scholarly journals Using network clustering to predict copy number variations associated with health disparities

2014 ◽  
Author(s):  
Yi Jiang ◽  
Hong HQ Qin ◽  
Li Yang
Keyword(s):  
Health Disparities ◽  
African Americans ◽  
Copy Number ◽  
Gene Networks ◽  
The United States ◽  
Copy Number Variations ◽  
Network Clustering ◽  
Network Cluster ◽  
Pathogenic Genes ◽  
Causal Genes

Substantial health disparities exist between African Americans and Caucasians in the United States. Copy number variations (CNVs) are one form of human genetic variations that have been linked with complex diseases and often occur at different frequencies among African Americans and Caucasian populations. Here, we aimed to investigate whether CNVs with differential frequencies can contribute to health disparities from the perspective of gene networks. We inferred network clusters from human gene/protein networks based on two different data sources. We then evaluated each network cluster for the occurrences of known pathogenic genes and genes located in CNVs with different population frequencies, and used false discovery rates to rank network clusters. This approach let us identify five clusters enriched with known pathogenic genes and with genes located in CNVs with different frequencies between African Americans and Caucasians. These clustering patterns predict two candidate causal genes located in four population-specific CNVs that play potential roles in health disparities

scholarly journals Using network clustering to predict copy number variations associated with health disparities

2014 ◽  
Author(s):  
Yi Jiang ◽  
Hong HQ Qin ◽  
Li Yang
Keyword(s):  
Health Disparities ◽  
African Americans ◽  
Copy Number ◽  
Gene Networks ◽  
The United States ◽  
Copy Number Variations ◽  
Network Clustering ◽  
Network Cluster ◽  
Pathogenic Genes ◽  
Causal Genes

Substantial health disparities exist between African Americans and Caucasians in the United States. Copy number variations (CNVs) are one form of human genetic variations that have been linked with complex diseases and often occur at different frequencies among African Americans and Caucasian populations. Here, we aimed to investigate whether CNVs with differential frequencies can contribute to health disparities from the perspective of gene networks. We inferred network clusters from human gene/protein networks based on two different data sources. We then evaluated each network cluster for the occurrences of known pathogenic genes and genes located in CNVs with different population frequencies, and used false discovery rates to rank network clusters. This approach let us identify five clusters enriched with known pathogenic genes and with genes located in CNVs with different frequencies between African Americans and Caucasians. These clustering patterns predict two candidate causal genes located in four population-specific CNVs that play potential roles in health disparities

Classification and characterization of multigene family proteins of African swine fever viruses

2020 ◽  
Author(s):  
Zhaozhong Zhu ◽  
Huiting Chen ◽  
Li Liu ◽  
Yang Cao ◽  
Taijiao Jiang ◽  
...  
Keyword(s):  
Multigene Family ◽  
Copy Number ◽  
African Swine Fever Virus ◽  
African Swine Fever ◽  
Copy Number Variations ◽  
Network Clustering ◽  
Sequence Motifs ◽  
Conserved Sequence ◽  
Protein Sequence Homology ◽  
And Function

Abstract African swine fever virus (ASFV) poses serious threats to the pig industry. The multigene family (MGF) proteins are extensively distributed in ASFVs and are generally classified into five families, including MGF-100, MGF-110, MGF-300, MGF-360 and MGF-505. Most MGF proteins, however, have not been well characterized and classified within each family. To bridge this gap, this study first classified MGF proteins into 31 groups based on protein sequence homology and network clustering. A web server for classifying MGF proteins was established and kept available for free at http://www.computationalbiology.cn/MGF/home.html. Results showed that MGF groups of the same family were most similar to each other and had conserved sequence motifs; the genetic diversity of MGF groups varied widely, mainly due to the occurrence of indels. In addition, the MGF proteins were predicted to have large structural and functional diversity, and MGF proteins of the same MGF family tended to have similar structure, location and function. Reconstruction of the ancestral states of MGF groups along the ASFV phylogeny showed that most MGF groups experienced either the copy number variations or the gain-or-loss changes, and most of these changes happened within strains of the same genotype. It is found that the copy number decrease and the loss of MGF groups were much larger than the copy number increase and the gain of MGF groups, respectively, suggesting the ASFV tended to lose MGF proteins in the evolution. Overall, the work provides a detailed classification for MGF proteins and would facilitate further research on MGF proteins.

Genomics of esophageal squamous cell carcinoma in African Americans.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16552-e16552
Author(s):  
Robert George Wadleigh ◽  
Nirmala Akula ◽  
Susan Lazerow ◽  
Gustavo Marino ◽  
Suman Chauhan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
African Americans ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Mutation Rate ◽  
Squamous Cell ◽  
Copy Number ◽  
Copy Number Variations ◽  
Mesenchymal Transition ◽  
Copy Number Changes

e16552 Background: Esophageal cancer (EC) is one of the most lethal cancers with 90% mortality rate. Uneven Worldwide geographical distribution and varying etiologic factors contribute to the heterogenic nature of EC worldwide. In the US, 75% esophageal squamous cell carcinoma (ESCC) is diagnosed in African Americans (AA). However, despite comprehensive and multi-geographical efforts to understand the genomic basis of ESCC, the knowledge of molecular and genetic mechanisms leading to genomic subtyping of AA has been limited due to the underrepresentation of AAs in these studies. We hypothesized that the differences in mutational events in AA ESCC might, in part, cause the disparity in outcome and the mutational events may determine treatment options. Methods: Whole exome sequencing (WES) of matched- tumor and normal-cell DNA from late-stage ESCC of ten AA patients were performed by using Agilent SureSelect XT Human All Exon V6+UTR. Somatic variants per tumor samples called by two or more methods (Mutect2, VarScan2, and Strelka2) were combined and used for downstream population filtering. Somatic copy number changes were determined by using CNVKit in SevenBridges Genomics. Results: Somatic variants called by two or more algorithms filtered and sorted for rare mutations (equal to or less than 1% African originated population frequency) demonstrated an average of 23 nonsynonymous mutations per MB in high mutation rate AA ESCC. The remaining four samples had two or fewer nonsynonymous mutations per MB. TP53 was one of the most frequently mutated gene with 50% of mutation frequency. ARID2 mutated in 30%, EP300 in 20%, and RB1 in 10% of our cohort. Multiple amplified and deleted regions ranging from 94 to 46 were observed in seven samples in contrast to three samples that were silent in terms of copy number variations ranging from 29 to 9. Significant CNV were mostly seen in proliferation, cell cycle and checkpoint genes, squamous cell homeostasis, epithelial to mesenchymal transition, invasion and metastasis, receptor tyrosine kinase and signaling pathways, chromatin remodeling, detoxification, RNA/DNA editing and angiogenesis. Conclusions: WES of ten AA ESCC samples demonstrated a higher mutation rate in a group of patients with many passenger mutations and complex and recurrent copy number changes that affect oncogenic driver genes, which might suggest enhanced subtyping of ESCC in AA.

scholarly journals Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Yaxin Hou ◽  
Junyi Hu ◽  
Lijie Zhou ◽  
Lilong Liu ◽  
Ke Chen ◽  
...  
Keyword(s):  
Network Analysis ◽  
Clinical Outcomes ◽  
Copy Number ◽  
Rho Gtpase ◽  
Specific Antigen ◽  
The United States ◽  
Prostate Adenocarcinoma ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators

Prostate adenocarcinoma (PRAD) is the most pervasive carcinoma diagnosed in men with over 170,000 new cases every year in the United States and is the second leading cause of death from cancer in men despite its indolent clinical course. Prostate-specific antigen testing, which is the most commonly used non-invasive diagnostic method for PRAD, has improved early detection rates in the past decade, but its effectiveness for monitoring disease progression and predicting prognosis is controversial. To identify novel biomarkers for these purposes, we carried out weighted gene co-expression network analysis of the top 10,000 variant genes in PRAD from The Cancer Genome Atlas in order to identify gene modules associated with clinical outcomes. Methylation and copy number variation analysis were performed to screen aberrantly expressed genes, and the Kaplan–Meier survival and gene set enrichment analyses were conducted to evaluate the prognostic value and potential mechanisms of the identified genes. Cyclin E2 (CCNE2), rhophilin Rho GTPase-binding protein (RHPN1), enhancer of zeste homolog 2 (EZH2), tonsoku-like DNA repair protein (TONSL), epoxide hydrolase 2 (EPHX2), fibromodulin (FMOD), and solute carrier family 7 member (SLC7A4) were identified as potential prognostic indicators and possible therapeutic targets as well. These findings can improve diagnosis and disease monitoring to achieve better clinical outcomes in PRAD.

Health Disparities and the Heterogeneity of Blacks/African Americans in the United States: Why Should We Care?

2019 ◽  
Vol 21 (4) ◽  
pp. 492-495 ◽  
Author(s):  
Ann Oyare Amuta-Jimenez ◽  
Wura Jacobs ◽  
Gabrielle Smith
Keyword(s):  
Health Disparities ◽  
African Americans ◽  
Scientific Evidence ◽  
The United States ◽  
Health Interventions ◽  
Sociocultural Factors ◽  
Black Immigrants ◽  
Public Health Interventions ◽  
Black African ◽  
Health And Mortality

Each year, millions of dollars are spent on research and public health interventions targeted toward reducing health disparities primarily among the “Black/African Americans” community, yet the progress made lags far behind the amount of money and effort spent. We hypothesize that part of the problem is that sociocultural factors play a significant role in disease prevention. Most studies and programs aggregate “Black immigrants” (BIs) and “African Americans” (AAs) as “Black/African American.” This categorization assumes that the sociocultural determinants that influence BIs are the same as for AAs. BIs have health and mortality profiles that vary from AAs. This commentary aims to (1) introduce this idea in more depth and provide a brief scope of the problem, (2) provide scientific evidence of noteworthy differences between AAs and BIs in areas of sociodemographics, health behaviors, and health outcomes, (3) discuss implications of considering the Black/AA group as homogeneous and provide recommendations for disaggregation.

Eliminating Health Disparities in the African American Population: The Interface of Culture, Gender, and Power

2006 ◽  
Vol 33 (4) ◽  
pp. 488-501 ◽  
Author(s):  
Collins O. Airhihenbuwa ◽  
Leandris Liburd
Keyword(s):  
African American ◽  
Health Disparities ◽  
African Americans ◽  
Task Force ◽  
Clinical Care ◽  
The United States ◽  
Task Force Report ◽  
Excess Death ◽  
Sociocultural Environment ◽  
Gender And Power

Since the release of former Secretary Margaret Heckler’s Secretary’s Task Force Report on Black and Minority Health more than two decades ago, excess death from chronic diseases and other conditions between African Americans and Whites have increased. The conclusion of that report emphasized excess death and thus clinical care, paying little attention to the sociocultural environment and its effects on risk of disease. The authors of this article contend that eliminating health disparities between the African American and White populations in the United States requires a focus on improving the social environment of African Americans. They examine the interface of culture, gender, and power and how those are central to analysis of the root causes of health disparities. The REACH 2010 project of the Centers for Disease Control offers examples on how a coalition of community and research organizations can infuse community interventions with informed considerations of culture, gender, and power to eliminate health disparities

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