With the continuous development of next-generation sequencing (NGS), more research and medical testing in recent years have begun to adopt NGS to explore sequence variation[14; 15]. Compared with methods of microarray, NGS has the advantages of greater single throughput, faster detection speed, higher resolution, lower cost, and high repeatability. For the identification of chromosomal abnormalities at the sub-microscopic level, the most common method was CNV-seq, it was based on estimating the extension of different statistical models in the confidence interval, and was suitable for the comparison and recognition of the proportion of CNVs[16]. Different from microarray genotyping of target fragments, CNV-seq adopted the READS reference sequence as a template[17]. When comparing sequences, double of Shotgun sequences were adopted for pairing, and two-dimensional sequence comparisons were performed with the templates. The data reading method was Slide Window Mode, finally, we compared the confidence level of the calculation results with above method was not suitable for long sequences and the accuracy of analysis of large fragments needs to be improved[18].
ABD is actually an adaptive behavior defect and cognitive impairment accompanied by human development. The prevalence rate of this disease is about 6%-8%. It is one of the important diseases that endanger physical and mental health. The main causes include genetic and environmental factors. Chromosomal abnormalities, gene mutations, and pCNVs might all lead to the occurrence of ABD. About 30–40% of ABD patients were caused by chromosomal abnormalities. In addition, the prevalence of ABD in the general population about was 1%~3%[19]. China has a very large population, so the number of ABD patients is correspondingly considerable. According to the current situation, most patients with ABD lack effective and targeted prevention and treatment. In other words, it is very important to clarify the cause of ABD. However, the etiology of ABD is very complicated. Based on data from the World Health Organization, it is reported that more than 50% of ABD patients have unknown causes of disease. In China, this rate is even more serious, accounting for about 67%[20]. In fact, genetic factors play a key role in ABD. ABD was divided into S-ABD and NS-ABD. The clinical phenotypes of patients with NS-ABD mainly include typical language disorders, motor developmental delays, and mental decline; unlike NS-ABD, patients with S-ABD included the above abnormalities, but also combine other diseases or systemic deformities, included congenital heart disease, abnormal face, and cleft lip and palate[21].
In current study, 130 ABD patients were selected for CNV-seq analysis. In addition, we combined the clinical phenotypes and ultrasound indicators of the patients involved in the study to group the ABD patient population into NS-ABD group and S-ABD group. Through data analysis, it was suggested that there were 42 cases of abnormal results (42/130). It was worth noting that among these patients, there have been cases where the same patient contains multiple CNVs regional abnormalities. In other words, the same patient carries 2 or more abnormal CNVs at the same time. More and more studies have shown that the adopt of CNV-seq method in genetic diseases that might be caused by chromosomal aberrations such as mental developmental delay and sexual dysplasia could be very effective in improving the detection rate. Therefore, the method was indeed worthy of being recommended as one of the suitable methods for clinical diagnosis [22], Based on the statistical results of this study, our detection rate is as high as 32.3%, which also supports the above view. In current study, the cases detected by CNV-seq included ABD patients with aneuploidy abnormalities, and in addition, they also included ABD patients caused by pCNVs. According to the classification of ABD phenotypes, we further performed an intergroup comparison between NS-ABD and S-ABD, and the results showed that there was a significant difference (χ2 = 40.03, P<0.05) in the detection rate of pathogenic CNVs between the these of two groups. What’s more, based on the results of inter-group comparison, this study continued to analyze the difference in the positivity rate (total detection rate) of the two pathogenic factors aneuploidy abnormality and pCNVs. The results suggested that in the above-mentioned patient groups, the positivity rate of the NS-ABD group was 33.33%, and the positivity rate of the S-ABD group was 77.78%, obviously, the positivity rate of the two groups of patients was also significantly different (χ2 = 40.97, P < 0.05). According to the results above, the current study showed that chromosomal abnormalities and pCNVS were indeed more likely to appear among S-ABD patients. And there were limitations of the above methods: considering that many patients refuse to provide their own information for the current study, the data volume of this study was not large, the current rate of detection and positivity could be fluctuating or uncertain. We would further increase the number of samples or patient groups in future studies.
In the current study, a total of 27 kinds of pCNVs included 15q11.2-q13.2, 2q33.1-q33.3, 17p11.2 and Xp22.33-p11.1 were found, pCNVs such as 15q11.2-q13.2 micro-deletion syndrome[23] and 22q11.21 microdeletion syndrome[24], which have been reported various times and might cause ABD, have been discovered in the current studies, What's more, we also found rarely reported pCNV fragments associated with ABD such as p11.23. There was no obvious pattern in the distribution of these of pCNVs within the chromosomes, which further indicated the widespread of the ABD-associated CNVs region, and also suggested the complexity of the ABD genetic mechanism. Therefore, we adopted the information included in the such four public databases DECIPHER, OMIM, ClinGen and PubMed, and then investigated the highly associated genes located close to the region where the pCNVs fragments appeared, based on the above-mentioned pCNVs fragments. a total of 7 candidate genes associated with ABD were selected. Within the 15q11.2-q13.2 chromosomal region, mutations in the UBE3A and AUTS2 genes were associated with two distinct neurodevelopmental disorders: 15q11-q13 microdeletion syndrome and Angelman syndrome. These syndromes share a common clinical presentation characterized by intellectual disability, ataxia, and motor delays[25], and it was true that many studies have proved that UBE3A was the essential gene for Angelman syndrome[26]; The GLSS and SATB2 contained within the 2q33.1-q33.3 region were involved in Glass Syndrome. Common clinical manifestations of this syndrome include growth delay and severe intellectual backwardness, and these of phenotypes would continue to extend to the prenatal and postpartum stages[27; 28]; The SMCR contained within the 17p11.2 region involved Smith-Magenis Syndrome, and its main clinical manifestations included mild to moderate intellectual disability and lag of reflexes[29]; It should be noted that the ARSL and CDPX1 contained within the Xp22.33 region were closely associated with dot-shaped cartilage dysplasia typeⅠ. Although the phenotypes of the syndrome mainly include short phalangeal cartilage dysplasia and distal phalangeal hypoplasia of the fingers, many previous reports have also found that the syndrome also has common manifestations including developmental delays and extreme mental decline in infancy[30; 31]. In short, the candidate genes discovered in these of crucial pCNVs regions were closely associated with the occurrence of ABD.
With the continuous development of next-generation sequencing (NGS), more research and medical testing in recent years have begun to adopt NGS to explore sequence variation[14; 15]. Compared with methods of microarray, NGS has the advantages of greater single throughput, faster detection speed, higher resolution, lower cost, and high repeatability. For the identification of chromosomal abnormalities at the sub-microscopic level, the most common method was CNV-seq, it was based on estimating the extension of different statistical models in the confidence interval, and was suitable for the comparison and recognition of the proportion of CNVs[16]. Different from microarray genotyping of target fragments, CNV-seq adopted the READS reference sequence as a template[17]. When comparing sequences, double of Shotgun sequences were adopted for pairing, and two-dimensional sequence comparisons were performed with the templates. The data reading method was Slide Window Mode, finally, we compared the confidence level of the calculation results with above method was not suitable for long sequences and the accuracy of analysis of large fragments needs to be improved[18].
ABD is actually an adaptive behavior defect and cognitive impairment accompanied by human development. The prevalence rate of this disease is about 6%-8%. It is one of the important diseases that endanger physical and mental health. The main causes include genetic and environmental factors. Chromosomal abnormalities, gene mutations, and pCNVs might all lead to the occurrence of ABD. About 30–40% of ABD patients were caused by chromosomal abnormalities. In addition, the prevalence of ABD in the general population about was 1%~3%[19]. China has a very large population, so the number of ABD patients is correspondingly considerable. According to the current situation, most patients with ABD lack effective and targeted prevention and treatment. In other words, it is very important to clarify the cause of ABD. However, the etiology of ABD is very complicated. Based on data from the World Health Organization, it is reported that more than 50% of ABD patients have unknown causes of disease. In China, this rate is even more serious, accounting for about 67%[20]. In fact, genetic factors play a key role in ABD. ABD was divided into S-ABD and NS-ABD. The clinical phenotypes of patients with NS-ABD mainly include typical language disorders, motor developmental delays, and mental decline; unlike NS-ABD, patients with S-ABD included the above abnormalities, but also combine other diseases or systemic deformities, included congenital heart disease, abnormal face, and cleft lip and palate[21].
In current study, 130 ABD patients were selected for CNV-seq analysis. In addition, we combined the clinical phenotypes and ultrasound indicators of the patients involved in the study to group the ABD patient population into NS-ABD group and S-ABD group. Through data analysis, it was suggested that there were 42 cases of abnormal results (42/130). It was worth noting that among these patients, there have been cases where the same patient contains multiple CNVs regional abnormalities. In other words, the same patient carries 2 or more abnormal CNVs at the same time. More and more studies have shown that the adopt of CNV-seq method in genetic diseases that might be caused by chromosomal aberrations such as mental developmental delay and sexual dysplasia could be very effective in improving the detection rate. Therefore, the method was indeed worthy of being recommended as one of the suitable methods for clinical diagnosis [22], Based on the statistical results of this study, our detection rate is as high as 32.3%, which also supports the above view. In current study, the cases detected by CNV-seq included ABD patients with aneuploidy abnormalities, and in addition, they also included ABD patients caused by pCNVs. According to the classification of ABD phenotypes, we further performed an intergroup comparison between NS-ABD and S-ABD, and the results showed that there was a significant difference (χ2 = 40.03, P<0.05) in the detection rate of pathogenic CNVs between the these of two groups. What’s more, based on the results of inter-group comparison, this study continued to analyze the difference in the positivity rate (total detection rate) of the two pathogenic factors aneuploidy abnormality and pCNVs. The results suggested that in the above-mentioned patient groups, the positivity rate of the NS-ABD group was 33.33%, and the positivity rate of the S-ABD group was 77.78%, obviously, the positivity rate of the two groups of patients was also significantly different (χ2 = 40.97, P < 0.05). According to the results above, the current study showed that chromosomal abnormalities and pCNVS were indeed more likely to appear among S-ABD patients. And there were limitations of the above methods: considering that many patients refuse to provide their own information for the current study, the data volume of this study was not large, the current rate of detection and positivity could be fluctuating or uncertain. We would further increase the number of samples or patient groups in future studies.
In the current study, a total of 27 kinds of pCNVs included 15q11.2-q13.2, 2q33.1-q33.3, 17p11.2 and Xp22.33-p11.1 were found, pCNVs such as 15q11.2-q13.2 micro-deletion syndrome[23] and 22q11.21 microdeletion syndrome[24], which have been reported various times and might cause ABD, have been discovered in the current studies, What's more, we also found rarely reported pCNV fragments associated with ABD such as p11.23. There was no obvious pattern in the distribution of these of pCNVs within the chromosomes, which further indicated the widespread of the ABD-associated CNVs region, and also suggested the complexity of the ABD genetic mechanism. Therefore, we adopted the information included in the such four public databases DECIPHER, OMIM, ClinGen and PubMed, and then investigated the highly associated genes located close to the region where the pCNVs fragments appeared, based on the above-mentioned pCNVs fragments. a total of 7 candidate genes associated with ABD were selected. Within the 15q11.2-q13.2 chromosomal region, mutations in the UBE3A and AUTS2 genes were associated with two distinct neurodevelopmental disorders: 15q11-q13 microdeletion syndrome and Angelman syndrome. These syndromes share a common clinical presentation characterized by intellectual disability, ataxia, and motor delays[25], and it was true that many studies have proved that UBE3A was the essential gene for Angelman syndrome[26]; The GLSS and SATB2 contained within the 2q33.1-q33.3 region were involved in Glass Syndrome. Common clinical manifestations of this syndrome include growth delay and severe intellectual backwardness, and these of phenotypes would continue to extend to the prenatal and postpartum stages[27; 28]; The SMCR contained within the 17p11.2 region involved Smith-Magenis Syndrome, and its main clinical manifestations included mild to moderate intellectual disability and lag of reflexes[29]; It should be noted that the ARSL and CDPX1 contained within the Xp22.33 region were closely associated with dot-shaped cartilage dysplasia typeⅠ. Although the phenotypes of the syndrome mainly include short phalangeal cartilage dysplasia and distal phalangeal hypoplasia of the fingers, many previous reports have also found that the syndrome also has common manifestations including developmental delays and extreme mental decline in infancy[30; 31]. In short, the candidate genes discovered in these of crucial pCNVs regions were closely associated with the occurrence of ABD.