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Schematic representation of congenital abnormalities in the number of chromosomes in terms of aneuploidy (triploidy and teraploidy) and euploidy (deletion, overexpression, and translocation)
Source publication
Abstract
Cytogenetics is concerned with the structure and number of chromosomes (Karyotyping) and their abnormalities not only
in congenital but also in acquired genetic disorders. Chromosomal abnormalities can form when there is an error occurred
in chromosome number and, or their structural changes. Such changes happen by itself or inductively...
Citations
... A chromosomal abnormality refers to a rearrangement in the structure or number of chromosomes that deviates from the normal karyotype in an organism or cell [20,21]. Such rearrangements can be categorized as constitutional or acquired [19,23]. Constitutional changes are present from conception or occur during the initial divisions of the zygote. ...
Background
Chromosomal abnormalities contribute significantly to human morbidity and mortality, leading to various pathologies. This study aimed to assess the prevalence of chromosomal abnormalities among patients suspected of genetic disorders in Ouagadougou, Burkina Faso.
Methods and results
A descriptive cross-sectional study was conducted from January 1, 2018, to July 16, 2021, involving patients from different university hospitals in Ouagadougou. Blood samples were collected at Hôpital Saint Camille de Ouagadougou (HOSCO) and sent to the Cerba laboratory in France for cytogenetic analysis. A total of 61 cases with suspected genetic disorders were referred for cytogenetic examination. The average age of the patients was 26.81 years ± 18.92, ranging from 1 month to 68 years. Among the cases, 37 (60.65%) exhibited chromosomal abnormalities. Structural abnormalities were the most prevalent (78.38%), while number anomalies accounted for 21.62% of the cases. Chronic myeloid leukemia was detected in 59.45% of cases, followed by free and homogeneous trisomy 21 (18.91%) and sexual inversion (8.10%). Additionally, one case each of Turner syndrome and Klinefelter syndrome were identified.
Conclusion
This this study revealed a high frequency of chromosomal abnormalities, with a predominance of structural abnormalities, among patients suspected of genetic disorders in Ouagadougou. The findings emphasize the significance of genetic evaluation and counseling services in the region, particularly for autosomal abnormalities.
... There are 46 chromosomes in a normal human cell, with a karyotype of 22 pairs of autosomes (classes and two sex chromosomes (either XY in males or XX in females) [1]. There are two main types of chromosomal abnormalities: numerical abnormalities and structural abnormalities [2]. Numerical abnormalities result from the gain or loss of an entire chromosome and can cause Down syndrome, Turner syndrome, Edwards syndrome, and Klinefelter's syndrome [3][4][5]. ...
... That is, the more bands with higher resolution acquired, the easier it was to diagnose. (2). The location and the size of the abnormal fragment were important influencing factors. ...
Background and objective: Karyotyping is an important technique in cytogenetic practice for the early diagnosis of genetic diseases. Clinical karyotyping is tedious, time-consuming, and error-prone. The objective of our study was to develop a single-stage deep convolutional neural networks (DCNN)-based model to automatically classify normal and abnormal chromosomes in an end-to-end manner.
Methods: We analyzed 2,424 normal chromosomes and 544 abnormal chromosomes. A preliminary support vector machine (SVM) model was developed to evaluate the basic recognition performance on the dataset. A DCNN-based model was then proposed to process the same dataset.
Results: By utilizing the SVM model, the classification accuracy of 24 normal chromosomes was 86.01 %. The 32 types of normal and abnormal chromosomes got an accuracy of 85.37 %. The accuracy of the DCNN-based model performing the 24 normal chromosomal classification was 91.75 %. The accuracy of the 32 type classification was 87.76 %. To differentiate eight common structural abnormalities, we obtained accuracies that ranged from
90.84 % to 100 %, and the values of the AUC ranged from 91.81 % to 100 %.
Conclusions: Our proposed DCNN-based model effectively performed the karyotype classification in an end-to-end manner. It had the competence to be used as a prediction tool for abnormal karyotype detection and screening in genetic diagnosis without initial feature extraction. We believe our work is meaningful for genetic triage management
to lower the cost in clinical practice.
... Following sufficient time for hybridisation, the probes are examined under a fluorescence microscope. Under the fluorescence microscope, hybridisation of the DNA probes with the chromosomal DNA may be seen [37,38]. ...
Cancer is caused by genetic changes controlling cell progression and differentiation. These changes are unregulated when tumours advance and acquire invasive and metastatic capacities due to the innate biologic characteristics of the cancer cell. In vivo and in vitro models show that these molecular changes are crucial for tumour development and survival. These molecular changes can be used to develop pristine cancer treatments. New methodological molecules are being developed to identify cancer-specific modifications in proteins, DNA, and RNA, as well as molecular distinctions between healthy and cancer cells. This approach enables effective early detection, precise diagnosis, and quick cancer therapy. DNA microarray techniques have been developed for identifying cancer-associated mutations and gene profiles. Molecular cancer diagnostics need improvement alongside advances in genomics, precision medicine, and immunotherapy. This chapter discusses different molecular diagnostics in the evaluation of cancers.
... Chromosomal abnormalities can appear when there is an anomaly in the structure or number of chromosomes [7]. Conventional karyotyping analysis is the gold standard for prenatal diagnosis of chromosomal abnormalities, although it is considered to be a time-consuming and labour-intensive technique [8]. ...
... Several studies have compared the diagnostic efficiency of BoBs [12,13], microarrays [14] and conventional karyotyping [7]. However, those studies were from different laboratories and used various detection platforms and inconsistent reporting criteria. ...
Background
A growing number of cytogenetic techniques have been used for prenatal diagnosis. This study aimed to demonstrate the usefulness of karyotyping, BACs-on-Beads (BoBs) assay and single nucleotide polymorphism (SNP) array in prenatal diagnosis during the second trimester based on our laboratory experience.
Methods
A total of 10,580 pregnant women with a variety of indications for amniocentesis were enrolled in this retrospective study between January 2015 and December 2020, of whom amniotic fluid samples were analysed in 10,320 women. The main technical indicators of participants in the three different technologies were summarized, and cases of chromosome abnormalities were further evaluated.
Results
The overall abnormality detection rate of karyotyping among all the amniotic fluid samples was 15.4%, and trisomy 21 was the most common abnormality (20.9%). The total abnormality detection rate of the BoBs assay was 5.6%, and the diagnosis rate of microdeletion/microduplication syndromes that were not identified by karyotyping was 0.2%. The detection results of the BoBs assay were 100.0% concordant with karyotyping analysis in common aneuploidies. Seventy (87.5%) cases of structural abnormalities were missed by BoBs assay. The total abnormality detection rate of the SNP array was 21.6%. The detection results of common aneuploidies were exactly the same between SNP array and karyotyping. Overall, 60.1% of structural abnormalities were missed by SNP array. The further detection rate of pathogenic significant copy number variations (CNVs) by SNP was 1.4%.
Conclusions
Karyotyping analysis combined with BoBs assay or SNP array for prenatal diagnosis could provide quick and accurate results. Combined use of the technologies, especially with SNP array, improved the diagnostic yield and interpretation of the results, which contributes to genetic counselling. BoBs assay or SNP array could be a useful supplement to karyotyping.
... 8 Chromosomal abnormalities include numerical chromosomal abnormalities (such as monosomy, trisomy and polyploidy) and structural chromosomal abnormalities (such as deletion, duplication, insertion, inversion, cross-displacement, ring chromosome and translocation). 9,10 Around the beginning of the 21st Century, scientists began to recognize an intermediate size variation. Copy number variants (CNVs) are copy number changes of the genome, with variants ranging in size from several dozens of bases (> 50 bp) to megabases. ...
Objective:
To explore the etiological relationship between miscarriage and stillbirth and copy number variations (CNVs), and to provide useful genetic guidance for high-risk pregnancy.
Methods:
659 fetal samples were recruited and subjected to DNA extraction and CNV sequencing (CNV-Seq), relevant medical records were collected.
Results:
There were 322 cases (48.86%) with chromosomal abnormalities, including 230 with numerical abnormalities, 92 with structural abnormalities. Chromosomal monosomy variations mainly occurred on sex chromosomes, and trisomy variations mainly occurred on chromosomes 16, 22, 21, 18, 13, and 15. 41 pathogenic CNVs (23 microdeletions and 18 microduplications) were detected in 27 fetal tissues. The rates of numerical chromosomal abnormalities were 29.30% (109/372), 32.39% (57/176) and 57.66% (64/111) in <30-year old, 30-34-year old, and ≥35-year old age pregnant women, respectively, increased with the increasing age (P<0.001). There was statistically significant difference (χ2 =7.595, P=0.022) in the rates of structural chromosomal abnormalities in these groups (13.71%, 18.75% and 7.21%, respectively). The rates of numerical chromosomal abnormalities were 45.44% (219/482), 7.80% (11/141) and 0% (0/36) in ≤13 gestational weeks, 14-27 weeks, and ≥28 weeks groups, respectively, decreased with the increasing gestational week of fetuses (P<0.001).
Conclusion:
Some useful and accurate genetic etiology information has been obtained, it provides useful genetic guidance for high-risk pregnancy.
