residual tumor in the wide local resection specimen revealed a mature teratoma with melanoma. Molecular studies demonstrated that the residual germ cell tumor harbored KIT and NRAS mutations associated with malignant melanoma.

Pre-Intubation Veno-Venous Extracorporeal Membrane Oxygenation in Patients at Risk for Respiratory Decompensation.

Veno-venous extracorporeal membrane oxygenation (VV-ECMO) has emerged as a potential life-saving treatment for patients with acute respiratory failure. Given the accumulating literature supporting the use of VV-ECMO without therapeutic levels of anticoagulation, it might be feasible to use it for planned intubation before surgical procedures. Here, we report consecutive series of patients who underwent planned initiation of VV-ECMO, without anticoagulation, before induction of general anesthesia for anticipated difficult airways or respiratory decompensation. We describe the approach to safely initiate VV-ECMO in an awake patient. We retrospectively identified patients in a prospectively maintained database who underwent planned initiation of VV-ECMO before intubation. Standard statistical methods were used to determine post-procedure outcomes. Patients included were three men and one woman, with a mean age of 34.3 ± 10.4 years. Indications included mediastinal lymphoma, foreign body obstruction, hemoptysis, and tracheo-esophageal fistula. VV-ECMO was initiated electively for all patients, and no anticoagulation was used. The median duration of VV-ECMO support was 2.5 days (1-11 days), the median length of ventilator dependence and intensive care unit stay was 1 day (1-23 days) and 5 days (4-31 days), respectively. The median length of stay was 18.5 days (8-39 days). There were no thrombotic complications and no mortality at 30 days. Initiation of awake VV-ECMO is feasible and is safe before intubation and induction of anesthesia in patients at high risk for respiratory decompensation.

DNA methylation biomarkers discovered in silico detect cancer in liquid biopsies from non-small cell lung cancer patients.

Identification of cancer-specific methylation of DNA released by tumours can be used for non-invasive diagnostics and monitoring. We previously reported in silico identification of DNA methylation loci specifically hypermethylated in common human cancers that could be used as epigenetic biomarkers. Using DNA methylation specific qPCR we now clinically tested a group of these cancer-specific loci on cell-free DNA (cfDNA) extracted from the plasma fraction of blood samples from healthy controls and non-small cell lung cancer (NSCLC) patients. These DNA methylation biomarkers distinguish lung cancer cases from controls with high sensitivity and specificity (AUC = 0.956), and furthermore, the signal from the markers correlates with tumour size and decreases after surgical resection of lung tumours. Presented observations suggest the clinical value of these DNA methylation biomarkers for NSCLC diagnostics and monitoring. Since we successfully validated the biomarkers using independent DNA methylation data from multiple additional common carcinoma cohorts (bladder, breast, colorectal, oesophageal, head and neck, pancreatic or prostate cancer) we predict that these DNA methylation biomarkers will detect additional carcinoma types from plasma samples as well.

Genes with High Network Connectivity Are Enriched for Disease Heritability.

Recent studies have highlighted the role of gene networks in disease biology. To formally assess this, we constructed a broad set of pathway, network, and pathway+network annotations and applied stratified LD score regression to 42 diseases and complex traits (average N = 323K) to identify enriched annotations. First, we analyzed 18,119 biological pathways. We identified 156 pathway-trait pairs whose disease enrichment was statistically significant (FDR < 5%) after conditioning on all genes and 75 known functional annotations (from the baseline-LD model), a stringent step that greatly reduced the number of pathways detected; most significant pathway-trait pairs were previously unreported. Next, for each of four published gene networks, we constructed probabilistic annotations based on network connectivity. For each gene network, the network connectivity annotation was strongly significantly enriched. Surprisingly, the enrichments were fully explained by excess overlap between network annotations and regulatory annotations from the baseline-LD model, validating the informativeness of the baseline-LD model and emphasizing the importance of accounting for regulatory annotations in gene network analyses. Finally, for each of the 156 enriched pathway-trait pairs, for each of the four gene networks, we constructed pathway+network annotations by annotating genes with high network connectivity to the input pathway. For each gene network, these pathway+network annotations were strongly significantly enriched for the corresponding traits. Once again, the enrichments were largely explained by the baseline-LD model. In conclusion, gene network connectivity is highly informative for disease architectures, but the information in gene networks may be subsumed by regulatory annotations, emphasizing the importance of accounting for known annotations.

Optimal surgical intervention for achalasia: laparoscopic or robotic approach.

Laparoscopic esophageal myotomy is the standard surgical intervention for achalasia. Compared to standard laparoscopic techniques, use of the robot has theoretical advantages of improved visualization and dexterity. We evaluated the University of Arizona's experience with the two alternatives to compare outcomes. Patients who underwent either laparoscopic or robot-assisted myotomy were identified from a retrospective database from 1/1/2006 to 12/31/2015. Patient demographics, prior treatment, intra-operative complications, operative time, post-operative length of stay and complications, and long-term results were compared between the two groups. We identified 35 laparoscopic and 37 robot-assisted Heller myotomies performed by multiple surgeons. Patient demographics were similar between the two groups with no statistical difference in age, gender, previous operations, pre-operative Botox or dilation treatment, or pre-op Eckardt score. In univariate analysis, the patients with the robotic procedure received a longer myotomy (5.85 cm vs. 5.56 cm for esophageal and 2.92 cm vs. 2.68 cm for gastric) and had a lower post-operative Eckardt score (0.51 vs. 1.09). A trend toward lower incidence of recurrent achalasia symptoms was found in the robotic group (0 patient vs. 4 patients) compared with those who had laparoscopic surgery (p < 0.05). Multivariate analysis showed that a longer gastric myotomy was associated with a lower recurrence rate (p = 0.0002). Both laparoscopic and robot-assisted Heller myotomy can provide definitive treatment of achalasia with good results and few complications. The mechanical advantage provided by the robotic approach may improve outcomes by providing a more complete myotomy and durable long-term result.

Double-negative (CD27-IgD-) B cells are expanded in NSCLC and inversely correlate with affinity-matured B cell populations.

BACKGROUND: The presence of B cells in early stage non-small cell lung cancer (NSCLC) is associated with longer survival, however, the role these cells play in the generation and maintenance of anti-tumor immunity is unclear. B cells differentiate into a variety of subsets with differing characteristics and functions. To date, there is limited information on the specific B cell subsets found within NSCLC. To better understand the composition of the B cell populations found in NSCLC we have begun characterizing B cells in lung tumors and have detected a population of B cells that are CD79A+CD27-IgD-. These CD27-IgD- (double-negative) B cells have previously been characterized as unconventional memory B cells and have been detected in some autoimmune diseases and in the elderly population but have not been detected previously in tumor tissue. METHODS: A total of 15 fresh untreated NSCLC tumors and 15 matched adjacent lung control tissues were dissociated and analyzed by intracellular flow cytometry to detect the B cell-related markers CD79A, CD27 and IgD. All CD79A+ B cells subsets were classified as either naïve (CD27-IgD+), affinity-matured (CD27+IgD-), early memory/germinal center cells (CD27+IgD+) or double-negative B cells (CD27-IgD-). Association of double-negative B cells with clinical data including gender, age, smoking status, tumor diagnosis and pathologic differentiation status were also examined using the logistic regression analysis for age and student's t-test for all other variables. Associations with other B cell subpopulations were examined using Spearman's rank correlation. RESULTS: We observed that double-negative B cells were frequently abundant in lung tumors compared to normal adjacent controls (13 out of 15 cases), and in some cases made up a substantial proportion of the total B cell compartment. The presence of double-negative cells was also found to be inversely related to the presence of affinity-matured B cells within the tumor, Spearman's coefficient of - 0.76. CONCLUSIONS: This study is the first to observe the presence of CD27-IgD- double-negative B cells in human NSCLC and that this population is inversely correlated with traditional affinity-matured B cell populations.

Roadmap on semiconductor-cell biointerfaces.

This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world.