scholarly journals Clinical implications of copy number variations in autoimmune disorders

2015 ◽  
Vol 30 (3) ◽  
pp. 294 ◽  
Author(s):  
Seon-Hee Yim ◽  
Seung-Hyun Jung ◽  
Boram Chung ◽  
Yeun-Jun Chung
Keyword(s):  
Copy Number ◽  
Copy Number Variations ◽  
Autoimmune Disorders ◽  
Clinical Implications

Recurrent copy number variations as risk factors for autism spectrum disorders: analysis of the clinical implications

2016 ◽  
Vol 89 (6) ◽  
pp. 708-718 ◽  
Author(s):  
V. Oikonomakis ◽  
K. Kosma ◽  
A. Mitrakos ◽  
C. Sofocleous ◽  
P. Pervanidou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Autism Spectrum Disorders ◽  
Copy Number ◽  
Autism Spectrum ◽  
Copy Number Variations ◽  
Clinical Implications ◽  
Spectrum Disorders

scholarly journals The integrated multiomic diagnosis of sporadic meningiomas: a review of its clinical implications

2021 ◽  
Author(s):  
Stephanie M. Robert ◽  
Shaurey Vetsa ◽  
Arushii Nadar ◽  
Sagar Vasandani ◽  
Mark W. Youngblood ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Clinical Trials ◽  
Copy Number ◽  
Clinical Characteristics ◽  
Copy Number Variations ◽  
Driver Mutations ◽  
Clinical Implications ◽  
Tumor Characteristics ◽  
And Behavior

Abstract Introduction Meningiomas are generally considered “benign,” however, these tumors can demonstrate variability in behavior and a surprising aggressiveness with elevated rates of recurrence. The advancement of next-generation molecular technologies have led to the understanding of the genomic and epigenomic landscape of meningiomas and more recent correlations with clinical characteristics and behavior. Methods Based on a thorough review of recent peer-reviewed publications (PubMed) and edited texts, we provide a molecular overview of meningiomas with a focus on relevant clinical implications. Results The identification of specific somatic driver mutations has led to the classification of several major genomic subgroups, which account for more than 80% of sporadic meningiomas, and can be distinguished using noninvasive clinical variables to help guide management decisions. Other somatic genomic modifications, including non-coding alterations and copy number variations, have also been correlated with tumor characteristics. Furthermore, epigenomic modifications in meningiomas have recently been described, with DNA methylation being the most widely studied and potentially most clinically relevant. Based on these molecular insights, several clinical trials are currently underway in an effort to establish effective medical therapeutic options for meningioma. Conclusion As we enhance our multiomic understanding of meningiomas, our ability to care for patients with these tumors will continue to improve. Further biological insights will lead to additional progress in precision medicine for meningiomas.

X-linked CNV and skewed X-chromosome inactivation

2020 ◽  
pp. 19-21
Author(s):  
Е.А. Фонова ◽  
Е.Н. Толмачева ◽  
А.А. Кашеварова ◽  
М.Е. Лопаткина ◽  
К.А. Павлова ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Intellectual Disability ◽  
X Chromosome ◽  
Copy Number ◽  
Copy Number Variations ◽  
X Chromosome Inactivation ◽  
Chromosome Inactivation ◽  
Chromosome X ◽  
Skewed X Chromosome Inactivation

Смещение инактивации Х-хромосомы может быть следствием и маркером нарушения клеточной пролиферации при вариациях числа копий ДНК на Х-хромосоме. Х-сцепленные CNV выявляются как у женщин с невынашиванием беременности и смещением инактивации Х-хромосомы (с частотой 33,3%), так и у пациентов с умственной отсталостью и смещением инактивацией у их матерей (с частотой 40%). A skewed X-chromosome inactivation can be a consequence and a marker of impaired cell proliferation in the presence of copy number variations (CNV) on the X chromosome. X-linked CNVs are detected in women with miscarriages and a skewed X-chromosome inactivation (with a frequency of 33.3%), as well as in patients with intellectual disability and skewed X-chromosome inactivation in their mothers (with a frequency of 40%).

scholarly journals Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans

2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim
Keyword(s):  
Copy Number ◽  
Genome Wide Association Study ◽  
Copy Number Gain ◽  
Copy Number Variations ◽  
Gene Gain ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Control And Prevention

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

scholarly journals Performance of In Silico Prediction Tools for the Detection of Germline Copy Number Variations in Cancer Predisposition Genes in 4208 Female Index Patients with Familial Breast and Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 118
Author(s):  
Louisa Lepkes ◽  
Mohamad Kayali ◽  
Britta Blümcke ◽  
Jonas Weber ◽  
Malwina Suszynska ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
In Silico ◽  
Copy Number ◽  
Gc Content ◽  
Copy Number Variations ◽  
Cancer Predisposition ◽  
Predictive Values ◽  
Prediction Tools ◽  
Predisposition Genes ◽  
Female Index

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.

Sign in / Sign up

Export Citation Format

Share Document