Characterization of Polybrominated Diphenyl Ether Toxicity in Wistar Han Rats and Use of Liver Microarray Data for Predicting Disease Susceptibilities

The toxicity of polybrominated diphenyl ethers (PBDEs), flame-retardant components, was characterized in offspring from Wistar Han dams exposed by gavage to a PBDE mixture (DE71) starting at gestation day 6 and continuing to weaning on postnatal day (PND) 21. Offspring from the dams underwent PBDE direct dosing by gavage at the same dose as their dams from PND 12 to PND 21, and then after weaning for another thirteen weeks. Liver samples were collected at PND 22 and week 13 for liver gene expression analysis (Affymetrix Rat Genome 230 2.0 Array). Treatment with PBDE induced 1,066 liver gene transcript changes in females and 1,200 transcriptional changes in males at PND 22 (false discovery rate < 0.01), but only 263 liver transcriptional changes at thirteen weeks in male rats (false discovery rate < 0.05). No significant differences in dose response were found between male and female pups. Transcript changes at PND 22 coded for proteins in xenobiotic, sterol, and lipid metabolism, and cell cycle regulation, and overlapped rodent liver transcript patterns after a high-fat diet or phenobarbital exposure. These findings, along with the observed PBDE-induced liver hypertrophy and vacuolization, suggest that long-term PBDE exposure has the potential to modify cell functions that contribute to metabolic disease and/or cancer susceptibilities.

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Polybrominated Diphenyl Ether (DE-71) Interferes With Thyroid Hormone Action Independent of Effects on Circulating Levels of Thyroid Hormone in Male Rats

Endocrinology ◽

10.1210/en.2014-1154 ◽

2014 ◽

Vol 155 (10) ◽

pp. 4104-4112 ◽

Cited By ~ 18

Author(s):

Ruby Bansal ◽

Daniel Tighe ◽

Amin Danai ◽

Dorothea F. K. Rawn ◽

Dean W. Gaertner ◽

...

Keyword(s):

Thyroid Hormone ◽

Polybrominated Diphenyl Ethers ◽

Diphenyl Ether ◽

Chemical Exposure ◽

Epidemiological Studies ◽

Heart Tissue ◽

Male Rats ◽

Pregnant Rats ◽

Serum T4 ◽

Human Fetal Tissues

Abstract Polybrominated diphenyl ethers (PBDEs) are routinely found in human tissues including cord blood and breast milk. PBDEs may interfere with thyroid hormone (TH) during development, which could produce neurobehavioral deficits. An assumption in experimental and epidemiological studies is that PBDE effects on serum TH levels will reflect PBDE effects on TH action in tissues. To test whether this assumption is correct, we performed the following experiments. First, five concentrations of diphenyl ether (0–30 mg/kg) were fed daily to pregnant rats to postnatal day 21. PBDEs were measured in dam liver and heart to estimate internal dose. The results were compared with a separate study in which four concentrations of propylthiouracil (PTU; 0, 1, 2, and 3 ppm) was provided to pregnant rats in drinking water for the same duration as for diphenyl ether. PBDE exposure reduced serum T4 similar in magnitude to PTU, but serum TSH was not elevated by PBDE. PBDE treatment did not affect the expression of TH response genes in the liver or heart as did PTU treatment. PTU treatment reduced T4 in liver and heart, but PBDE treatment reduced T4 only in the heart. Tissue PBDEs were in the micrograms per gram lipid range, only slightly higher than observed in human fetal tissues. Thus, PBDE exposure reduces serum T4 but does not produce effects on tissues typical of low TH produced by PTU, demonstrating that the effects of chemical exposure on serum T4 levels may not always be a faithful proxy measure of chemical effects on the ability of thyroid hormone to regulate development and adult physiology.

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Faculty Opinions recommendation of An investigation of the false discovery rate and the misinterpretation of p-values.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725432010.793514527 ◽

2016 ◽

Author(s):

Geoffrey Goodhill

Keyword(s):

False Discovery Rate ◽

P Values ◽

False Discovery

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A simple yet efficient method of local false discovery rate estimation designed for genome-wide association data analysis

Statistical Methods & Applications ◽

10.1007/s10260-021-00560-y ◽

2021 ◽

Author(s):

Ali Karimnezhad

Keyword(s):

Data Analysis ◽

False Discovery Rate ◽

Efficient Method ◽

Genome Wide Association ◽

Local False Discovery Rate ◽

Rate Estimation ◽

False Discovery ◽

Genome Wide ◽

False Discovery Rate Estimation ◽

Association Data

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False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation

Journal of the American Statistical Association ◽

10.1080/01621459.2021.1945459 ◽

2021 ◽

pp. 1-34

Author(s):

Lilun Du ◽

Xu Guo ◽

Wenguang Sun ◽

Changliang Zou

Keyword(s):

False Discovery Rate ◽

Rate Control ◽

Data Aggregation ◽

False Discovery Rate Control ◽

False Discovery

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False Discovery Rate in Linkage and Association Genome Screens for Complex Disorders

Genetics ◽

10.1093/genetics/164.2.829 ◽

2003 ◽

Vol 164 (2) ◽

pp. 829-833

Author(s):

Chiara Sabatti ◽

Susan Service ◽

Nelson Freimer

Keyword(s):

Gene Mapping ◽

False Discovery Rate ◽

Disease Gene ◽

Susceptibility Genes ◽

Complex Disorders ◽

Disease Gene Mapping ◽

False Discovery ◽

Simple Step ◽

Multiple Comparison Procedure ◽

Step Down

Abstract We explore the implications of the false discovery rate (FDR) controlling procedure in disease gene mapping. With the aid of simulations, we show how, under models commonly used, the simple step-down procedure introduced by Benjamini and Hochberg controls the FDR for the dependent tests on which linkage and association genome screens are based. This adaptive multiple comparison procedure may offer an important tool for mapping susceptibility genes for complex diseases.

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P14.21 Tehila Kaisman-Elbaz MD/PhD

Neuro-Oncology ◽

10.1093/neuonc/noz126.256 ◽

2019 ◽

Vol 21 (Supplement_3) ◽

pp. iii71-iii71

Author(s):

T Kaisman-Elbaz ◽

Y Elbaz ◽

V Merkin ◽

L Dym ◽

A Noy ◽

...

Keyword(s):

Overall Survival ◽

Multivariate Analysis ◽

False Discovery Rate ◽

Medical Center ◽

Tumor Resection ◽

Multiple Hypothesis Testing ◽

Hemoglobin Level ◽

Distribution Width ◽

False Discovery ◽

Dismal Prognosis

Abstract BACKGROUND Glioblastoma is known for its dismal prognosis though its dependency on patients’ readily available RBCs parameters defining the patient’s anemic status such as hemoglobin level and Red blood cells distribution Width (RDW) is not fully established. Several works demonstrated a connection between low hemoglobin level or high RDW values to overall glioblastoma patient’s survival, but in other works, a clear connection was not found. This study addresses this unclarity. MATERIAL AND METHODS In this work, 170 glioblastoma patients, diagnosed and treated in Soroka University Medical Center (SUMC) in the last 12 years were retrospectively inspected for their survival dependency on pre-operative RBCs parameters using multivariate analysis followed by false discovery rate procedure due to the multiple hypothesis testing. A survival stratification tree and Kaplan-Meier survival curves that indicate the patient’s prognosis according to these parameters were prepared. RESULTS Beside KPS>70 and tumor resection supplemented by oncological treatment, age<70 (HR=0.4, 95% CI 0.24–0.65), low hemoglobin level (HR=1.79, 95% CI 1.06–2.99) and RDW<14% (HR=0.57, 95% CI 0.37–0.88) were found to be prognostic to patients’ overall survival in multivariate analysis, accounting for false discovery rate of less than 5%. CONCLUSION A survival stratification highlighted a non-anemic subgroup of nearly 30% of the cohort’s patients whose median overall survival was 21.1 months (95% CI 16.2–27.2) - higher than the average Stupp protocol overall median survival of about 15 months. A discussion on the beneficial or detrimental effect of RBCs parameters on glioblastoma prognosis and its possible causes is given.

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Associations Between Genetically Predicted Protein Levels and COVID-19 Severity

The Journal of Infectious Diseases ◽

10.1093/infdis/jiaa660 ◽

2020 ◽

Vol 223 (1) ◽

pp. 19-22

Author(s):

Jingjing Zhu ◽

Chong Wu ◽

Lang Wu

Keyword(s):

False Discovery Rate ◽

Drug Repurposing ◽

Bonferroni Correction ◽

Host Genetics ◽

Protein Levels ◽

False Discovery

Abstract It is critical to identify potential causal targets for SARS-CoV-2, which may guide drug repurposing options. We assessed the associations between genetically predicted protein levels and COVID-19 severity. Leveraging data from the COVID-19 Host Genetics Initiative comparing 6492 hospitalized COVID-19 patients and 1 012 809 controls, we identified 18 proteins with genetically predicted levels to be associated with COVID-19 severity at a false discovery rate of <0.05, including 12 that showed an association even after Bonferroni correction. Of the 18 proteins, 6 showed positive associations and 12 showed inverse associations. In conclusion, we identified 18 candidate proteins for COVID-19 severity.

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