Prescription and Prescriber Specialty Characteristics of Initial Opioid Prescriptions Associated with Chronic Use.

OBJECTIVE: This study evaluated the characteristics of opioid prescriptions, including prescriber specialty, given to opioid-naïve patients and their association with chronic use. DESIGN: Cross-sectional analysis of the Ohio prescription drug monitoring program from January 2010 to November 2017. SETTING: Ohio, USA. SUBJECTS: Patients who had no opioid prescriptions from 2010 to 2012 and a first-time prescription from January 2013 to November 2016. METHODS: Chronic use was defined as at least six opioid prescriptions in one year and either one or more years between the first and last prescription or an average of ≤30 days not covered by an opioid during that year. RESULTS: A total of 4,252,809 opioid-naïve patients received their first opioid prescription between 2013 and 2016; 364,947 (8.6%) met the definition for chronic use. Those who developed chronic use were older (51.7 vs 45.6 years) and more likely to be female (53.6% vs 52.8%), and their first prescription had higher pill quantities (44.9 vs 30.2), higher morphine milligram equivalents (MME; 355.3 vs 200.0), and was more likely to be an extended-release formulation (2.9% vs 0.7%, all P < 0.001). When compared with internal medicine, the adjusted odds of chronic use were highest with anesthesiology (odds ratio [OR] = 1.46) and neurology (OR = 1.43) and lowest with ophthalmology (OR = 0.33) and gynecology (OR = 0.37). CONCLUSIONS: Eight point six percent of opioid-naïve individuals who received an opioid prescription developed chronic use. This rate varied depending on the specialty of the provider who wrote the prescription. The risk of chronic use increased with higher MME content of the initial prescription and use of extended-release opioids.

Deep sequencing of 10,000 human genomes.

We report on the sequencing of 10,545 human genomes at 30×-40× coverage with an emphasis on quality metrics and novel variant and sequence discovery. We find that 84% of an individual human genome can be sequenced confidently. This high-confidence region includes 91.5% of exon sequence and 95.2% of known pathogenic variant positions. We present the distribution of over 150 million single-nucleotide variants in the coding and noncoding genome. Each newly sequenced genome contributes an average of 8,579 novel variants. In addition, each genome carries on average 0.7 Mb of sequence that is not found in the main build of the hg38 reference genome. The density of this catalog of variation allowed us to construct high-resolution profiles that define genomic sites that are highly intolerant of genetic variation. These results indicate that the data generated by deep genome sequencing is of the quality necessary for clinical use.

Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer.

Much of the mechanism by which Wnt signaling drives proliferation during oncogenesis is attributed to its regulation of the cell cycle. Here, we show how Wnt/ß-catenin signaling directs another hallmark of tumorigenesis, namely Warburg metabolism. Using biochemical assays and fluorescence lifetime imaging microscopy (FLIM) to probe metabolism in vitro and in living tumors, we observe that interference with Wnt signaling in colon cancer cells reduces glycolytic metabolism and results in small, poorly perfused tumors. We identify pyruvate dehydrogenase kinase 1 (PDK1) as an important direct target within a larger gene program for metabolism. PDK1 inhibits pyruvate flux to mitochondrial respiration and a rescue of its expression in Wnt-inhibited cancer cells rescues glycolysis as well as vessel growth in the tumor microenvironment. Thus, we identify an important mechanism by which Wnt-driven Warburg metabolism directs the use of glucose for cancer cell proliferation and links it to vessel delivery of oxygen and nutrients.

Opioid Prescriptions by Specialty in Ohio, 2010-2014.

Background: The current US opioid epidemic is attributed to the large volume of prescribed opioids. This study analyzed the contribution of different medical specialties to overall opioids by evaluating the pill counts and morphine milligram equivalents (MMEs) of opioid prescriptions, stratified by provider specialty, and determined temporal trends. Methods: This was an analysis of the Ohio prescription drug monitoring program database, which captures scheduled medication prescriptions filled in the state as well as prescriber specialty. We extracted prescriptions for pill versions of opioids written in the calendar years 2010 to 2014. The main outcomes were the number of filled prescriptions, pill counts, MMEs, and extended-released opioids written by physicians in each specialty, and annual prescribing trends. Results: There were 56,873,719 prescriptions for the studied opioids dispensed, for which 41,959,581 (73.8%) had prescriber specialty type available. Mean number of pills per prescription and MMEs were highest for physical medicine/rehabilitation (PM&R; 91.2 pills, 1,532 mg, N = 1,680,579), anesthesiology/pain (89.3 pills, 1,484 mg, N = 3,261,449), hematology/oncology (88.2 pills, 1,534 mg, N = 516,596), and neurology (84.4 pills, 1,230 mg, N = 573,389). Family medicine (21.8%) and internal medicine (17.6%) wrote the most opioid prescriptions overall. Time trends in the average number of pills and MMEs per prescription also varied depending on specialty. Conclusions: The numbers of pills and MMEs per opioid prescription vary markedly by prescriber specialty, as do trends in prescribing characteristics. Pill count and MME values define each specialty's contribution to overall opioid prescribing more accurately than the number of prescriptions alone.

Utilization of defined microbial communities enables effective evaluation of meta-genomic assemblies.

BACKGROUND: Metagenomics is the study of the microbial genomes isolated from communities found on our bodies or in our environment. By correctly determining the relation between human health and the human associated microbial communities, novel mechanisms of health and disease can be found, thus enabling the development of novel diagnostics and therapeutics. Due to the diversity of the microbial communities, strategies developed for aligning human genomes cannot be utilized, and genomes of the microbial species in the community must be assembled de novo. However, in order to obtain the best metagenomic assemblies, it is important to choose the proper assembler. Due to the rapidly evolving nature of metagenomics, new assemblers are constantly created, and the field has not yet agreed on a standardized process. Furthermore, the truth sets used to compare these methods are either too simple (computationally derived diverse communities) or complex (microbial communities of unknown composition), yielding results that are hard to interpret. In this analysis, we interrogate the strengths and weaknesses of five popular assemblers through the use of defined biological samples of known genomic composition and abundance. We assessed the performance of each assembler on their ability to reassemble genomes, call taxonomic abundances, and recreate open reading frames (ORFs). RESULTS: We tested five metagenomic assemblers: Omega, metaSPAdes, IDBA-UD, metaVelvet and MEGAHIT on known and synthetic metagenomic data sets. MetaSPAdes excelled in diverse sets, IDBA-UD performed well all around, metaVelvet had high accuracy in high abundance organisms, and MEGAHIT was able to accurately differentiate similar organisms within a community. At the ORF level, metaSPAdes and MEGAHIT had the least number of missing ORFs within diverse and similar communities respectively. CONCLUSIONS: Depending on the metagenomics question asked, the correct assembler for the task at hand will differ. It is important to choose the appropriate assembler, and thus clearly define the biological problem of an experiment, as different assemblers will give different answers to the same question.

The Effect of Opioid Prescribing Guidelines on Prescriptions by Emergency Physicians in Ohio.

STUDY OBJECTIVE: The objective of our study is to evaluate the association between Ohio's April 2012 emergency physician guidelines aimed at reducing inappropriate opioid prescribing and the number and type of opioid prescriptions dispensed by emergency physicians. METHODS: We used Ohio's prescription drug monitoring program data from January 1, 2010, to December 31, 2014, and included the 5 most commonly prescribed opioids (hydrocodone, oxycodone, tramadol, codeine, and hydromorphone). The primary outcome was the monthly statewide prescription total of opioids written by emergency physicians in Ohio. We used an interrupted time series analysis to compare pre- and postguideline level and trend in number of opioid prescriptions dispensed by emergency physicians per month, number of prescriptions stratified by 5 commonly prescribed opioids, and number of prescriptions for greater than 3 days' supply of opioids. RESULTS: Beginning in January 2010, the number of prescriptions dispensed by all emergency physicians in Ohio decreased by 0.3% per month (95% confidence interval [CI] -0.49% to -0.15%). The implementation of the guidelines in April 2012 was associated with a 12% reduction (95% CI -17.7% to -6.3%) in the level of statewide total prescriptions per month and an additional decline of 0.9% (95% CI -1.1% to -0.7%) in trend relative to the preguideline trend. The estimated effect of the guidelines on total monthly prescriptions greater than a 3-day supply was an 11.2% reduction in level (95% CI -18.8% to -3.6%) and an additional 0.9% (95% CI -1.3% to -0.5%) decline in trend per month after the guidelines. Guidelines were also associated with a reduction in prescribing for each of the 5 individual opioids, with various effect. CONCLUSION: In Ohio, emergency physician opioid prescribing guidelines were associated with a decrease in the quantity of opioid prescriptions written by emergency physicians. Although introduction of the guidelines occurred in parallel with other opioid-related interventions, our findings suggest an additional effect of the guidelines on prescribing behavior. Similar guidelines may have the potential to reduce opioid prescribing in other geographic areas and for other specialties as well.

Novel polymorphisms in caspase-8 are associated with breast cancer risk in the California Teachers Study.

BACKGROUND: The ability of tamoxifen and raloxifene to decrease breast cancer risk varies among different breast cancer subtypes. It is important to determine one's subtype-specific breast cancer risk when considering chemoprevention. A number of single nucleotide polymorphisms (SNPs), including one in caspase-8 (CASP8), have been previously associated with risk of developing breast cancer. Because caspase-8 is an important protein involved in receptor-mediated apoptosis whose activity is affected by estrogen, we hypothesized that additional SNPs in CASP8 could be associated with breast cancer risk, perhaps in a subtype-specific manner. METHODS: Twelve tagging SNPs of CASP8 were analyzed in a nested case control study (1,353 cases and 1,384 controls) of non-Hispanic white women participating in the California Teachers Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each SNP using all, estrogen receptor (ER)-positive, ER-negative, human epidermal growth factor receptor 2 (HER2)-positive, and HER2-negative breast cancers as separate outcomes. RESULTS: Several SNPs were associated with all, ER-positive, and HER2-positive breast cancers; however, after correcting for multiple comparisons (i.e., p < 0.0008), only rs2293554 was statistically significantly associated with HER2-positive breast cancer (OR = 1.98, 95% CI 1.34-2.92, uncorrected p = 0.0005). CONCLUSIONS: While our results for CASP8 SNPs should be validated in other cohorts with subtype-specific information, we conclude that some SNPs in CASP8 are associated with subtype-specific breast cancer risk. This study contributes to our understanding of CASP8 SNPs and breast cancer risk by subtype.

A Case Study of Fixed-Effects and Random-Effects Meta-Analysis Models for Genome-Wide Association Studies in Celiac Disease.

BACKGROUND/AIMS: Amongst the many approaches to genome-wide association study (GWAS) meta-analysis (MA), the most popular methods are based on fixed-effects (FE) modeling because it tends to be the statistically most powerful approach in the absence of heterogeneity. However, FE-based MA ignores the potential heterogeneity that may exist between studies. The purpose of our analysis was to test whether results from random effects (RE)-based methods that account for heterogeneity differed significantly from the results that were originally published. METHODS: We reanalyzed two GWAS FE-based MAs of celiac disease with RE-based methods: (1) a two-stage GWAS MA that includes 9,451 celiac disease cases and 16,434 controls from 12 collections and (2) a single-stage GWAS MA using a custom dense genotyping platform to capture low-frequency and rare variants in 12,041 cases and 12,228 controls from 7 collections. RESULTS: We present evidence that SNPs at loci that were previously reported to be genome-wide significant (GWS; p < 5 × 10(-8)) in either the two-stage GWAS MA or the single-stage GWAS MA were not GWS when heterogeneity was accounted for by an RE MA method. CONCLUSION: This case study highlights the strengths of RE MA methods in the presence of heterogeneity and of pooled FE methods.

Global genetic architecture of an erythroid quantitative trait locus, HMIP-2.

HMIP-2 is a human quantitative trait locus affecting peripheral numbers, size and hemoglobin composition of red blood cells, with a marked effect on the persistence of the fetal form of hemoglobin, HbF, in adults. The locus consists of multiple common variants in an enhancer region for MYB (chr 6q23.3), which encodes the hematopoietic transcription factor cMYB. Studying a European population cohort and four African-descended groups of patients with sickle cell anemia, we found that all share a set of two spatially separate HbF-promoting alleles at HMIP-2, termed "A" and "B." These typically occurred together ("A-B") on European chromosomes, but existed on separate homologous chromosomes in Africans. Using haplotype signatures for "A" and "B," we interrogated public population datasets. Haplotypes carrying only "A" or "B" were typical for populations in Sub-Saharan Africa. The "A-B" combination was frequent in European, Asian, and Amerindian populations. Both alleles were infrequent in tropical regions, possibly undergoing negative selection by geographical factors, as has been reported for malaria with other hematological traits. We propose that the ascertainment of worldwide distribution patterns for common, HbF-promoting alleles can aid their further genetic characterization, including the investigation of gene-environment interaction during human migration and adaptation.

Impact of the Communities That HEAL Intervention on Buprenorphine-Waivered Practitioners and Buprenorphine Prescribing: A Prespecified Secondary Analysis of the HCS Randomized Clinical Trial.

Importance: Buprenorphine significantly reduces opioid-related overdose mortality. From 2002 to 2022, the Drug Addiction Treatment Act of 2000 (DATA 2000) required qualified practitioners to receive a waiver from the Drug Enforcement Agency to prescribe buprenorphine for treatment of opioid use disorder. During this period, waiver uptake among practitioners was modest; subsequent changes need to be examined. Objective: To determine whether the Communities That HEAL (CTH) intervention increased the rate of practitioners with DATA 2000 waivers and buprenorphine prescribing. Design, Setting, and Participants: This prespecified secondary analysis of the HEALing Communities Study, a multisite, 2-arm, parallel, community-level, cluster randomized, open, wait-list-controlled comparison clinical trial was designed to assess the effectiveness of the CTH intervention and was conducted between January 1, 2020, to December 31, 2023, in 67 communities in Kentucky, Massachusetts, New York, and Ohio, accounting for approximately 8.2 million adults. The participants in this trial were communities consisting of counties (n = 48) and municipalities (n = 19). Trial arm randomization was conducted using a covariate constrained randomization procedure stratified by state. Each state was balanced by community characteristics including urban/rural classification, fatal opioid overdose rate, and community population. Thirty-four communities were randomized to the intervention and 33 to wait-list control arms. Data analysis was conducted between March 20 and September 29, 2023, with a focus on the comparison period from July 1, 2021, to June 30, 2022. Intervention: Waiver trainings and other educational trainings were offered or supported by the HEALing Communities Study research sites in each state to help build practitioner capacity. Main Outcomes and Measures: The rate of practitioners with a DATA 2000 waiver (overall, and stratified by 30-, 100-, and 275-patient limits) per 100 000 adult residents aged 18 years or older during July 1, 2021, to June 30, 2022, were compared between the intervention and wait-list control communities. The rate of buprenorphine prescribing among those waivered practitioners was also compared between the intervention and wait-list control communities. Intention-to-treat and per-protocol analyses were performed. Results: A total of 8 166 963 individuals aged 18 years or older were residents of the 67 communities studied. There was no evidence of an effect of the CTH intervention on the adjusted rate of practitioners with a DATA 2000 waiver (adjusted relative rate [ARR], 1.04; 95% CI, 0.94-1.14) or the adjusted rate of practitioners with a DATA 2000 waiver who actively prescribed buprenorphine (ARR, 0.97; 95% CI, 0.86-1.10). Conclusions and Relevance: In this randomized clinical trial, the CTH intervention was not associated with increases in the rate of practitioners with a DATA 2000 waiver or buprenorphine prescribing among those waivered practitioners. Supporting practitioners to prescribe buprenorphine remains a critical yet challenging step in the continuum of care to treat opioid use disorder. Trial Registration: ClinicalTrials.gov Identifier: NCT04111939.

HbA2 levels in normal adults are influenced by two distinct genetic mechanisms.

Using a genome-wide association study, we found that common inter-individual differences in haemoglobin A(2) (HbA(2) , α(2) δ(2) ) levels are largely governed by genetic factors (42% of variability). The influence of age (1%) and sex (4%) was small. HbA(2) levels were influenced by two loci: the HBS1L-MYB locus on chromosome 6q, which has been shown to have pleiotropic effects on other haematological traits; and a second locus surrounding HBB, the gene encoding ß-globin. Our results suggest that HbA(2) levels in adults are influenced by two different biological processes: one via kinetics of erythropoiesis, and the other, via competition between HBB and HBD activity.

Association between celiac disease and iron deficiency in Caucasians, but not non-Caucasians.

BACKGROUND & AIMS: Celiac disease is an increasingly recognized disorder in Caucasian populations of European origin. Little is known about its prevalence in non-Caucasians. Although it is thought to be a cause of iron-deficiency anemia, little is known about the extent to which celiac disease contributes to iron deficiency in Caucasians, and especially non-Caucasians. We analyzed samples collected from participants in the Hemochromatosis and Iron Overload Screening study to identify individuals with iron deficiency and to assess the frequency of celiac disease. METHODS: We analyzed serum samples from white men (≥25 y) and women (≥50 y) who participated in the Hemochromatosis and Iron Overload Screening study; cases were defined as individuals with iron deficiency (serum ferritin level, ≤12 µg/L) and controls were those without (serum ferritin level, >100 µg/L in men and >50 µg/L in women). All samples also were analyzed for human recombinant tissue transglutaminase immunoglobulin A; positive results were confirmed by an assay for endomysial antibodies. Patients with positive results from both celiac disease tests were presumed to have untreated celiac disease, and those with a positive result from only 1 test were excluded from analysis. We analyzed HLA genotypes and frequencies of celiac disease between Caucasians and non-Caucasians with iron deficiency. RESULTS: Celiac disease occurred in 14 of 567 cases (2.5%) and in only 1 of 1136 controls (0.1%; Fisher exact test, P = 1.92 × 10(-6)). Celiac disease was more common in Caucasian cases (14 of 363; 4%) than non-Caucasian cases (0 of 204; P = .003). Only 1 Caucasian control and no non-Caucasian controls had celiac disease. The odds of celiac disease in individuals with iron deficiency was 28-fold (95% confidence interval, 3.7-212.8) that of controls; 13 of 14 cases with celiac disease carried the DQ2.5 variant of the HLA genotype. CONCLUSIONS: Celiac disease is associated with iron deficiency in Caucasians. Celiac disease is rare among non-Caucasians-even among individuals with features of celiac disease, such as iron deficiency. Celiac disease also is rare among individuals without iron deficiency. Men and postmenopausal women with iron deficiency should be tested for celiac disease.

Population pharmacokinetics and exposure-response analysis of a single dose of sotrovimab in the early treatment of patients with mild to moderate COVID-19.

Sotrovimab is a recombinant human monoclonal antibody that has been shown to prevent progression to hospitalization or death in non-hospitalized high-risk patients with mild to moderate coronavirus disease 2019 following either intravenous (i.v.) or intramuscular (i.m.) administration. Population pharmacokinetic (PopPK) and exposure-response (ER) analyses were performed to characterize single dose sotrovimab pharmacokinetics (PK) and the relationship between exposure and response (probability of progression), as well as covariates that may contribute to between-participant variability in sotrovimab PK and efficacy following i.v. or i.m. administration. Sotrovimab PK was described by a two-compartment model with linear elimination; i.m. absorption was characterized by a sigmoid absorption model. PopPK covariate analysis led to the addition of the effect of body weight on systemic clearance and peripheral volume of distribution, sex on i.m. bioavailability and first-order absorption rate (KA), and body mass index on KA. However, the magnitude of covariate effect was not pronounced and was therefore not expected to be clinically relevant based on available data to date. For ER analysis, sotrovimab exposure measures were predicted using the final PopPK model. An ER model was developed using the exposure measure of sotrovimab concentration at 168 h that described the relationship between exposure and probability of progression within the ER dataset for COMET-TAIL. The number of risk factors (≤1 vs. >1) was incorporated as an additive shift on the model-estimated placebo response but had no impact on overall drug response. Limitations in the ER model may prevent generalization of these results to describe the sotrovimab exposure-progression relationship across severe acute respiratory syndrome-coronavirus 2 variants.

Confounded by sequencing depth in association studies of rare alleles.

Next-generation DNA sequencing technologies are facilitating large-scale association studies of rare genetic variants. The depth of the sequence read coverage is an important experimental variable in the next-generation technologies and it is a major determinant of the quality of genotype calls generated from sequence data. When case and control samples are sequenced separately or in different proportions across batches, they are unlikely to be matched on sequencing read depth and a differential misclassification of genotypes can result, causing confounding and an increased false-positive rate. Data from Pilot Study 3 of the 1000 Genomes project was used to demonstrate that a difference between the mean sequencing read depth of case and control samples can result in false-positive association for rare and uncommon variants, even when the mean coverage depth exceeds 30× in both groups. The degree of the confounding and inflation in the false-positive rate depended on the extent to which the mean depth was different in the case and control groups. A logistic regression model was used to test for association between case-control status and the cumulative number of alleles in a collapsed set of rare and uncommon variants. Including each individual's mean sequence read depth across the variant sites in the logistic regression model nearly eliminated the confounding effect and the inflated false-positive rate. Furthermore, accounting for the potential error by modeling the probability of the heterozygote genotype calls in the regression analysis had a relatively minor but beneficial effect on the statistical results.

A statistical method for scanning the genome for regions with rare disease alleles.

Studying the role of rare alleles in common disease has been prevented by the impractical task of determining the DNA sequence of large numbers of individuals. Next-generation DNA sequencing technologies are being developed that will make it possible for genetic studies of common disease to study the full frequency spectrum of genetic variation, including rare alleles. This report describes a method for scanning the genome for disease susceptibility regions that show an increased number of rare alleles among a sample of disease cases versus an ethnically matched sample of controls. The method was based on a hidden Markov model and the statistical support for a disease susceptibility region characterized by rare alleles was measured by a likelihood ratio statistic. Due to the lack of empirical data, the method was evaluated through simulation. The performance of the method was tested under the null and alternative hypotheses under a range of sequence generating and hidden Markov models parameters. The results showed that the statistical method performs well at identifying true disease susceptibility regions and that performance was primarily affected by the amount of variation in the neutral sequence and the number of rare disease alleles found in the disease susceptibility region.

Control of fetal hemoglobin: new insights emerging from genomics and clinical implications.

Increased levels of fetal hemoglobin (HbF, alpha(2)gamma(2)) are of no consequence in healthy adults, but confer major clinical benefits in patients with sickle cell anemia (SCA) and beta thalassemia, diseases that represent major public health problems. Inter-individual HbF variation is largely genetically controlled, with one extreme caused by mutations involving the beta globin gene (HBB) complex, historically referred to as pancellular hereditary persistence of fetal hemoglobin (HPFH). These Mendelian forms of HPFH are rare and do not explain the common form of heterocellular HPFH which represents the upper tail of normal HbF variation, and is clearly inherited as a quantitative genetic trait. Genetic studies have identified three major quantitative trait loci (QTLs) (Xmn1-HBG2, HBS1L-MYB intergenic region on chromosome 6q23, and BCL11A on chromosome 2p16) that account for 20-50% of the common variation in HbF levels in patients with SCA and beta thalassemia, and in healthy adults. Two of the major QTLs include oncogenes, emphasizing the importance of cell proliferation and differentiation as an important contribution to the HbF phenotype. The review traces the story of HbF quantitative genetics that uncannily mirrors the changing focus in genetic methodology, from candidate genes through positional cloning, to genome-wide association, that have expedited the dissection of the genetic architecture underlying HbF variability. These genetic results have already provided remarkable insights into molecular mechanisms that underlie the hemoglobin 'switch'.

Glycolytic expression in lower-grade glioma reveals an epigenetic association between IDH mutation status and PDL1/2 expression.

BACKGROUND: The interplay between glycolysis and immunosuppression in cancer has recently emerged as an intriguing area of research. The aim of this study was to elucidate a potential epigenetic link between glycolysis, isocitrate hydrogenase (IDH) status, and immune checkpoint expression in human lower-grade glioma (LGG). METHODS: Genomic analysis was conducted on 507 LGG samples from The Cancer Genome Atlas (TCGA). Data types analyzed included RNA-seq (IlluminaHiSeq) and DNA methylation (Methylation450K). Unsupervised clustering grouped samples according to glycolytic expression level and IDH status. Global promoter methylation patterns were examined, as well as methylation levels of LDHA/LDHB and immune checkpoint genes. Methylation data from a knock-in IDH1R132H/WT allele in HCT116 cells and ChIP-seq data from immortalized human astrocytes using an inducible IDH1R132H mutation were also assessed. RESULTS: Glycolytic expression distinguished a tumor cluster enriched for wild-type IDH and poorer overall survival (P < .0001). This cluster showed lower levels of LDHA promoter methylation and a higher LDHA/LDHB expression ratio. These samples also displayed lower PDL1/2 promoter methylation and higher PDL1/2 expression, which was more pronounced for PDL2. IDH1R132H/WT cell line data showed that induced changes in methylation were enriched for genes involved in immune regulation, and ChIP-seq data showed that promoter H3K4me3 decreased for LDHA, PDL2, and PDL1 upon induction of IDH1R132H. CONCLUSIONS: These results suggest a previously unrecognized epigenetic link between glycolysis and immune checkpoint expression in LGG. This work advances our understanding of glioma genomics and provides support for further exploration of the metabolic-immune interface in LGG.

A twins heritability study on alpha hemoglobin stabilizing protein (AHSP) expression variability.

Cytotoxic precipitation of free α-globin monomers and its production of reactive oxygen species cause red cell membrane damage that leads to anemia and eventually ineffective erythropoiesis in ß-thalassemia. Alpha hemoglobin stabilizing protein (AHSP) was found to bind only to free α-globin monomers creating a stable and inert complex which remains soluble in the cytoplasm thus preventing harmful precipitations. Alpha hemoglobin stabilizing protein was shown to bind nascent α-globin monomers with transient strength before transferring α-globin to ß-globin to form hemoglobin tetramer. A classical twin study would be beneficial to investigate the role of genetics and environment in the variation of alpha hemoglobin stabilizing protein expression as this knowledge will enable us to determine further investigations with regards to therapeutic interventions if alpha hemoglobin stabilizing protein is to be a therapeutic agent for ß-thalassemia. This study investigates the heritability influence of alpha hemoglobin stabilizing protein expression and factors that may contribute to this. Results indicated that a major proportion of alpha hemoglobin stabilizing protein expression was influenced by genetic heritability (46%) with cis-acting factors accounting for 19% and trans-acting factors at 27%.

Genotype determination for polymorphisms in linkage disequilibrium.

BACKGROUND: Genome-wide association studies with single nucleotide polymorphisms (SNPs) show great promise to identify genetic determinants of complex human traits. In current analyses, genotype calling and imputation of missing genotypes are usually considered as two separated tasks. The genotypes of SNPs are first determined one at a time from allele signal intensities. Then the missing genotypes, i.e., no-calls caused by not perfectly separated signal clouds, are imputed based on the linkage disequilibrium (LD) between multiple SNPs. Although many statistical methods have been developed to improve either genotype calling or imputation of missing genotypes, treating the two steps independently can lead to loss of genetic information. RESULTS: We propose a novel genotype calling framework. In this framework, we consider the signal intensities and underlying LD structure of SNPs simultaneously by estimating both cluster parameters and haplotype frequencies. As a result, our new method outperforms some existing algorithms in terms of both call rates and genotyping accuracy. Our studies also suggest that jointly analyzing multiple SNPs in LD provides more accurate estimation of haplotypes than haplotype reconstruction methods that only use called genotypes. CONCLUSION: Our study demonstrates that jointly analyzing signal intensities and LD structure of multiple SNPs is a better way to determine genotypes and estimate LD parameters.

An immunogenic NSCLC microenvironment is associated with favorable survival in lung adenocarcinoma.

The tumor microenvironment consists of an intricately organized system through which immune cells and cancer cells may communicate to regulate anti-tumor immunogenicity. To this end, non-small cell lung cancer (NSCLC) has been shown to activate a variety of immunological mechanisms, thereby broadening our understanding of lung cancer immunobiology. However, while recent work has highlighted the importance of NSCLC immunology and prognosis, studies have not yet examined the tumor microenvironment (TME) globally in regards to the survival outcomes between two major NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In the present study, we identify an immunogenic tumor microenvironment state in NSCLC that is enriched for the lung adenocarcinoma subtype. By utilizing TME cell enrichment scores and RNA-seq expression data, we show that the inflamed TME is associated with favorable patient survival in lung adenocarcinoma, but this does not hold true for lung squamous cell carcinoma. Moreover, differentially regulated pathways between immune-inflamed and immune-excluded tumors within LUAD and LUSC were not subtype specific. Instead, immune-inflamed LUSC samples possessed elevated immune checkpoint marker expression when compared to those of the LUAD samples, thereby offering a putative explanation for our prognostic observations. These results shed light on the immunological prognostic effects within lung cancer and may encourage further TME exploration between these two subtypes as the landscape of NSCLC therapy progresses.