Prenatal diagnosis of a trisomy 7 mosaic case: CMA, CNV-seq, karyotyping, interphase FISH, and MS-MLPA, which technique to choose?

OBJECTIVE: This study aims to perform a prenatal genetic diagnosis of a high-risk fetus with trisomy 7 identified by noninvasive prenatal testing (NIPT) and to evaluate the efficacy of different genetic testing techniques for prenatal diagnosis of trisomy mosaicism. METHODS: For prenatal diagnosis of a pregnant woman with a high risk of trisomy 7 suggested by NIPT, karyotyping and chromosomal microarray analysis (CMA) were performed on an amniotic fluid sample. Low-depth whole-genome copy number variation sequencing (CNV-seq) and fluorescence in situ hybridization (FISH) were used to clarify the results further. In addition, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) was performed to analyze the possibility of uniparental disomy(UPD). RESULTS: Amniotic fluid karyotype analysis revealed a 46, XX result. Approximately 20% mosaic trisomy 7 was detected according to the CMA result. About 16% and 4% of mosaicism was detected by CNV-seq and FISH, respectively. MS-MLPA showed no methylation abnormalities. The fetal ultrasound did not show any detectable abnormalities except for mild intrauterine growth retardation seen at 39 weeks of gestation. After receiving genetic counseling, the expectant mother decided to continue the pregnancy, and follow-up within three months of delivery was normal. CONCLUSION: In high-risk NIPT diagnosis, a combination of cytogenetic and molecular genetic techniques proves fruitful in detecting low-level mosaicism. Furthermore, the exclusion of UPD on chromosome 7 remains crucial when NIPT indicates a positive prenatal diagnosis of trisomy 7.

Diagnostic yield of the chromosomal microarray analysis in turkish patients with unexplained development delay/intellectual disability(ID), autism spectrum disorders and/or multiple congenital anomalies and new clinical findings.

BACKGROUND: Chromosomal microarray analysis is an essential tool for copy number variants detection in patients with unexplained developmental delay/intellectual disability, autism spectrum disorders, and multiple congenital anomalies. The study aims to determine the clinical significance of chromosomal microarray analysis in this patient group. Another crucial aspect is the evaluation of copy number variants detected in terms of the diagnosis of patients. METHODS AND RESULTS: A Chromosomal microarray analysis was was conducted on a total of 1227 patients and phenotype-associated etiological diagnosis was established in 135 patients. Phenotype-associated copy number variants were detected in 11% of patients. Among these, 77 patients 77 (57%, 77/135) were diagnosed with well-recognized genetic syndromes and phenotype-associated copy number variants were found in 58 patients (42.9%, 58/135). The study was designed to collect data of patients in Kocaeli Derince Training and Research Hospital retrospectively. In our study, we examined 135 cases with clinically significant copy number variability among all patients. CONCLUSIONS: In this study, chromosomal microarray analysis revealed pathogenic de novo copy number variants with new clinical features. Chromosomal microarray analysis in the Turkish population has been reported in the largest patient cohort to date.

The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities.

BACKGROUND: Chromosomal microarray analysis (CMA) has emerged as a critical instrument in prenatal diagnostic procedures, notably in assessing congenital heart diseases (CHD). Nonetheless, current research focuses solely on CHD, overlooking the necessity for thorough comparative investigations encompassing fetuses with varied structural abnormalities or those without apparent structural anomalies. OBJECTIVE: This study sought to assess the relation of single nucleotide polymorphism-based chromosomal microarray analysis (SNP-based CMA) in identifying the underlying causes of fetal cardiac ultrasound abnormalities. METHODS: A total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the specific type of abnormality. The results of the SNP-Array test conducted on amniotic fluid samples from these groups were analyzed. RESULTS: Findings from the study revealed that the non-isolated CHD group exhibited the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, demonstrating statistically significant differences from the other groups (p < 0.001). Regarding the distribution frequency of copy number variation (CNV) segment size, no statistically significant distinctions were observed between the isolated CHD group and the non-isolated CHD group (p > 0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated CHD group and the non-isolated congenital heart defect group (p > 0.05). CONCLUSION: SNP-based CMA enhances the capacity to detect abnormal CNVs in CHD fetuses, offering valuable insights for diagnosing chromosomal etiology and facilitating genetic counseling. This research contributes to the broader understanding of the utility of SNP-based CMA in the context of fetal cardiac ultrasound abnormalities.

Differential Glycoform Analysis of MUC1 Derived from Biological Specimens Using an Antibody-Overlay Lectin Microarray.

The association between altered glycosylation of MUC1 and various disease events has sparked significant interest. However, analytical technologies to investigate the disease-related glycoforms of endogenous MUC1 in blood and tissue specimens are limited. Therefore, we devised a reliable technique for differential analysis of endogenous MUC1 glycoforms based on an antibody-assisted lectin microarray. Its highly sensitive detection aids in analyzing soluble MUC1 from relatively small amounts of serum via a simple enrichment process. Micro-/macro-dissection of the MUC1-positive region is combined with glycoform analysis of the membrane-tethered MUC1. Thus, we have optimized the protocol for sample qualification using immunohistochemistry, sample pretreatment for tissue sections, protein extraction, purification via immunoprecipitation, and the antibody-overlay lectin microarray, which are sequentially essential for differential glycoform analysis of endogenous MUC1.

Reusable glycan microarrays using a microwave assisted wet-erase (MAWE) process.

Modern studies on binding of proteins to glycans commonly involve the use of synthetic glycans and their derivatives in which a small amount of the material is covalently printed onto a functionalized slide in a glycan microarray format. While incredibly useful to explore binding interactions with many types of samples, the common techniques involve drying the slides, which leads to irreversible association of the protein to the spots on slides to which they bound, thus limiting a microarray to a single use. We have developed a new technique which we term Microwave Assisted Wet-Erase (MAWE) glycan microarrays. In this approach we image the slides under wet conditions to acquire the data, after which the slides are cleaned of binding proteins by treatment with a denaturing SDS solution along with microwave treatment. Slides cleaned in this way can be reused multiple times, and an example here shows the reuse of a single array 15 times. We also demonstrate that this method can be used for a single-array per slide or multi-array per slide platforms. Importantly, the results obtained using this technique for a variety of lectins sequentially applied to a single array, are concordant to those obtained via the classical dry approaches on multiple slides. We also demonstrate that MAWE can be used for different types of samples, such as serum for antibody binding, and whole cells, such as yeast. This technique will greatly conserve precious glycans and prolong the use of existing and new glycan microarrays.

Prenatal diagnosis and genetic etiology analysis of talipes equinovarus by chromosomal microarray analysis.

BACKGROUND: With the advancement of molecular technology, fetal talipes equinovarus (TE) is believed to be not only associated with chromosome aneuploidy, but also related to chromosomal microdeletion and microduplication. The study aimed to explore the molecular etiology of fetal TE and provide more information for the clinical screening and genetic counseling of TE by Chromosomal Microarray Analysis (CMA). METHODS: This retrospectively study included 131 fetuses with TE identified by ultrasonography. Conventional karyotyping and SNP array analysis were performed for all the subjects. They were divided into isolated TE group (n = 55) and complex group (n = 76) according to structural anomalies. RESULTS: Among the total of 131 fetuses, karyotype analysis found 12(9.2%) abnormal results, while SNP array found 27 (20.6%) cases. Trisomy 18 was detected most frequently among abnormal karyotypes. The detection rate of SNP array was significantly higher than that of traditional chromosome karyotype analysis (P < 0.05). SNP array detected 15 (11.5%) cases of submicroscopic abnormalities that karyotype analysis did not find. The most common CNV was the 22q11.2 microdeletion. For both analyses, the overall detection rates were significantly higher in the complex TE group than in the isolated TE group (karyotype: P < 0.05; SNP array: P < 0.05). The incremental yield of chromosomal abnormalities in fetuses with unilateral TE (22.0%) was higher than in fetuses with bilateral TE (19.8%), but this difference was not statistically significant (P > 0.05). Abnormal chromosomes were most frequently detected in fetuses with TE plus cardiovascular system abnormalities. CONCLUSION: Fetal TE is related to chromosomal microdeletion or microduplication. Prenatal diagnosis is recommended for fetuses with TE, and CMA testing is preferred. CMA can improve the detection rate of chromosomal abnormalities associated with fetal TE, especially in pregnancies with complex TE.

Microarray Polymer Profiling (MAPP) for High-Throughput Glycan Analysis.

Microarray polymer profiling (MAPP) is a robust and reproducible approach to systematically determine the composition and relative abundance of glycans and glycoconjugates within a variety of biological samples, including plant and algal tissues, food materials, and human, animal, and microbial samples. Microarray technology underpins the efficacy of this method by providing a miniaturized, high-throughput screening platform, allowing thousands of interactions between glycans and highly specific glycan-directed molecular probes to be characterized concomitantly, using only small amounts of analytes. Constituent glycans are chemically and enzymatically fractionated, before being sequentially extracted from the sample and directly immobilized onto nitrocellulose membranes. The glycan composition is determined by the attachment of specific glycan-recognizing molecular probes to the extorted and printed molecules. MAPP is complementary to conventional glycan analysis techniques, such as monosaccharide and linkage analysis and mass spectrometry. However, glycan-recognizing molecular probes provide insight into the structural configurations of glycans, which can aid in elucidating biological interactions and functional roles.

A Holistic 4D Approach to Optimize Intrinsic and Extrinsic Factors Contributing to Variability in Microarray Biosensing in Glycomics.

Protein-carbohydrate interactions happen to be a crucial facet of biology, discharging a myriad of functions. Microarrays have become a premier choice to discern the selectivity, sensitivity and breadth of these interactions in a high-throughput manner. The precise recognition of target glycan ligands among the plethora of others is central for any glycan-targeting probe being tested by microarray analyses. Ever since the introduction of the microarray as an elemental tool for high-throughput glycoprofiling, numerous distinct array platforms possessing different customizations and assemblies have been developed. Accompanying these customizations are various factors ushering variances across array platforms. In this primer, we investigate the influence of various extrinsic factors, namely printing parameters, incubation procedures, analyses and array storage conditions on the protein-carbohydrate interactions and evaluate these factors for the optimal performance of microarray glycomics analysis. We hereby propose a 4D approach (Design-Dispense-Detect-Deduce) to minimize the effect of these extrinsic factors on glycomics microarray analyses and thereby streamline cross-platform analyses and comparisons. This work will aid in optimizing microarray analyses for glycomics, minimize cross-platform disparities and bolster the further development of this technology.

Fetal congenital gastrointestinal obstruction: prenatal diagnosis of chromosome microarray analysis and pregnancy outcomes.

OBJECTIVE: The aim of this study was to investigate the incidence of chromosome anomalies in different types of congenital gastrointestinal obstruction and assess pregnancy outcomes of fetuses with congenital gastrointestinal obstruction. METHODS: A total of 64 cases with gastrointestinal obstruction between January 2014 and December 2020 were enrolled in this study. They were divided into three groups according to sonographic images. Group A: isolated upper gastrointestinal obstruction; Group B: isolated lower gastrointestinal obstruction; Group C: non-isolated gastrointestinal obstruction. The rate of chromosome anomalies in different groups was calculated. Pregnant women with amniocentesis were followed up by medical records and telephone. The follow-up included pregnancy outcomes and development of the live born infants. RESULT: From January 2014 to December 2020, there were 64 fetus with congenital gastrointestinal obstruction underwent chromosome microarray analysis(CMA), the overall detection rate of CMA testing was 14.1%(9/64). The detection rate of Group A, B and C were 16.2%, 0 and 25.0% respectively. 9 fetuses with abnormal CMA results were all terminated. Among 55 fetuses with normal chromosomes, 10(18.2%) fetuses were not found to have any gastrointestinal obstruction after birth. 17(30.9%) fetuses were diagnosed with gastrointestinal obstruction and underwent surgical treatment after birth, one of which had lower gastrointestinal obstruction combined with biliary obstruction and died due to liver cirrhosis. 11(20.0%) pregnancy were terminated due to multiple abnormalities. 5(9.1%) fetuses were intrauterine death. 3(5.5%) fetuses were neonatal deaths. 9(16.4%) fetuses were lost to follow-up. CONCLUSION: It is crucial to understand whether the gastrointestinal tract abnormality is isolated or associated to other findings. The risk of chromosomal abnormalities in fetuses with isolated lower gastrointestinal obstruction is lower than upper gastrointestinal obstruction. While genetic abnormalities excluded, a promising prognosis is expected for fetuses with congenital gastrointestinal obstruction.

Droplet microarray platforms for high-throughput drug screening.

High-throughput screening platforms are fundamental for the rapid and efficient processing of large amounts of experimental data. Parallelization and miniaturization of experiments are important for improving their cost-effectiveness. The development of miniaturized high-throughput screening platforms is essential in the fields of biotechnology, medicine, and pharmacology. Currently, most laboratories use 96- or 384-well microtiter plates for screening; however, they have disadvantages, such as high reagent and cell consumption, low throughput, and inability to avoid cross-contamination, which need to be further optimized. Droplet microarrays, as novel screening platforms, can effectively avoid these shortcomings. Here, the preparation method of the droplet microarray, method of adding compounds in parallel, and means to read the results are briefly described. Next, the latest research on droplet microarray platforms in biomedicine is presented, including their application in high-throughput culture, cell screening, high-throughput nucleic acid screening, drug development, and individualized medicine. Finally, the challenges and future trends in droplet microarray technology are summarized.

Diagnostic Yield of Exome Sequencing in Fetuses with Sonographic Features of Skeletal Dysplasias but Normal Karyotype or Chromosomal Microarray Analysis: A Systematic Review.

Skeletal dysplasias are a group of diseases characterized by bone and joint abnormalities, which can be detected during prenatal ultrasound. Next-generation sequencing has rapidly revolutionized molecular diagnostic approaches in fetuses with structural anomalies. This review studies the additional diagnostic yield of prenatal exome sequencing in fetuses with prenatal sonographic features of skeletal dysplasias. This was a systematic review by searching PubMed for studies published between 2013 and July 2022 that identified the diagnostic yield of exome sequencing after normal karyotype or chromosomal microarray analysis (CMA) for cases with suspected fetal skeletal dysplasias based on prenatal ultrasound. We identified 10 out of 85 studies representing 226 fetuses. The pooled additional diagnostic yield was 69.0%. The majority of the molecular diagnoses involved de novo variants (72%), while 8.7% of cases were due to inherited variants. The incremental diagnostic yield of exome sequencing over CMA was 67.4% for isolated short long bones and 77.2% for non-isolated cases. Among phenotypic subgroup analyses, features with the highest additional diagnostic yield were an abnormal skull (83.3%) and a small chest (82.5%). Prenatal exome sequencing should be considered for cases with suspected fetal skeletal dysplasias with or without a negative karyotype or CMA results. Certain sonographic features, including an abnormal skull and small chest, may indicate a potentially higher diagnostic yield.

Prenatal exome sequencing analysis in fetuses with central nervous system anomalies.

OBJECTIVE: To evaluate the utility of prenatal exome sequencing (pES) in fetuses with central nervous system (CNS) abnormalities. METHODS: This was a retrospective cohort study of fetuses identified to have CNS abnormality on prenatal ultrasound and/or magnetic resonance imaging. All fetuses were first analyzed by chromosomal microarray analysis (CMA). Fetuses with a confirmed aneuploidy or causal pathogenic copy-number variant (CNV) on CMA did not undergo pES analysis and were excluded, while those with a negative CMA result were offered pES testing. RESULTS: Of the 167 pregnancies included in the study, 42 (25.1%) were identified to have a pathogenic or likely pathogenic (P/LP) variant. The diagnostic rate was significantly higher in fetuses with a non-isolated CNS abnormality than in those with a single CNS abnormality (35.7% (20/56) vs 14.5% (8/55); P = 0.010). Moreover, when a fetus had three or more CNS abnormalities, the positive diagnostic rate increased to 42.9%. A total of 25/42 (59.5%) cases had de-novo mutations, while, in the remaining cases, mutations were inherited and carried a significant risk of recurrence. Families whose fetus carried a P/LP mutation were more likely to choose advanced pregnancy termination than those with a variant of uncertain significance, secondary/incidental finding or negative pES result (83.3% (25/30) vs 41.3% (38/92); P < 0.001). CONCLUSION: pES improved the identification of genetic disorders in fetuses with CNS anomalies without a chromosomal abnormality or CNV identified on CMA, regardless of the number of CNS anomalies and presence of extracranial abnormality. We also demonstrated that pES findings can significantly impact parental decision-making. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data.

BACKGROUND: Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is "large p and small n" in that data contain a small number of subjects but a large number of genes. It may affect the validity of the classification. Thus, there is a pressing demand of techniques able to select genes relevant to cancer classification. RESULTS: This study proposed a novel feature (gene) selection method, Iso-GA, for cancer classification. Iso-GA hybrids the manifold learning algorithm, Isomap, in the genetic algorithm (GA) to account for the latent nonlinear structure of the gene expression in the microarray data. The Davies-Bouldin index is adopted to evaluate the candidate solutions in Isomap and to avoid the classifier dependency problem. Additionally, a probability-based framework is introduced to reduce the possibility of genes being randomly selected by GA. The performance of Iso-GA was evaluated on eight benchmark microarray datasets of cancers. Iso-GA outperformed other benchmarking gene selection methods, leading to good classification accuracy with fewer critical genes selected. CONCLUSIONS: The proposed Iso-GA method can effectively select fewer but critical genes from microarray data to achieve competitive classification performance.

Non-fouling polymer brush grafted fluorine-doped tin oxide enabled optical and chemical enhancement for sensitive label-free antibody microarrays.

Oblique-incidence reflectivity difference (OIRD) is a compelling technique for real-time, label-free and non-destructive detection of antibody microarray chips, but its sensitivity needs essential improvement for clinical diagnosis. In this study, we report an innovative high-performance OIRD microarray by using poly[oligo(ethylene glycol) methacrylate-co-glycidyl methacrylate] (POEGMA-co-GMA) brush grafted fluorine-doped tin oxide (FTO) as the chip substrate. The polymer brush enhances the interfacial binding reaction efficiency of targets from the complicated sample matrix due to its high antibody loading and excellent anti-fouling merits; the FTO-polymer brush layered structure, on the other hand, excites the interference enhancement effect of OIRD to achieve enhanced intrinsic optical sensitivity. Synergistically, the sensitivity of this chip is significantly improved compared to rival chips, achieving a limit of detection (LOD) as low as 25 ng mL-1 for the model target C-reactive protein (CRP) in 10% human serum. This work explores the tremendous influence of the chip interfacial structure on the OIRD sensitivity and proposes a rational interfacial engineering strategy to boost the performance of the label-free OIRD based microarray and other bio-devices.

Estimation on risk of spontaneous abortions by genomic disorders from a meta-analysis of microarray results on large case series of pregnancy losses.

A meta-analysis on seven large case series (>1000 cases) of chromosome microarray analysis (CMA) on products of conceptions (POC) evaluated the diagnostic yields of genomic disorders and syndromic pathogenic copy number variants (pCNVs) from a collection of 35,130 POC cases. CMA detected chromosomal abnormalities and pCNVs in approximately 50% and 2.5% of cases, respectively. The genomic disorders and syndromic pCNVs accounted for 31% of the detected pCNVs, and their incidences in POC ranged from 1/750 to 1/12,000. The newborn incidences of these genomic disorders and syndromic pCNVs were estimated in a range of 1/4000 to 1/50,000 live births from population genetic studies and diagnostic yields of a large case series of 32,587 pediatric patients. The risk of spontaneous abortion (SAB) for DiGeorge syndrome (DGS), Wolf-Hirschhorn syndrome (WHS), and William-Beuren syndrome (WBS) was 42%, 33%, and 21%, respectively. The estimated overall risk of SAB for major genomic disorders and syndromic pCNVs was approximately 38%, which was significantly lower than the 94% overall risk of SAB for chromosomal abnormalities. Further classification on levels of risk of SAB to high (>75%), intermediate (51%-75%), and low (26%-50%) for known chromosomal abnormalities, genomic disorders, and syndromic pCNVs could provide evidence-based interpretation in prenatal diagnosis and genetic counseling.

Leveraging Unique Chromosomal Microarray Probes to Accurately Detect Copy Number at the Highly Homologous 15q15.3 Deafness-Infertility Syndrome Locus.

BACKGROUND: Biallelic deletions at 15q15.3, including STRC and CATSPER2, cause autosomal recessive deafness-infertility syndrome (DIS), while biallelic deletions of STRC alone cause nonsyndromic hearing loss. These deletions are among the leading genetic causes of mild-moderate hearing loss, but their detection using chromosomal microarray (CMA) is impeded by a tandem duplication containing highly homologous pseudogenes. We sought to assess copy number variant (CNV) detection in this region by a commonly-employed CMA platform. METHODS: Twenty-two specimens with known 15q15.3 CNVs, determined by droplet digital PCR (ddPCR), were analyzed by CMA. To investigate the impact of pseudogene homology on CMA performance, a probe-level analysis of homology was performed, and log2 ratios of unique and pseudogene-homologous probes compared. RESULTS: Assessment of 15q15.3 CNVs by CMA compared to ddPCR revealed 40.9% concordance, with frequent mis-assignment of zygosity by the CMA automated calling software. Probe-level analysis of pseudogene homology suggested that probes with high homology contributed to this discordance, with significant differences in log2 ratios between unique and pseudogene-homologous CMA probes. Two clusters containing several unique probes could reliably detect CNVs involving STRC and CATSPER2, despite the noise of surrounding probes, discriminating between homozygous vs heterozygous losses and complex rearrangements. CNV detection by these probe clusters showed 100% concordance with ddPCR. CONCLUSIONS: Manual analysis of clusters containing unique CMA probes without significant pseudogene homology improves CNV detection and zygosity assignment in the highly homologous DIS region. Incorporation of this method into CMA analysis and reporting processes can improve DIS diagnosis and carrier detection.

[The value of chromosomal microarray analysis and fluorescence in situ hybridization for the prenatal diagnosis of chromosomal mosaicisms].

OBJECTIVE: To assess the value of chromosomal microarray analysis (CMA) and fluorescence in situ hybridization (FISH) for the prenatal diagnosis of chromosomal mosaicisms. METHODS: A total of 775 pregnant women who had visited the Prenatal Diagnosis Center of Yancheng Maternal and Child Health Care Hospital from January 2018 to December 2020 were selected as study subjects. Chromosome karyotyping analysis and CMA were carried out for all women, and FISH was used to validate the suspected mosaicism cases. RESULTS: Among the 775 amniotic fluid samples, karyotyping has identified 13 mosaicism cases, which yielded a detection rate of 1.55%. Respectively, there were 4, 3, 4 and 2 cases for sex chromosome number mosaicisms, abnormal sex chromosome structure mosaicisms, abnormal autosomal number mosaicisms and abnormal autosomal structure mosaicisms. CMA has only detected only 6 of the 13 cases. Among 3 cases verified by FISH, 2 cases were consistent with the karyotyping and CMA results, and clearly showed low proportion mosaicism, and 1 case was consistent with the result of karyotyping but with a normal result by CMA. Eight pregnant women had chosen to terminate the pregnancy (5 with sex chromosome mosaicisms and 3 with autosomal mosaicisms). CONCLUSION: For fetuses suspected for chromosomal mosaicisms, CMA, FISH and G-banding karyotyping should be combined to determine the type and proportion of mosaicisms more precisely in order to provide more information for genetic counseling.

Diagnostic yield of exome sequencing in isolated fetal growth restriction: Systematic review and meta-analysis.

The aim of this study was to determine the diagnostic yield of exome sequencing (ES) above that of chromosomal microarray analysis (CMA) or karyotyping in fetuses with isolated fetal growth restriction (FGR). This was a systematic review conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Selected studies included those with (a) only fetuses with FGR in the absence of fetal structural anomalies and (b) negative CMA or karyotyping results. Only positive variants classified as likely pathogenic or pathogenic determined as causative of the fetal phenotype were considered. A negative CMA or karyotype result was treated as the reference standard. Eight studies with data on ES diagnostic yield, including 146 fetuses with isolated FGR, were identified. Overall, a pathogenic variant determined as potentially causative of the fetal phenotype was found in 17 cases, resulting in a 12% (95% CI: 7%-18%) incremental performance pool of ES. The vast majority were studied before 32 weeks'gestation. In conclusion, a monogenic disorder was prenatally found in association with apparently isolated FGR in 12% of these fetuses.

[Genetic diagnosis of microcephaly].

Objective: To explore the diagnostic value of chromosome karyotype analysis, chromosomal microarray analysis (CMA) and whole exome sequencing (WES) in microcephaly. Methods: A total of 9 cases of microcephaly fetuses diagnosed by prenatal ultrasound or children with microcephaly diagnosed after birth were selected from the Sixth Affiliated Hospital of Guangzhou Medical University from January 2014 to August 2022.Karyotype analysis and/or CMA were used to detect. The cases with negative karyotype analysis and CMA results were further sequenced by trio-based WES (Trio-WES). Then the coding genes contained in the pathogenic copy number variation (CNV) fragments were analyzed by gene ontology (GO) enrichment. The genes related to the development of the central nervous system contained in the pathogenic CNV and the pathogenic genes found by Trio-WES were combined for gene interaction network analysis. Results: In this study, 9 cases of microcephaly were recruited, with the time of diagnosis ranged from 23 weeks of gestation to 7 years after birth, and the head circumference of fetus or children ranged from 18.3 to 42.5 cm (-7SD to -2SD). Karyotype analysis was detected in all 9 cases and no abnormality result was found. Eight cases were detected by CMA, and one abnormal was found. Five cases were detected by Trio-WES, and two cases were detected with likely pathogenic genes. The GO enrichment analysis of the coding gene in the 4p16.3 microdeletion (pathogenic CNV) region showed that: in biological process, it was mainly concentrated in phototransduction, visible light; in terms of molecular function, it was mainly concentrated in fibroblast growth factor binding; in terms of cell components, it was mainly concentrated in rough endoplasmic reticulum. Gene interaction network analysis suggested that CDC42 gene could interact with CTBP1, HTT and ASPM gene. Conclusions: CMA could be used as a first-line detection technique for microcephaly. When the results of chromosome karyotype analysis and/or CMA are negative, Trio-WES could improve the detection rate of pathogenicity of microcephaly.