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Annals of Medicine Dec 2022It has been found that childhood obesity (CO) may play an important role in the onset and progression of osteoarthritis (OA). Thus we conducted this mendelian...
PURPOSE
It has been found that childhood obesity (CO) may play an important role in the onset and progression of osteoarthritis (OA). Thus we conducted this mendelian randomisation analysis (MR) to evaluate the causal association between childhood obesity and osteoarthritis.
METHODS
Instrumental variables (IVs) were obtained from publicly available genome-wide association study datasets. The leave-one-out sensitivity test, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and Cochran's test were used to confirm the heterogeneity and pleiotropy of identified IVs, then five different models, including the inverse variance weighted model (IVW), weighted median estimator model (WME), weighted model-based method (WM), MR-Egger regression model (MER), and MR-Robust Adjusted Profile Score (MRAPS) were applied in this MR analysis.
RESULTS
After excluding all outliers identified by the MR-PRESSO test, no evident directional pleiotropy was found. Significant heterogeneity was found in the secondary MR and as a result, the multiplicative random-effect model was used. Significant causal association between CO and OA (OR 1.0075, 95% CI [1.0054, 1.0010], = 8.12 × 10). The secondary MR also revealed that CO was causally associated with knee OA (OR 1.1067, 95% CI [1.0769, 1.1373], = 3.30 × 10) and hip OA (OR 1.1272, 95% CI [1.0610, 1.1976], = 1.07 × 10). The accuracy and robustness of these findings were confirmed by sensitivity tests.
CONCLUSION
There appears to be a causal relationship between childhood obesity and OA. Our results indicate that individuals with a history of childhood obesity require specific clinical attention to prevent the development of knee and hip OA.
Topics: Child; Genome-Wide Association Study; Humans; Mendelian Randomization Analysis; Osteoarthritis, Hip; Pediatric Obesity; Polymorphism, Single Nucleotide
PubMed: 35703935
DOI: 10.1080/07853890.2022.2085883 -
Frontiers in Endocrinology 2022At present, clinical studies have confirmed that osteoporosis (OP) has an inverse relationship with osteoarthritis (OA), but it has not been proven from the point of...
INTRODUCTION
At present, clinical studies have confirmed that osteoporosis (OP) has an inverse relationship with osteoarthritis (OA), but it has not been proven from the point of view of genetics, so our study hopes to clarify the potential effect of OP on OA at the level of gene prediction through two-sample Mendelian randomization (MR) analysis.
METHODS
A two-sample MR was adopted to research the causal relationship of OP with OA (including total OA, knee OA and hip OA). All data come from a public shared database. Such traditional methods as simple and weighted models, inverse variance weighted, weighted median, and Mendelian Randomization (MR-Egger) regression were employed to assess the causal effect of OP on OA. We used the Pleiotrophy RESidual Sum and Outlier (MR-PRESSO) method and MR-Egger method to study sensitivity. The leave-one-out test is used to determine the influence of outliers. The heterogeneity was calculated by using Cochran Q statistics and MR-Egger regression in the inverse variance-weighted (IVW) method. > 0.05 indicates that there is a large heterogeneity. MR-Robust Adjustment Profile Score (RAPS) is stable to both systematic and specific multiplicity, so we used MR-RAPS as a supplementary method to verify the results of IVW.
RESULTS
According to the results of IVW, we found that there was a causal relationship between OP and total OA, and OP reduced the incidence of total OA (beta=-0.285, OR=0.751, value< 0.016). The MR estimation of the causal effect of OP on knee OA suggested that the genetic prediction of OP was negatively correlated with knee osteoarthritis (KOA) (IVW: beta=-6.11, OR=0.002, value< 0.016). The IVW results suggested that OP was causally related to hip OA, and OP had a protective effect on hip OA (beta=-5.48, OR=4.15e-3, value= 3.99e-3). Except for heterogeneity in the analysis of OP and knee OA, there was no horizontal pleiotropy or heterogeneity in the other analyses.
CONCLUSION
We explored the causal relationship between OP and OA through a two-sample MR analysis and found that OP can reduce the incidence of OA (including knee OA and hip OA).
Topics: Humans; Genome-Wide Association Study; Mendelian Randomization Analysis; Osteoarthritis, Hip; Osteoarthritis, Knee; Osteoporosis; Polymorphism, Single Nucleotide
PubMed: 36339427
DOI: 10.3389/fendo.2022.1011246 -
Frontiers in Nutrition 2022The relationship between tea consumption and the risk of breast cancer is inconsistent in previous observational studies and is still in dispute. We intended to detect...
BACKGROUND
The relationship between tea consumption and the risk of breast cancer is inconsistent in previous observational studies and is still in dispute. We intended to detect the causal association between tea consumption and breast cancer risk using two-sample Mendelian randomization (MR) analysis.
MATERIALS AND METHODS
The summary statistics of tea consumption was obtained from the UK Biobank Consortium with 349,376 individuals and breast cancer information was obtained from the Breast Cancer Association Consortium (BCAC) (122,977 cases and 105,974 non-cases). Sensitivity analyses of evaluating the influence of outliers and pleiotropy effects were performed by a variety of MR methods under different model assumptions.
RESULTS
After potentially excluding pleiotropic single nucleotide polymorphisms (SNPs) using the MR Pleiotropy RESidual Sum and Outlier method, the odds ratio (OR) for per extra daily cup of tea intake for overall, estrogen receptor (ER)-positive, and ER-negative breast cancer risk was 1.029 [95% confidence interval (CI) = 0.983-1.077, = 0.2086], 1.050 (95% CI = 0.994-1.109, = 0.078), and 1.081 (95% CI = 0.990-1.103, = 0.6513), respectively. The results were consistent with a sensitivity analysis that excluded SNPs associated with other phenotypes, manifesting that the findings were convincing and robust. Moreover, in the multivariable MR analysis, the null associations for breast cancer risk remained after adjusting for smoking and alcohol consumption separately or together.
CONCLUSION
Our MR results based on genetic data did not support a causal relationship between tea consumption and breast cancer risk.
PubMed: 36330145
DOI: 10.3389/fnut.2022.956969 -
Frontiers in Immunology 2022Multiple sclerosis (MS) is a chronic inflammatory autoimmune and degenerative disorder of the central nervous system. Telomeres are protective structures located at the...
OBJECTIVES
Multiple sclerosis (MS) is a chronic inflammatory autoimmune and degenerative disorder of the central nervous system. Telomeres are protective structures located at the ends of linear chromosomes, and leukocyte telomere length (LTL) is closely connected with cell aging and senescence. However, the relationship between LTL and the risk of MS remains unknown.
METHODS
We performed a two-sample Mendelian randomization (MR) to evaluate whether LTL was causally associated with MS risk.
RESULTS
In our MR analysis, 12 LTL-related variants were selected as valid instrumental variables, and a causal relationship between LTL and MS was suggested. The risk of MS nearly doubled as the genetically predicted LTL shortened by one standard deviation (SD) under the inverse variance weighted (IVW) fixed effect model (odds ratio (OR) = 2.00, 95% confidence interval (CI): 1.52-2.62, = 6.01e-07). Similar estimated causal effects were also observed under different MR models. The MR-Egger regression test did not reveal any evidence of directional pleiotropy (intercept = -0.005, stand error (SE) = 0.03, = 0.87). The Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) analysis also indicated no directional pleiotropy or outliers for any LTL-related IVs (-global test = 0.13). In addition, a leave-one-out sensitivity analysis showed similar findings, which further emphasized the validity and stability of the causal relationship.
CONCLUSIONS
Our results suggest a potential causal effect of LTL on the risk of MS. Genetically predicted shorter LTL could increase the risk of MS in the European population. LTL should be noted and emphasized in the pathogenesis and treatment of MS.
Topics: Genome-Wide Association Study; Humans; Leukocytes; Mendelian Randomization Analysis; Multiple Sclerosis; Polymorphism, Single Nucleotide; Telomere
PubMed: 35911771
DOI: 10.3389/fimmu.2022.922922 -
Frontiers in Endocrinology 2022Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity,...
BACKGROUND
Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.
METHODS
We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.
RESULTS
Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.
CONCLUSIONS
Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.
Topics: Diabetes Mellitus, Type 2; Genome-Wide Association Study; Gout; Humans; Hypertension; Mendelian Randomization Analysis; Obesity; Uric Acid
PubMed: 35992130
DOI: 10.3389/fendo.2022.917056 -
Translational Psychiatry Nov 2022The muscarinic receptor agonist xanomeline improved cognition in phase 2 trials in Alzheimer's disease and schizophrenia. We present data on the effect of KarXT... (Randomized Controlled Trial)
Randomized Controlled Trial
Effectiveness of KarXT (xanomeline-trospium) for cognitive impairment in schizophrenia: post hoc analyses from a randomised, double-blind, placebo-controlled phase 2 study.
The muscarinic receptor agonist xanomeline improved cognition in phase 2 trials in Alzheimer's disease and schizophrenia. We present data on the effect of KarXT (xanomeline-trospium) on cognition in schizophrenia from the 5-week, randomised, double-blind, placebo-controlled EMERGENT-1 trial (NCT03697252). Analyses included 125 patients with computerised Cogstate Brief Battery (CBB) subtest scores at baseline and endpoint. A post hoc subgroup analysis evaluated the effects of KarXT on cognitive performance in patients with or without clinically meaningful cognitive impairment at baseline, and a separate outlier analysis excluded patients with excessive intraindividual variability (IIV) across cognitive subdomains. ANCOVA models assessed treatment effects for completers and impairment subgroups, with or without removal of outliers. Sample-wide, cognitive improvement was numerically but not statistically greater with KarXT (n = 60) than placebo (n = 65), p = 0.16. However, post hoc analyses showed 65 patients did not exhibit clinically meaningful cognitive impairment at baseline, while eight patients had implausibly high IIV at one or both timepoints. Significant treatment effects were observed after removing outliers (KarXT n = 54, placebo n = 63; p = 0.04). Despite the small sample size, a robust (d = 0.50) and significant effect was observed among patients with cognitive impairment (KarXT n = 23, placebo n = 37; p = 0.03). These effects did not appear to be related to improvement in PANSS total scores (linear regression, R= 0.03). Collectively, these findings suggest that KarXT may have a separable and meaningful impact on cognition, particularly among patients with cognitive impairment.
Topics: Humans; Schizophrenia; Cognitive Dysfunction; Thiadiazoles; Pyridines; Quaternary Ammonium Compounds
PubMed: 36414626
DOI: 10.1038/s41398-022-02254-9 -
Scientific Reports Oct 2023Observational studies have reported a correlation between Helicobacter pylori infection and colorectal cancer (CRC); however, the underlying cause has remained unclear....
Observational studies have reported a correlation between Helicobacter pylori infection and colorectal cancer (CRC); however, the underlying cause has remained unclear. This research was aimed at determining whether there is a correlation between H. pylori infection and CRC by measuring the prevalence of H. pylori CagA antibodies and VacA antibodies. Using data from many genome-wide association studies (GWAS), we conducted a Mendelian randomization (MR) study with two sample GWAS. Then, we used bidirectional MR to evaluate the association between H. pylori infection and CRC for identifying causation. The most common method of analysis was the inverse variance-weighted technique. In addition, we performed supplementary analyses using the weighted median technique and MR-Egger regression. Horizontal pleiotropic outliers were identified and corrected using the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) method. Genetically predicted anti-H. pylori IgG seropositivity was not causally associated with CRC [odds ratio (OR): 1.12; 95% confidence interval (CI): 0.98-1.27, P = 0.08] and neither were H. pylori VacA antibody levels (OR = 0.96, 95% CI: 0.90-1.02, P = 0.25) or H. pylori CagA antibody levels (OR = 1.00, 95% CI: 0.93-1.07, P = 0.92). Furthermore, reverse MR analysis did not reveal evidence for a causal effect of CRC on H. pylori infection. The weighted median, the MR-Egger method, and MR-PRESSO yielded identical results. Using genetic data, MR analysis showed there was no evidence for a causal association between seroprevalence of H. pylori infection and CRC. The relationship between H. pylori infection and CRC requires further research.
Topics: Humans; Helicobacter Infections; Genome-Wide Association Study; Helicobacter pylori; Mendelian Randomization Analysis; Seroepidemiologic Studies; Antibodies, Bacterial; Calgranulin A; Colorectal Neoplasms
PubMed: 37899462
DOI: 10.1038/s41598-023-45545-x -
Scientific Reports Feb 2023Outlier detection is an important topic in machine learning and has been used in a wide range of applications. Outliers are objects that are few in number and deviate...
Outlier detection is an important topic in machine learning and has been used in a wide range of applications. Outliers are objects that are few in number and deviate from the majority of objects. As a result of these two properties, we show that outliers are susceptible to a mechanism called fluctuation. This article proposes a method called fluctuation-based outlier detection (FBOD) that achieves a low linear time complexity and detects outliers purely based on the concept of fluctuation without employing any distance, density or isolation measure. Fundamentally different from all existing methods. FBOD first converts the Euclidean structure datasets into graphs by using random links, then propagates the feature value according to the connection of the graph. Finally, by comparing the difference between the fluctuation of an object and its neighbors, FBOD determines the object with a larger difference as an outlier. The results of experiments comparing FBOD with eight state-of-the-art algorithms on eight real-worlds tabular datasets and three video datasets show that FBOD outperforms its competitors in the majority of cases and that FBOD has only 5% of the execution time of the fastest algorithm. The experiment codes are available at: https://github.com/FluctuationOD/Fluctuation-based-Outlier-Detection .
PubMed: 36765095
DOI: 10.1038/s41598-023-29549-1 -
The VLDB Journal : Very Large Data... 2022While many techniques for outlier detection have been proposed in the literature, the interpretation of detected outliers is often left to users. As a result, it is...
While many techniques for outlier detection have been proposed in the literature, the interpretation of detected outliers is often left to users. As a result, it is difficult for users to promptly take appropriate actions concerning the detected outliers. To lessen this difficulty, when outliers are identified, they should be presented together with their explanations. There are survey papers on outlier detection, but none exists for outlier explanations. To fill this gap, in this paper, we present a survey on outlier explanations in which meaningful knowledge is mined from anomalous data to explain them. We define different types of outlier explanations and discuss the challenges in generating each type. We review the existing outlier explanation techniques and discuss how they address the challenges. We also discuss the applications of outlier explanations and review the existing methods used to evaluate outlier explanations. Furthermore, we discuss possible future research directions.
PubMed: 35095253
DOI: 10.1007/s00778-021-00721-1 -
Genomics Jan 2021The ΔΔct method estimates fold change in gene expression data from RT-PCR assay. The ΔΔct estimate aggregates replicates using mean and standard deviation (sd) and...
The ΔΔct method estimates fold change in gene expression data from RT-PCR assay. The ΔΔct estimate aggregates replicates using mean and standard deviation (sd) and is not robust to outliers which are in practice often removed before the non-outlying replicates are aggregated. The alternative of using robust statistics such as median and median absolute deviation (MAD) to aggregate the replicates is not done in practice perhaps because the distribution of a robust ΔΔct estimate based on median and MAD is not straightforward to deduce. We introduce a robust ΔΔct estimate and deduce an approximate distribution for it. Simulations show that when data has outliers, the robust ΔΔct estimate compared to the non-robust ΔΔct estimate leads to significantly reduced confidence interval length and a coverage close to the nominal coverage. The analysis of an RT-PCR data from a Novartis clinical trial demonstrates benefit of a robust ΔΔct estimate.
Topics: Algorithms; Biomarkers, Tumor; Clinical Trials as Topic; Gene Expression Profiling; Humans; Real-Time Polymerase Chain Reaction; Reference Standards
PubMed: 33309766
DOI: 10.1016/j.ygeno.2020.12.009