A hexasome is the preferred substrate for the INO80 chromatin remodeling complex, allowing versatility of function.

The critical role of the INO80 chromatin remodeling complex in transcription is commonly attributed to its nucleosome sliding activity. Here, we have found that INO80 prefers to mobilize hexasomes over nucleosomes. INO80's preference for hexasomes reaches up to ∼60 fold when flanking DNA overhangs approach ∼18-bp linkers in yeast gene bodies. Correspondingly, deletion of INO80 significantly affects the positions of hexasome-sized particles within yeast genes in vivo. Our results raise the possibility that INO80 promotes nucleosome sliding by dislodging an H2A-H2B dimer, thereby making a nucleosome transiently resemble a hexasome. We propose that this mechanism allows INO80 to rapidly mobilize nucleosomes at promoters and hexasomes within gene bodies. Rapid repositioning of hexasomes that are generated in the wake of transcription may mitigate spurious transcription. More generally, such versatility may explain how INO80 regulates chromatin architecture during the diverse processes of transcription, replication, and repair.

Human Epidemiology and RespOnse to SARS-CoV-2 (HEROS): Objectives, Design and Enrollment Results of a 12-City Remote Observational Surveillance Study of Households with Children using Direct-to-Participant Methods.

The Human Epidemiology and Response to SARS-CoV-2 (HEROS) is a prospective multi-city 6-month incidence study which was conducted from May 2020-February 2021. The objectives were to identify risk factors for SARS-CoV-2 infection and household transmission among children and people with asthma and allergic diseases, and to use the host nasal transcriptome sampled longitudinally to understand infection risk and sequelae at the molecular level. To overcome challenges of clinical study implementation due to the coronavirus pandemic, this surveillance study used direct-to-participant methods to remotely enroll and prospectively follow eligible children who are participants in other NIH-funded pediatric research studies and their household members. Households participated in weekly surveys and biweekly nasal sampling regardless of symptoms. The aim of this report is to widely share the methods and study instruments and to describe the rationale, design, execution, logistics and characteristics of a large, observational, household-based, remote cohort study of SARS-CoV-2 infection and transmission in households with children. The study enrolled a total of 5,598 individuals, including 1,913 principal participants (children), 1,913 primary caregivers, 729 secondary caregivers and 1,043 other household children. This study was successfully implemented without necessitating any in-person research visits and provides an approach for rapid execution of clinical research.

IL-13-associated epithelial remodeling correlates with clinical severity in nasal polyposis.

BACKGROUND: Epithelial remodeling is a histopathologic feature of chronic inflammatory airway diseases including chronic rhinosinusitis (CRS). Cell-type shifts and their relationship to CRS endotypes and severity are incompletely described. OBJECTIVE: We sought to understand the relationship of epithelial cell remodeling to inflammatory endotypes and disease outcomes in CRS. METHODS: Using cell-type transcriptional signatures derived from epithelial single-cell sequencing, we analyzed bulk RNA-sequencing data from sinus epithelial brushings obtained from patients with CRS with and without nasal polyps in comparison to healthy controls. RESULTS: The airway epithelium in nasal polyposis displayed increased tuft cell transcripts and decreased ciliated cell transcripts along with an IL-13 activation signature. In contrast, CRS without polyps showed an IL-17 activation signature. IL-13 activation scores were associated with increased tuft cell, goblet cell, and mast cell scores and decreased ciliated cell scores. Furthermore, the IL-13 score was strongly associated with a previously reported activated ("polyp") tuft cell score and a prostaglandin E2 activation signature. The Lund-Mackay score, a computed tomographic metric of sinus opacification, correlated positively with activated tuft cell, mast cell, prostaglandin E2, and IL-13 signatures and negatively with ciliated cell transcriptional signatures. CONCLUSIONS: These results demonstrate that cell-type alterations and prostaglandin E2 stimulation are key components of IL-13-induced epithelial remodeling in nasal polyposis, whereas IL-17 signaling is more prominent in CRS without polyps, and that clinical severity correlates with the degree of IL-13-driven epithelial remodeling.

Colocalization of Gene Expression and DNA Methylation with Genetic Risk Variants Supports Functional Roles of MUC5B and DSP in Idiopathic Pulmonary Fibrosis.

Rationale: Common genetic variants have been associated with idiopathic pulmonary fibrosis (IPF). Objectives: To determine functional relevance of the 10 IPF-associated common genetic variants we previously identified. Methods: We performed expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL) mapping, followed by co-localization of eQTL and mQTL with genetic association signals and functional validation by luciferase reporter assays. Illumina multi-ethnic genotyping arrays, mRNA sequencing, and Illumina 850k methylation arrays were performed on lung tissue of participants with IPF (234 RNA and 345 DNA samples) and non-diseased controls (188 RNA and 202 DNA samples). Measurements and Main Results: Focusing on genetic variants within 10 IPF-associated genetic loci, we identified 27 eQTLs in controls and 24 eQTLs in cases (false-discovery-rate-adjusted P < 0.05). Among these signals, we identified associations of lead variants rs35705950 with expression of MUC5B and rs2076295 with expression of DSP in both cases and controls. mQTL analysis identified CpGs in gene bodies of MUC5B (cg17589883) and DSP (cg08964675) associated with the lead variants in these two loci. We also demonstrated strong co-localization of eQTL/mQTL and genetic signal in MUC5B (rs35705950) and DSP (rs2076295). Functional validation of the mQTL in MUC5B using luciferase reporter assays demonstrates that the CpG resides within a putative internal repressor element. Conclusions: We have established a relationship of the common IPF genetic risk variants rs35705950 and rs2076295 with respective changes in MUC5B and DSP expression and methylation. These results provide additional evidence that both MUC5B and DSP are involved in the etiology of IPF.

Possibilities and promise: Leveraging advances in transcriptomics for clinical decision making in allergic diseases.

Transcriptomics has revolutionized our understanding of the pathobiologic heterogeneity underlying complex allergic diseases, leading to both the discovery of multiple inflammatory allergic disease endotypes and the development of targeted biologic therapies. In addition, transcriptomic endotypes have been associated with disease severity, exacerbation propensity, and responsiveness to nontargeted therapies, suggesting an unrealized potential for transcriptomic assays and endotyping to be used as diagnostic, predictive, and prognostic biomarkers. In this review, we discuss current and emerging transcriptomic technologies and how they have been used to uncover allergic disease endotypes and generate other clinically relevant findings. We then discuss how transcriptomics could be leveraged in the clinic for the delivery of personalized, rational patient care, and we consider strategies for and impediments to their future clinical deployment.

Refractory neutrophilic asthma and ciliary genes.

BACKGROUND: Refractory asthma (RA) remains poorly controlled, resulting in high health care utilization despite guideline-based therapies. Patients with RA manifest higher neutrophilia as a result of increased airway inflammation and subclinical infection, the underlying mechanisms of which remain unclear. OBJECTIVE: We sought to characterize and clinically correlate gene expression differences between refractory and nonrefractory (NR) asthma to uncover molecular mechanisms driving group distinctions. METHODS: Microarray gene expression of paired airway epithelial brush and endobronchial biopsy samples was compared between 60 RA and 30 NR subjects. Subjects were hierarchically clustered to identify subgroups of RA, and biochemical and clinical traits (airway inflammatory molecules, respiratory pathogens, chest imaging) were compared between groups. Weighted gene correlation network analysis was used to identify coexpressed gene modules. Module expression scores were compared between groups using linear regression, controlling for age, sex, and body mass index. RESULTS: Differential gene expression analysis showed upregulation of proneutrophilic and downregulation of ciliary function genes/pathways in RA compared to NR. A subgroup of RA with downregulated ciliary gene expression had increased levels of subclinical infections, airway neutrophilia, and eosinophilia as well as higher chest imaging mucus burden compared to other RA, the dominant differences between RA and NR. Weighted gene correlation network analysis identified gene modules related to ciliary function, which were downregulated in RA and were associated with lower pulmonary function and higher airway wall thickness/inflammation, markers of poorer asthma control. CONCLUSIONS: Identification of a novel ciliary-deficient subgroup of RA suggests that diminished mucociliary clearance may underlie repeated asthma exacerbations despite adequate treatment, necessitating further exploration of function, mechanism, and therapeutics.

Risk factors for SARS-CoV-2 infection and transmission in households with children with asthma and allergy: A prospective surveillance study.

BACKGROUND: Whether children and people with asthma and allergic diseases are at increased risk for severe acute respiratory syndrome virus 2 (SARS-CoV-2) infection is unknown. OBJECTIVE: Our aims were to determine the incidence of SARS-CoV-2 infection in households with children and to also determine whether self-reported asthma and/or other allergic diseases are associated with infection and household transmission. METHODS: For 6 months, biweekly nasal swabs and weekly surveys were conducted within 1394 households (N = 4142 participants) to identify incident SARS-CoV-2 infections from May 2020 to February 2021, which was the pandemic period largely before a vaccine and before the emergence of SARS-CoV-2 variants. Participant and household infection and household transmission probabilities were calculated by using time-to-event analyses, and factors associated with infection and transmission risk were determined by using regression analyses. RESULTS: In all, 147 households (261 participants) tested positive for SARS-CoV-2. The household SARS-CoV-2 infection probability was 25.8%; the participant infection probability was similar for children (14.0% [95% CI = 8.0%-19.6%]), teenagers (12.1% [95% CI = 8.2%-15.9%]), and adults (14.0% [95% CI = 9.5%-18.4%]). Infections were symptomatic in 24.5% of children, 41.2% of teenagers, and 62.5% of adults. Self-reported doctor-diagnosed asthma was not a risk factor for infection (adjusted hazard ratio [aHR] = 1.04 [95% CI = 0.73-1.46]), nor was upper respiratory allergy or eczema. Self-reported doctor-diagnosed food allergy was associated with lower infection risk (aHR = 0.50 [95% CI = 0.32-0.81]); higher body mass index was associated with increased infection risk (aHR per 10-point increase = 1.09 [95% CI = 1.03-1.15]). The household secondary attack rate was 57.7%. Asthma was not associated with household transmission, but transmission was lower in households with food allergy (adjusted odds ratio = 0.43 [95% CI = 0.19-0.96]; P = .04). CONCLUSION: Asthma does not increase the risk of SARS-CoV-2 infection. Food allergy is associated with lower infection risk, whereas body mass index is associated with increased infection risk. Understanding how these factors modify infection risk may offer new avenues for preventing infection.

lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models.

BACKGROUND: Studies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity. This R package contains a set of utilities to fit linear mixed effects models to transformed RNA-Seq counts that properly account for this dependence when performing statistical analyses. RESULTS: In a simulation study comparing lmerSeq and two existing methodologies that also work with transformed RNA-Seq counts, we found that lmerSeq was comprehensively better in terms of nominal error rate control and statistical power. CONCLUSIONS: Existing R packages for analyzing transformed RNA-Seq data with linear mixed models are limited in the variance structures they allow and/or the transformation methods they support. The lmerSeq package offers more flexibility in both of these areas and gave substantially better results in our simulations.

PTPα promotes fibroproliferative responses after acute lung injury.

The acute respiratory distress syndrome (ARDS) is a major healthcare problem, accounting for significant mortality and long-term disability. Approximately 25% of patients with ARDS will develop an overexuberant fibrotic response, termed fibroproliferative ARDS (FP-ARDS) that portends a poor prognosis and increased mortality. The cellular pathological processes that drive FP-ARDS remain incompletely understood. We have previously shown that the transmembrane receptor-type tyrosine phosphatase protein tyrosine phosphatase-α (PTPα) promotes pulmonary fibrosis in preclinical murine models through regulation of transforming growth factor-ß (TGF-ß) signaling. In this study, we examine the role of PTPα in the pathogenesis of FP-ARDS in a preclinical murine model of acid (HCl)-induced acute lung injury. We demonstrate that although mice genetically deficient in PTPα (Ptpra-/-) are susceptible to early HCl-induced lung injury, they exhibit markedly attenuated fibroproliferative responses. In addition, early profibrotic gene expression is reduced in lung tissue after acute lung injury in Ptpra-/- mice, and stimulation of naïve lung fibroblasts with the BAL fluid from these mice results in attenuated fibrotic outcomes compared with wild-type littermate controls. Transcriptomic analyses demonstrate reduced extracellular matrix (ECM) deposition and remodeling in mice genetically deficient in PTPα. Importantly, human lung fibroblasts modified with a CRISPR-targeted deletion of PTPRA exhibit reduced expression of profibrotic genes in response to TGF-ß stimulation, demonstrating the importance of PTPα in human lung fibroblasts. Together, these findings demonstrate that PTPα is a key regulator of fibroproliferative processes following acute lung injury and could serve as a therapeutic target for patients at risk for poor long-term outcomes in ARDS.

Combination of Mycobacterium tuberculosis RS Ratio and CFU Improves the Ability of Murine Efficacy Experiments to Distinguish between Drug Treatments.

Murine tuberculosis drug efficacy studies have historically monitored bacterial burden based on CFU of Mycobacterium tuberculosis in lung homogenate. In an alternative approach, a recently described molecular pharmacodynamic marker called the RS ratio quantifies drug effect on a fundamental cellular process, ongoing rRNA synthesis. Here, we evaluated the ability of different pharmacodynamic markers to distinguish between treatments in three BALB/c mouse experiments at two institutions. We confirmed that different pharmacodynamic markers measure distinct biological responses. We found that a combination of pharmacodynamic markers distinguishes between treatments better than any single marker. The combination of the RS ratio with CFU showed the greatest ability to recapitulate the rank order of regimen treatment-shortening activity, providing proof of concept that simultaneous assessment of pharmacodynamic markers measuring different properties will enhance insight gained from animal models and accelerate development of new combination regimens. These results suggest potential for a new era in which antimicrobial therapies are evaluated not only on culture-based measures of bacterial burden but also on molecular assays that indicate how drugs impact the physiological state of the pathogen.

A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments.

BACKGROUND: As the cost of RNA-sequencing decreases, complex study designs, including paired, longitudinal, and other correlated designs, become increasingly feasible. These studies often include multiple hypotheses and thus multiple degree of freedom tests, or tests that evaluate multiple hypotheses jointly, are often useful for filtering the gene list to a set of interesting features for further exploration while controlling the false discovery rate. Though there are several methods which have been proposed for analyzing correlated RNA-sequencing data, there has been little research evaluating and comparing the performance of multiple degree of freedom tests across methods. METHODS: We evaluated 11 different methods for modelling correlated RNA-sequencing data by performing a simulation study to compare the false discovery rate, power, and model convergence rate across several hypothesis tests and sample size scenarios. We also applied each method to a real longitudinal RNA-sequencing dataset. RESULTS: Linear mixed modelling using transformed data had the best false discovery rate control while maintaining relatively high power. However, this method had high model non-convergence, particularly at small sample sizes. No method had high power at the lowest sample size. We found a mix of conservative and anti-conservative behavior across the other methods, which was influenced by the sample size and the hypothesis being evaluated. The patterns observed in the simulation study were largely replicated in the analysis of a longitudinal study including data from intensive care unit patients experiencing cardiogenic or septic shock. CONCLUSIONS: Multiple degree of freedom testing is a valuable tool in longitudinal and other correlated RNA-sequencing experiments. Of the methods that we investigated, linear mixed modelling had the best overall combination of power and false discovery rate control. Other methods may also be appropriate in some scenarios.

Airspace Macrophages and Monocytes Exist in Transcriptionally Distinct Subsets in Healthy Adults.

Rationale: Macrophages are the most abundant immune cell in the alveoli and small airways and are traditionally viewed as a homogeneous population during health. Whether distinct subsets of airspace macrophages are present in healthy humans is unknown. Single-cell RNA sequencing allows for examination of transcriptional heterogeneity between cells and between individuals. Understanding the conserved repertoire of airspace macrophages during health is essential to understanding cellular programing during disease.Objectives: We sought to determine the transcriptional heterogeneity of human cells obtained from BAL of healthy adults.Methods: Ten subjects underwent bronchoscopy with BAL. Cells from lavage were subjected to single-cell RNA sequencing. Unique cell populations and putative functions were identified. Transcriptional profiles were compared across individuals.Measurements and Main Results: We identify two novel subgroups of resident airspace macrophages-defined by proinflammatory and metallothionein gene expression profiles. We define subsets of monocyte-like cells and compare them with peripheral blood mononuclear cells. Finally, we compare global macrophage and monocyte programing between males and females.Conclusions: Healthy human airspaces contain multiple populations of myeloid cells that are highly conserved between individuals and between sexes. Resident macrophages make up the largest population and include novel subsets defined by inflammatory and metal-binding profiles. Monocyte-like cells within the airspaces are transcriptionally aligned with circulating blood cells and include a rare population defined by expression of cell-matrix interaction genes. This study is the first to delineate the conserved heterogeneity of airspace immune cells during health and identifies two previously unrecognized macrophage subsets.

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers.

BACKGROUND: Exposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in "deployers" with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls. METHODS: Chest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings. RESULTS: Gender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m2, p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1. CONCLUSIONS: Quantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

Urine tungsten and chronic kidney disease in rural Colorado.

BACKGROUND: Chronic kidney disease (CKD) is a cause of global morbidity and mortality in agricultural communities. The San Luis Valley (SLV) is a rural agricultural community in southern Colorado with geographic and sociodemographic risk factors for CKD, including a water supply contaminated by heavy metals. METHODS: We obtained pre-existing sociodemographic, clinical, and urine trace metal data for 1659 subjects from the San Luis Valley Diabetes Study, a prospective cohort study. We assessed prospective associations between urine tungsten (W) and time-to-CKD using accelerated failure time models (n = 1659). Additionally, logistic models were used to assess relationships between urine W and renal injury markers (NGAL, KIM1) using Tobit regression (n = 816), as well as epidemiologically-defined CKD of unknown origin (CKDu) using multiple logistic regression (n = 620). RESULTS: Elevated urine W was strongly associated with decreased time-to-CKD, even after controlling for hypertension and diabetes. Depending on how CKD was defined, a doubling of urine W was associated with a 27% (95% CI 11%, 46%) to 31% (14%, 51%) higher odds of developing CKD within 5 years. The relationship between urine W and select renal injury markers was not significant, although urine NGAL was modified by diabetes status. Elevated (>95%ile) urinary W was significantly associated with CKDu (OR 5.93, 1.83, 19.21) while adjusting for known CKD risk factors. CONCLUSIONS: Our data suggest that increased exposure to W is associated with decreased time-to-CKD and may be associated with CKDu. Given persistence of associations after controlling for diabetes and hypertension, W may exert a primary effect on the kidney, although this needs to be evaluated further in future studies.

A comparison of covariate selection techniques applied to pre-exposure prophylaxis (PrEP) drug concentration data in men and transgender women at risk for HIV.

Pre-exposure prophylaxis (PrEP) containing antiretrovirals tenofovir disoproxil fumarate (TDF) or tenofovir alafenamide (TAF) can reduce the risk of acquiring HIV. Concentrations of intracellular tenofovir-diphosphate (TFV-DP) measured in dried blood spots (DBS) have been used to quantify PrEP adherence; although even under directly observed dosing, unexplained between-subject variation remains. Here, we wish to identify patient-specific factors associated with TFV-DP levels. Data from the iPrEX Open Label Extension (OLE) study were used to compare multiple covariate selection methods for determining demographic and clinical covariates most important for drug concentration estimation. To allow for the possibility of non-linear relationships between drug concentration and explanatory variables, the component selection and smoothing operator (COSSO) was implemented. We compared COSSO to LASSO, a commonly used machine learning approach, and traditional forward and backward selection. Training (N = 387) and test (N = 166) datasets were utilized to compare prediction accuracy across methods. LASSO and COSSO had the best predictive ability for the test data. Both predicted increased drug concentration with increases in age and self-reported adherence, the latter with a steeper trajectory among Asians. TFV-DP reductions were associated with increasing eGFR, hemoglobin and transgender status. COSSO also predicted lower TFV-DP with increasing weight and South American countries. COSSO identified non-linear relationships between log(TFV-DP) and adherence, weight and eGFR, with differing trajectories for some races. COSSO identified non-linear log(TFV-DP) trajectories with a subset of covariates, which may better explain variation and enhance prediction. Future research is needed to examine differences identified in trajectories by race and country.

MCMSeq: Bayesian hierarchical modeling of clustered and repeated measures RNA sequencing experiments.

BACKGROUND: As the barriers to incorporating RNA sequencing (RNA-Seq) into biomedical studies continue to decrease, the complexity and size of RNA-Seq experiments are rapidly growing. Paired, longitudinal, and other correlated designs are becoming commonplace, and these studies offer immense potential for understanding how transcriptional changes within an individual over time differ depending on treatment or environmental conditions. While several methods have been proposed for dealing with repeated measures within RNA-Seq analyses, they are either restricted to handling only paired measurements, can only test for differences between two groups, and/or have issues with maintaining nominal false positive and false discovery rates. In this work, we propose a Bayesian hierarchical negative binomial generalized linear mixed model framework that can flexibly model RNA-Seq counts from studies with arbitrarily many repeated observations, can include covariates, and also maintains nominal false positive and false discovery rates in its posterior inference. RESULTS: In simulation studies, we showed that our proposed method (MCMSeq) best combines high statistical power (i.e. sensitivity or recall) with maintenance of nominal false positive and false discovery rates compared the other available strategies, especially at the smaller sample sizes investigated. This behavior was then replicated in an application to real RNA-Seq data where MCMSeq was able to find previously reported genes associated with tuberculosis infection in a cohort with longitudinal measurements. CONCLUSIONS: Failing to account for repeated measurements when analyzing RNA-Seq experiments can result in significantly inflated false positive and false discovery rates. Of the methods we investigated, whether they model RNA-Seq counts directly or worked on transformed values, the Bayesian hierarchical model implemented in the mcmseq R package (available at https://github.com/stop-pre16/mcmseq ) best combined sensitivity and nominal error rate control.

A Bayesian natural cubic B-spline varying coefficient method for non-ignorable dropout.

BACKGROUND: Dropout is a common problem in longitudinal clinical trials and cohort studies, and is of particular concern when dropout occurs for reasons that may be related to the outcome of interest. This paper reviews common parametric models to account for dropout and introduces a Bayesian semi-parametric varying coefficient model for exponential family longitudinal data with non-ignorable dropout. METHODS: To demonstrate these methods, we present results from a simulation study and estimate the impact of drug use on longitudinal CD4 + T cell count and viral load suppression in the Women's Interagency HIV Study. Sensitivity analyses are performed to consider the impact of model assumptions on inference. We compare results between our semi-parametric method and parametric models to account for dropout, including the conditional linear model and a parametric frailty model. We also compare results to analyses that fail to account for dropout. RESULTS: In simulation studies, we show that semi-parametric methods reduce bias and mean squared error when parametric model assumptions are violated. In analyses of the Women's Interagency HIV Study data, we find important differences in estimates of changes in CD4 + T cell count over time in untreated subjects that report drug use between different models used to account for dropout. We find steeper declines over time using our semi-parametric model, which makes fewer assumptions, compared to parametric models. Failing to account for dropout or to meet parametric assumptions of models to account for dropout could lead to underestimation of the impact of hard drug use on CD4 + cell count decline in untreated subjects. In analyses of subjects that initiated highly active anti-retroviral treatment, we find that the estimated probability of viral load suppression is lower in models that account for dropout. CONCLUSIONS: Non-ignorable dropout is an important consideration when analyzing data from longitudinal clinical trials and cohort studies. While methods that account for non-ignorable dropout must make some unavoidable assumptions that cannot be verified from the observed data, many methods make additional parametric assumptions. If these assumptions are not met, inferences can be biased, making more flexible methods with minimal assumptions important.

Resequencing Study Confirms That Host Defense and Cell Senescence Gene Variants Contribute to the Risk of Idiopathic Pulmonary Fibrosis.

Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 × 10-295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence.

Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification.

INTRODUCTION: When analyzing data from large-scale genetic association studies, such as targeted or genome-wide resequencing studies, it is common to assume a single genetic model, such as dominant or additive, for all tests of association between a given genetic variant and the phenotype. However, for many variants, the chosen model will result in poor model fit and may lack statistical power due to model misspecification. OBJECTIVE: We develop power and sample size calculations for tests of gene and gene × environment interaction, allowing for misspecification of the true mode of genetic susceptibility. METHODS: The power calculations are based on a likelihood ratio test framework and are implemented in an open-source R package ("genpwr"). RESULTS: We use these methods to develop an analysis plan for a resequencing study in idiopathic pulmonary fibrosis and show that using a 2-degree of freedom test can increase power to detect recessive genetic effects while maintaining power to detect dominant and additive effects. CONCLUSIONS: Understanding the impact of model misspecification can aid in study design and developing analysis plans that maximize power to detect a range of true underlying genetic effects. In particular, these calculations help identify when a multiple degree of freedom test or other robust test of association may be advantageous.