Citations

In this article, we describe the long-term outcomes of children who were previously reported to have developed hypophosphatemic bone disease in association with elemental formula use. An extended chart review allowed for an updated report of 34 children with regard to severity/duration of bone disease, extent of recovery, and time to correction using radiology reports and biochemical data. After implementation of formula change and/or phosphate supplementation, we found that serum phosphorus concentration increased and serum alkaline phosphatase activity decreased in all patients, normalizing by 6.6 ± 4.0 (mean ± SD) months following diagnosis. The decrease in serum alkaline phosphatase from diagnosis to the time of correction was moderately correlated with the concurrent increase in serum phosphorus ( R = 0.48, P < .05). Age at diagnosis significantly correlated with time to resolution ( R = 0.51, P = .01). This study supports the earlier report that bone disease associated with hypophosphatemia during elemental formula use responds to formula change and/or phosphate supplementation.

Abstract Background: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. Methods: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. Results: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10−4), KRT16 (PG×E = 2.3 × 10−4), CD14 (PG×E = 9.38 × 10−4), and CYP27A1 (PG×E = 1.44 × 10−3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10−5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR &lt; 0.2. Conclusions: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. Impact: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.

Objectives Based on our previous findings that postmenopausal women with estrone (E1) and estradiol (E2) concentrations at or above 1.3 pg/ml and 0.5 pg/ml, respectively, after 6 months of adjuvant anastrozole therapy had a three-fold risk of recurrence, we aimed to identify a single-nucleotide polymorphism (SNP)-based model that would predict elevated E1 and E2 and then validate it in an independent dataset. Patients and methods The test set consisted of 322 women from the M3 study and the validation set consisted of 152 patients from MA.27. All patients were treated with adjuvant anastrozole, had on-anastrozole E1 and E2 concentrations and genome-wide genotyping. Results SNPs were identified from the M3 genome-wide association study. The best model to predict the E1-E2 phenotype with high balanced accuracy was a support vector machine model using clinical factors plus 46 SNPs. We did not have an independent cohort that is similar to the M3 study with clinical, E1-E2 phenotypes and genotype data to test our model. Hence, we chose a nested matched case-control cohort (MA.27 study) for testing. Our E1-E2 model was not validated but we found the MA.27 validation cohort was both clinically and genomically different. Conclusions We identified a SNP-based model that had excellent performance characteristics for predicting the phenotype of elevated E1 and E2 in women treated with anastrozole. This model was not validated in an independent dataset but that dataset was clinically and genomically substantially different. The model will need validation in a prospective study.

Background: An understanding of financial trends is important to advance agreeable reimbursement models in plastic surgery. This study aimed to evaluate trends in Medicare reimbursement rates for the 20 most commonly billed reconstructive plastic surgery procedures from 2000 to 2019. Methods: The Centers for Medicare and Medicaid Services Physician and Other Supplier Public Use File was used to identify the 20 reconstructive procedures most commonly billed to Medicare by plastic surgeons in 2016. Reimbursement data were extracted from The Physician Fee Schedule Look-Up Tool from the Centers for Medicare and Medicaid Services for each CPT code. Monetary data were adjusted for inflation to 2019 U.S. dollars. Average annual and total percentage changes in reimbursement were calculated based on these adjusted trends. Results: The average adjusted reimbursement for all procedures decreased by 14.0 percent from 2000 to 2019. The greatest mean decrease was observed in complex wound repair of the scalp, arms, or legs (−33.2 percent). The only procedure with an increased adjusted reimbursement rate was layer-closure of the scalp, axillae, trunk, and/or extremities (6.5 percent). From 2000 to 2019, the adjusted reimbursement rate for all procedures decreased by an average of 0.8 percent annually. Conclusions: This is the first comprehensive study evaluating trends in Medicare reimbursement in plastic surgery. When adjusted for inflation, Medicare reimbursement for the included procedures has steadily decreased from 2000 to 2019. Increased consideration of these trends will be important for U.S. policymakers, hospitals, and surgeons to ensure continued access to meaningful reconstructive plastic surgery care.

Abstract Purpose: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with &gt;95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271

Abstract Genetic variants that define two distinct haplotypes at the TMEM106B locus have been implicated in multiple neurodegenerative diseases and in healthy brain ageing. In frontotemporal dementia (FTD), the high expressing TMEM106B risk haplotype was shown to increase susceptibility for FTD with TDP-43 inclusions (FTD-TDP) and to modify disease penetrance in progranulin mutation carriers (FTD-GRN). To elucidate the biological function of TMEM106B and determine whether lowering TMEM106B may be a viable therapeutic strategy, we performed brain transcriptomic analyses in 8-month-old animals from our recently developed Tmem106b−/− mouse model. We included 10 Tmem106b+/+ (wild-type), 10 Tmem106b+/− and 10 Tmem106−/− mice. The most differentially expressed genes (153 downregulated and 60 upregulated) were identified between Tmem106b−/− and wild-type animals, with an enrichment for genes implicated in myelination-related cellular processes including axon ensheathment and oligodendrocyte differentiation. Co-expression analysis also revealed that the most downregulated group of correlated genes was enriched for myelination-related processes. We further detected a significant loss of OLIG2-positive cells in the corpus callosum of Tmem106b−/− mice, which was present already in young animals (21 days) and persisted until old age (23 months), without worsening. Quantitative polymerase chain reaction revealed a reduction of differentiated but not undifferentiated oligodendrocytes cellular markers. While no obvious changes in myelin were observed at the ultrastructure levels in unchallenged animals, treatment with cuprizone revealed that Tmem106b−/− mice are more susceptible to cuprizone-induced demyelination and have a reduced capacity to remyelinate, a finding which we were able to replicate in a newly generated Tmem106b CRISPR/cas9 knock-out mouse model. Finally, using a TMEM106B HeLa knock-out cell line and primary cultured oligodendrocytes, we determined that loss of TMEM106B leads to abnormalities in the distribution of lysosomes and PLP1. Together these findings reveal an important function for TMEM106B in myelination with possible consequences for therapeutic strategies aimed at lowering TMEM106B levels.