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BMC Medical Research Methodology Aug 2023Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations...
BACKGROUND
Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential 'outlier' evaluators are needed to improve data quality during data collection stage.
METHODS
In this paper, we propose a two-stage algorithm to detect 'outlier' evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators' effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect 'outlier' evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential 'outlier' audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses' Health Study II.
RESULTS
Our simulation study shows that our method not only can detect true 'outlier' evaluators, but also is less likely to falsely reject true 'normal' evaluators.
CONCLUSIONS
Our two-stage 'outlier' detection algorithm is a flexible approach that can effectively detect 'outlier' evaluators, and thus data quality can be improved during data collection stage.
Topics: Humans; Computer Simulation; Algorithms; Data Collection; Risk Factors; Data Accuracy
PubMed: 37528402
DOI: 10.1186/s12874-023-01988-4 -
Epilepsia Open Dec 2023Observational studies have suggested a link between telomere length (TL) and epilepsy, but the direction of the effect and whether it is causal or not is still being... (Observational Study)
Observational Study
OBJECTIVE
Observational studies have suggested a link between telomere length (TL) and epilepsy, but the direction of the effect and whether it is causal or not is still being debated. The objective of this study was to investigate the causal relationship between TL and epilepsy using Mendelian randomization (MR) analysis.
METHODS
We performed a bidirectional two-sample MR analysis using pooled statistics from genome-wide association studies (GWAS) of TL and epilepsy. Additionally, we conducted a replication analysis using data from another GWAS study on epilepsy to validate our findings. The final results were analyzed using five MR methods, with the inverse-variance weighted (IVW) method as the primary outcome. We applied methods such as radial MR, MR pleiotropy residual and outlier test and MR Steiger filters to exclude outliers. Sensitivity analyses were also conducted to assess heterogeneity and pleiotropy.
RESULTS
Our analysis found no evidence of a causal relationship between epilepsy and TL (all p-values >0.05). The sensitivity analysis confirms the robustness of these results.
SIGNIFICANCE
In summary, our study contradicts existing observational reports by not finding any evidence to support a causal relationship between epilepsy and TL. Further research is necessary to determine the underlying mechanism behind the association observed in observational studies.
Topics: Humans; Genome-Wide Association Study; Mendelian Randomization Analysis; Epilepsy; Causality; Telomere
PubMed: 37593897
DOI: 10.1002/epi4.12817 -
Frontiers in Cardiovascular Medicine 2023Although observational studies have shown that patients who experienced transient ischemic attacks (TIAs) had a higher risk of coronary artery disease (CAD), the causal...
BACKGROUND
Although observational studies have shown that patients who experienced transient ischemic attacks (TIAs) had a higher risk of coronary artery disease (CAD), the causal relationship is ambiguous.
METHODS
We conducted a two-sample Mendelian randomization (MR) study to analyze the causal relationship between TIA and CAD using data from the FinnGen genome-wide association study. Analysis was performed using the inverse-variance weighted (IVW) method. The robustness of the results was evaluated using MR-Egger regression, the weighted median, MR pleiotropy residual sum, and outlier (MR-PRESSO) and multivariable MR analysis.
RESULTS
Results from IVW random-effect model showed that TIA was associated with an increased risk of coronary artery atherosclerosis (OR 1.17, 95% CI 1.06-1.28, = 0.002), ischemic heart disease (OR 1.15, 95% CI 1.04-1.27, = 0.007), and myocardial infarction (OR1.15, 95% CI 1.02-1.29, = 0.025). In addition, heterogeneity and horizontal pleiotropy were observed in the ischemic heart disease results, while the sensitivity analysis revealed no evidence of horizontal pleiotropy in other outcomes.
CONCLUSIONS
This MR study demonstrated a potential causal relationship between TIA and CAD. Further research should be conducted to investigate the mechanism underlying the association.
PubMed: 37671135
DOI: 10.3389/fcvm.2023.1192664 -
Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization.Frontiers in Public Health 2023Many studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between...
BACKGROUNDS
Many studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between particulate matter 2.5 (PM) and diabetes based on genetic approaches are scarce. The study estimated the causal relationship between diabetes and PM using two sample mendelian randomization (TSMR).
METHODS
We collected genetic data from European ancestry publicly available genome wide association studies (GWAS) summary data through the MR-BASE repository. The IEU GWAS information output PM from the Single nucleotide polymorphisms (SNPs) GWAS pipeline using pheasant-derived variables (Consortium = MRC-IEU, sample size: 423,796). The annual relationship of PM (2010) were modeled for each address using a Land Use Regression model developed as part of the European Study of Cohorts for Air Pollution Effects. Diabetes GWAS information (Consortium = MRC-IEU, sample size: 461,578) were used, and the genetic variants were used as the instrumental variables (IVs). We performed three representative Mendelian Randomization (MR) methods: Inverse Variance Weighted regression (IVW), Egger, and weighted median for causal relationship using genetic variants. Furthermore, we used a novel method called MR Mixture to identify outlier SNPs.
RESULTS
From the IVW method, we revealed the causal relationship between PM and diabetes (Odds ratio [OR]: 1.041, 95% CI: 1.008-1.076, = 0.016), and the finding was substantiated by the absence of any directional horizontal pleiotropy through MR-Egger regression (β = 0.016, = 0.687). From the IVW fixed-effect method (i.e., one of the MR machine learning mixture methods), we excluded outlier SNP (rs1537371) and showed the best predictive model (AUC = 0.72) with a causal relationship between PM and diabetes (OR: 1.028, 95% CI: 1.006-1.049, = 0.012).
CONCLUSION
We identified the hypothesis that there is a causal relationship between PM and diabetes in the European population, using MR methods.
Topics: Humans; Genome-Wide Association Study; Mendelian Randomization Analysis; Diabetes Mellitus; Air Pollution; Particulate Matter
PubMed: 37637811
DOI: 10.3389/fpubh.2023.1164647 -
Dermatology and Therapy Oct 2023Previous studies have proposed a possible gut-skin axis, and linked gut microbiota to psoriasis risks. However, there is heterogeneity in existing evidence....
INTRODUCTION
Previous studies have proposed a possible gut-skin axis, and linked gut microbiota to psoriasis risks. However, there is heterogeneity in existing evidence. Observational research is prone to bias, and it is hard to determine causality. Therefore, this study aims to evaluate possible causal associations between gut microbiota (GM) and psoriasis.
METHODS
With published large-scale GWAS (genome-wide association study) summary datasets, two-sample Mendelian randomization (MR) was performed to sort out possible causal roles of GM in psoriasis and arthropathic psoriasis (PsA). The inverse variance weighted (IVW) method was taken as the primary evaluation of causal association. As complements to the IVW method, we also applied MR-Egger, weighted median. Sensitivity analyses were conducted using Cochrane's Q test, MR-Egger intercept test, MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier) global test, and leave-one-out analysis.
RESULTS
By primary IVW analysis, we identified nominal protective roles of Bacteroidetes (odds ratio, OR 0.81, P = 0.033) and Prevotella9 (OR 0.87, P = 0.045) in psoriasis risks. Bacteroidia (OR 0.65, P = 0.03), Bacteroidales (OR 0.65, P = 0.03), and Ruminococcaceae UCG002 (OR 0.81, P = 0.038) are nominally associated with lower risks for PsA. On the other hand, Pasteurellales (OR 1.22, P = 0.033), Pasteurellaceae (OR 1.22, P = 0.033), Blautia (OR 1.46, P = 0.014), Methanobrevibacter (OR 1.27, P = 0.026), and Eubacterium fissicatena group (OR 1.21, P = 0.028) are nominal risk factors for PsA. Additionally, E. fissicatena group is a possible risk factor for psoriasis (OR 1.22, P = 0.00018). After false discovery rate (FDR) correction, E. fissicatena group remains a risk factor for psoriasis (P = 0.03798).
CONCLUSION
We comprehensively evaluated possible causal associations of GM with psoriasis and arthropathic psoriasis, and identified several nominal associations. E. fissicatena group remains a risk factor for psoriasis after FDR correction. Our results offer promising therapeutic targets for psoriasis clinical management.
PubMed: 37653234
DOI: 10.1007/s13555-023-01007-w -
Journal of the American Heart... Sep 2023Background Observational associations between type 2 diabetes (T2D) and atrial fibrillation (AF) have been established, but causality remains undetermined. We performed...
Background Observational associations between type 2 diabetes (T2D) and atrial fibrillation (AF) have been established, but causality remains undetermined. We performed Mendelian randomization (MR) to study causal effects of genetically predicted T2D on AF risk, independent of cardiometabolic risk factors. Methods and Results Instrumental variables included 182 uncorrelated single nucleotide polymorphisms associated with T2D at genome-wide significance ( <5×10). Genetic association estimates for cardiometabolic exposures were obtained from genome-wide association studies including 188 577 individuals for low-density lipoprotein-C, 694 649 individuals for body mass index, and 757 601 for systolic blood pressure. Two-sample, inverse-variance weighted MR formed the primary analyses. The MR-TRYX approach was used to dissect potential pleiotropic pathways, with multivariable MR performed to investigate cardiometabolic mediation. Genetically predicted T2D associated with increased AF liability in univariable MR (odds ratio [OR], 1.08 [95% CI, 1.02-1.13], =0.003). Sensitivity analyses indicated potential pleiotropy, with radial MR identifying 4 outlier single nucleotide polymorphisms that were likely contributors. Phenomic scanning on MR-base and subsequent least absolute shrinkage and selection operator regression allowed prioritization of 7 candidate traits. The outlier-adjusted effect estimate remained consistent with the original inverse-variance weighted estimate (OR, 1.07 [95% CI, 1.02-1.12], =0.008). On multivariable MR, T2D remained associated with increased AF liability after adjustment for low-density lipoprotein-C and body mass index. Following adjustment for systolic blood pressure, the relationship between T2D and AF became nonsignificant (OR, 1.04 [95% CI, 0.95-1.13], =0.40). Conclusions These data provide novel genetic evidence that while T2D likely causally associates with AF, mediation via systolic blood pressure exists. Endeavoring to lower systolic blood pressure alongside achieving normoglycemia may provide particular benefit on AF risk in patients with T2D.
Topics: Humans; Atrial Fibrillation; Diabetes Mellitus, Type 2; Genome-Wide Association Study; Mendelian Randomization Analysis; Lipoproteins, LDL
PubMed: 37609985
DOI: 10.1161/JAHA.123.030298 -
Data in Brief Aug 2023Data from a bathymetric mapping project conducted in seven Israeli coastal micro-estuaries (Lachish, Sorek, Yarkon, Alexander, Hadera, Taninim, and Kishon) is presented....
Data from a bathymetric mapping project conducted in seven Israeli coastal micro-estuaries (Lachish, Sorek, Yarkon, Alexander, Hadera, Taninim, and Kishon) is presented. The data were collected by rowing a kayak along an S-shaped track through the estuaries. An echosounder equipped with a Global Positioning System (GPS) unit were mounted on the kayak. The data preparation consisted of a) manual removal of outliers, mostly caused by instrument echo in water depths below the instrument's 0.5 m minimum; b) correction of the measured water level to sea level; and c) interpolation of the sampling points into a regular grid using a terrain-following interpolation algorithm. For each of the estuaries, the raw measurements as a text (csv) file and the interpolated data both as a text (CSV) file and a GeoTiff file were produced.
PubMed: 37577739
DOI: 10.1016/j.dib.2023.109444 -
Scientific Reports Dec 2023Elevated Gamma-glutamyl transferase (GGT) levels are often suggestive of cholelithiasis, and previous studies have indicated that GGT is highly expressed in the urinary...
Elevated Gamma-glutamyl transferase (GGT) levels are often suggestive of cholelithiasis, and previous studies have indicated that GGT is highly expressed in the urinary system. Therefore, we hypothesized that there may be an association between GGT levels and calculus of kidney (CK) incidence. To investigate this potential causal relationship, we employed Mendelian randomization (MR) analysis. Additionally, we analyzed the levels of other liver enzymes, including alanine transaminase (ALT) and alkaline phosphatase (ALP). The relationship between GGT levels and CK incidence was analyzed using two-sample Mendelian randomization. Summary Genome-Wide Association Studies data were utilized for this analysis. 33 single nucleotide polymorphisms known to be associated with GGT levels were employed as instrumental variables. We employed several MR methods including IVW (inverse variance weighting), MR-Egger, weighted median, weighted mode, and MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier). Furthermore, we conducted tests for horizontal multivariate validity, heterogeneity, and performed leave-one-out analysis to ensure the stability of the results. Overall, several MR methods yielded statistically significant results with a p-value < 0.05. The results from the IVW analysis yielded an odds ratio (OR) of 1.0062 with a 95% confidence interval (CI) of 1.0016-1.0109 (p = 0.0077). Additional MR methods provided supplementary results: MR-Egger (OR 1.0167, 95% CI 1.0070-1.0266, p = 0.0040); weighted median (OR 1.0058, 95% CI 1.0002-1.0115, p = 0.0423); and weighted mode (OR 1.0083, 95% CI 1.0020-1.0146, p- = 0.0188). Sensitivity analyses did not reveal heterogeneity or outliers. Although potential horizontal pleiotropy emerged, we speculate that this could be attributed to inadequate test efficacy. However, subsequent use of MR-PRESSO did not provide evidence of pleiotropy. Our analysis suggests a positive association between elevated GGT levels and CK incidence, indicating an increased risk of CK development. However, no causal relationship was observed between levels of ALP or ALT and CK incidence.
Topics: Humans; gamma-Glutamyltransferase; Genome-Wide Association Study; Mendelian Randomization Analysis; Kidney Calculi; Alanine Transaminase; Alkaline Phosphatase; Coloring Agents; Ubiquitin-Protein Ligases; Kidney
PubMed: 38071316
DOI: 10.1038/s41598-023-48610-7 -
Journal of Clinical Medicine Jul 2023Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve... (Review)
Review
Immune checkpoint inhibitor (ICI) therapy has revolutionized renal cell carcinoma treatment. Patients previously thought to be palliative now occasionally achieve complete cures from ICI. However, since immunotherapies stimulate the immune system to induce anti-tumor immunity, they often lead to adverse autoimmunity. Furthermore, some patients receive no benefit from ICI, thereby unnecessarily risking adverse events. In many tumor types, PD-L1 expression levels, immune infiltration, and tumor mutation burden predict the response to ICI and help inform clinical decision making to better target ICI to patients most likely to experience benefits. Unfortunately, renal cell carcinoma is an outlier, as these biomarkers fail to discriminate between positive and negative responses to ICI therapy. Emerging biomarkers such as gene expression profiles and the loss of pro-angiogenic proteins VHL and PBRM-1 show promise for identifying renal cell carcinoma cases likely to respond to ICI. This review provides an overview of the mechanistic underpinnings of different biomarkers and describes the theoretical rationale for their use. We discuss the effectiveness of each biomarker in renal cell carcinoma and other cancer types, and we introduce novel biomarkers that have demonstrated some promise in clinical trials.
PubMed: 37568390
DOI: 10.3390/jcm12154987 -
BMJ Global Health May 2024Currently, about 8% of deaths worldwide are maternal or neonatal deaths, or stillbirths. Maternal and neonatal mortality have been a focus of the Millenium Development... (Review)
Review
Learning from success: the main drivers of the maternal and newborn health transition in seven positive-outlier countries and implications for future policies and programmes.
Currently, about 8% of deaths worldwide are maternal or neonatal deaths, or stillbirths. Maternal and neonatal mortality have been a focus of the Millenium Development Goals and the Sustainable Development Goals, and mortality levels have improved since the 1990s. We aim to answer two questions: What were the key drivers of maternal and neonatal mortality reductions seen in seven positive-outlier countries from 2000 to the present? How generalisable are the findings?We identified positive-outlier countries with respect to maternal and neonatal mortality reduction since 2000. We selected seven, and synthesised experience to assess the contribution of the health sector to the mortality reduction, including the roles of access, uptake and quality of services, and of health system strengthening. We explored the wider context by examining the contribution of fertility declines, and the roles of socioeconomic and human development, particularly as they affected service use, the health system and fertility. We analysed government levers, namely policies and programmes implemented, investments in data and evidence, and political commitment and financing, and we examined international inputs. We contextualised these within a mortality transition framework.We found that strategies evolved over time as the contacts women and neonates had with health services increased. The seven countries tended to align with global recommendations but could be distinguished in that they moved progressively towards implementing their goals and in scaling-up services, rather than merely adopting policies. Strategies differed by phase in the transition framework-one size did not fit all.
Topics: Humans; Infant, Newborn; Female; Maternal Mortality; Infant Mortality; Health Policy; Pregnancy; Infant; Infant Health; Maternal Health Services; Developing Countries; Maternal Health
PubMed: 38770812
DOI: 10.1136/bmjgh-2023-012126