Publications by authors named "Guimin Gao"

Article Synopsis
  • * This study introduced a comprehensive multi-tissue joint splicing-TWAS approach that analyzed splicing signals across 11 tissues and used data from a large sample of 424,650 women, leading to the identification of 240 significant genes.
  • * The findings revealed that many of these genes were novel, with 88 not previously reported and 110 identified solely via splicing-TWASs, indicating that splicing events may significantly influence breast cancer risk, independent of traditional gene expression measures.
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Background: Although several transcriptome-wide association studies (TWASs) have been performed to identify genes associated with overall breast cancer (BC) risk, only a few TWAS have explored the differences in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) breast cancer. Additionally, these studies were based on gene expression prediction models trained primarily in breast tissue, and they did not account for alternative splicing of genes.

Methods: In this study, we utilized two approaches to perform multi-tissue TWASs of breast cancer by ER subtype: (1) an expression-based TWAS that combined TWAS signals for each gene across multiple tissues and (2) a splicing-based TWAS that combined TWAS signals of all excised introns for each gene across tissues.

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Article Synopsis
  • Genome-wide association studies (GWAS) have identified common variants associated with breast cancer (BC), but the specific genes and their effects on BC subtypes are still unclear.
  • This study used transcriptome-wide association studies (TWAS) to analyze gene expression and splicing across various tissues, revealing 235 genes linked to five distinct BC subtypes in a large sample of cases and controls.
  • The findings highlight subtype-specific genes, such as CHEK2 for Luminal A-like BC and MDM4 for triple-negative BC, providing new insights into the genetic risk factors for different types of breast cancer.
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Genome-wide association studies (GWAS) have led to rapid growth in detecting genetic variants associated with various phenotypes. Owing to a great number of publicly accessible GWAS summary statistics, and the difficulty in obtaining individual-level genotype data, many existing gene-based association tests have been adapted to require only GWAS summary statistics rather than individual-level data. However, these association tests are restricted to unrelated individuals and thus do not apply to family samples directly.

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Article Synopsis
  • Scientists looked at how certain genes may affect breast cancer in women with African ancestry.
  • They studied 9,241 women with breast cancer and compared them to 10,193 healthy women to find links between the genes and the disease.
  • They found specific gene variations that could increase the risk of breast cancer, especially types of cancer that don't depend on estrogen.
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Developing a confidence interval for the ratio of two quantities is an important task in statistics because of its omnipresence in real world applications. For such a problem, the MOVER-R (method of variance recovery for the ratio) technique, which is based on the recovery of variance estimates from confidence limits of the numerator and the denominator separately, was proposed as a useful and efficient approach. However, this method implicitly assumes that the confidence interval for the denominator never includes zero, which might be violated in practice.

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Article Synopsis
  • Genome-wide association studies (GWASs) have pinpointed over 200 genomic loci linked to breast cancer risk, but many causal genes remain unidentified.
  • A joint analysis combining results from the UK Biobank and the Breast Cancer Association Consortium revealed eight new loci and identified 309 significant genes associated with breast cancer through transcriptome-wide association studies (TWASs).
  • The study enhances understanding of breast cancer genetics by mapping candidate genes in existing loci while also uncovering new genomic regions related to the disease.
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Objectives: Mesothelioma is a lethal disease that arises from the serosal lining of organ cavities. Several recurrent alterations have been observed in pleural and peritoneal -mesotheliomas, including in BAP1, NF2, and CDKN2A. Although specific histopathologic parameters have been correlated with prognosis, it is not as well known whether genetic alterations correlate with histologic findings.

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Purpose: Guidelines recommend all patients with pancreatic ductal adenocarcinoma (PDAC) undergo germline genetic testing (GT). Rates of recommendation and completion of GT among diverse patients with PDAC are not known. The aim was to determine rates of recommendation and completion of point-of-care GT in diverse patients with PDAC.

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There is increasing recognition that pathogenic germ line variants drive the development of hematopoietic cancers in many individuals. Currently, patients with hereditary hematologic malignancies (HHMs) receive similar standard therapies and hematopoietic stem cell transplant (HSCT) approaches as those with sporadic disease. We hypothesize that patients with myeloid malignancies and deleterious germ line predisposition variants have different posttransplant outcomes than those without such alleles.

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Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10ā€‰184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana.

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Background: DNA methylation and gene expression are known to play important roles in the etiology of human diseases such as prostate cancer (PCa). However, it has not yet been possible to incorporate information of DNA methylation and gene expression into polygenic risk scores (PRSs). Here, we aimed to develop and validate an improved PRS for PCa risk by incorporating genetically predicted gene expression and DNA methylation, and other genomic information using an integrative method.

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Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at Pā€‰<ā€‰0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium.

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Article Synopsis
  • Polygenic risk scores (PRSs) can identify increased breast cancer risk in women of African ancestry, but they are less effective than in European, Asian, and Latino populations.
  • A study with over 9,200 cases and 10,000 controls evaluated PRSs and found that the odds of developing breast cancer increased with higher PRS scores.
  • Despite the potential of a recalibrated PRS to better represent risk in African women, it did not significantly enhance breast cancer risk prediction, indicating a need for further research tailored to this demographic.
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Objectives: Prior literature has suggested a decreased prevalence of pelvic organ prolapse (POP) in Black women. We sought to describe POP rates by race, investigate whether specific types of prolapse differ based on race, and investigate the role of uterine weight and fibroids on POP.

Methods: We conducted a retrospective cohort study of new patients seen between April 2017 and April 2019 at a tertiary urogynecology clinic.

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Constructing a confidence interval for the ratio of bivariate normal means is a classical problem in statistics. Several methods have been proposed in the literature. The Fieller method is known as an exact method, but can produce an unbounded confidence interval if the denominator of the ratio is not significantly deviated from 0; while the delta and some numeric methods are all bounded, they are only first-order correct.

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Background: There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts.

Methods: We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.

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Background: Although several studies have associated the use of nonsteroidal anti-inflammatory drugs with disease flares in patients with inflammatory bowel disease (IBD), little is known about the impact of daily aspirin use on clinical outcomes in patients with IBD.

Methods: We conducted a retrospective analysis of a prospectively collected registry of patients with IBD from May 2008 to June 2015. Patients with any disease activity with daily aspirin use were matched 1:4 to controls by age, sex, disease, disease location, and presence of cardiac comorbidity.

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Background: Despite the abundance of data documenting the consequences of poor sleep quality on blood pressure (BP), no previous study to our knowledge has addressed the impact of sleep improvement on resistant hypertension among patients with chronic kidney disease (CKD).

Methods: The aim of this pilot study was to determine whether improved sleep quality and duration will improve BP control in patients with resistant hypertension and CKD. It was a prospective single-center cohort study that involved 30 hypertensive subjects with CKD presenting with primary resistant hypertension and poor sleep quality or duration <6 h/night.

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Somatic mutation signatures may represent footprints of genetic and environmental exposures that cause different cancer. Few studies have comprehensively examined their association with germline variants, and none in an indigenous African population. SomaticSignatures was employed to extract mutation signatures based on whole-genome or whole-exome sequencing data from female patients with breast cancer (TCGA, training set, n = 1,011; Nigerian samples, validation set, n = 170), and to estimate contributions of signatures in each sample.

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Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and is characterized by gradual cyst growth and expansion, increase in kidney volume with an ultimate decline in kidney function leading to end stage renal disease (ESRD). Given the decades long period of stable kidney function while cyst growth occurs, it is important to identify those patients who will progress to ESRD. Recent data from our and other laboratories have demonstrated that metabolic reprogramming may play a key role in cystic epithelial proliferation resulting in cyst growth in ADPKD.

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It has been well acknowledged that methods for secondary trait (ST) association analyses under a case-control design (ST$_{\text{CC}}$) should carefully consider the sampling process to avoid biased risk estimates. A similar situation also exists in the extreme phenotype sequencing (EPS) designs, which is to select subjects with extreme values of continuous primary phenotype for sequencing. EPS designs are commonly used in modern epidemiological and clinical studies such as the well-known National Heart, Lung, and Blood Institute Exome Sequencing Project.

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Testicular cell apoptosis is associated with impaired spermatogenesis. It has been reported that Asiatic acid (AA) may suppress apoptosis. However, little is known about the effect of AA on high-fat diet (HFD)-induced impairment of spermatogenesis.

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