LRRK2 regulates production of reactive oxygen species in cell and animal models of Parkinson's disease.

Oxidative stress has long been implicated in Parkinson's disease (PD) pathogenesis, although the sources and regulation of reactive oxygen species (ROS) production are poorly defined. Pathogenic mutations in the gene encoding leucine-rich repeat kinase 2 (LRRK2) are associated with increased kinase activity and a greater risk of PD. The substrates and downstream consequences of elevated LRRK2 kinase activity are still being elucidated, but overexpression of mutant LRRK2 has been associated with oxidative stress, and antioxidants reportedly mitigate LRRK2 toxicity. Here, using CRISPR-Cas9 gene-edited HEK293 cells, RAW264.7 macrophages, rat primary ventral midbrain cultures, and PD patient-derived lymphoblastoid cells, we found that elevated LRRK2 kinase activity was associated with increased ROS production and lipid peroxidation and that this was blocked by inhibitors of either LRRK2 kinase or NADPH oxidase 2 (NOX2). Oxidative stress induced by the pesticide rotenone was ameliorated by LRRK2 kinase inhibition and was absent in cells devoid of LRRK2. In a rat model of PD induced by rotenone, a LRRK2 kinase inhibitor prevented the lipid peroxidation and NOX2 activation normally seen in nigral dopaminergic neurons in this model. Mechanistically, LRRK2 kinase activity was shown to regulate phosphorylation of serine-345 in the p47phox subunit of NOX2. This, in turn, led to translocation of p47phox from the cytosol to the membrane-associated gp91phox (NOX2) subunit, activation of the NOX2 enzyme complex, and production of ROS. Thus, LRRK2 kinase activity may drive cellular ROS production in PD through the regulation of NOX2 activity.

ROBUST QUANTIFICATION OF PERCENT EMPHYSEMA ON CT VIA DOMAIN ATTENTION: THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA) LUNG STUDY.

Robust quantification of pulmonary emphysema on computed tomography (CT) remains challenging for large-scale research studies that involve scans from different scanner types and for translation to clinical scans. Although the domain shifts in different CT scanners are subtle compared to shifts existing in other modalities (e.g., MRI) or cross-modality, emphysema is highly sensitive to it. Such subtle difference limits the application of general domain adaptation methods, such as image translation-based methods, as the contrast difference is too subtle to be distinguished. Existing studies have explored several directions to tackle this challenge, including density correction, noise filtering, regression, hidden Markov measure field (HMMF) model-based segmentation, and volume-adjusted lung density. Despite some promising results, previous studies either required a tedious workflow or eliminated opportunities for downstream emphysema subtyping, limiting efficient adaptation on a large-scale study. To alleviate this dilemma, we developed an end-to-end deep learning framework based on an existing HMMF segmentation framework. We first demonstrate that a regular UNet cannot replicate the existing HMMF results because of the lack of scanner priors. We then design a novel domain attention block, a simple yet efficient cross-modal block to fuse image visual features with quantitative scanner priors (a sequence), which significantly improves the results.

Deep Learning Estimation of Small Airways Disease from Inspiratory Chest CT is Associated with FEV1 Decline in COPD.

Rationale: Quantifying functional small airways disease (fSAD) requires additional expiratory computed tomography (CT) scan, limiting clinical applicability. Artificial intelligence (AI) could enable fSAD quantification from chest CT scan at total lung capacity (TLC) alone (fSADTLC). Objectives: To evaluate an AI model for estimating fSADTLC and study its clinical associations in chronic obstructive pulmonary disease (COPD). Methods: We analyzed 2513 participants from the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS). Using a subset (n = 1055), we developed a generative model to produce virtual expiratory CTs for estimating fSADTLC in the remaining 1458 SPIROMICS participants. We compared fSADTLC with dual volume, parametric response mapping fSADPRM. We investigated univariate and multivariable associations of fSADTLC with FEV1, FEV1/FVC, six-minute walk distance (6MWD), St. George's Respiratory Questionnaire (SGRQ), and FEV1 decline. The results were validated in a subset (n = 458) from COPDGene study. Multivariable models were adjusted for age, race, sex, BMI, baseline FEV1, smoking pack years, smoking status, and percent emphysema. Measurements and Main Results: Inspiratory fSADTLC was highly correlated with fSADPRM in SPIROMICS (Pearson's R = 0.895) and COPDGene (R = 0.897) cohorts. In SPIROMICS, fSADTLC was associated with FEV1 (L) (adj.ß = -0.034, P < 0.001), FEV1/FVC (adj.ß = -0.008, P < 0.001), SGRQ (adj.ß = 0.243, P < 0.001), and FEV1 decline (mL / year) (adj.ß = -1.156, P < 0.001). fSADTLC was also associated with FEV1 (L) (adj.ß = -0.032, P < 0.001), FEV1/FVC (adj.ß = -0.007, P < 0.001), SGRQ (adj.ß = 0.190, P = 0.02), and FEV1 decline (mL / year) (adj.ß = -0.866, P = 0.001) in COPDGene. We found fSADTLC to be more repeatable than fSADPRM with intraclass correlation of 0.99 (95% CI: 0.98, 0.99) vs. 0.83 (95% CI: 0.76, 0.88). Conclusions: Inspiratory fSADTLC captures small airways disease as reliably as fSADPRM and is associated with FEV1 decline.

CT strain metrics allow for earlier diagnosis of bronchiolitis obliterans syndrome after hematopoietic cell transplant.

ABSTRACT: Bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is associated with substantial morbidity and mortality. Quantitative computed tomography (qCT) can help diagnose advanced BOS meeting National Institutes of Health (NIH) criteria (NIH-BOS) but has not been used to diagnose early, often asymptomatic BOS (early BOS), limiting the potential for early intervention and improved outcomes. Using pulmonary function tests (PFTs) to define NIH-BOS, early BOS, and mixed BOS (NIH-BOS with restrictive lung disease) in patients from 2 large cancer centers, we applied qCT to identify early BOS and distinguish between types of BOS. Patients with transient impairment or healthy lungs were included for comparison. PFTs were done at month 0, 6, and 12. Analysis was performed with association statistics, principal component analysis, conditional inference trees (CITs), and machine learning (ML) classifier models. Our cohort included 84 allogeneic HCT recipients, 66 with BOS (NIH-defined, early, or mixed) and 18 without BOS. All qCT metrics had moderate correlation with forced expiratory volume in 1 second, and each qCT metric differentiated BOS from those without BOS (non-BOS; P < .0001). CITs distinguished 94% of participants with BOS vs non-BOS, 85% of early BOS vs non-BOS, 92% of early BOS vs NIH-BOS. ML models diagnosed BOS with area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.74-0.94) and early BOS with AUC of 0.84 (95% CI, 0.69-0.97). qCT metrics can identify individuals with early BOS, paving the way for closer monitoring and earlier treatment in this vulnerable population.

Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

Background: The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. Objectives: Accordingly, with National Heart, Lung and Blood Institute support, we initiated the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. Methods/Discussion: SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global initiative for chronic Obstructive Lung Disease (GOLD) groups 0-2 or with preserved ratio-impaired spirometry; and an additional n=40 never-smoker controls. Participants undergo baseline and 3-year follow-up visits, each including high-resolution computed tomography, respiratory oscillometry and spirometry (pre- and postbronchodilator administration), exhaled breath condensate (baseline only), and extensive biospecimen collection, including sputum induction. Symptoms, interim health care utilization, and exacerbations are captured every 6 months via follow-up phone calls. An embedded bronchoscopy substudy involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. Conclusion: SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

Adrenal suppression from vamorolone and prednisone in Duchenne muscular dystrophy: results from the phase 2b clinical trial.

CONTEXT: Vamorolone, a novel "dissociative" steroid, demonstrated similar efficacy in muscle function relative to prednisone 0.75 mg/kg/day but improved linear growth and bone turnover markers in a randomized trial of pediatric Duchenne muscular dystrophy (DMD). OBJECTIVES: To determine the frequency of adrenal suppression (AS) induced by vamorolone and prednisone in pediatric DMD, and to assess cortisol thresholds using a monoclonal antibody immunoassay. METHODS: Post-hoc analysis of cortisol levels was performed on data from a randomized, double-blind, placebo- and prednisone-controlled 24-week trial of vamorolone with a 24-week crossover extension. Morning and ACTH-stimulated cortisol levels were measured using the Elecsys II immunoassay, with AS defined as a stimulated cortisol of <500nmol/L ("historical threshold") and <400nmol/L ("revised threshold"). RESULTS: Mean age at enrolment was 5.41±0.86 years (N=118). At Week 24, proportion of participants with AS using the historical and revised cortisol thresholds, respectively, were as follows: prednisone 0.75 mg/kg/day=100% (25/25) and 92.0% (23/25); vamorolone 6 mg/kg/day=95.2% (20/21) and 90.5% (19/21); vamorolone 2 mg/kg/day=84.2% (16/19) and 47.5% (9/19); and placebo=20.0% (4/20) and 0% (0/20). Morning and peak ACTH-stimulated cortisol were strongly correlated in steroid-treated boys (Spearman correlation week 48=0.83). CONCLUSIONS: AS after vamorolone and prednisone was frequent and vamorolone-associated AS appeared dose-dependent. A lower stimulated cortisol threshold may be appropriate when using a monoclonal assay. We recommend hydrocortisone for glucocorticoid stress dosing in patients receiving vamorolone.

Evaluating the role of sex-related structure-function differences on airway aerosol transport and deposition.

Several experimental studies have found that females have higher deposition of particles in the airways compared with males. This has implications for the delivery of aerosolized therapeutics and for understanding sex differences in respiratory system response to environmental exposures. This study evaluates several factors that potentially contribute to sex differences in particle deposition, using scale-specific structure-function models of 1D ventilation distribution, particle transport, and deposition. The impact of gravity, inhalation flow rate, and dead space are evaluated in 12 structure-based models (seven female; five male). Females were found to have significantly higher total, bronchial, and alveolar deposition than males across a particle size range from 0.01 to 10 . Results suggest that higher deposition fraction in females is due to higher alveolar deposition for smaller particle sizes, and higher bronchial deposition for larger particles. Females had higher alveolar deposition in the lower lobes, and slightly lower particle concentration in the left upper lobe. Males were found to be more sensitive to changes due to gravity, showing greater reduction in bronchial deposition fraction. Males were also more sensitive to change in inhalation flow rate, and to scaling of dead space due to the larger male baseline airway size. Predictions of sex differences in particle deposition - that are consistent with the literature - suggest that sex-based characteristics of lung and airway size interacting with particle size gives rise to differences in regional deposition.

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

BACKGROUND: Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed. PURPOSE: To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions. METHODS: An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD. RESULTS: Dice scores of accuracy (n = 20), reproducibility (n = 5), and generalizability (n = 12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean ± SD) 73.6 ± 6.6 years) show that males have significantly greater (p < 0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p = 0.05) at the medial half of the femoral neck than males. CONCLUSION: Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

Dysanapsis Genetic Risk Predicts Lung Function Across the Lifespan.

Rationale Dysanapsis refers to a mismatch between airway tree caliber and lung size arising early in life. Dysanapsis assessed by computed tomography (CT) is evident by early adulthood and associated with chronic obstructive pulmonary disease (COPD) risk later in life. Objective By examining the genetic factors associated with CT-assessed dysanapsis, we aimed to elucidate its molecular underpinnings and physiological significance across the lifespan. Methods We performed a genome-wide association study (GWAS) of CT-assessed dysanapsis in 11,951 adults, including individuals from two population-based and two COPD-enriched studies. We applied colocalization analysis to integrate GWAS and gene expression data from whole blood and lung. Genetic variants associated with dysanapsis were combined into a genetic risk score that was applied to examine association with lung function in children from a population-based birth cohort (n=1,278) and adults from the UK Biobank (n=369,157). Measurements and Main Results CT-assessed dysanapsis was associated with genetic variants from 21 independent signals in 19 gene regions, implicating HHIP, DSP, and NPNT as potential molecular targets based on colocalization of their expression. Higher dysanapsis genetic risk score was associated with obstructive spirometry among 5 year old children and among adults in the 5th, 6th and 7th decades of life. Conclusions CT-assessed dysanapsis is associated with variation in genes previously implicated in lung development and dysanapsis genetic risk is associated with obstructive lung function from early life through older adulthood. Dysanapsis may represent an endo-phenotype link between the genetic variations associated with lung function and COPD.

Association of Ground Glass Opacities with Systemic Inflammation and Progression of Emphysema.

RATIONAL: Ground glass opacities (GGO) in the absence of interstitial lung disease are understudied. OBJECTIVE: To assess the association of GGO with white blood cells (WBCs) and progression of quantified chest CT emphysema. METHODS: We analyzed data of participants in the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS). Chest radiologists and pulmonologists labeled regions of the lung as GGO and adaptive multiple feature method (AMFM) trained the computer to assign those labels to image voxels and quantify the volume of the lung with GGO (%GGOAMFM). We used multivariable linear regression, zero-inflated negative binomial, and proportional hazards regression models to assess the association of %GGOAMFM with WBC, changes in %emphysema, and clinical outcomes. MEASUREMENTS AND MAIN RESULTS: Among 2,714 participants, 1,680 had COPD and 1,034 had normal spirometry. Among COPD participants, based on the multivariable analysis, current smoking and chronic productive cough was associated with higher %GGOAMFM. Higher %GGOAMFM was cross-sectionally associated with higher WBCs and neutrophils levels. Higher %GGOAMFM per interquartile range at visit 1 (baseline) was associated with an increase in emphysema at one-year follow visit by 11.7% (Relative increase; 95%CI 7.5-16.1%;P<0.001). We found no association between %GGOAMFM and one-year FEV1 decline but %GGOAMFM was associated with exacerbations and all-cause mortality during a median follow-up time of 1,544 days (Interquartile Interval=1,118-2,059). Among normal spirometry participants, we found similar results except that %GGOAMFM was associated with progression to COPD at one-year follow-up. CONCLUSIONS: Our findings suggest that GGOAMFM is associated with increased systemic inflammation and emphysema progression.

15-Lipoxygenase-Mediated Lipid Peroxidation Regulates LRRK2 Kinase Activity.

Mutations in leucine-rich repeat kinase 2 (LRRK2) that increase its kinase activity are strongly linked to genetic forms of Parkinson's disease (PD). However, the regulation of endogenous wild-type (WT) LRRK2 kinase activity remains poorly understood, despite its frequent elevation in idiopathic PD (iPD) patients. Various stressors such as mitochondrial dysfunction, lysosomal dyshomeostasis, or vesicle trafficking deficits can activate WT LRRK2 kinase, but the specific molecular mechanisms are not fully understood. We found that the production of 4-hydroxynonenal (4-HNE), a lipid hydroperoxidation end-product, is a common biochemical response to these diverse stimuli. 4-HNE forms post-translational adducts with Cys2024 and Cys2025 in the kinase activation loop of WT LRRK2, significantly increasing its kinase activity. Additionally, we discovered that the 4-HNE responsible for regulating LRRK2 is generated by the action of 15-lipoxygenase (15-LO), making 15-LO an upstream regulator of the pathogenic hyperactivation of LRRK2 kinase activity. Pharmacological inhibition or genetic ablation of 15-LO prevents 4-HNE post-translational modification of LRRK2 kinase and its subsequent pathogenic hyperactivation. Therefore, 15-LO inhibitors, or methods to lower 4-HNE levels, or the targeting of Cys2024/2025 could provide new therapeutic strategies to modulate LRRK2 kinase activity and treat PD.

Increased Muc5AC and Decreased Ciliated Cells in Severe Asthma Partially Restored by Inhibition of IL-4Rα Receptor.

BACKGROUND: The role of IL-13 on the airway epithelium in severe asthma leading to airway remodeling remains poorly understood. OBJECTIVE: To study IL-13 induced airway remodeling on goblet cells and cilia in the airway epithelium in severe asthma and the impact of an anti-IL4Rα antibody, dupilumab, in vitro. METHODS: Quantitative CT (qCT) lungs and endobronchial biopsies and brushings were obtained in 51 participants (22 severe, 11 non-severe asthma and 18 healthy participants) in the Severe Asthma Research Program (SARPIII) and measured for mucin and cilia related proteins. Epithelial cells were differentiated in air-liquid interphase (ALI) with IL-13 +/-dupilumab and assessed for mucin, cilia, cilia beat frequency (CBF) and epithelial integrity (transepithelial electrical resistance, TEER). RESULTS: Increased Muc5AC (Δ+263.2±92.7 lums/EpiArea) and decreased ciliated cells (Δ-0.07±0.03 Foxj1+cells/EpiArea) were observed in biopsies from severe asthma when compared to healthy (p<0.01 and p=0.047 respectively). RNAseq of epithelial cell brushes confirmed a Muc5AC increase with a decrease in a 5-gene cilia-related mean in severe asthma compared to healthy (all p<0.05). IL-13 (5 ng/mL) differentiated ALI cultures of healthy and asthmatic (severe and non-severe participants) increased Muc5AC, decreased cilia (α-acytl-tubulin) in healthy (Δ+6.5±1.5%, Δ-14.1±2.7%; all p<0.001 respectively) and asthma (Δ+4.4±2.5%, Δ-13.1±2.7%; p=0.084, p<0.001 respectively); decreased epithelial integrity (TEER) in healthy (-140.9±21.3 [ohms], p<0.001) while decreasing CBF in asthma (Δ-4.4±1.7 [Hz], p<0.01). When dupilumab was added to ALI with IL-13, there was no significant decrease in Mu5AC but there was restoration of cilia in healthy and asthma participants (absolute increase of 67.5% and 32.5% cilia, all p<0.05 respectively) while CBF increased (Δ+3.6±1.1 [Hz], p<0.001) and TEER decreased (only in asthma Δ-37.8±16.2 [ohms] p<0.05). CONCLUSIONS: IL-13 drives features of airway remodeling in severe asthma which are partially reversed by inhibiting IL-4Rα receptor in vitro.

MSO-GP: 3-D segmentation of large and complex conjoined tree structures.

Robust segmentation of large and complex conjoined tree structures in 3-D is a major challenge in computer vision. This is particularly true in computational biology, where we often encounter large data structures in size, but few in number, which poses a hard problem for learning algorithms. We show that merging multiscale opening with geodesic path propagation, can shed new light on this classic machine vision challenge, while circumventing the learning issue by developing an unsupervised visual geometry approach (digital topology/morphometry). The novelty of the proposed MSO-GP method comes from the geodesic path propagation being guided by a skeletonization of the conjoined structure that helps to achieve robust segmentation results in a particularly challenging task in this area, that of artery-vein separation from non-contrast pulmonary computed tomography angiograms. This is an important first step in measuring vascular geometry to then diagnose pulmonary diseases and to develop image-based phenotypes. We first present proof-of-concept results on synthetic data, and then verify the performance on pig lung and human lung data with less segmentation time and user intervention needs than those of the competing methods.

LRRK2 kinase inhibition protects against Parkinson's disease-associated environmental toxicants.

Idiopathic Parkinson's disease (PD) is epidemiologically linked with exposure to toxicants such as pesticides and solvents, which comprise a wide array of chemicals that pollute our environment. While most are structurally distinct, a common cellular target for their toxicity is mitochondrial dysfunction, a key pathological trigger involved in the selective vulnerability of dopaminergic neurons. We and others have shown that environmental mitochondrial toxicants such as the pesticides rotenone and paraquat, and the organic solvent trichloroethylene (TCE) appear to be influenced by the protein LRRK2, a genetic risk factor for PD. As LRRK2 mediates vesicular trafficking and influences endolysosomal function, we postulated that LRRK2 kinase activity may inhibit the autophagic removal of toxicant damaged mitochondria, resulting in elevated oxidative stress. Conversely, we suspected that inhibition of LRRK2, which has been shown to be protective against dopaminergic neurodegeneration caused by mitochondrial toxicants, would reduce the intracellular production of reactive oxygen species (ROS) and prevent mitochondrial toxicity from inducing cell death. To do this, we tested in vitro if genetic or pharmacologic inhibition of LRRK2 (MLi2) protected against ROS caused by four toxicants associated with PD risk - rotenone, paraquat, TCE, and tetrachloroethylene (PERC). In parallel, we assessed if LRRK2 inhibition with MLi2 could protect against TCE-induced toxicity in vivo, in a follow up study from our observation that TCE elevated LRRK2 kinase activity in the nigrostriatal tract of rats prior to dopaminergic neurodegeneration. We found that LRRK2 inhibition blocked toxicant-induced ROS and promoted mitophagy in vitro, and protected against dopaminergic neurodegeneration, neuroinflammation, and mitochondrial damage caused by TCE in vivo. We also found that cells with the LRRK2 G2019S mutation displayed exacerbated levels of toxicant induced ROS, but this was ameliorated by LRRK2 inhibition with MLi2. Collectively, these data support a role for LRRK2 in toxicant-induced mitochondrial dysfunction linked to PD risk through oxidative stress and the autophagic removal of damaged mitochondria.

Island demographics and trait associations in white-tailed deer.

When a population is isolated and composed of few individuals, genetic drift is the paramount evolutionary force and results in the loss of genetic diversity. Inbreeding might also occur, resulting in genomic regions that are identical by descent, manifesting as runs of homozygosity (ROHs) and the expression of recessive traits. Likewise, the genes underlying traits of interest can be revealed by comparing fixed SNPs and divergent haplotypes between affected and unaffected individuals. Populations of white-tailed deer (Odocoileus virginianus) on islands of Saint Pierre and Miquelon (SPM, France) have high incidences of leucism and malocclusions, both considered genetic defects; on the Florida Keys islands (USA) deer exhibit smaller body sizes, a polygenic trait. Here we aimed to reconstruct island demography and identify the genes associated with these traits in a pseudo case-control design. The two island populations showed reduced levels of genomic diversity and a build-up of deleterious mutations compared to mainland deer; there was also significant genome-wide divergence in Key deer. Key deer showed higher inbreeding levels, but not longer ROHs, consistent with long-term isolation. We identified multiple trait-related genes in ROHs including LAMTOR2 which has links to pigmentation changes, and NPVF which is linked to craniofacial abnormalities. Our mixed approach of linking ROHs, fixed SNPs and haplotypes matched a high number (~50) of a-priori body size candidate genes in Key deer. This suite of biomarkers and candidate genes should prove useful for population monitoring, noting all three phenotypes show patterns consistent with a complex trait and non-Mendelian inheritance.

Chest CT-based automated vertebral fracture assessment using artificial intelligence and morphologic features.

BACKGROUND: Spinal degeneration and vertebral compression fractures are common among the elderly that adversely affect their mobility, quality of life, lung function, and mortality. Assessment of vertebral fractures in chronic obstructive pulmonary disease (COPD) is important due to the high prevalence of osteoporosis and associated vertebral fractures in COPD. PURPOSE: We present new automated methods for (1) segmentation and labelling of individual vertebrae in chest computed tomography (CT) images using deep learning (DL), multi-parametric freeze-and-grow (FG) algorithm, and separation of apparently fused vertebrae using intensity autocorrelation and (2) vertebral deformity fracture detection using computed vertebral height features and parametric computational modelling of an established protocol outlined for trained human experts. METHODS: A chest CT-based automated method was developed for quantitative deformity fracture assessment following the protocol by Genant et al. The computational method was accomplished in the following steps: (1) computation of a voxel-level vertebral body likelihood map from chest CT using a trained DL network; (2) delineation and labelling of individual vertebrae on the likelihood map using an iterative multi-parametric FG algorithm; (3) separation of apparently fused vertebrae in CT using intensity autocorrelation; (4) computation of vertebral heights using contour analysis on the central anterior-posterior (AP) plane of a vertebral body; (5) assessment of vertebral fracture status using ratio functions of vertebral heights and optimized thresholds. The method was applied to inspiratory or total lung capacity (TLC) chest scans from the multi-site Genetic Epidemiology of COPD (COPDGene) (ClinicalTrials.gov: NCT00608764) study, and the performance was examined (n = 3231). One hundred and twenty scans randomly selected from this dataset were partitioned into training (n = 80) and validation (n = 40) datasets for the DL-based vertebral body classifier. Also, generalizability of the method to low dose CT imaging (n = 236) was evaluated. RESULTS: The vertebral segmentation module achieved a Dice score of .984 as compared to manual outlining results as reference (n = 100); the segmentation performance was consistent across images with the minimum and maximum of Dice scores among images being .980 and .989, respectively. The vertebral labelling module achieved 100% accuracy (n = 100). For low dose CT, the segmentation module produced image-level minimum and maximum Dice scores of .995 and .999, respectively, as compared to standard dose CT as the reference; vertebral labelling at low dose CT was fully consistent with standard dose CT (n = 236). The fracture assessment method achieved overall accuracy, sensitivity, and specificity of 98.3%, 94.8%, and 98.5%, respectively, for 40,050 vertebrae from 3231 COPDGene participants. For generalizability experiments, fracture assessment from low dose CT was consistent with the reference standard dose CT results across all participants. CONCLUSIONS: Our CT-based automated method for vertebral fracture assessment is accurate, and it offers a feasible alternative to manual expert reading, especially for large population-based studies, where automation is important for high efficiency. Generalizability of the method to low dose CT imaging further extends the scope of application of the method, particularly since the usage of low dose CT imaging in large population-based studies has increased to reduce cumulative radiation exposure.

Air Pollution Exposure and Interstitial Lung Features in SPIROMICS Participants with Chronic Obstructive Pulmonary Disease.

Rationale: It is unknown whether air pollution is associated with radiographic features of interstitial lung disease in individuals with chronic obstructive pulmonary disease (COPD). Objectives: To determine whether air pollution increases the prevalence of interstitial lung abnormalities (ILA) or percent high-attenuation areas (HAA) on computed tomography (CT) in individuals with a heavy smoking history and COPD. Methods: We performed a cross-sectional study of SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), focused on current or former smokers with COPD. Ten-year exposure to particulate matter ⩽2.5 µm in aerodynamic diameter (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone before enrollment CT (completed between 2010 and 2015) were estimated with validated spatiotemporal models at residential addresses. We applied adjusted multivariable modified Poisson regression and linear regression to investigate associations between pollution exposure and relative risk (RR) of ILA or increased percent HAA (between -600 and -250 Hounsfield units), respectively. We assessed for effect modification by MUC5B-promoter polymorphism (variant allele carriers GT or TT vs. GG at rs3705950), smoking status, sex, and percent emphysema. Results: Among 1,272 participants with COPD assessed for HAA, 424 were current smokers, and 249 were carriers of the variant MUC5B allele. A total of 519 participants were assessed for ILA. We found no association between pollution exposure and ILA or HAA. Associations between pollutant exposures and risk of ILA were modified by the presence of MUC5B polymorphism (P value interaction term for NOx = 0.04 and PM2.5 = 0.05) and smoking status (P value interaction term for NOx = 0.05; NO2 = 0.01; and ozone = 0.05). With higher exposure to NOx and PM2.5, MUC5B variant carriers had an increased risk of ILA (RR per 26 ppb NOx, 2.41; 95% confidence interval [CI], 0.97-6.0; and RR per 4 µg ⋅ m-3 PM2.5, 1.43; 95% CI, 0.93-2.2, respectively). With higher exposure to NO2, former smokers had an increased risk of ILA (RR per 10 ppb, 1.64; 95% CI, 1.0-2.7). Conclusions: Exposure to ambient air pollution was not associated with interstitial features on CT in this population of heavy smokers with COPD. MUC5B modified the association between pollution and ILA, suggesting that gene-environment interactions may influence prevalence of interstitial lung features in COPD.