Extreme Downregulation of Chromosome Y and Cancer Risk in Men

Abstract Background Understanding the biological differences between sexes in cancer is essential for personalized treatment and prevention. We hypothesized that the extreme downregulation of chromosome Y gene expression (EDY) is a signature of cancer risk in men and the functional mediator of the reported association between the mosaic loss of chromosome Y (LOY) and cancer. Methods We advanced a method to measure EDY from transcriptomic data. We studied EDY across 47 nondiseased tissues from the Genotype Tissue-Expression Project (n = 371) and its association with cancer status across 12 cancer studies from The Cancer Genome Atlas (n = 1774) and seven other studies (n = 7562). Associations of EDY with cancer status and presence of loss-off function mutations in chromosome X were tested with logistic regression models, and a Fisher’s test was used to assess genome-wide association of EDY with the proportion of copy number gains. All statistical tests were two-sided. Results EDY was likely to occur in multiple nondiseased tissues (P < .001) and was statistically significantly associated with the EGFR tyrosine kinase inhibitor resistance pathway (false discovery rate = 0.028). EDY strongly associated with cancer risk in men (odds ratio [OR] = 3.66, 95% confidence interval [CI] = 1.58 to 8.46, P = .002), adjusted by LOY and age, and its variability was largely explained by several genes of the nonrecombinant region whose chromosome X homologs showed loss-of-function mutations that co-occurred with EDY during cancer (OR = 2.82, 95% CI = 1.32 to 6.01, P = .007). EDY associated with a high proportion of EGFR amplifications (OR = 5.64, 95% CI = 3.70 to 8.59, false discovery rate < 0.001) and EGFR overexpression along with SRY hypomethylation and nonrecombinant region hypermethylation, indicating alternative causes of EDY in cancer other than LOY. EDY associations were independently validated for different cancers and exposure to smoking, and its status was accurately predicted from individual methylation patterns. Conclusions EDY is a male-specific signature of cancer susceptibility that supports the escape from X-inactivation tumor suppressor hypothesis for genes that protect women compared with men from cancer risk.

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Blood DNA Methylation and Breast Cancer: A Prospective Case-Cohort Analysis in the Sister Study

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djz065 ◽

2019 ◽

Vol 112 (1) ◽

pp. 87-94 ◽

Cited By ~ 17

Author(s):

Zongli Xu ◽

Dale P Sandler ◽

Jack A Taylor

Keyword(s):

Breast Cancer ◽

Dna Methylation ◽

False Discovery Rate ◽

Invasive Breast Cancer ◽

Ductal Carcinoma ◽

Statistical Tests ◽

Cohort Analysis ◽

Cancer Susceptibility Genes ◽

False Discovery ◽

Time To Diagnosis

Abstract Background Peripheral blood DNA methylation may be associated with breast cancer, but studies of candidate genes and global and genome-wide DNA methylation have been inconsistent. Methods We performed an epigenome-wide study using Infinium HumanMethylation450 BeadChips with prospectively collected blood DNA samples from the Sister Study (1552 cases, 1224 subcohort). Differentially methylated cytosine-phosphate-guanine sites (dmCpGs) were identified using case-cohort proportional hazard models and replicated using deposited data from European Prospective Investigation into Cancer and Nutrition in Italy (EPIC-Italy) (n = 329). The correlation between methylation and time to diagnosis was examined using robust linear regression. Causal or consequential relationships of methylation to breast cancer were examined by Mendelian randomization using OncoArray 500 K single-nucleotide polymorphism data. All statistical tests were two-sided. Results We identified 9601 CpG markers associated with invasive breast cancer (false discovery rate = q < 0.01), with 510 meeting a strict Bonferroni correction threshold (10–7). A total of 2095 of these CpGs replicated in the independent EPIC-Italy dataset, including 144 meeting the Bonferroni threshold. Sister Study women who developed ductal carcinoma in situ had methylation similar to noncases. Most (1501, 71.6%) dmCpGs showed lower methylation in invasive cases. In case-only analysis, methylation was statistically significantly associated (false discovery rate = q < 0.05) with time to diagnosis for 892 (42.6%) of the dmCpGs. Analyses based on genetic association suggest that methylation differences are likely a consequence rather than a cause of breast cancer. Pathway analysis shows enrichment of breast cancer-related gene pathways, and dmCpGs are overrepresented in known breast cancer susceptibility genes. Conclusions Our findings suggest that the DNA methylation profile of blood starts to change in response to invasive breast cancer years before the tumor is clinically detected.

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Identification of Genetic Variants Associated with Sex-Specific Lung-Cancer Risk

Cancers ◽

10.3390/cancers13246379 ◽

2021 ◽

Vol 13 (24) ◽

pp. 6379

Author(s):

Xiaoshun Shi ◽

Sylvia Young ◽

Grant Morahan

Keyword(s):

Lung Cancer ◽

Cancer Risk ◽

X Chromosome ◽

Genetic Variants ◽

Lung Cancer Risk ◽

Cancer Susceptibility ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Sequencing Data ◽

Lung Cancer Patients

Background: The incidence of lung cancer differs between men and women, suggesting the potential role of sex-specific influences in susceptibility to this cancer. While behavioural differences may account for some of the risk, another possibility is that X chromosome susceptibility genes may have an effect. Little is known about genetic variants on the X chromosome that contribute to sex-specific lung-cancer risk, so we investigated this in a previously characterized cohort. Methods: We conducted a genetic association reanalysis of 518 lung cancer patients and 844 controls to test for lung cancer susceptibility variants on the X chromosome. Annotated gene expression, co-expression analysis, pathway, and immune infiltration analyses were also performed. Results: 24 SNPs were identified as significantly associated with male, but not female, lung cancer cases. These resided in blocks near the annotated genes DMD, PTCHD1-AS, and AL008633.1. Of these, DMD was differentially expressed in lung cancer cases curated in The Cancer Genome Atlas. A functional enrichment and a KEGG pathway analysis of co-expressed genes revealed that differences in immune function could play a role in sex-specific susceptibility. Conclusions: Our analyses identified potential genetic variants associated with sex-specific lung cancer risk. Integrating GWAS and RNA-sequencing data revealed potential targets for lung cancer prevention.

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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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