Coronary artery disease (CAD) is the leading cause of death in both developed and developing nations. The objective of this study was to identify risk factors for coronary artery disease through machine-learning and assess this methodology. A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. Univariate logistic models, with CAD as the outcome, were used to identify covariates that were associated with CAD. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the Cover statistic to identify risk factors for CAD. Shapely Additive Explanations (SHAP) explanations were utilized to visualize the relationship between these potential risk factors and CAD. Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51%) were female, 2,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of other race. A total of 338 (4.5%) of patients had coronary artery disease. These were fitted into the XGBoost model and an AUROC = 0.89, Sensitivity = 0.85, Specificity = 0.87 were observed (Fig 1). The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were age (Cover = 21.1%), Platelet count (Cover = 5.1%), family history of heart disease (Cover = 4.8%), and Total Cholesterol (Cover = 4.1%). Machine learning models can effectively predict coronary artery disease using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.

Use of machine learning to identify risk factors for coronary artery disease

Association between whole blood essential trace elements and cognitive function in older adults.

Long-term exposure to cadmium-polluted environments may lead to shortened leukocyte telomere length and cognitive decline. This study aims to investigate (1) the associations among blood cadmium levels, leukocyte telomere length, and cognitive function, and (2) the mediating role of leukocyte telomere length between blood cadmium levels and cognitive function among older adults in the United States.Using data from the National Health and Nutrition Examination Survey (NHANES) 1999-2002. Cadmium exposure level was assessed by measuring cadmium levels in blood samples. Leukocyte telomere length was measured by quantitative polymerase chain reaction, and cognitive function was measured by the digit symbol substitution test (DSST).A total of 2185 older adults aged over 60 were included in this study, comprising 1109 (49.65%) males. Elevated blood cadmium levels were significantly associated with the risk of a decline in cognitive function (β = - 2.842, p = 0.018). Shorter leukocyte telomere lengths were significantly associated with a higher risk of a decline in cognitive function (β = 4.144, p = 0.020). The total indirect effect on the blood cadmium level and cognitive function via leukocyte telomere length was - 0.218 (p = 0.012). The mediation effect was estimated to be 0.218/2.084 × 100% = 10.46%.The findings suggest that cadmium exposure may increase the risk of cognitive impairment by causing shortened leukocyte telomere length. 

Leukocyte telomere length mediates the association between cadmium exposure and cognitive function in US older adults

Relatively little is known about the immediate and prospective neurodevelopmental impacts of joint exposure to multiple metals (i.e., metal mixtures) in early childhood.To estimate associations of early childhood (∼3 years of age) blood metal concentrations with cognitive test scores at early and mid-childhood (∼8 years of age).We studied children from the Project Viva cohort. We measured erythrocyte concentrations of seven essential (Co, Cu, Mg, Mn, Mo, Se, and Zn) and eight non-essential metals (As, Ba, Cd, Cs, Hg, Pb, Sn, and Sr) in early childhood blood samples. Trained research assistants administered cognitive tests assessing vocabulary, visual-motor ability, memory, and general intelligence (standard deviations: ∼10 points), in early and mid-childhood. We employed multivariable linear regression to examine associations of individual metals with test scores adjusting for confounders, other concurrently measured metals, and first-trimester maternal blood metals. We also estimated joint associations and explored interaction between metals in mixture analyses.We analyzed 349 children (median whole blood Pb ∼1 μg/dL). In cross-sectional analyses, each doubling of Pb was associated with lower visual-motor function (mean difference: -2.43 points, 95% confidence interval (CI): -4.01, -0.86) and receptive vocabulary, i.e., words understood (-1.45 points, 95% CI: -3.26, 0.36). Associations of Pb with mid-childhood cognition were weaker and less precise by comparison. Mg was positively associated with cognition in cross-sectional but not prospective analyses, and cross-sectional associations were attenuated in a sensitivity analysis removing adjustment for concurrent metals. We did not observe joint associations nor interactions.In this cohort with low blood Pb levels, increased blood Pb was robustly associated with lower cognitive ability in cross-sectional analyses, even after adjustment for prenatal Pb exposure, and regardless of adjustment for metal co-exposures. However, associations with mid-childhood cognition were attenuated and imprecise, suggesting some buffering of Pb neurotoxicity in early life.Relatively few studies have comprehensively separated the effects of neurotoxic metals such as lead (Pb) from pre- and postnatal co-occurring metals, nor examined persistence of associations across childhood. In a cohort of middle-class children, we found higher early childhood (∼3 y) blood Pb was associated with lower scores on cognitive tests, independent of other metals and prenatal blood Pb. However, early childhood Pb was only weakly associated with cognition in mid-childhood (∼8 y). Our results suggest the effects of low-level Pb exposure may attenuate over time in some populations, implying the presence of factors that may buffer Pb neurotoxicity in early life. 

Cross-sectional and prospective associations of early childhood circulating metals with early and mid-childhood cognition in the project viva cohort.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein–protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Background Epidemiological evidence on Urine metals and cognitive impairment in older individuals is sparse and limited. The goal of this study was to analyze if there was a link between urinary metal levels and cognitive performance in U.S. people aged 60 and up. Methods The National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2014 were utilized in this cross-sectional analysis. Memory function was quantified using the following methods: Established Consortium for Word Learning in Alzheimer's Disease (CERAD-WL) (immediate learning and recall and delayed recall), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). An inductively coupled plasma mass spectrometry (ICP-MS) was used to estimate urine metal concentrations. The connection of Urine metals level with cognitive function was investigated employing binary logistic regression and restricted cubic spline models. Results A total of 840 participants aged 60 years and over were enrolled in this study. After controlling for confounders, the association between cadmium, barium, cobalt, cesium, manganese, and thallium and poor cognitive performance showed significance in multiple logistic regression compared to the lowest quartile of metals. In the DSST test, the weighted multivariate adjusted ORs (95% CI) for cadmium in the highest quartile, barium and cesium in the third quartile were 2.444 (1.310–4.560), 0.412 (0.180–0.942) and 0.440 (0.198–0.979), respectively. There were L-shaped associations between urine cesium, barium, or manganese and low cognitive performance in DSST. Urine lead, molybdenum and uranium did not show any significant relationships with cognitive impairment, respectively, compared to the respective lowest quartile concentrations. Conclusion The levels of barium (Ba), cobalt (Co), cesium (Cs), manganese (Mn), and thallium (Tl) in urine were found to be negatively related to the prevalence of impaired cognitive performance in our cross-sectional investigation. Higher cadmium (Cd) levels were associated with cognitive impairment.

/pdf/relationships-between-urinary-metals-concentrations-and-k52rpk90.pdf

Relationships between urinary metals concentrations and cognitive performance among U.S. older people in NHANES 2011–2014

BACKGROUND
Lung adenocarcinoma (LUAD) is one of the most common pathological types of lung cancer. The gene Chloride Intracellular Channel 5 (CLIC5) has an important role in neurophysiology, cardiovascular biology, and tumour biology. Here, we explored the prognostic value and immune infiltration of CLIC5 expression in LUAD patients.


METHODS
We extracted transcriptional LUAD data from The Cancer Genome Atlas (TCGA) and the University of Alabama Cancer Database to explore CLIC5 expression profiles and their relation to CLIC5 and clinicopathological parameters. The relationship between CLIC5 and survival time was explored using Kaplan-Meier Plotter. Then, we integrated the data from TCGA and the Gene Expression Omnibus (GEO) database to perform univariate and multivariate Cox regression. We performed CLIC5 immunohistochemical staining on 167 lung adenocarcinoma samples for further verification. In addition, we analysed the Gene Ontology (GO) database, Kyoto Encyclopaedia of Genes and Genomes pathways and network analysis of protein-protein interactions in lung tissue, to explore the potential mechanism of CLIC5. To analyse the correlation between immune infiltration and CLIC5 expression, we first compared the expression of immune cells in tumour tissues and normal tissues based on the TCGA and GEO databases. We found 51 immunomodulators related to CLIC5 and structured their enrichment pathways as well as those of 50 correlated genes. We used a Cox regression model to identify multiple-gene risk prediction signatures. Finally, we assessed the prognostic accuracy of the risk scores via receiver operating characteristic curves.


RESULTS
CLIC5 expression levels were significantly lower in LUAD tissue than in normal tissue. Lower CLIC5 expression was negatively correlated to the overall survival of LUAD patients based on survival analysis. We identified CLIC5 as an independent prognosis predictor. Functional network analysis suggested that CLIC5 is related to multiple pathways. CLIC5 expression is closely related to infiltration levels of many immune cells and immune marker sets in LUAD patients. Furthermore, the risk score based on immunomodulators related to CLIC5 was an independent prognosis predictor in the TCGA lung cohorts.


CONCLUSION
Our findings suggest that CLIC5 is a promising molecular marker for the prognosis and immune infiltration of LUAD patients.

Identification of CLIC5 as a Prognostic Biomarker and Correlated Immunomodulator for Lung Adenocarcinoma.

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Relationships between urinary metals concentrations and cognitive performance among U.S. older people in NHANES 2011–2014

Identification of CLIC5 as a Prognostic Biomarker and Correlated Immunomodulator for Lung Adenocarcinoma.