SWOG S1820: A pilot randomized trial of the Altering Intake, Managing Bowel Symptoms Intervention in Survivors of Rectal Cancer.

BACKGROUND: Survivors of rectal cancer experience persistent bowel dysfunction after treatments. Dietary interventions may be an effective approach for symptom management and posttreatment diet quality. SWOG S1820 was a pilot randomized trial of the Altering Intake, Managing Symptoms in Rectal Cancer (AIMS-RC) intervention for bowel dysfunction in survivors of rectal cancer. METHODS: Ninety-three posttreatment survivors were randomized to the AIMS-RC group (N = 47) or the Healthy Living Education attention control group (N = 46) after informed consent and completion of a prerandomization run-in. Outcome measures were completed at baseline and at 18 and 26 weeks postrandomization. The primary end point was total bowel function score, and exploratory end points included low anterior resection syndrome (LARS) score, quality of life, dietary quality, motivation, self-efficacy, and positive/negative affect. RESULTS: Most participants were White and college educated, with a mean age of 55.2 years and median time since surgery of 13.1 months. There were no statistically significant differences in total bowel function score by group, with the AIMS-RC group demonstrating statistically significant improvements in the exploratory end points of LARS (p = .01) and the frequency subscale of the bowel function index (p = .03). The AIMS-RC group reported significantly higher acceptability of the study. CONCLUSIONS: SWOG S1820 did not provide evidence of benefit from the AIMS-RC intervention relative to the attention control. Select secondary end points did demonstrate improvements. The study was highly feasible and acceptable for participants in the National Cancer Institute Community Oncology Research Program. Findings provide strong support for further refinement and effectiveness testing of the AIMS-RC intervention.

Letter to the Editor: on the stability and internal consistency of component-wise sparse mixture regression-based clustering.

Understanding the relationship between molecular markers and a phenotype of interest is often obfuscated by patient-level heterogeneity. To address this challenge, Chang et al. recently published a novel method called Component-wise Sparse Mixture Regression (CSMR), a regression-based clustering method that promises to detect heterogeneous relationships between molecular markers and a phenotype of interest under high-dimensional settings. In this Letter to the Editor, we raise awareness to several issues concerning the assessment of CSMR in Chang et al., particularly its assessment in settings where the number of features, P, exceeds the study sample size, N, and advocate for additional metrics/approaches when assessing the performance of regression-based clustering methodologies.

optima: an open-source R package for the Tapestri platform for integrative single cell multiomics data analysis.

SUMMARY: The Tapestri platform offers DNA and protein analysis at the single-cell level. Integrating both types of data is beneficial for studying multiple cell populations in heterogeneous microenvironments, such as tumor tissues. Here, we present optima, an R package for the processing and analysis of data generated from the Tapestri platform. This package provides streamlined functionality for raw data filtering, integration, normalization, transformation, and visualization. Insights gained from the optima package help users to identify unique cell populations and uncover surface protein expression patterns. The results generated by optima help researchers elucidate dynamic changes at the single-cell level in heterogeneous microenvironments. AVAILABILITY AND IMPLEMENTATION: This package is available in Github: https://github.com/rachelgriffard/optima.

Improving the accuracy and internal consistency of regression-based clustering of high-dimensional datasets.

Component-wise Sparse Mixture Regression (CSMR) is a recently proposed regression-based clustering method that shows promise in detecting heterogeneous relationships between molecular markers and a continuous phenotype of interest. However, CSMR can yield inconsistent results when applied to high-dimensional molecular data, which we hypothesize is in part due to inherent limitations associated with the feature selection method used in the CSMR algorithm. To assess this hypothesis, we explored whether substituting different regularized regression methods (i.e. Lasso, Elastic Net, Smoothly Clipped Absolute Deviation (SCAD), Minmax Convex Penalty (MCP), and Adaptive-Lasso) within the CSMR framework can improve the clustering accuracy and internal consistency (IC) of CSMR in high-dimensional settings. We calculated the true positive rate (TPR), true negative rate (TNR), IC and clustering accuracy of our proposed modifications, benchmarked against the existing CSMR algorithm, using an extensive set of simulation studies and real biological datasets. Our results demonstrated that substituting Adaptive-Lasso within the existing feature selection method used in CSMR led to significantly improved IC and clustering accuracy, with strong performance even in high-dimensional scenarios. In conclusion, our modifications of the CSMR method resulted in improved clustering performance and may thus serve as viable alternatives for the regression-based clustering of high-dimensional datasets.

The influence of biopsy site and pregnancy on stable isotope ratios in humpback whale skin.

RATIONALE: Stable isotope analysis (SIA) of free-swimming mysticetes using biopsies is often limited in sample size and uses only one sample per individual, failing to capture both intra-individual variability and the influence of demographic and physiological factors on isotope ratios. METHODS: We applied SIA of δ13C and δ15N to humpback whale (Megaptera novaeangliae) biopsies taken during the foraging season along the western Antarctic Peninsula to quantify intra-individual variation from repeatedly sampled individuals, as well as to determine the effect of biopsy collection site, sex, and pregnancy on isotope ratios. RESULTS: There was substantial variability in δ13C from multiple biopsies taken from the same individuals, though δ15N was much more consistent. Side of the body (left versus right) and biopsy location (dorsal, anterior, ventral, and posterior) did marginally affect the isotopic composition of δ15N but not δ13C. Pregnancy had a significant effect on both δ13C and δ15N, where pregnant females were depleted in both when compared to non-pregnant females and males. CONCLUSIONS: These results indicate that isotopic signatures are influenced by multiple endogenous and exogenous factors and emphasize value in accounting for intra-individual variability and pregnancy status within a sampled population. Placed within an ecological context, the endogenous variability in δ13C observed here may be informative for future isotopic analyses.

Selective Reduction of Socioeconomic Disparities in the Experimental Tobacco Marketplace: Effects of Cigarette and E-cigarette Flavor Restrictions.

INTRODUCTION: Cigarette smoking accounts for >30% of the socioeconomic gap in life expectancy. Flavored restrictions claim to promote equity; however, no previous studies have compared the effect of cigarette and e-cigarette flavor restrictions among individuals who smoke with lower and higher socioeconomic status (SES). AIMS AND METHODS: In a between-group within-subject design, individuals with lower (n = 155) and higher (n = 125) SES completed hypothetical purchasing trials in the experimental tobacco marketplace (ETM). Conditions were presented in a 2 × 2 factorial design (cigarette flavors restricted or unrestricted and e-cigarette flavors restricted or unrestricted) with increasing cigarette prices across trials. RESULTS: Results show (1) SES differences in cigarette, e-cigarette, and NRT purchases under unrestricted policies, with lower SES showing higher cigarette demand and lower e-cigarette and NRT substitution than higher SES, (2) cigarette restrictions decreased cigarette and increased NRT purchases among lower SES, but no significant changes among higher SES, (3) decreased SES differences in cigarette demand under cigarette restrictions, but persistence under e-cigarette restrictions or their combination, (4) persistence of SES differences in e-cigarette purchases when all restrictions were enforced, and (5) waning of SES differences in NRT purchasing under all restrictions. CONCLUSIONS: Flavor restrictions differentially affected individuals based on SES. Within-group comparisons demonstrated restrictions significantly impacted lower SES, but not higher SES. Between-group comparisons showed SES differences in cigarette purchasing decreased under cigarette restrictions, but persisted under e-cigarette-restrictions or their combination. Additionally, SES differences in NRT substitution decreased under flavor restrictions. These findings highlight the utility of the ETM to investigate SES disparities. IMPLICATIONS: With increasing trends of socioeconomic differences in smoking prevalence and cessation rates, smoking-related health disparities are expected to continue to widen. Restricting menthol flavor in cigarettes while enhancing the availability and affordability of NRT have the potential to alleviate SES disparities in tobacco use, therefore, positively impacting health equity. However, this effect may depend on flavor availability in other tobacco products.

"You're Someone Different Now": An Autoethnography on Identity and Occupational Identity Disruption After Traumatic Brain Injury.

IMPORTANCE: Identity disruption and occupational identity disruption are common after traumatic brain injury (TBI), but the relationship between these two phenomena is underexplored. Occupational therapy practitioners should be knowledgeable about identity challenges after TBI and ways to reconstruct a sense of self. OBJECTIVE: To sensitize readers to the experience of identity disruption and occupational identity disruption and describe how those two experiences are interrelated and transactional in nature. DESIGN: We completed an autoethnography, because this method privileges the insider perspective of participants as members of the research team. We interviewed Andi's family and friends, with textual and nontextual data being reviewed during team meetings that occurred 3 times per month over 3 yr. Data were analyzed by hand-coding transcripts to organize findings until we identified themes and salient text for constructing a narrative.  Setting: Community. PARTICIPANTS: TBI survivor. RESULTS: Identity disruption after TBI occurs because of physiological difficulties, psychological changes, and cognitive deficits. Additionally, survivors face interruptions in occupational participation that affect their identity as doers. Andi experienced identity disruption that was exacerbated by being unable to engage in written expression. When he was able to resume writing and regain his occupational identity, Andi was able to reconstruct his sense of self. CONCLUSIONS AND RELEVANCE: Identity is created by occupational engagement. Occupational therapy practitioners can better serve their clients by exploring identity disruption and occupational identity disruption after TBI. Plain-Language Summary: This article describes the lived experience of identity disruption and occupational identity disruption with an emphasis on the transformative nature of occupation. Occupational therapists should work collaboratively with clients to identify key occupations that support their sense of identity.

Antibodies to oral pathobionts and colon cancer risk in the CLUE I cohort study.

Periodontitis has been associated with an increased risk for gastrointestinal cancers. The objective of our study was to investigate the association of antibodies to oral bacteria and the risk of colon cancer in a cohort setting. Using the CLUE I cohort, a prospective cohort initiated in 1974 in Washington County, Maryland, we conducted a nested case-control study to examine the association of levels of IgG antibodies to 11 oral bacterial species (13 total strains) with risk of colon cancer diagnosed a median of 16 years later (range: 1-26 years). Antibody response was measured using checkerboard immunoblotting assays. We included 200 colon cancer cases and 200 controls matched on age, sex, cigarette smoking status, time of blood draw and pipe or cigar smoking status. Controls were selected using incidence density sampling. Conditional logistic regression models were used to assess the association between antibody levels and colon cancer risk. In the overall analysis, we observed significant inverse associations for 6 of the 13 antibodies measured (P-trends <.05) and one positive association for antibody levels to Aggregatibacter actinomycetemcomitans (ATCC 29523; P-trend = .04). While we cannot rule out a role for periodontal disease in colon cancer risk, findings from our study suggest that a strong adaptive immune response may be associated with a lower risk of colon cancer. More studies will need to examine whether the positive associations we observed with antibodies to A. actinomycetemcomitans reflect a true causal association for this bacterium.

Assessing Breast Cancer Molecular Subtypes Using Extracellular Vesicles' mRNA.

Extracellular vesicles (EVs) carry RNA cargo that is believed to be associated with the cell-of-origin and thus have the potential to serve as a minimally invasive liquid biopsy marker for supplying molecular information to guide treatment decisions (i.e., precision medicine). We report the affinity isolation of EV subpopulations with monoclonal antibodies attached to the surface of a microfluidic chip that is made from a plastic to allow for high-scale production. The EV microfluidic affinity purification (EV-MAP) chip was used for the isolation of EVs sourced from two-orthogonal cell types and was demonstrated for its utility in a proof-of-concept application to provide molecular subtyping information for breast cancer patients. The orthogonal selection process better recapitulated the epithelial tumor microenvironment by isolating two subpopulations of EVs: EVEpCAM (epithelial cell adhesion molecule, epithelial origin) and EVFAPα (fibroblast activation protein α, mesenchymal origin). The EV-MAP provided recovery >80% with a specificity of 99 ± 1% based on exosomal mRNA (exo-mRNA) and real time-droplet digital polymerase chain reaction results. When selected from the plasma of healthy donors and breast cancer patients, EVs did not differ in size or total RNA mass for both markers. On average, 0.5 mL of plasma from breast cancer patients yielded ∼2.25 ng of total RNA for both EVEpCAM and EVFAPα, while in the case of cancer-free individuals, it yielded 0.8 and 1.25 ng of total RNA from EVEpCAM and EVFAPα, respectively. To assess the potential of these two EV subpopulations to provide molecular information for prognostication, we performed the PAM50 test (Prosigna) on exo-mRNA harvested from each EV subpopulation. Results suggested that EVEpCAM and EVFAPα exo-mRNA profiling using subsets of the PAM50 genes and a novel algorithm (i.e., exo-PAM50) generated 100% concordance with the tumor tissue.

Placental microRNAs relate to early childhood growth trajectories.

BACKGROUND: Poor placental function is a common cause of intrauterine growth restriction, which in turn is associated with increased risks of adverse health outcomes. Our prior work suggests that birthweight and childhood obesity-associated genetic variants functionally impact placental function and that placental microRNA are associated with birthweight. To address the influence of the placenta beyond birth, we assessed the relationship between placental microRNAs and early childhood growth. METHODS: Using the SITAR package, we generated two parameters that describe individual weight trajectories of children (0-5 years) in the New Hampshire Birth Cohort Study (NHBCS, n = 238). Using negative binomial generalized linear models, we identified placental microRNAs that relate to growth parameters (FDR < 0.1), while accounting for sex, gestational age at birth, and maternal parity. RESULTS: Genes targeted by the six growth trajectory-associated microRNAs are enriched (FDR < 0.05) in growth factor signaling (TGF/beta: miR-876; EGF/R: miR-155, Let-7c; FGF/R: miR-155; IGF/R: Let-7c, miR-155), calmodulin signaling (miR-216a), and NOTCH signaling (miR-629). CONCLUSIONS: Growth-trajectory microRNAs target pathways affecting placental proliferation, differentiation and function. Our results suggest a role for microRNAs in regulating placental cellular dynamics and supports the Developmental Origins of Health and Disease hypothesis that fetal environment can have impacts beyond birth. IMPACT: We found that growth trajectory associated placenta microRNAs target genes involved in signaling pathways central to the formation, maintenance and function of placenta; suggesting that placental cellular dynamics remain critical to infant growth to term and are under the control of microRNAs. Our results contribute to the existing body of research suggesting that the placenta plays a key role in programming health in the offspring. This is the first study to relate molecular patterns in placenta, specifically microRNAs, to early childhood growth trajectory.

Human placental microRNAs dysregulated by cadmium exposure predict neurobehavioral outcomes at birth.

BACKGROUND: Prenatal cadmium (Cd) exposure has been implicated in both placental toxicity and adverse neurobehavioral outcomes. Placental microRNAs (miRNAs) may function to developmentally program adverse pregnancy and newborn health outcomes in response to gestational Cd exposure. METHODS: In a subset of the Rhode Island Child Health Study (RICHS, n = 115) and the New Hampshire Birth Cohort Study (NHBCS, = 281), we used small RNA sequencing and trace metal analysis to identify Cd-associated expression of placental miRNAs using negative binomial generalized linear models. We predicted mRNAs targeted by Cd-associated miRNAs and relate them to neurobehavioral outcomes at birth through the integration of transcriptomic data and summary scores from the NICU Network Neurobehavioral Scale (NNNS). RESULTS: Placental Cd concentrations are significantly associated with the expression level of five placental miRNAs in NHBCS, with similar effect sizes in RICHS. These miRNA target genes overrepresented in nervous system development, and their expression is correlated with NNNS metrics suggestive of atypical neurobehavioral outcomes at birth. CONCLUSIONS: Gestational Cd exposure is associated with the expression of placental miRNAs. Predicted targets of these miRNAs are involved in nervous system development and may also regulate placental physiology, allowing their dysregulation to modify developmental programming of early life health outcomes. IMPACT: This research aims to address the poor understanding of the molecular mechanisms governing adverse pregnancy and newborn health outcomes in response to Gestational cadmium (Cd) exposure. Our results outline a robust relationship between Cd-associated placental microRNA expression and NICU Network Neurobehavioral Scales (NNNS) at birth indicative of atypical neurobehavior. This study utilized healthy mother-infant cohorts to describe the role of Cd-associated dysregulation of placental microRNAs as a potential mechanism by which adverse neurobehavioral outcomes are developmentally programmed.

pwrBRIDGE: a user-friendly web application for power and sample size estimation in batch-confounded microarray studies with dependent samples.

Batch effect Reduction of mIcroarray data with Dependent samples usinG Empirical Bayes (BRIDGE) is a recently developed statistical method to address the issue of batch effect correction in batch-confounded microarray studies with dependent samples. The key component of the BRIDGE methodology is the use of samples run as technical replicates in two or more batches, "bridging samples", to inform batch effect correction/attenuation. While previously published results indicate a relationship between the number of bridging samples, M, and the statistical power of downstream statistical testing on the batch-corrected data, there is of yet no formal statistical framework or user-friendly software, for estimating M to achieve a specific statistical power for hypothesis tests conducted on the batch-corrected data. To fill this gap, we developed pwrBRIDGE, a simulation-based approach to estimate the bridging sample size, M, in batch-confounded longitudinal microarray studies. To illustrate the use of pwrBRIDGE, we consider a hypothetical, longitudinal batch-confounded study whose goal is to identify Alzheimer's disease (AD) progression-associated genes from amnestic mild cognitive impairment (aMCI) to AD in human blood after a 5-year follow-up. pwrBRIDGE helps researchers design and plan batch-confounded microarray studies with dependent samples to avoid over- or under-powered studies.

Epigenome-wide association study using peripheral blood leukocytes identifies genomic regions associated with periodontal disease and edentulism in the Atherosclerosis Risk in Communities study.

AIM: To investigate individual susceptibility to periodontitis by conducting an epigenome-wide association study using peripheral blood. MATERIALS AND METHODS: We included 1077 African American and 457 European American participants of the Atherosclerosis Risk in Communities (ARIC) study who had completed a dental examination or reported being edentulous at Visit 4 and had available data on DNA methylation from Visit 2 or 3. DNA methylation levels were compared by periodontal disease severity and edentulism through discovery analyses and subsequent testing of individual CpGs. RESULTS: Our discovery analysis replicated findings from a previous study reporting a region in gene ZFP57 (6p22.1) that was significantly hypomethylated in severe periodontal disease compared with no/mild periodontal disease in European American participants. Higher methylation levels in a separate region in an unknown gene (located in Chr10: 743,992-744,958) was associated with significantly higher odds of edentulism compared with no/mild periodontal disease in African American participants. In subsequent CpG testing, four CpGs in a region previously associated with periodontitis located within HOXA4 were significantly hypermethylated in severe periodontal disease compared with no/mild periodontal disease in African American participants (odds ratio per 1 SD increase in methylation level: cg11015251: 1.28 (1.02, 1.61); cg14359292: 1.24 (1.01, 1.54); cg07317062: 1.30 (1.05, 1.61); cg08657492: 1.25 (1.01, 1.55)). CONCLUSIONS: Our study highlights epigenetic variations in ZPF57 and HOXA4 that are significantly and reproducibly associated with periodontitis. Future studies should evaluate gene regulatory mechanisms in the candidate regions of these loci.

The Associations between Remission Status, Discounting Rates, and Recovery from Substance Use Disorders.

Background: Recovery from substance use disorders (SUDs) requires sustained and purposeful support to maintain long-term remission. Methods: This study investigated the association between assessment of recovery capital, household chaos, delay discounting (DD) and probability discounting (PD), and remission status among individuals in recovery from SUD. Data from 281 participants from the International Quit & Recovery Registry (IQRR), an ongoing online registry that aims to study the recovery process, were included in the analysis. Results: Lower DD rates and higher recovery capital were found among those in remission compared to those not in remission after controlling for demographics. In contrast, the association of household chaos and PD with remission status were insignificant. Overall, DD accounted for 20% of the total effect between the recovery capital and the remission status. Conclusion: This study contributes to the understanding of recovery as a multidimensional process, supports DD as a behavioral marker of addiction, and suggests areas for future research.

HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data.

BACKGROUND: Cellular compositions of solid tumor microenvironments are heterogeneous, varying across patients and tumor types. High-resolution profiling of the tumor microenvironment cell composition is crucial to understanding its biological and clinical implications. Previously, tumor microenvironment gene expression and DNA methylation-based deconvolution approaches have been shown to deconvolve major cell types. However, existing methods lack accuracy and specificity to tumor type and include limited identification of individual cell types. RESULTS: We employed a novel tumor-type-specific hierarchical model using DNA methylation data to deconvolve the tumor microenvironment with high resolution, accuracy, and specificity. The deconvolution algorithm is named HiTIMED. Seventeen cell types from three major tumor microenvironment components can be profiled (tumor, immune, angiogenic) by HiTIMED, and it provides tumor-type-specific models for twenty carcinoma types. We demonstrate the prognostic significance of cell types that other tumor microenvironment deconvolution methods do not capture. CONCLUSION: We developed HiTIMED, a DNA methylation-based algorithm, to estimate cell proportions in the tumor microenvironment with high resolution and accuracy. HiTIMED deconvolution is amenable to archival biospecimens providing high-resolution profiles enabling to study of clinical and biological implications of variation and composition of the tumor microenvironment.

Synergistic anti-proliferative activity of JQ1 and GSK2801 in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) constitutes 10-20% of breast cancers and is challenging to treat due to a lack of effective targeted therapies. Previous studies in TNBC cell lines showed in vitro growth inhibition when JQ1 or GSK2801 were administered alone, and enhanced activity when co-administered. Given their respective mechanisms of actions, we hypothesized the combinatorial effect could be due to the target genes affected. Hence the target genes were characterized for their expression in the TNBC cell lines to prove the combinatorial effect of JQ1 and GSK2801. METHODS: RNASeq data sets of TNBC cell lines (MDA-MB-231, HCC-1806 and SUM-159) were analyzed to identify the differentially expressed genes in single and combined treatments. The topmost downregulated genes were characterized for their downregulated expression in the TNBC cell lines treated with JQ1 and GSK2801 under different dose concentrations and combinations. The optimal lethal doses were determined by cytotoxicity assays. The inhibitory activity of the drugs was further characterized by molecular modelling studies. RESULTS: Global expression profiling of TNBC cell lines using RNASeq revealed different expression patterns when JQ1 and GSK2801 were co-administered. Functional enrichment analyses identified several metabolic pathways (i.e., systemic lupus erythematosus, PI3K-Akt, TNF, JAK-STAT, IL-17, MAPK, Rap1 and signaling pathways) enriched with upregulated and downregulated genes when combined JQ1 and GSK2801 treatment was administered. RNASeq identified downregulation of PTPRC, MUC19, RNA5-8S5, KCNB1, RMRP, KISS1 and TAGLN (validated by RT-qPCR) and upregulation of GPR146, SCARA5, HIST2H4A, CDRT4, AQP3, MSH5-SAPCD1, SENP3-EIF4A1, CTAGE4 and RNASEK-C17orf49 when cells received both drugs. In addition to differential gene regulation, molecular modelling predicted binding of JQ1 and GSK2801 with PTPRC, MUC19, KCNB1, TAGLN and KISS1 proteins, adding another mechanism by which JQ1 and GSK2801 could elicit changes in metabolism and proliferation. CONCLUSION: JQ1-GSK2801 synergistically inhibits proliferation and results in selective gene regulation. Besides suggesting that combinatorial use could be useful therapeutics for the treatment of TNBC, the findings provide a glimpse into potential mechanisms of action for this combination therapy approach.

Batch effect reduction of microarray data with dependent samples using an empirical Bayes approach (BRIDGE).

Batch-effects present challenges in the analysis of high-throughput molecular data and are particularly problematic in longitudinal studies when interest lies in identifying genes/features whose expression changes over time, but time is confounded with batch. While many methods to correct for batch-effects exist, most assume independence across samples; an assumption that is unlikely to hold in longitudinal microarray studies. We propose Batch effect Reduction of mIcroarray data with Dependent samples usinGEmpirical Bayes (BRIDGE), a three-step parametric empirical Bayes approach that leverages technical replicate samples profiled at multiple timepoints/batches, so-called "bridge samples", to inform batch-effect reduction/attenuation in longitudinal microarray studies. Extensive simulation studies and an analysis of a real biological data set were conducted to benchmark the performance of BRIDGE against both ComBat and longitudinalComBat. Our results demonstrate that while all methods perform well in facilitating accurate estimates of time effects, BRIDGE outperforms both ComBat and longitudinal ComBat in the removal of batch-effects in data sets with bridging samples, and perhaps as a result, was observed to have improved statistical power for detecting genes with a time effect. BRIDGE demonstrated competitive performance in batch effect reduction of confounded longitudinal microarray studies, both in simulated and a real data sets, and may serve as a useful preprocessing method for researchers conducting longitudinal microarray studies that include bridging samples.

Low variability in the underlying cellular landscape adversely affects the performance of interaction-based approaches for conducting cell-specific analyses of DNA methylation in bulk samples.

Statistical methods that allow for cell type specific DNA methylation (DNAm) analyses based on bulk-tissue methylation data have great potential to improve our understanding of human disease and have created unprecedented opportunities for new insights using the wealth of publicly available bulk-tissue methylation data. These methodologies involve incorporating interaction terms formed between the phenotypes/exposures of interest and proportions of the cell types underlying the bulk-tissue sample used for DNAm profiling. Despite growing interest in such "interaction-based" methods, there has been no comprehensive assessment how variability in the cellular landscape across study samples affects their performance. To answer this question, we used numerous publicly available whole-blood DNAm data sets along with extensive simulation studies and evaluated the performance of interaction-based approaches in detecting cell-specific methylation effects. Our results show that low cell proportion variability results in large estimation error and low statistical power for detecting cell-specific effects of DNAm. Further, we identified that many studies targeting methylation profiling in whole-blood may be at risk to be underpowered due to low variability in the cellular landscape across study samples. Finally, we discuss guidelines for researchers seeking to conduct studies utilizing interaction-based approaches to help ensure that their studies are adequately powered.

A comparison of sagittal MRI and lateral radiography in determining the Insall-Salvati ratio and diagnosing patella alta in the pediatric knee.

BACKGROUND: The Insall-Salvati ratio is a technique for determining patellar height that relies on bony landmarks. Magnetic resonance imaging (MRI) and plain radiography are used interchangeably to assess the Insall-Salvati ratio in the pediatric population despite the lack of validity in the literature. OBJECTIVE: The purpose of this study was to investigate if the Insall-Salvati ratio and patella alta as determined on MRI are comparable to those determined on radiography in pediatric patients. MATERIALS AND METHODS: We conducted a retrospective review of 49 pediatric patients (age range: 7.5-17.0 years) with unfused growth plates who underwent both knee MRI and lateral knee radiography. Measurements for calculating the Insall-Salvati ratio (the ratio of patella tendon length to patella length) were obtained by three observers. Data were analyzed using paired t-tests and Pearson's correlation. A reliability assessment and inter-method agreements were performed. Patella alta was defined as an Insall-Salvati ratio > 1.2. Additional cutoffs of Insall-Salvati ratios > 1.3 and > 1.4 were also analyzed. RESULTS: There was no statistically significant difference between Insall-Salvati ratio as determined on MRI (mean: 1.20) and radiographs (mean: 1.25; P > 0.05). There was a strong correlation between Insall-Salvati ratio as determined on MRI and radiographs (Pearson's r = 0.6) with moderate consistency (Cronbach's alpha = 0.78). There was a good level of agreement between the diagnosis of patella alta on MRI and radiographs when defined as an Insall-Salvati ratio greater than 1.2 and 1.3 (Cohen's kappa = 0.61). CONCLUSION: The results demonstrate a strong association between Insall-Salvati ratio and patella alta derived from MRI and radiographs in children ages 7.5 years and older.

Are Transmetatarsal Amputations a Durable Limb Salvage Option? A Single-Institution Descriptive Analysis.

In limb and life-threatening diabetic foot infections, transmetatarsal amputations are often indicated as a limb salvage procedure. The aim of this study is to analyze the long-term durability of initially successful transmetatarsal amputations in the diabetic population. We defined a successful transmetatarsal amputation as one which had clinical healing 1 year after surgery. A retrospective review of transmetatarsal amputations completed at our institution over an 11-year period was performed. We identified 83 amputations that met inclusion criteria. The mean follow-up was 4 years. The mean time to surgical healing was 109.8 days. After successfully healing the transmetatarsal amputation the long-term outcomes were analyzed. Re-ulcerations occurred in 44% of the transmetatarsal amputations a mean of 15 months after surgical healing. Patients who re-ulcerated were noted to be significantly younger (p value 0.02) with a significantly higher preprocedure hemoglobin A1c (p value < .001). Additional procedures after successful healing included 13 (15.66%) revision surgeries and 12 (14.46%) more proximal amputations. While transmetatarsal amputations remain a viable and durable limb preserving surgery, all patients who have undergone a transmetatarsal amputation should be monitored lifelong as they remain at risk for re-ulceration and more proximal amputation.