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Hypertension (Dallas, Tex. : 1979) Dec 2023
Topics: Adult; Humans; United States; Nutrition Surveys; Hypertension; Risk Factors; Renal Insufficiency, Chronic
PubMed: 37967159
DOI: 10.1161/HYPERTENSIONAHA.123.21996 -
Cureus Feb 2024Extended wrist rotation provides a simple clinical measure of rigidity in movement disorders. The supinator-pronator muscles of the forearm form an agonist-antagonist...
Extended wrist rotation provides a simple clinical measure of rigidity in movement disorders. The supinator-pronator muscles of the forearm form an agonist-antagonist pair that can be isolated for diagnosis and monitoring. Patients rarely can isolate these muscles without extraordinary training and body awareness. Clinicians may find documenting the impact of the shoulder girdle, wrist, and hand movements overburdensome. A preliminary study shows that restricting the olecranon and keeping the wrist in line with the hand can provide a simple, reproducible measure of rigidity. We study a two-handed "handshake" examination and the use of a pulley-based goniometer. This preliminary analysis indicates that both offer the same observer and between-observer reliability. Two-way analysis of variance showed no statistical differences or outliers.
PubMed: 38371435
DOI: 10.7759/cureus.54319 -
BMC Medical Genomics Nov 2023Altered interleukin (IL)-18 levels are associated with immune-mediated inflammatory diseases (IMIDs), but no studies have investigated their causal relationship. This...
BACKGROUND
Altered interleukin (IL)-18 levels are associated with immune-mediated inflammatory diseases (IMIDs), but no studies have investigated their causal relationship. This study aimed to examine the causal associations between IL-18 and IMIDs.
METHODS
We performed a two-sample Mendelian randomization (MR) analysis. Genetic variants were selected from genome-wide association study datasets following stringent assessments. We then used these variants as instrumental variables to estimate the causal effects of IL-18 levels on the risk of developing five common IMIDs: rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), ankylosing spondylitis (AS), and psoriasis. We used the inverse variance-weighted (IVW) method as the primary analysis, with sensitivity analyses performed to avoid potential bias. Reverse-direction MR analyses were performed to rule out the possibility of reverse associations.
RESULTS
We found that genetically determined higher circulating IL-18 levels were causally associated with a higher risk for SLE (P = 0.009; OR, 1.214; 95% CI, 1.049 - 1.404) and IBD (P < 0.001; OR, 1.142; 95% CI, 1.062 - 1.228), but found no significant associations of IL-18 with RA (P = 0.496; OR, 1.044; 95% CI, 0.923 - 1.180), AS (P = 0.021; OR, 1.181; 95% CI, 1.025 - 1.361), or psoriasis (P = 0.232; OR, 1.198; 95% CI, 0.891 - 1.611). In the reverse direction, no causal relationship existed between SLE or IBD and IL-18 levels. Globally, sensitivity studies using alternative MR methods supported the results that were robust and reliable. The Cochran's Q test, MR-Egger intercept, and MR-Pleiotropy RESidual Sum and Outlier excluded the influence of heterogeneity, horizontal pleiotropy, and outliers.
CONCLUSIONS
We have demonstrated that elevated IL-18 levels increase the risk of SLE and IBD but not RA, AS, or psoriasis. The results enhanced our understanding of IL-18 in the pathology of IMIDs.
Topics: Humans; Arthritis, Rheumatoid; Genome-Wide Association Study; Immunomodulating Agents; Inflammatory Bowel Diseases; Interleukin-18; Lupus Erythematosus, Systemic; Mendelian Randomization Analysis; Psoriasis
PubMed: 38031150
DOI: 10.1186/s12920-023-01744-z -
Frontiers in Immunology 2024The co-occurrence of primary biliary cholangitis (PBC) and systemic lupus erythematosus (SLE) has been consistently reported in observational studies. Nevertheless, the...
Investigating the causal relationship and potential shared diagnostic genes between primary biliary cholangitis and systemic lupus erythematosus using bidirectional Mendelian randomization and transcriptomic analyses.
BACKGROUND
The co-occurrence of primary biliary cholangitis (PBC) and systemic lupus erythematosus (SLE) has been consistently reported in observational studies. Nevertheless, the underlying causal correlation between these two conditions still needs to be established.
METHODS
We performed a bidirectional two-sample Mendelian randomization (MR) study to assess their causal association. Five MR analysis methods were utilized for causal inference, with inverse-variance weighted (IVW) selected as the primary method. The Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and the IVW Radial method were applied to exclude outlying SNPs. To assess the robustness of the MR results, five sensitivity analyses were carried out. Multivariable MR (MVMR) analysis was also employed to evaluate the effect of possible confounders. In addition, we integrated transcriptomic data from PBC and SLE, employing Weighted Gene Co-expression Network Analysis (WGCNA) to explore shared genes between the two diseases. Then, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment methods to perform on the shared genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was utilized to identify potential shared diagnostic genes. Finally, we verified the potential shared diagnostic genes in peripheral blood mononuclear cells (PBMCs)-specific cell populations of SLE patients by single-cell analysis.
RESULTS
Our MR study provided evidence that PBC had a causal relationship with SLE (IVW, OR: 1.347, 95% CI: 1.276 - 1.422, P < 0.001) after removing outliers (MR-PRESSO, rs35464393, rs3771317; IVW Radial, rs11065987, rs12924729, rs3745516). Conversely, SLE also had a causal association with PBC (IVW, OR: 1.225, 95% CI: 1.141 - 1.315, P < 0.001) after outlier correction (MR-PRESSO, rs11065987, rs3763295, rs7774434; IVW Radial, rs2297067). Sensitivity analyses confirmed the robustness of the MR findings. MVMR analysis indicated that body mass index (BMI), smoking and drinking were not confounding factors. Moreover, bioinformatic analysis identified PARP9, ABCA1, CEACAM1, and DDX60L as promising diagnostic biomarkers for PBC and SLE. These four genes are highly expressed in CD14+ monocytes in PBMCs of SLE patients and potentially associated with innate immune responses and immune activation.
CONCLUSION
Our study confirmed the bidirectional causal relationship between PBC and SLE and identified PARP9, ABCA1, CEACAM1, and DDX60L genes as the most potentially shared diagnostic genes between the two diseases, providing insights for the exploration of the underlying mechanisms of these disorders.
Topics: Humans; Leukocytes, Mononuclear; Liver Cirrhosis, Biliary; Mendelian Randomization Analysis; Gene Expression Profiling; CEACAM1 Protein; Lupus Erythematosus, Systemic
PubMed: 38464525
DOI: 10.3389/fimmu.2024.1270401 -
PloS One 2024Previous observational studies have reported an association between Sjögren's syndrome (SS) and an increased risk of Parkinson's Disease (PD). However, the causal... (Observational Study)
Observational Study
BACKGROUND
Previous observational studies have reported an association between Sjögren's syndrome (SS) and an increased risk of Parkinson's Disease (PD). However, the causal relationship between these conditions remains unclear. The objective of this study was to investigate the causal impact of SS on the risk of developing PD, utilizing the Mendelian randomization (MR) approach.
METHODS
We conducted a bidirectional MR analysis using publicly available genome-wide association studies (GWAS) data. The primary analysis utilized the inverse-variance weighted (IVW) method. Complementary methods, such as MR-Egger regression, weighted mode, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were utilized to identify and correct for the presence of horizontal pleiotropy.
RESULTS
The IVW MR analysis revealed no significant association between SS and PD (IVW: OR = 1.00, 95% CI = 0.94-1.07, P = 0.95). Likewise, the reverse MR analysis did not identify any significant causal relationship between PD and SS (IVW: OR = 0.98, 95% CI = 0.85-1.12, P = 0.73). The results from MR-Egger regression, weighted median, and weighted mode approaches were consistent with the IVW method. Sensitivity analyses suggested that horizontal pleiotropy is unlikely to introduce bias to the causal estimates.
CONCLUSION
This study does not provide evidence to support the assertion that SS has a conclusive impact on the risk of PD, which contradicts numerous existing observational reports. Further investigation is necessary to determine the possible mechanisms behind the associations observed in these observational studies.
Topics: Humans; Sjogren's Syndrome; Genome-Wide Association Study; Mendelian Randomization Analysis; Parkinson Disease
PubMed: 38568911
DOI: 10.1371/journal.pone.0298778 -
Bioinformatics (Oxford, England) Aug 2023Mixed molecular data combines continuous and categorical features of the same samples, such as OMICS profiles with genotypes, diagnoses, or patient sex. Like all...
MOTIVATION
Mixed molecular data combines continuous and categorical features of the same samples, such as OMICS profiles with genotypes, diagnoses, or patient sex. Like all high-dimensional molecular data, it is prone to incorrect values that can stem from various sources for example the technical limitations of the measurement devices, errors in the sample preparation, or contamination. Most anomaly detection algorithms identify complete samples as outliers or anomalies. However, in most cases, not all measurements of those samples are erroneous but only a few one-dimensional features within the samples are incorrect. These one-dimensional data errors are continuous measurements that are either located outside or inside the normal ranges of their features but in both cases show atypical values given all other continuous and categorical features in the sample. Additionally, categorical anomalies can occur for example when the genotype or diagnosis was submitted wrongly.
RESULTS
We introduce ADMIRE (Anomaly Detection using MIxed gRaphical modEls), a novel approach for the detection and correction of anomalies in mixed high-dimensional data. Hereby, we focus on the detection of single (one-dimensional) data errors in the categorical and continuous features of a sample. For that the joint distribution of continuous and categorical features is learned by mixed graphical models, anomalies are detected by the difference between measured and model-based estimations and are corrected using imputation. We evaluated ADMIRE in simulation and by screening for anomalies in one of our own metabolic datasets. In simulation experiments, ADMIRE outperformed the state-of-the-art methods of Local Outlier Factor, stray, and Isolation Forest.
AVAILABILITY AND IMPLEMENTATION
All data and code is available at https://github.com/spang-lab/adadmire. ADMIRE is implemented in a Python package called adadmire which can be found at https://pypi.org/project/adadmire.
Topics: Humans; Algorithms; Computer Simulation; Genotype; Software
PubMed: 37584673
DOI: 10.1093/bioinformatics/btad501 -
Frontiers in Genetics 2023Type 2 diabetes (T2D) is associated with severe mental illnesses (SMIs), such as schizophrenia, bipolar disorder, and depression. However, causal relationships between...
Type 2 diabetes (T2D) is associated with severe mental illnesses (SMIs), such as schizophrenia, bipolar disorder, and depression. However, causal relationships between SMIs and T2D remain unclear owing to potential bias in observational studies. We aimed to characterize the causal effect of SMI liability on T2D using two-sample Mendelian randomization (MR). The causality between liability to SMI and T2D was investigated using the inverse-variance weighted (IVW), MREgger, MR-Egger with a simulation extrapolation, weighted median, and the MR pleiotropy residual sum and outlier method. Similarly, we performed additional MR which can detect the reverse causation effect by switching exposure and outcome for T2D liability for SMI. To further consider pleiotropic effects between SMIs, multivariable MR analysis was performed after accounting for the other traits. In the univariable IVW method, depression showed a causal effect on T2D (odds ratio [OR]: 1.128, 95% confidence interval [CI]: 1.024-1.245, = 0.014). Multinomial MR more strongly supported these results (IVW OR: 1.197, 95% CI: 1.069, 1.340, = 0.002; MR-Egger OR: 1.198, 95% CI: 1.062, 1.349, = 0.003). Bidirectional MR showed absence of reversecausality between depression and T2D. However, causal relationship of bipolar and schizophrenia on T2D was not detected. Careful attention is needed for patients with depression regarding T2D prevention and treatment.
PubMed: 37693321
DOI: 10.3389/fgene.2023.1181851 -
Frontiers in Psychology 2023The presence of outliers in response times can affect statistical analyses and lead to incorrect interpretation of the outcome of a study. Therefore, it is a widely...
The presence of outliers in response times can affect statistical analyses and lead to incorrect interpretation of the outcome of a study. Therefore, it is a widely accepted practice to try to minimize the effect of outliers by preprocessing the raw data. There exist numerous methods for handling outliers and researchers are free to choose among them. In this article, we use computer simulations to show that serious problems arise from this flexibility. Choosing between alternative ways for handling outliers can result in the inflation of -values and the distortion of confidence intervals and measures of effect size. Using Bayesian parameter estimation and probability distributions with heavier tails eliminates the need to deal with response times outliers, but at the expense of opening another source of flexibility.
PubMed: 37691812
DOI: 10.3389/fpsyg.2023.1220281 -
Frontiers in Psychiatry 2023Observational studies have reported the association between fatigue and coronary artery disease (CAD), but the causal association between fatigue and CAD is unclear.
BACKGROUND
Observational studies have reported the association between fatigue and coronary artery disease (CAD), but the causal association between fatigue and CAD is unclear.
METHOD
We conducted a bidirectional Mendelian randomization (MR) study using publicly available genome-wide association studies (GWAS) data. The inverse-variance weighted (IVW) method was used as the primary analysis. We performed three complementary methods, including weighted median, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO) to evaluate the sensitivity and horizontal pleiotropy of the results.
RESULT
Self-reported fatigue had a causal effect on coronary artery atherosclerosis (CAA) (OR 1.047, 95%CI 1.033-1.062), myocardial infarction (MI) (OR 1.027 95%CI 1.014-1.039) and coronary heart disease (CHD) (OR 1.037, 95%CI 1.021-1.053). We did not find a significant reverse causality between self-reported fatigue and CAD. Given the heterogeneity revealed by MR-Egger regression, we employed the IVW random effect model. For the examination of fatigue on CHD and the reverse analysis of CAA, and MI on fatigue, the MR-PRESSO test found horizontal pleiotropy. No significant outliers were found.
CONCLUSION
The MR analysis reveals a causal relationship between self-reported fatigue and CAD. The results should be interpreted with caution due to horizontal pleiotropy.
PubMed: 37799396
DOI: 10.3389/fpsyt.2023.1166689 -
BMC Medical Informatics and Decision... Sep 2023Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in claims is procedure code...
BACKGROUND
Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in claims is procedure code overutilization, where one or more prescribed procedures may not be relevant to a given diagnosis and patient profile, resulting in unnecessary and unwarranted treatments and medical payments. This study aims to identify such unwarranted procedures from millions of healthcare claims. In the absence of labeled examples of unwarranted procedures, the study focused on the application of unsupervised machine learning techniques.
METHODS
Experiments were conducted with deep autoencoders to find claims containing anomalous procedure codes indicative of FWA, and were compared against a baseline density-based clustering model. Diagnoses, procedures, and demographic data associated with healthcare claims were used as features for the models. A dataset of one hundred thousand claims sampled from a larger claims database is used to initially train and tune the models, followed by experimentations on a dataset with thirty-three million claims. Experimental results show that the autoencoder model, when trained with a novel feature-weighted loss function, outperforms the density-based clustering approach in finding potential outlier procedure codes.
RESULTS
Given the unsupervised nature of our experiments, model performance was evaluated using a synthetic outlier test dataset, and a manually annotated outlier test dataset. Precision, recall and F1-scores on the synthetic outlier test dataset for the autoencoder model trained on one hundred thousand claims were 0.87, 1.0 and 0.93, respectively, while the results for these metrics on the manually annotated outlier test dataset were 0.36, 0.86 and 0.51, respectively. The model performance on the manually annotated outlier test dataset improved further when trained on the larger thirty-three million claims dataset with precision, recall and F1-scores of 0.48, 0.90 and 0.63, respectively.
CONCLUSIONS
This study demonstrates the feasibility of leveraging unsupervised, deep-learning methods to identify potential procedure overutilization from healthcare claims.
Topics: Humans; Deep Learning; Unsupervised Machine Learning; Delivery of Health Care; Databases, Factual; Fraud
PubMed: 37770866
DOI: 10.1186/s12911-023-02268-3