Mitofusin-2 Regulates Platelet Mitochondria and Function.

BACKGROUND: Single-nucleotide polymorphisms linked with the rs1474868 T allele (MFN2 [mitofusin-2] T/T) in the human mitochondrial fusion protein MFN2 gene are associated with reduced platelet MFN2 RNA expression and platelet counts. This study investigates the impact of MFN2 on megakaryocyte and platelet biology. METHODS: Mice with megakaryocyte/platelet deletion of Mfn2 (Mfn2-/- [Mfn2 conditional knockout]) were generated using Pf4-Cre crossed with floxed Mfn2 mice. Human megakaryocytes were generated from cord blood and platelets isolated from healthy subjects genotyped for rs1474868. Ex vivo approaches assessed mitochondrial morphology, function, and platelet activation responses. In vivo measurements included endogenous/transfused platelet life span, tail bleed time, transient middle cerebral artery occlusion, and pulmonary vascular permeability/hemorrhage following lipopolysaccharide-induced acute lung injury. RESULTS: Mitochondria was more fragmented in megakaryocytes derived from Mfn2-/- mice and from human cord blood with MFN2 T/T genotype compared with control megakaryocytes. Human resting platelets of MFN2 T/T genotype had reduced MFN2 protein, diminished mitochondrial membrane potential, and an increased rate of phosphatidylserine exposure during ex vivo culture. Platelet counts and platelet life span were reduced in Mfn2-/- mice accompanied by an increased rate of phosphatidylserine exposure in resting platelets, especially aged platelets, during ex vivo culture. Mfn2-/- also decreased platelet mitochondrial membrane potential (basal) and activated mitochondrial oxygen consumption rate, reactive oxygen species generation, calcium flux, platelet-neutrophil aggregate formation, and phosphatidylserine exposure following dual agonist activation. Ultimately, Mfn2-/- mice showed prolonged tail bleed times, decreased ischemic stroke infarct size after cerebral ischemia-reperfusion, and exacerbated pulmonary inflammatory hemorrhage following lipopolysaccharide-induced acute lung injury. Analysis of MFN2 SNPs in the iSPAAR study (Identification of SNPs Predisposing to Altered ALI Risk) identified a significant association between MFN2 and 28-day mortality in patients with acute respiratory distress syndrome. CONCLUSIONS: Mfn2 preserves mitochondrial phenotypes in megakaryocytes and platelets and influences platelet life span, function, and outcomes of stroke and lung injury.

Impact of climate change on immune responses and barrier defense.

Climate change is not just jeopardizing the health of our planet but is also increasingly affecting our immune health. There is an expanding body of evidence that climate-related exposures such as air pollution, heat, wildfires, extreme weather events, and biodiversity loss significantly disrupt the functioning of the human immune system. These exposures manifest in a broad range of stimuli, including antigens, allergens, heat stress, pollutants, microbiota changes, and other toxic substances. Such exposures pose a direct and indirect threat to our body's primary line of defense, the epithelial barrier, affecting its physical integrity and functional efficacy. Furthermore, these climate-related environmental stressors can hyperstimulate the innate immune system and influence adaptive immunity-notably, in terms of developing and preserving immune tolerance. The loss or failure of immune tolerance can instigate a wide spectrum of noncommunicable diseases such as autoimmune conditions, allergy, respiratory illnesses, metabolic diseases, obesity, and others. As new evidence unfolds, there is a need for additional research in climate change and immunology that covers diverse environments in different global settings and uses modern biologic and epidemiologic tools.

Environmental pollutants exposure-derived extracellular vesicles: crucial players in respiratory disorders.

BACKGROUND: Individual exposure to environmental pollutants, as one of the most influential drivers of respiratory disorders, has received considerable attention due to its preventability and controllability. Considering that the extracellular vesicle (EV) was an emerging intercellular communication medium, recent studies have highlighted the crucial role of environmental pollutants derived EVs (EPE-EVs) in respiratory disorders. METHODS: PubMed and Web of Science were searched from January 2018 to December 2023 for publications with key words of environmental pollutants, respiratory disorders and EVs. RESULTS: Environmental pollutants could disrupt airway intercellular communication by indirectly stimulating airway barrier cells to secrete endogenous EVs, or directly transmitting exogenous EVs, mainly by biological pollutants. Mechanistically, EPE-EVs transferred specific contents to modulate biological functions of recipient cells, to induce respiratory inflammation and impair tissue and immune function, which consequently contributed to the development of respiratory diseases, such as asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, pulmonary hypertension, lung cancer and infectious lung diseases. Clinically, EVs could emerged as promising biomarkers and biological agents for respiratory diseases attributed by their specificity, convenience, sensibility and stability. CONCLUSIONS: Further studies of EPE-EVs are helpful to understand the aetiology and pathology of respiratory diseases, and facilitate the precision respiratory medicine in risk screening, early diagnosis, clinical management and biotherapy.

Penalized deep partially linear cox models with application to CT scans of lung cancer patients.

Lung cancer is a leading cause of cancer mortality globally, highlighting the importance of understanding its mortality risks to design effective patient-centered therapies. The National Lung Screening Trial (NLST) employed computed tomography texture analysis, which provides objective measurements of texture patterns on CT scans, to quantify the mortality risks of lung cancer patients. Partially linear Cox models have gained popularity for survival analysis by dissecting the hazard function into parametric and nonparametric components, allowing for the effective incorporation of both well-established risk factors (such as age and clinical variables) and emerging risk factors (eg, image features) within a unified framework. However, when the dimension of parametric components exceeds the sample size, the task of model fitting becomes formidable, while nonparametric modeling grapples with the curse of dimensionality. We propose a novel Penalized Deep Partially Linear Cox Model (Penalized DPLC), which incorporates the smoothly clipped absolute deviation (SCAD) penalty to select important texture features and employs a deep neural network to estimate the nonparametric component of the model. We prove the convergence and asymptotic properties of the estimator and compare it to other methods through extensive simulation studies, evaluating its performance in risk prediction and feature selection. The proposed method is applied to the NLST study dataset to uncover the effects of key clinical and imaging risk factors on patients' survival. Our findings provide valuable insights into the relationship between these factors and survival outcomes.

Urine cadmium and urolithiasis: A systematic review and meta-analysis.

Exposure to cadmium may increase risk of urolithiasis, but the results remain inconclusive. This systematic review and meta-analysis aimed to access the association between cadmium exposure and urolithiasis. We searched Medline/PubMed, Embase, Web of Science Core Collection, and Cochrane Central for studies. The primary outcome was the incidence of urolithiasis compared to reference groups. We used relative risk as the summary effect measure. This meta-analysis included eight observational studies and divided into 39 study populations. Among 63,051 subjects, 5018 (7.96%) individuals had urolithiasis. The results indicated that people with an increment of 0.1 µg/g creatinine in urinary cadmium had a 2% increased risk of urolithiasis (pooled relative risk [RR], 1.02; 95% confidence interval [CI], 1.01-1.03) and there is no difference in the risk of urolithiasis in high and low cadmium exposure levels. Meanwhile, people with an increment of 0.1 µg/L in urinary cadmium had a 4% increased risk of urolithiasis (pooled RR, 1.04; 95% CI, 1.02-1.07). Our findings also showed similar associations in both sex, different region (Sweden, China, and Thailand), general and occupational population. The results indicate that cadmium exposure was significantly associated with an elevated risk of urolithiasis. Therefore, it is imperative to take steps to minimize cadmium exposure.

Maternal arsenic exposure modifies associations between arsenic, folate and arsenic metabolism gene variants, and spina bifida risk: A case‒control study in Bangladesh.

BACKGROUND: Spina bifida is a type of neural tube defect (NTD); NTDs are developmental malformations of the spinal cord that result from failure of neural tube closure during embryogenesis and are likely caused by interactions between genetic and environmental factors. Arsenic induces NTDs in animal models, and studies demonstrate that mice with genetic defects related to folate metabolism are more susceptible to arsenic's effects. We sought to determine whether 25 single-nucleotide polymorphisms (SNPs) in genes involved in folate and arsenic metabolism modified the associations between maternal arsenic exposure and risk of spina bifida (a common NTD) among a hospital-based case-control study population in Bangladesh. METHODS: We used data from 262 mothers and 220 infants who participated in a case‒control study at the National Institutes of Neurosciences & Hospital and Dhaka Shishu Hospital in Dhaka, Bangladesh. Neurosurgeons assessed infants using physical examinations, review of imaging, and we collected histories using questionnaires. We assessed arsenic from mothers' toenails using inductively coupled plasma mass spectrometry (ICP-MS), and we genotyped participants using the Illumina Global Screening Array v1.0. We chose candidate genes and SNPs through a review of the literature. We assessed SNP-environment interactions using interaction terms and stratified models, and we assessed gene-environment interactions using interaction sequence/SNP-set kernel association tests (iSKAT). RESULTS: The median toenail arsenic concentration was 0.42 µg/g (interquartile range [IQR]: 0.27-0.86) among mothers of cases and 0.47 µg/g (IQR: 0.30-0.97) among mothers of controls. We found an two SNPs in the infants' AS3MT gene (rs11191454 and rs7085104) and one SNP in mothers' DNMT1 gene (rs2228611) were associated with increased odds of spina bifida in the setting of high arsenic exposure (rs11191454, OR 3.01, 95% CI: 1.28-7.09; rs7085104, OR 2.33, 95% CI: 1.20-4.and rs2228611, OR 2.11, 95% CI: 1.11-4.01), along with significant SNP-arsenic interactions. iSKAT analyses revealed significant interactions between mothers' toenail concentrations and infants' AS3MT and MTR genes (p = 0.02), and mothers' CBS gene (p = 0.05). CONCLUSIONS: Our results support the hypothesis that arsenic increases spina bifida risk via interactions with folate and arsenic metabolic pathways and suggests that individuals in the population who have certain genetic polymorphisms in genes involved with arsenic and folate metabolism may be more susceptible than others to the arsenic teratogenicity.

Arsenic modifies the effect of folic acid in spina bifida prevention, a large hospital-based case-control study in Bangladesh.

BACKGROUND: Spina bifida, a developmental malformation of the spinal cord, is associated with high rates of mortality and disability. Although folic acid-based preventive strategies have been successful in reducing rates of spina bifida, some areas continue to be at higher risk because of chemical exposures. Bangladesh has high arsenic exposures through contaminated drinking water and high rates of spina bifida. This study examines the relationships between mother's arsenic exposure, folic acid, and spina bifida risk in Bangladesh. METHODS: We conducted a hospital-based case-control study at the National Institute of Neurosciences & Hospital (NINS&H) in Dhaka, Bangladesh, between December 2016 and December 2022. Cases were infants under age one year with spina bifida and further classified by a neurosurgeon and imaging. Controls were drawn from children seen at NINS&H and nearby Dhaka Shishu Hospital. Mothers reported folic acid use during pregnancy, and we assessed folate status with serum assays. Arsenic exposure was estimated in drinking water using graphite furnace atomic absorption spectrophotometry (GF-AAS) and in toenails using inductively coupled plasma mass spectrometry (ICP-MS). We used logistic regression to examine the associations between arsenic and spina bifida. We used stratified models to examine the associations between folic acid and spina bifida at different levels of arsenic exposure. RESULTS: We evaluated data from 294 cases of spina bifida and 163 controls. We did not find a main effect of mother's arsenic exposure on spina bifida risk. However, in stratified analyses, folic acid use was associated with lower odds of spina bifida (adjusted odds ratio [OR]: 0.50, 95% confidence interval [CI]: 0.25-1.00, p = 0.05) among women with toenail arsenic concentrations below the median value of 0.46 µg/g, and no association was seen among mothers with toenail arsenic concentrations higher than 0.46 µg/g (adjusted OR: 1.09, 95% CI: 0.52-2.29, p = 0.82). CONCLUSIONS: Mother's arsenic exposure modified the protective association of folic acid with spina bifida. Increased surveillance and additional preventive strategies, such as folic acid fortification and reduction of arsenic, are needed in areas of high arsenic exposure.

Review on novel toxicological effects and personalized health hazard in workers exposed to low doses of benzene.

Several recent reports indicate health hazards for workers with below occupational limit exposure to benzene (BZ). Our updated review indicates that such low exposures induced traditional as well as novel toxicity/genotoxicity, e.g., increased mitochondria copy numbers, prolongation of telomeres, impairment of DNA damage repair response (DDRR), perturbations of expression in non-coding RNAs, and epigenetic changes. These abnormalities were associated with alterations of gene expression and cellular signaling pathways which affected hematopoietic cell development, expression of apoptosis, autophagy, etc. The overarching mechanisms for induction of health risk are impaired DDRR, inhibition of tumor suppressor genes, and changes of MDM2-p53 axis activities that contribute to perturbed control for cancer pathways. Evaluation of the unusual dose-responses to BZ exposure indicates cellular over-compensation and reprogramming to overcome toxicity and to promote survival. However, these abnormal mechanisms also promote the induction of leukemia. Further investigations indicate that the current exposure limits for workers to BZ are unacceptable. Based on these studies, the new exposure limits should be less than 0.07 ppm rather than the current 1 ppm. This review also emphasizes the need to conduct appropriate bioassays, and to provide more reliable decisions on health hazards as well as on exposure limits for workers. In addition, it is important to use scientific data to provide significantly improved risk assessment, i.e., shifting from a population- to an individual-based risk assessment.

Vaping habits and respiratory symptoms using a smartphone app platform.

BACKGROUND: Widespread use of e-cigarette (EC) or vaping products causes respiratory disorders including the nationwide outbreak of e-cigarette or vaping product use-associated lung injury (EVALI) in 2019. Chronic adverse health effects are now being reported as well. To address this important public health issue, an innovative approach of epidemic control and epidemiologic study is required. We aimed to assess the association between short-term and long-term use of EC products and respiratory health in adults using smartphone app data. METHODS: A population-based, repeated measures, longitudinal smartphone app study that performed 8-day survey participation over 60 days for each participant from August 2020 to March 2021, including 306 participants aged 21 years and older in the US. The participants were asked to complete the respiratory health questionnaire daily, weekly, and monthly on their smartphone app. We analyzed the association between vaping habits and respiratory health using generalized linear mixed models (GLMMs). RESULTS: EC use in the previous 7 days was associated with frequent cough (OR: 5.15, 95% CI: 2.18, 12.21), chronic cough (OR: 3.92, 95% CI: 1.62, 9.45), frequent phlegm (OR: 3.99, 95% CI: 1.44, 11.10), chronic phlegm (OR: 3.55, 95% CI: 1.41, 8.96), episodes of cough and phlegm (OR: 4.68, 95% CI: 1.94, 11.28), mMRC grade 3-4 dyspnea (OR: 3.32, 95% CI: 1.35 to 8.13), chest cold (OR: 3.07, 95% CI: 1.29, 7.33), eye irritation (OR: 2.94, 95% CI: 1.34, 6.47) and nose irritation (OR : 2.02, 95% CI: 0.95, 4.30). Relatively long-term effects of the past 90 days EC use was associated with an increased risk of wheeze (OR: 3.04, 95% CI: 1.31, 7.03), wheeze attack (OR: 2.78, 95% CI: 1.07, 7.24), mMRC grade 3-4 dyspnea (OR: 2.54, 9% CI: 1.05 to 6.18), eye irritation (OR: 3.16, 95% CI: 1.49, 6.68), and eye irritation during the past month (OR: 3.50, 95% CI: 1.52, 8.04). CONCLUSIONS: In this smartphone app-based repeated measures study, short-term and relatively long-term use of EC increased the risk of respiratory symptoms.

Novel trace elements detected in multiple stages of pregnancy impact neonatal birth weight by affecting gestational age.

Prenatal exposure to elements may be associated with birth weight via shortening of gestation. This study aimed to determine if prenatal exposure is associated with birth weight, and to explore the potential mediating role of gestational age in the association. Within an established Bangladesh prospective birth cohort (2008-2011), we analyzed the concentrations of 15 elements in maternal serum samples collected during the first (n = 780) and second (n = 610) trimesters using inductively coupled plasma mass spectrometry. Mediation analyses explored the relationships between these elements, gestational age, and birth weight. Serum concentrations of cobalt (Co) (first trimester: b = 56.5; 95% confidence interval [CI]: 13.5-99.0; false discovery rate [FDR]-q = 0.035; second trimester: b = 73.3; 95% CI: 20.4-130.2; FDR-q = 0.037) and antimony (Sb) in both trimesters (first trimester:b = 92.1; 95% CI: 66.0-118.9; FDR-q < 0.001; second trimester: b = 93.3; 95% CI: 67.3-118.4; FDR-q < 0.001), and strontium (Sr) in the first trimester (b = 142.4; 95% CI: 41.6-247.9; FDR-q = 0.035) were positively associated with birth weight, while negative associations were observed for barium (Ba) (first trimester: b = -154.8; 95% CI: -217.9 to 91.8; FDR-q <0.001; second trimester: b = -26.7; 95% CI: -44.9 to 10.2; FDR-q < 0.001). These elements act partially by affecting gestation age and appear to have heightened impact among smaller infants. Further research is needed to determine the biological underpinnings of these effects, which may inform strategies to avert low birth weight.

Lung cancer in patients who have never smoked - an emerging disease.

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

Lung cancer clustering by identification of similarities and discrepancies of DNA copy numbers using maximal information coefficient.

Lung cancer is the second most diagnosed cancer and the first cause of cancer related death for men and women in the United States. Early detection is essential as patient survival is not optimal and recurrence rate is high. Copy number (CN) changes in cancer populations have been broadly investigated to identify CN gains and deletions associated with the cancer. In this research, the similarities between cancer and paired peripheral blood samples are identified using maximal information coefficient (MIC) and the spatial locations with substantially high MIC scores in each chromosome are used for clustering analysis. The results showed that a sizable reduction of feature set can be obtained using only a subset of locations with high MIC values. The clustering performance was evaluated using both true rate and normalized mutual information (NMI). Clustering results using the reduced feature set outperformed the performance of clustering using entire feature set in several chromosomes that are highly associated with lung cancer with several identified oncogenes.

Serial platelet count as a dynamic prediction marker of hospital mortality among septic patients.

Background: Platelets play a critical role in hemostasis and inflammatory diseases. Low platelet count and activity have been reported to be associated with unfavorable prognosis. This study aims to explore the relationship between dynamics in platelet count and in-hospital morality among septic patients and to provide real-time updates on mortality risk to achieve dynamic prediction. Methods: We conducted a multi-cohort, retrospective, observational study that encompasses data on septic patients in the eICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The joint latent class model (JLCM) was utilized to identify heterogenous platelet count trajectories over time among septic patients. We assessed the association between different trajectory patterns and 28-day in-hospital mortality using a piecewise Cox hazard model within each trajectory. We evaluated the performance of our dynamic prediction model through area under the receiver operating characteristic curve, concordance index (C-index), accuracy, sensitivity, and specificity calculated at predefined time points. Results: Four subgroups of platelet count trajectories were identified that correspond to distinct in-hospital mortality risk. Including platelet count did not significantly enhance prediction accuracy at early stages (day 1 C-indexDynamic  vs C-indexWeibull: 0.713 vs 0.714). However, our model showed superior performance to the static survival model over time (day 14 C-indexDynamic  vs C-indexWeibull: 0.644 vs 0.617). Conclusions: For septic patients in an intensive care unit, the rapid decline in platelet counts is a critical prognostic factor, and serial platelet measures are associated with prognosis.

Potentially functional variants of INPP5D and EXOSC3 in immunity B cell-related genes are associated with non-small cell lung cancer survival.

B cells are adaptive immune cells in the tumor microenvironment and play an important role in tumor development and metastasis. However, the roles of genetic variants of the immunity B cell-related genes in the survival of patients with non-small cell lung cancer (NSCLC) remain unknown. In the present study, we first evaluated associations between 10,776 single nucleotide polymorphisms (SNPs) in 220 immunity B cell-related genes and survival of NSCLC in a discovery dataset of 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. We found that 369 SNPs were significantly associated with overall survival (OS) of NSCLC in multivariable Cox proportional hazards regression analysis (P ≤ 0.05, Bayesian false discovery probability ≤ 0.80), of which 18 SNPs were validated in another independent genotyping dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. We then performed linkage disequilibrium (LD) analysis, followed by stepwise analysis with a multivariable Cox regression model. Finally, two independent SNPs, inositol polyphosphate-5-phosphatase D (INPP5D) rs13385922 C>T and exosome component 3 (EXOSC3) rs3208406 A>G, remained significantly associated withNSCLC OS with a combined hazards ratio (HR) of 1.14 (95% confidence interval = 1.06-1.23, P = 2.41×10-4) and 1.20 (95% confidence interval = 1.14-1.28, P = 3.41×10-9), respectively. Furthermore, NSCLC patients with the combination of unfavorable genotypes for these two SNPs were associated with a poor OS (P trend = 0.0002) and disease-specific survival (DSS, P trend < 0.0001) in the PLCO dataset. Expression quantitative trait loci (eQTL) analysis suggested that the INPP5D rs6782875 T allele was significantly correlated with elevated INPP5D mRNA expression levels in normal lung tissues and whole blood samples, while the EXOSC3 rs3208406 G allele was significantly correlated with increased EXOSC3 mRNA expression levels in normal lung tissues. Our data indicated that genetic variants in these immunity B cell-related genes may predict NSCLC survival possibly by influencing the gene expression.

Potentially functional variants of ERRFI1 in hypoxia-related genes predict survival of non-small cell lung cancer patients.

BACKGROUND: Hypoxia is often involved in tumor microenvironment, and the hypoxia-induced signaling pathways play a key role in aggressive cancer phenotypes, including angiogenesis, immune evasion, and therapy resistance. However, it is unknown what role genetic variants in the hypoxia-related genes play in survival of patients with non-small cell lung cancer (NSCLC). METHODS: We evaluated the associations between 16,092 single-nucleotide polymorphisms (SNPs) in 182 hypoxia-related genes and survival outcomes of NSCLC patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were used as the discovery dataset, and the Harvard Lung Cancer Susceptibility (HLCS) Study served as the replication dataset. We also performed additional linkage disequilibrium analysis and a stepwise multivariable Cox proportional hazards regression analysis in the PLCO dataset. RESULTS: An independent SNP, ERRFI1 rs28624 A > C, was identified with an adjusted hazards ratio (HR) of 1.31 (95% CI = 1.14-1.51, p = 0.0001) for overall survival (OS). In further analyses, unfavorable genotypes AC and CC, compared with the AA genotype, were associated a worse OS (HR = 1.20, 95% CI = 1.03-1.39, p = 0.014) and disease-specific survival (HR = 1.21, 95% CI = 1.04-1.42, p = 0.016). Further expression quantitative trait loci analysis indicated that ERRFI1 rs28624C genotypes were significantly associated with higher ERRFI1 mRNA expression levels in the whole blood. Additional analysis showed that high ERRFI1 mRNA expression levels were associated with a worse OS in patients with lung adenocarcinoma. CONCLUSION: Our findings suggest that genetic variants in the hypoxia-related gene ERRFI1 may modulate NSCLC survival, potentially through their effect on the gene expression.

Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients. Our collaborative efforts with Michigan Medicine in monitoring patient outcomes within the ICU have motivated us to investigate the potential advantages of incorporating clinical information and chest X-ray images for predicting patient outcomes. We propose an analytical workflow to address challenges such as the absence of standardized approaches for image pre-processing and data utilization. We then propose an ensemble learning approach designed to maximize the information derived from multiple prediction algorithms. This entails optimizing the weights within the ensemble and considering the common variability present in individual risk scores. Our simulations demonstrate the superior performance of this weighted ensemble averaging approach across various scenarios. We apply this refined ensemble methodology to analyze post-ICU COVID-19 mortality, an occurrence observed in 21% of COVID-19 patients admitted to the ICU at Michigan Medicine. Our findings reveal substantial performance improvement when incorporating imaging data compared to models trained solely on clinical risk factors. Furthermore, the addition of radiomic features yields even larger enhancements, particularly among older and more medically compromised patients. These results may carry implications for enhancing patient outcomes in similar clinical contexts.

A cross-trait study of lung cancer and its related respiratory diseases based on large-scale exome sequencing population.

Background: Genome-wide association studies (GWASs) explain the genetic susceptibility between diseases and common variants. Nevertheless, with the appearance of large-scale sequencing profiles, we could explore the rare coding variants in disease pathogenesis. Methods: We estimated the genetic correlation of nine respiratory diseases and lung cancer in the UK Biobank (UKB) by linkage disequilibrium score regression (LDSC). Then, we performed exome-wide association studies at single-variant level and gene-level for lung cancer and lung cancer-related respiratory diseases using the whole-exome sequencing (WES) data of 427,934 European participants. Cross-trait meta-analysis was conducted by association analysis based on subsets (ASSET) to identify the pleiotropic variants, while in-silico functional analysis was performed to explore their function. Causal mediation analysis was used to explore whether these pleiotropic variants lead to lung cancer is mediated by affecting the chronic respiratory diseases. Results: Five respiratory diseases [emphysema, pneumonia, asthma, chronic obstructive pulmonary disease (COPD), and fibrosis] were genetically correlated with lung cancer. We identified 102 significant independent variants at single-variant levels for lung cancer and five lung cancer-related diseases. 15:78590583:G>A (missense variant in CHRNA5) was shared in lung cancer, emphysema, and COPD. Meanwhile, 14 significant genes and 87 suggestive genes were identified in gene-based association tests, including HSD3B7 (lung cancer), SRSF2 (pneumonia), TNXB (asthma), TERT (fibrosis), MOSPD3 (emphysema). Based on the cross-trait meta-analysis, we detected 145 independent pleiotropic variants. We further identified abundant pathways with significant enrichment effects, demonstrating that these pleiotropic genes were functional. Meanwhile, the proportion of mediation effects of these variants ranged from 6 to 23 (emphysema: 23%; COPD: 20%; pneumonia: 20%; fibrosis: 7%; asthma: 6%) through these five respiratory diseases to the incidence of lung cancer. Conclusions: The identified shared genetic variants, genes, biological pathways, and potential intermediate causal pathways provide a basis for further exploration of the relationship between lung cancer and respiratory diseases.

Genome-wide analysis of spina bifida risk variants in a case-control study from Bangladesh.

BACKGROUND: Human studies of genetic risk factors for neural tube defects, severe birth defects associated with long-term health consequences in surviving children, have predominantly been restricted to a subset of candidate genes in specific biological pathways including folate metabolism. METHODS: In this study, we investigated the association of genetic variants spanning the genome with risk of spina bifida (i.e., myelomeningocele and meningocele) in a subset of families enrolled from December 2016 through December 2022 in a case-control study in Bangladesh, a population often underrepresented in genetic studies. Saliva DNA samples were analyzed using the Illumina Global Screening Array. We performed genetic association analyses to compare allele frequencies between 112 case and 121 control children, 272 mothers, and 128 trios. RESULTS: In the transmission disequilibrium test analyses with trios only, we identified three novel exonic spina bifida risk loci, including rs140199800 (SULT1C2, p = 1.9 × 10-7), rs45580033 (ASB2, p = 4.2 × 10-10), and rs75426652 (LHPP, p = 7.2 × 10-14), after adjusting for multiple hypothesis testing. Association analyses comparing cases and controls, as well as models that included their mothers, did not identify genome-wide significant variants. CONCLUSIONS: This study identified three novel single nucleotide polymorphisms involved in biological pathways not previously associated with neural tube defects. The study warrants replication in larger groups to validate findings and to inform targeted prevention strategies.

Proteome-wide Mendelian randomization identifies causal plasma proteins in lung cancer.

Plasma proteins are promising biomarkers and potential drug targets in lung cancer. To evaluate the causal association between plasma proteins and lung cancer, we performed proteome-wide Mendelian randomization meta-analysis (PW-MR-meta) based on lung cancer genome-wide association studies (GWASs), protein quantitative trait loci (pQTLs) of 4,719 plasma proteins in deCODE and 4,775 in Fenland. Further, causal-protein risk score (CPRS) was developed based on causal proteins and validated in the UK Biobank. 270 plasma proteins were identified using PW-MR meta-analysis, including 39 robust causal proteins (both FDR-q < 0.05) and 78 moderate causal proteins (FDR-q < 0.05 in one and p < 0.05 in another). The CPRS had satisfactory performance in risk stratification for lung cancer (top 10% CPRS:Hazard ratio (HR) (95%CI):4.33(2.65-7.06)). The CPRS [AUC (95%CI): 65.93 (62.91-68.78)] outperformed the traditional polygenic risk score (PRS) [AUC (95%CI): 55.71(52.67-58.59)]. Our findings offer further insight into the genetic architecture of plasma proteins for lung cancer susceptibility.