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Adenocarcinomas from multiple tissues can converge to treatment-resistant small cell neuroendocrine (SCN) cancers composed of ASCL1, POU2F3, NEUROD1, and YAP1 subtypes. We investigated how mitochondrial metabolism influences SCN cancer (SCNC) progression. Extensive bioinformatics analyses encompassing thousands of patient tumors and human cancer cell lines uncovered enhanced expression of proliferator-activatedreceptor gamma coactivator 1-alpha (PGC-1α), a potent regulator of mitochondrial oxidative phosphorylation (OXPHOS), across several SCNCs. PGC-1α correlated tightly with increased expression of the lineage marker Achaete-scute homolog 1, (ASCL1) through a positive feedback mechanism. Analyses using a human prostate tissue-based SCN transformation system showed that the ASCL1 subtype has heightened PGC-1α expression and OXPHOS activity. PGC-1α inhibition diminished OXPHOS, reduced SCNC cell proliferation, and blocked SCN prostate tumor formation. Conversely, PGC-1α overexpression enhanced OXPHOS, validated by small-animal Positron Emission Tomography mitochondrial imaging, tripled the SCN prostate tumor formation rate, and promoted commitment to the ASCL1 lineage. These results establish PGC-1α as a driver of SCNC progression and subtype determination, highlighting metabolic vulnerabilities in SCNCs across different tissues.

PurposeWe investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities.MethodsNon-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC).ResultsThis study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p

IntroductionAlthough dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.MethodsWe applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43.ResultsFinal included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility.DiscussionA novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies.HighlightsLatent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

ObjectiveTo describe the participation of racial and ethnic minority groups (REMGs) in gynecologic oncology trials.MethodsGynecologic oncology studies registered on ClinicalTrials.gov between 2007 and 2020 were identified. Trials with published results were analyzed based on reporting of race/ethnicity in relation to disease site and trial characteristics. Expected enrollment by race/ethnicity was calculated and compared to actual enrollment, adjusted for 2010 US Census population data.Results2146 gynecologic oncology trials were identified. Of published trials (n = 252), 99 (39.3%) reported race/ethnicity data. Recent trials were more likely to report these data (36% from 2007 to 2009; 51% 2013-2015; and 53% from 2016 to 2018, p = 0.01). Of all trials, ovarian cancer trials were least likely to report race/ethnicity data (32.1% vs 39.3%, p = 0.011). Population-adjusted under-enrollment for Blacks was 7-fold in ovarian cancer, Latinx 10-fold for ovarian and 6-fold in uterine cancer trials, Asians 2.5-fold in uterine cancer trials, and American Indian and Alaska Native individuals 6-fold in ovarian trials. Trials for most disease sites have enrolled more REMGs in recent years - REMGs made up 19.6% of trial participants in 2007-2009 compared to 38.1% in 2016-2018 (p

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma.

Background: Bladder cancer and therapy responses hinge on immune profiles in the tumor microenvironment (TME) and blood, yet studies linking tumor-infiltrating immune cells to peripheral immune profiles are limited. Methods: DNA methylation cytometry quantified TME and matched peripheral blood immune cell proportions. With tumor immune profile data as the input, subjects were grouped by immune infiltration status and consensus clustering. Results: Immune hot and cold groups had different immune compositions in the TME but not in circulating blood. Two clusters of patients identified with consensus clustering had different immune compositions not only in the TME but also in blood. Conclusion: Detailed immune profiling via methylation cytometry reveals the significance of understanding tumor and systemic immune relationships in cancer patients.

BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.FindingsThe application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).InterpretationOur results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.FundingThe specific funding of this article is provided in the acknowledgements section.

BackgroundImmune profiles have been associated with bladder cancer outcomes and may have clinical applications for prognosis. However, associations of detailed immune cell subtypes with patient outcomes remain underexplored and may contribute crucial prognostic information for better managing bladder cancer recurrence and survival.MethodsBladder cancer case peripheral blood DNA methylation was measured using the Illumina HumanMethylationEPIC array. Extended cell-type deconvolution quantified 12 immune cell-type proportions, including memory, naïve T and B cells, and granulocyte subtypes. DNA methylation clocks determined biological age. Cox proportional hazards models tested associations of immune cell profiles and age acceleration with bladder cancer outcomes. The partDSA algorithm discriminated 10-year overall survival groups from clinical variables and immune cell profiles, and a semi-supervised recursively partitioned mixture model (SS-RPMM) with DNA methylation data was applied to identify a classifier for 10-year overall survival.ResultsHigher CD8T memory cell proportions were associated with better overall survival [HR = 0.95, 95% confidence interval (CI) = 0.93-0.98], while higher neutrophil-to-lymphocyte ratio (HR = 1.36, 95% CI = 1.23-1.50), CD8T naïve (HR = 1.21, 95% CI = 1.04-1.41), neutrophil (HR = 1.04, 95% CI = 1.03-1.06) proportions, and age acceleration (HR = 1.06, 95% CI = 1.03-1.08) were associated with worse overall survival in patient with bladder cancer. partDSA and SS-RPMM classified five groups of subjects with significant differences in overall survival.ConclusionsWe identified associations between immune cell subtypes and age acceleration with bladder cancer outcomes.ImpactThe findings of this study suggest that bladder cancer outcomes are associated with specific methylation-derived immune cell-type proportions and age acceleration, and these factors could be potential prognostic biomarkers.

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

PurposeIn patients with diffuse low-grade glioma (LGG), the extent of surgical tumor resection (EOR) has a controversial role, in part because a randomized clinical trial with different levels of EOR is not feasible.MethodsIn a 20-year retrospective cohort of 392 patients with IDH-mutant grade 2 glioma, we analyzed the combined effects of volumetric EOR and molecular and clinical factors on overall survival (OS) and progression-free survival by recursive partitioning analysis. The OS results were validated in two external cohorts (n = 365). Propensity score analysis of the combined cohorts (n = 757) was used to mimic a randomized clinical trial with varying levels of EOR.ResultsRecursive partitioning analysis identified three survival risk groups. Median OS was shortest in two subsets of patients with astrocytoma: those with postoperative tumor volume (TV) > 4.6 mL and those with preoperative TV > 43.1 mL and postoperative TV ≤ 4.6 mL. Intermediate OS was seen in patients with astrocytoma who had chemotherapy with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL in addition to oligodendroglioma patients with either preoperative TV > 43.1 mL and residual TV ≤ 4.6 mL or postoperative residual volume > 4.6 mL. Longest OS was seen in astrocytoma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL who received no chemotherapy and oligodendroglioma patients with preoperative TV ≤ 43.1 mL and postoperative TV ≤ 4.6 mL. EOR ≥ 75% improved survival outcomes, as shown by propensity score analysis.ConclusionAcross both subtypes of LGG, EOR beginning at 75% improves OS while beginning at 80% improves progression-free survival. Nonetheless, maximal resection with preservation of neurological function remains the treatment goal. Our findings have implications for surgical strategies for LGGs, particularly oligodendroglioma.

DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

BackgroundOver the past decade, DNA methylation (DNAm)-based deconvolution methods that leverage cell-specific DNAm markers of immune cell types have been developed to provide accurate estimates of the proportions of leukocytes in peripheral blood. Immune cell phenotyping using DNAm markers, termed immunomethylomics or methylation cytometry, offers a solution for determining the body's immune cell landscape that does not require fresh blood and is scalable to large sample sizes. Despite significant advances in DNAm-based deconvolution, references at the population level are needed for clinical and research interpretation of these additional immune layers. Here we aim to provide some references for immune populations in a group of multi-ethnic post-menopausal American women.ResultsWe applied DNAm-based deconvolution to a large sample of post-menopausal women enrolled in the Women's Health Initiative (baseline, N = 58) or the ancillary Long Life Study (WHI-LLS, N = 1237) to determine the reference ranges of 58 immune parameters, including proportions and absolute counts for 19 leukocyte subsets and 20 derived cell ratios. Participants were 50-94 years old at the time of blood draw, and N = 898 (69.3%) self-identified as White. Using linear regression models, we observed significant associations between age at blood draw and absolute counts and proportions of naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ memory, neutrophils, and natural killer cells. We also assessed the same immune profiles in a subset of paired longitudinal samples collected 14-18 years apart across N = 52 participants. Our results demonstrate high inter-individual variability in rates of change of leukocyte subsets over this time. And, when conducting paired t tests to test the difference in counts and proportions between the baseline visit and LLS visit, there were significant changes in naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ cells and neutrophils, similar to the results seen when analyzing the association with age in the entire cohort.ConclusionsHere, we show that derived cell counts largely reflect the immune profile associated with proportions and that these novel methods replicate the known immune profiles associated with age. Further, we demonstrate the value this methylation cytometry approach can add as a potential application in epidemiological studies.

ObjectivesThe COVID-19 pandemic accelerated telemedicine use nationally, but differences across health systems are understudied. We examine telemedicine use for adults with diabetes and/or hypertension across 10 health systems and analyze practice and patient characteristics associated with greater use.Study designEncounter-level data from the AMGA Optum Data Warehouse for March 13, 2020, to December 31, 2020, were analyzed, which included 3,016,761 clinical encounters from 764,521 adults with diabetes and/or hypertension attributed to 1 of 1207 practice sites with at least 50 system-attributed patients.MethodsLinear spline regression estimated whether practice size and ownership were associated with telemedicine during the adoption (weeks 0-4), de-adoption (weeks 5-12), and maintenance (weeks 13-42) periods, controlling for patient socioeconomic and clinical characteristics.ResultsTelemedicine use peaked at 11% to 42% of weekly encounters after 4 weeks. In adjusted analyses, small practices had lower telemedicine use for adults with diabetes during the maintenance period compared with larger practices. Practice ownership was not associated with telemedicine use. Practices with higher proportions of Black patients continued to expand telemedicine use during the de-adoption and maintenance periods.ConclusionsPractice ownership was not associated with telemedicine use during first months of the pandemic. Small practices de-adopted telemedicine to a greater degree than medium and large practices. Technical support for small practices, irrespective of their ownership, could enable telemedicine use for adults with diabetes and/or hypertension.

We used data from the US Cancer Statistics database to determine trends in cancer incidence, stratified by age, race, and ethnicity, among women aged 20 years or older during an 18-year study period (2001-2018). We limited analysis to cancers associated with 5 modifiable risk factors: tobacco use, excess body fat, alcohol consumption, insufficient physical activity, and human papillomavirus infection. The incidence of cancers associated with obesity have risen, particularly among women aged 20 to 49 years (vs ≥50 y) and among Hispanic women. Strategies that address obesity rates in these populations may help decrease cancer risk.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

BackgroundIdentifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450).ResultsThe NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays.ConclusionsWe developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.

BackgroundThere is considerable evidence that epigenetic mechanisms and DNA methylation are critical drivers of immune cell lineage differentiation and activation. However, there has been limited coordinated investigation of common epigenetic pathways among cell lineages. Further, it remains unclear if long-lived memory cell subtypes differentiate distinctly by cell lineages.ResultsWe used the Illumina EPIC array to investigate the consistency of DNA methylation in B cell, CD4 T, and CD8 T naïve and memory cells states. In the process of naïve to memory activation across the three lineages, we identify considerable shared epigenetic regulation at the DNA level for immune memory generation. Further, in central to effector memory differentiation, our analyses revealed specific CpG dinucleotides and genes in CD4 T and CD8 T cells with DNA methylation changes. Finally, we identified unique DNA methylation patterns in terminally differentiated effector memory (TEMRA) CD8 T cells compared to other CD8 T memory cell subtypes.ConclusionsOur data suggest that epigenetic alterations are widespread and essential in generating human lymphocyte memory. Unique profiles are involved in methylation changes that accompany memory genesis in the three subtypes of lymphocytes.

Older patients and those who require interpreters are least likely to use telehealth for gynecologic oncology care, showing disparities which continued after statewide vaccinations.

BackgroundNon-muscle-invasive bladder cancer (NMIBC) patients receive frequent monitoring because ≥ 70% will have recurrent disease. However, screening is invasive, expensive, and associated with significant morbidity making bladder cancer the most expensive cancer to treat per capita. There is an urgent need to expand the understanding of markers related to recurrence and survival outcomes of NMIBC.Methods and resultsWe used the Illumina HumanMethylationEPIC array to measure peripheral blood DNA methylation profiles of NMIBC patients (N = 603) enrolled in a population-based cohort study in New Hampshire and applied cell type deconvolution to estimate immune cell-type proportions. Using Cox proportional hazard models, we identified that increasing CD4T and CD8T cell proportions were associated with a statistically significant decreased hazard of tumor recurrence or death (CD4T: HR = 0.98, 95% CI = 0.97-1.00; CD8T: HR = 0.97, 95% CI = 0.95-1.00), whereas increasing monocyte proportion and methylation-derived neutrophil-to-lymphocyte ratio (mdNLR) were associated with the increased hazard of tumor recurrence or death (monocyte: HR = 1.04, 95% CI = 1.00-1.07; mdNLR: HR = 1.12, 95% CI = 1.04-1.20). Then, using an epigenome-wide association study (EWAS) approach adjusting for age, sex, smoking status, BCG treatment status, and immune cell profiles, we identified 2528 CpGs associated with the hazard of tumor recurrence or death (P

BackgroundMyeloid-derived suppressor cells (MDSCs), which include monocytic (mMDSCs) and granulocytic (gMDSCs) cells, are an immunosuppressive, heterogeneous population of cells upregulated in cancer and other pathologic conditions, in addition to normal conditions of stress. The origin of MDSCs is debated, and the regulatory pattern responsible for gMDSC differentiation remains unknown. Since DNA methylation (DNAm) contributes to lineage differentiation, we have investigated whether it contributes to the acquisition of the gMDSC phenotype.ResultsUsing the Illumina EPIC array to measure DNAm of gMDSCs and neutrophils from diverse neonatal and adult blood sources, we found 189 differentially methylated CpGs between gMDSCs and neutrophils with a core of ten differentially methylated CpGs that were consistent across both sources of cells. Genes associated with these loci that are involved in immune responses include VCL, FATS, YAP1, KREMEN2, UBTF, MCC-1, and EFCC1. In two cancer patient groups that reflected those used to develop the methylation markers (head and neck squamous cell carcinoma (HNSCC) and glioma), all of the CpG loci were differentially methylated, reaching statistical significance in glioma cases and controls, while one was significantly different in the smaller HNSCC group.ConclusionsOur findings indicate that gMDSCs have a core of distinct DNAm alterations, informing future research on gMDSC differentiation and function.

BackgroundGenomic profiling studies of diffuse gliomas have led to new improved classification schemes that better predict patient outcomes compared to conventional histomorphology alone. One example is the recognition that patients with IDH-wildtype diffuse astrocytic gliomas demonstrating lower-grade histologic features but genomic and/or epigenomic profile characteristic of glioblastoma typically have poor outcomes similar to patients with histologically diagnosed glioblastoma. Here we sought to determine the clinical impact of prospective genomic profiling for these IDH-wildtype diffuse astrocytic gliomas lacking high-grade histologic features but with molecular profile of glioblastoma.MethodsClinical management and outcomes were analyzed for 38 consecutive adult patients with IDH-wildtype diffuse astrocytic gliomas lacking necrosis or microvascular proliferation on histologic examination that were genomically profiled on a prospective clinical basis revealing criteria for an integrated diagnosis of "diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV" per cIMPACT-NOW criteria.ResultsWe identified that this diagnosis consists of two divergent clinical scenarios based on integration of radiologic, histologic, and genomic features that we term "early/evolving" and "undersampled" glioblastoma, IDH-wildtype. We found that prospective genomically guided identification of early/evolving and undersampled IDH-wildtype glioblastoma resulted in more aggressive patient management and improved clinical outcomes compared to a biologically matched historical control patient cohort receiving standard-of-care therapy based on histomorphologic diagnosis alone.ConclusionsThese results support routine use of genomic and/or epigenomic profiling to accurately classify glial neoplasms, as these assays not only improve diagnostic classification but critically lead to more appropriate patient management that can improve clinical outcomes.

Diffusion tensor imaging (DTI) literature on single-center studies contains conflicting results regarding acute effects of mild traumatic brain injury (mTBI) on white matter (WM) microstructure and the prognostic significance. This larger-scale multi-center DTI study aimed to determine how acute mTBI affects WM microstructure over time and how early WM changes affect long-term outcome. From Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI), a cohort study at 11 United States level 1 trauma centers, a total of 391 patients with acute mTBI ages 17 to 60 years were included and studied at two weeks and six months post-injury. Demographically matched friends or family of the participants were the control group (n = 148). Axial diffusivity (AD), fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) were the measures of WM microstructure. The primary outcome was the Glasgow Outcome Scale Extended (GOSE) score of injury-related functional limitations across broad life domains at six months post-injury. The AD, MD, and RD were higher and FA was lower in mTBI versus friend control (FC) at both two weeks and six months post-injury throughout most major WM tracts of the cerebral hemispheres. In the mTBI group, AD and, to a lesser extent, MD decreased in WM from two weeks to six months post-injury. At two weeks post-injury, global WM AD and MD were both independently associated with six-month incomplete recovery (GOSE

OBJECTIVE:: Endometrial cancer (EC) is increasing in incidence and mortality rates, possibly due to the rising rates of obesity in the United States. The type I/II EC classification system was first proposed by Bokhman in 1983 following 20 years of personal observations among 366 women and established obesity as a classical risk factor for low-grade EC with a good prognosis. However, more recent pooled analyses suggest that the 2 types share many etiologic risk factors, including obesity. Given the increase in mortality as a consequence of high-risk EC, the relationship between obesity and uterine cancer, as proposed by Bohkman, may be oversimplified. This study aimed to analyze the trend of type I/II EC in the United States as it relates to obesity using national statistics. STUDY DESIGN:: Data were obtained from the United States Cancer Statistics database and the Behavioral Risk Factors Surveillance System survey from 2001 to 2017. The incidence of uterine cancer, histologic type, obesity, and average annual percentage change (AAPC) were calculated using Joinpoint regression. Endometrial histology was classified according to traditional type I (endometrioid grade 1–3) and type II (serous, clear cell, carcinosarcoma) categories. RESULTS:: Over this 17-year study period, 778,891 patients were diagnosed with uterine cancer. Overall, the rate of new uterine cancer cases increased by 0.82% annually (P

ObjectivePatients with advanced epithelial ovarian cancer (EOC) alive without progression at a landmark time-point of 10 years from diagnosis are likely cured. We report the proportion of patients with Stage III EOC who were long-term disease-free survivors (LTDFS≥10 years) following either intraperitoneal (IP) or intravenous (IV) chemotherapy as well as the predictors of LTDFS.MethodsData from 3 mature NRG/GOG trials (104, 114, 172) were analyzed and included demographics, clinicopathologic details, route of administration, and survival outcomes of patients living ≥10 years assessed according to the Kaplan-Meier method. Cox regression survival analysis was performed to evaluate independent prognostic predictors of LTDFS.ResultsOf 1174 patients randomized, 10-year overall survival (OS) was 26% (95% CI, 23-28%) and LTDFS ≥10 years was 18% (95% CI, 16-20%). Patients with LTDFS ≥10 years had a median age of 54.6 years (p < 0.001). Younger age (p < 0.001) was the only independent prognostic factor for LTDFS≥10 years on multivariate Cox analysis.ConclusionsApproximately 18% of patients were LTDFS ≥10 years. They form the tail end of the survival curve and are likely cured. Our results provide a comparative benchmark to evaluate the impact of PARP inhibitors in 1st line maintenance trials on survival outcomes.

Tissue-specific antigens can serve as targets for adoptive T cell transfer-based cancer immunotherapy. Recognition of tumor by T cells is mediated by interaction between peptide-major histocompatibility complexes (pMHCs) and T cell receptors (TCRs). Revealing the identity of peptides bound to MHC is critical in discovering cognate TCRs and predicting potential toxicity. We performed multimodal immunopeptidomic analyses for human prostatic acid phosphatase (PAP), a well-recognized tissue antigen. Three physical methods, including mild acid elution, coimmunoprecipitation, and secreted MHC precipitation, were used to capture a thorough signature of PAP on HLA-A*02:01. Eleven PAP peptides that are potentially A*02:01-restricted were identified, including five predicted strong binders by NetMHCpan 4.0. Peripheral blood mononuclear cells (PBMCs) from more than 20 healthy donors were screened with the PAP peptides. Seven cognate TCRs were isolated which can recognize three distinct epitopes when expressed in PBMCs. One TCR shows reactivity toward cell lines expressing both full-length PAP and HLA-A*02:01. Our results show that a combined multimodal immunopeptidomic approach is productive in revealing target peptides and defining the cloned TCR sequences reactive with prostatic acid phosphatase epitopes.

ObjectiveTo investigate the genetic architecture of internalizing symptoms in childhood and adolescence.MethodIn 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.ResultsThe meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.ConclusionGenetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

We herein present an overview of the upcoming 5th edition of the World Health Organization Classification of Haematolymphoid Tumours focussing on lymphoid neoplasms. Myeloid and histiocytic neoplasms will be presented in a separate accompanying article. Besides listing the entities of the classification, we highlight and explain changes from the revised 4th edition. These include reorganization of entities by a hierarchical system as is adopted throughout the 5th edition of the WHO classification of tumours of all organ systems, modification of nomenclature for some entities, revision of diagnostic criteria or subtypes, deletion of certain entities, and introduction of new entities, as well as inclusion of tumour-like lesions, mesenchymal lesions specific to lymph node and spleen, and germline predisposition syndromes associated with the lymphoid neoplasms.

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions.

The Glasgow Outcome Scale-Extended (GOSE) is a functional outcome measure intended to place individuals with traumatic brain injury (TBI) into one of eight broad levels of injury-related disability. This simplicity is not always optimal, particularly when more granular assessment of individuals' injury recovery is desired. The GOSE, however, is customarily assessed using a multi-question interview that contains richer information than is reflected in the GOSE score. Using data from the multi-center Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study (N = 1544), we used item response theory (IRT) to evaluate whether rescoring the GOSE using IRT, which posits that a continuous latent variable (disability) underlies responses, can yield a more precise index of injury-related functional limitations. We fit IRT models to GOSE interview responses collected at three months post-injury. Each participant's level of functional limitation was estimated from the model (GOSE-IRT) and comparisons were made between IRT-based and standard (GOSE-Ordinal) scores. The IRT scoring resulted in 141 possible scores (vs. 7 GOSE-Ordinal scores in this sample of individuals with GOSE scores ranging between 2 and 8). Moreover, GOSE-IRT scores were significantly more strongly associated with measures of TBI-related symptoms, psychological symptoms, and quality of life. Our findings demonstrate that rescoring the GOSE interview using IRT yields more granular, meaningful measurement of injury-related functional limitations, while adding no additional respondent or examiner burden. This technique may have utility for many applications, such as clinical trials aiming to detect small treatment effects, and small-scale studies that need to maximize statistical efficiency.

Glioma is a highly fatal cancer with prognostically significant molecular subtypes and few known risk factors. Multiple studies have implicated infections in glioma susceptibility, but evidence remains inconsistent. Genetic variants in the human leukocyte antigen (HLA) region modulate host response to infection and have been linked to glioma risk. In this study, we leveraged genetic predictors of antibody response to 12 viral antigens to investigate the relationship with glioma risk and survival. Genetic reactivity scores (GRSs) for each antigen were derived from genome-wide-significant (p

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Purpose of the reviewNeurocysticercosis (NCC) has been well recognized as a leading cause of epilepsy. More recently, studies of other parasitic diseases such as cerebral malaria (CM) and onchocerciasis are yielding novel insights into the pathogenesis of parasite-associated epilepsy. We compare the clinical and electrophysiological findings in epilepsy associated with these highly prevalent parasites and discuss the mechanisms involved in epileptogenesis.Recent findingsElectrophysiological and imaging biomarkers continue to emerge, and individuals who are at-risk of developing parasite-associated epilepsies are being identified with greater reliability. While both Taenia solium and Plasmodium falciparum directly affect the brain parenchyma, Onchocerca volvulus is not known to invade the central nervous system. Thus, the causal association between O. volvulus and epilepsy remains controversial. Both NCC and CM have a well-defined acute phase when the parasites directly or indirectly invade the brain parenchyma and lead to local inflammatory changes. This is followed by a chronic phase marked by recurrent seizures. However, these stages of epileptogenic process have not been identified in the case of O. volvulus.

BackgroundTumor-based classification of human glioma portends patient prognosis, but considerable unexplained survival variability remains. Host factors (eg, age) also strongly influence survival times, partly reflecting a compromised immune system. How blood epigenetic measures of immune characteristics and age augment molecular classifications in glioma survival has not been investigated. We assess the prognostic impact of immune cell fractions and epigenetic age in archived blood across glioma molecular subtypes for the first time.MethodsWe evaluated immune cell fractions and epigenetic age in archived blood from the University of California San Francisco Adult Glioma Study, which included a training set of 197 patients with IDH-wild type, 1p19q intact, TERT wild type (IDH/1p19q/TERT-WT) glioma, an evaluation set of 350 patients with other subtypes of glioma, and 454 patients without glioma.ResultsIDH/1p19q/TERT-WT patients had lower lymphocyte fractions (CD4+ T, CD8+ T, natural killer, and B cells) and higher neutrophil fractions than people without glioma. Recursive partitioning analysis delineated 4 statistically significantly different survival groups for patients with IDH/1p19q/TERT-WT based on an interaction between chronological age and 2 blood immune factors, CD4+ T cells, and neutrophils. Median overall survival ranged from 0.76 years (95% confidence interval = 0.55-0.99) for the worst survival group (n = 28) to 9.72 years (95% confidence interval = 6.18 to not available) for the best (n = 33). The recursive partitioning analysis also statistically significantly delineated 4 risk groups in patients with other glioma subtypes.ConclusionsThe delineation of different survival groups in the training and evaluation sets based on an interaction between chronological age and blood immune characteristics suggests that common host immune factors among different glioma types may affect survival. The ability of DNA methylation-based markers of immune status to capture diverse, clinically relevant information may facilitate noninvasive, personalized patient evaluation in the neuro-oncology clinic.

The mammalian kidney has extensive repair capacity; however, identifying adult renal stem cells has proven elusive. We applied an epigenetic marker of foetal cell origin (FCO) in diverse human tissues as a probe for developmental cell persistence, finding a 5.4-fold greater FCO proportion in kidney. Normal kidney FCO proportions averaged 49% with extensive interindividual variation. FCO proportions were significantly negatively correlated with immune-related gene expression and positively correlated with genes expressed in the renal medulla, including those involved in renal organogenesis (e.g., FGF2, PAX8, and HOXB7). FCO associated genes also mapped to medullary nephron segments in mouse and rat, suggesting evolutionary conservation of this cellular compartment. Renal cancer patients whose tumours contained non-zero FCO scores survived longer. The kidney appears unique in possessing substantial foetal epigenetic features. Further study of FCO-related gene methylation may elucidate regenerative regulatory programmes in tissues without apparent discrete stem cell compartments.

Immune checkpoint inhibitor-associated colitis (ICIC) affects approximately 15% of cancer patients treated with immunotherapy. Although histological evaluation is potentially valuable for both the diagnosis of ICIC and evaluation of disease activity, use in clinical practice is heterogeneous. We aimed to develop expert recommendations to standardize histological assessment of disease activity in patients with ICIC. Using the modified Research and Development/University of California Los Angeles (RAND/UCLA) appropriateness methodology, an international panel of 11 pathologists rated the appropriateness of 99 statements on a 9-point Likert scale during two rounds of anonymous voting. Results were discussed between rounds using moderated videoconferences. There are currently no disease-specific instruments for assessing histological features of ICIC. The panel considered that colonoscopy with at least three biopsies per segment from a total of at least five segments, including both endoscopically normal and inflamed areas, was appropriate for tissue acquisition. They agreed that biopsies should be oriented such that the long axis of the colonic crypts is visualized and should be stained with hematoxylin and eosin. Histological items that the panel voted were appropriate to evaluate in ICIC included the degree of structural/architectural change, chronic inflammatory infiltrate, lamina propria and intraepithelial neutrophils, crypt abscesses and destruction, erosions/ulcerations, apoptosis, surface intraepithelial lymphocytosis, and subepithelial collagen thickness. The appropriateness of routine immunohistochemistry was uncertain. These expert recommendations will help standardize assessment of histological activity in patients with ICIC. The panel also identified the development and validation of an ICIC-specific histological index as a research priority.

Symptom endorsement after traumatic brain injury (TBI) is common acutely post-injury and is associated with other adverse outcomes. Prevalence of persistent symptoms has been debated, especially in mild TBI (mTBI). A cohort of participants ≥17 years with TBI (n = 2039), 257 orthopedic trauma controls (OTCs), and 300 friend controls (FCs) were enrolled in the TRACK-TBI study and evaluated at 2 weeks and 3, 6, and 12 months post-injury using the Rivermead Post-Concussion Symptoms Questionnaire (RPQ). TBI participants had significantly higher symptom burden than OTCs or FCs at all times, with average scores more than double. TBI cases showed significant decreases in RPQ score between each evaluation (p 50% of each of the mild and moderate/severe TBI subsamples, continued to endorse three or more symptoms as worse than pre-injury through 12 months post-injury. A majority of TBI participants who endorsed a symptom at 3 months or later did so at the next evaluation as well. Contrary to reviews that report symptom resolution by 3 months post-injury among those with mTBI, this study of participants treated at level 1 trauma centers and having a computed tomography ordered found that persistent symptoms are common to at least a year after TBI. Additionally, although symptom endorsement was not specific to TBI given that they were also reported by OTC and FC participants, TBI participants endorsed over twice the symptom burden compared with the other groups.

BackgroundSomatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.MethodsThrough analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status.ResultsOf 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients.ConclusionsWe introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC.ImpactThe proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

ObjectiveTo assess the presentation, characteristics, and prognostic significance of symptoms in patients with high-risk early-stage epithelial ovarian cancer.MethodsA retrospective chart review was performed on all patients enrolled in a phase III clinical trial (GOG 157). All patients had surgically staged, high-risk early-stage epithelial ovarian cancer (stage IA-IB and grade 3, any clear cell, stage IC or II). Chi-square and Kaplan-Meier estimates and Cox proportional hazards models were used for statistical analyses.ResultsOf 419 patients evaluated for symptoms, 301 (72%) presented with one or more symptoms, and 118 (28%) were asymptomatic but had a mass found on examination. Forty percent had only one symptom, and 32% had more than one symptom. Among those with at least one symptom, the most common were abdominal and pelvic pain (31%), and increased girth or fullness (26%). Overall, 23% of patients with tumors 10 cm or smaller, 27% of patients with tumors larger than 10 cm to 15 cm, and 46% of patients with tumors larger than 15 cm had multiple symptoms (P

ObjectiveIn the Phase 3 VELIA trial (NCT02470585), veliparib added to carboplatin plus paclitaxel concomitantly and as maintenance for women with newly-diagnosed advanced ovarian cancer significantly improved progression-free survival (PFS) versus chemotherapy alone. Here we present exploratory analyses by paclitaxel dosing schedule and germline BRCA (gBRCA) status.MethodsWomen with untreated ovarian carcinoma were randomized (1:1:1) to: veliparib during chemotherapy and maintenance (veliparib-throughout), veliparib during chemotherapy followed by placebo maintenance (veliparib-combination only), or placebo during chemotherapy and maintenance (control). Chemotherapy included carboplatin plus dose-dense (DD; weekly) or every-3-week (Q3W) paclitaxel (a stratification factor at randomization), selected at the investigator's discretion pre-randomization. PFS was assessed by paclitaxel dosing schedule using a Cox proportional hazard model adjusted by treatment arm and stratification factors; safety was analyzed based on paclitaxel dosing schedule and gBRCA status.Results1132 patients were analyzed by paclitaxel schedule. Pooled treatment arms demonstrated longer median PFS with DD (n = 586) versus Q3W (n = 546) paclitaxel (ITT: 20.5 vs 15.7 months, hazard ratio [HR] 0.77; homologous recombination proficient cancer: 15.1 vs 11.8 months, HR 0.64; BRCAwt: 18.0 vs 12.9 months, HR 0.70). Comparison between arms favored veliparib-throughout versus control in both DD (PFS, 24.2 vs 18.3 months, hazard ratio 0.67) and Q3W (19.3 vs 14.6, hazard ratio 0.69) subgroups. DD paclitaxel was associated with higher incidence of Grade 3/4 neutropenia, fatigue, and anemia versus Q3W. There were no differences in toxicity between gBRCAm (n = 211) and gBRCAwt (n = 902) subgroups.ConclusionsDD paclitaxel was tolerable and associated with longer PFS in the HR proficient and gBRCAwt groups, versus Q3W. gBRCA status did not impact safety.

BackgroundCellular 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.ResultsWe 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.ConclusionWe 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.

Suicide among young people is an increasingly prevalent and devastating public health crisis around the world. To reduce the rate of suicide, it is important to identify factors that can help us better predict suicidal ideation and behaviors. Adolescent temperament (effortful control, negative emotionality, positive emotionality) may be a source of risk and resilience for the onset of suicidal ideation, plans, and attempts. The present study uses longitudinal data from a large, community sample of Mexican-origin youth (N = 674), assessed annually from age 12 to 21, to examine how temperament is associated with the onset of suicidal ideation and behaviors during adolescence and young adulthood. Results indicate that higher levels of effortful control (activation control, inhibitory control, attention) are associated with decreased probability of experiencing the onset of suicidal ideation, plans, and attempts, whereas higher levels of negative emotionality (particularly aggression, frustration, and depressed mood) are associated with increased probability of experiencing the onset of suicidal ideation and behaviors. Positive emotionality (surgency, affiliation) was not associated with the onset of suicidal ideation and behaviors. Supplemental analyses showed conceptually similar findings for the Big Five, with Conscientiousness associated with decreased risk, Neuroticism associated with increased risk, and the other three dimensions showing largely null results. The findings did not vary significantly for boys and girls or for youth born in the U.S. versus Mexico. Overall, these findings suggest that adolescent temperament serves as both a protective factor (via effortful control/Conscientiousness) and a risk factor (via negative emotionality/Neuroticism) for suicidal ideation and behaviors in Mexican-origin youth. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

DNA methylation microarrays can be employed to interrogate cell-type composition in complex tissues. Here, we expand reference-based deconvolution of blood DNA methylation to include 12 leukocyte subtypes (neutrophils, eosinophils, basophils, monocytes, naïve and memory B cells, naïve and memory CD4 + and CD8 + T cells, natural killer, and T regulatory cells). Including derived variables, our method provides 56 immune profile variables. The IDOL (IDentifying Optimal Libraries) algorithm was used to identify libraries for deconvolution of DNA methylation data for current and previous platforms. The accuracy of deconvolution estimates obtained using our enhanced libraries was validated using artificial mixtures and whole-blood DNA methylation with known cellular composition from flow cytometry. We applied our libraries to deconvolve cancer, aging, and autoimmune disease datasets. In conclusion, these libraries enable a detailed representation of immune-cell profiles in blood using only DNA and facilitate a standardized, thorough investigation of immune profiles in human health and disease.

It is important to measure quality of life (QoL) after traumatic brain injury (TBI), yet limited studies have compared QoL inventories. In 2579 TBI patients, orthopedic trauma controls, and healthy friend control participants, we compared the Quality of Life After Brain Injury-Overall Scale (QOLIBRI-OS), developed for TBI patients, to the Satisfaction with Life Scale (SWLS), an index of generic life satisfaction. We tested the hypothesis that group differences (TBI and orthopedic trauma vs. healthy friend controls) would be larger for the QOLIBRI-OS than the SWLS and that the QOLIBRI-OS would manifest more substantial changes over time in the injured groups, demonstrating more relevance of the QOLIBRI-OS to traumatic injury recovery. (1) We compared the group differences (TBI vs. orthopedic trauma control vs. friend control) in QoL as indexed by the SWLS versus the QOLIBRI-OS and (2) characterized changes across time in these two inventories across 1 year in these three groups. Our secondary objective was to characterize the relationship between TBI severity and QoL. As compared with healthy friend controls, the QOLIBRI reflected greater reductions in QoL than the SWLS for both the TBI group (all time points) and the orthopedic trauma control group (2 weeks and 3 months). The QOLIBRI-OS better captured expected improvements in QoL during the injury recovery course in injured groups than the SWLS, which demonstrated smaller changes over time. TBI severity was not consistently or robustly associated with self-reported QoL. The findings imply that, as compared with the SWLS, the QOLIBRI-OS appears to identify QoL issues more specifically relevant to traumatically injured patients and may be a more appropriate primary QoL outcome measure for research focused on the sequelae of traumatic injuries.

The National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH-NINDS) Traumatic Brain Injury (TBI) Imaging Common Data Elements (CDEs) are standardized definitions for pathological intracranial lesions based on their appearance on neuroimaging studies. The NIH-NINDS TBI Imaging CDEs were designed to be as consistent as possible with the U.S. Food and Drug Administration (FDA) definition of biomarkers as "an indicator of normal biological processes, pathogenic processes, or biological responses to an exposure or intervention." However, the FDA qualification process for biomarkers requires proof of reliable biomarker test measurements. We determined the interrater reliability of TBI Imaging CDEs on subacute brain magnetic resonance imaging (MRI) performed on 517 mild TBI patients presenting to 11 U.S. level 1 trauma centers. Three U.S. board-certified neuroradiologists independently evaluated brain MRI performed 2 weeks post-injury for the following CDEs: traumatic axonal injury (TAI), diffuse axonal injury (DAI), and brain contusion. We found very high interrater agreement for brain contusion, with prevalence- and bias-adjusted kappa (PABAK) values for pairs of readers from 0.92 [95% confidence interval, 0.88-0.95] to 0.94 [0.90-0.96]. We found intermediate agreement for TAI and DAI, with PABAK values of 0.74-0.78 [0.70-0.82]. The near-perfect agreement for subacute brain contusion is likely attributable to the high conspicuity and distinctive appearance of these lesions on T1-weighted images. Interrater agreement for TAI and DAI was lower, because signal void in small vascular structures, and artifactual foci of signal void, can be difficult to distinguish from the punctate round or linear areas of slight hemorrhage that are a common hallmark of TAI/DAI on MRI.

BackgroundAlthough specific interventions previously demonstrated benefit in patients with ARDS, use of these interventions is inconsistent, and patient mortality remains high. The impact of variability in center management practices on ARDS mortality rates remains unknown.Research questionWhat is the impact of treatment variability on mortality in patients with moderate to severe ARDS in the United States?Study design and methodsWe conducted a multicenter, observational cohort study of mechanically ventilated adults with ARDS and Pao2 to Fio2 ratio of ≤ 150 with positive end-expiratory pressure of ≥ 5 cm H2O, who were admitted to 29 US centers between October 1, 2016, and April 30, 2017. The primary outcome was 28-day in-hospital mortality. Center variation in ventilator management, adjunctive therapy use, and mortality also were assessed.ResultsA total of 2,466 patients were enrolled. Median baseline Pao2 to Fio2 ratio was 105 (interquartile range, 78.0-129.0). In-hospital 28-day mortality was 40.7%. Initial adherence to lung protective ventilation (LPV; tidal volume, ≤ 6.5 mL/kg predicted body weight; plateau pressure, or when unavailable, peak inspiratory pressure, ≤ 30 mm H2O) was 31.4% and varied between centers (0%-65%), as did rates of adjunctive therapy use (27.1%-96.4%), methods used (neuromuscular blockade, prone positioning, systemic steroids, pulmonary vasodilators, and extracorporeal support), and mortality (16.7%-73.3%). Center standardized mortality ratios (SMRs), calculated using baseline patient-level characteristics to derive expected mortality rate, ranged from 0.33 to 1.98. Of the treatment-level factors explored, only center adherence to early LPV was correlated with SMR.InterpretationSubstantial center-to-center variability exists in ARDS management, suggesting that further opportunities for improving ARDS outcomes exist. Early adherence to LPV was associated with lower center mortality and may be a surrogate for overall quality of care processes. Future collaboration is needed to identify additional treatment-level factors influencing center-level outcomes.Trial registryClinicalTrials.gov; No.: NCT03021824; URL: www.clinicaltrials.gov.

Missing data is a persistent and unavoidable problem in even the most carefully designed traumatic brain injury (TBI) clinical research. Missing data patterns may result from participant dropout, non-compliance, technical issues, or even death. This review describes the types of missing data that are common in TBI research, and assesses the strengths and weaknesses of the statistical approaches used to draw conclusions and make clinical decisions from these data. We review recent innovations in missing values analysis (MVA), a relatively new branch of statistics, as applied to clinical TBI data. Our discussion focuses on studies from the International Traumatic Brain Injury Research (InTBIR) initiative project: Transforming Research and Clinical Knowledge in TBI (TRACK-TBI), Collaborative Research on Acute TBI in Intensive Care Medicine in Europe (CREACTIVE), and Approaches and Decisions in Acute Pediatric TBI Trial (ADAPT). In addition, using data from the TRACK-TBI pilot study (n = 586) and the completed clinical trial assessing valproate (VPA) for the treatment of post-traumatic epilepsy (n = 379) we present real-world examples of typical missing data patterns and the application of statistical techniques to mitigate the impact of missing data in order to draw sound conclusions from ongoing clinical studies.

Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps-discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

The Glasgow Outcome Scale (GOS) in its original or extended (GOSE) form is the most widely used assessment of global disability in traumatic brain injury (TBI) research. Several publications have reported concerns about assessor scoring inconsistencies, but without documentation of contributing factors. We reviewed 6801 GOSE assessments collected longitudinally, across 18 sites in the 5-year, observational Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study. We recorded error rates (i.e., corrections to a section or an overall rating) based on site assessor documentation and categorized scoring issues, which then informed further training. In cohort 1 (n = 1261; February 2014 to May 2016), 24% of GOSEs had errors identified by central review. In cohort 2 (n = 1130; June 2016 to July 2018), acquired after curation of cohort 1 data, feedback, and further training of site assessors, the error rate was reduced to 10%. GOSE sections associated with the most frequent interpretation and scoring difficulties included whether current functioning represented a change from pre-injury (466 corrected ratings in cohort 1; 62 in cohort 2), defining dependency in the home and community (163 corrections in cohort 1; three in cohort 2) and return to work/school (72 corrections in cohort 1; 35 in cohort 2). These results highlight the importance of central review in improving consistency across sites and over time. Establishing clear scoring criteria, coupled with ongoing guidance and feedback to data collectors, is essential to avoid scoring errors and resultant misclassification, which carry potential to result in "failure" of clinical trials that rely on the GOSE as their primary outcome measure.