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Prenatal Diagnosis Aug 2023Unexplained stillbirth is defined as a stillbirth with no known cause after the exclusion of common causes, including obstetric complications, infections, placental... (Review)
Review
Unexplained stillbirth is defined as a stillbirth with no known cause after the exclusion of common causes, including obstetric complications, infections, placental insufficiency or abruption, umbilical cord complications, and congenital abnormalities with or without known genetic cause. More than 60% of stillbirth cases remain unexplained. The aim of this systematic review was to investigate the known genetic causes of unexplained stillbirth cases and to evaluate the current position and future directions for the use of genetic and genomic testing in expanding the knowledge in this field. A systematic search through several databases was performed using the keywords genetics and stillbirths in humans. Different methods to detect various types of causal genetic aberrations have been used in the past decades, from standard karyotyping to novel methods such as chromosomal microarray analysis and next generation sequencing technologies. Apart from common chromosomal aneuploidies, a promising hypothesis about genetic causes included genes related to cardiomyopathies and channelopathies. However, these were tested in the research settings, since molecular karyotyping is currently the standard approach in the routine evaluation of genetic causes of stillbirth. Hereby, we provide evidence that expanding knowledge using novel genetic and genomic testing might uncover new genetic causes of unexplained stillbirth.
Topics: Humans; Female; Pregnancy; Stillbirth; Placenta; Aneuploidy; Databases, Factual; Genetic Profile
PubMed: 37072878
DOI: 10.1002/pd.6354 -
Movement Disorders Clinical Practice Apr 2023Chromosome microarray analysis (CMA) can detect copy number variants (CNV) beyond the resolution of standard G-banded karyotyping. De novo or inherited microdeletions... (Review)
Review
BACKGROUND
Chromosome microarray analysis (CMA) can detect copy number variants (CNV) beyond the resolution of standard G-banded karyotyping. De novo or inherited microdeletions may cause autosomal dominant movement disorders.
OBJECTIVES
The purpose of this study was to analyze the clinical characteristics, associated features, and genetic information of children with deletions in known genes that cause movement disorders and to make recommendations regarding the diagnostic application of CMA.
METHODS
Clinical cases published in English were identified in scientific databases (PubMed, ClinVar, and DECIPHER) from January 1998 to July 2019 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Cases with deletions or microdeletions greater than 300 kb were selected. Information collected included age, sex, movement disorders, associated features, and the size and location of the deletion. Duplications or microduplications were not included.
RESULTS
A total of 18.097 records were reviewed, and 171 individuals were identified. Ataxia (30.4%), stereotypies (23.9%), and dystonia (21%) were the most common movement disorders. A total of 16% of the patients demonstrated more than one movement disorder. The most common associated features were intellectual disability or developmental delay (78.9%) and facial dysmorphism (57.8%). The majority (77.7%) of microdeletions were smaller than 5 Mb. We find no correlation between movement disorders, their associated features, and the size of microdeletions.
CONCLUSIONS
Our results support the use of CMA as an investigational test in children with movement disorders. As the majority of identified articles were case reports and small case series (low quality), future efforts should focus on larger prospective studies to examine the causation of microdeletions in pediatric movement disorders.
PubMed: 37070051
DOI: 10.1002/mdc3.13711 -
The Journal of Maternal-fetal &... Dec 2023To estimate the incremental yield of detecting pathogenic or likely pathogenic diagnostic genetic variants (DGV) by whole exome sequencing (WES) over standard karyotype... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
To estimate the incremental yield of detecting pathogenic or likely pathogenic diagnostic genetic variants (DGV) by whole exome sequencing (WES) over standard karyotype and chromosomal microarray (CMA) analyses in fetuses with isolated increased nuchal translucency (NT) and normal fetal anatomy at the time of 11-14 weeks scan.
MATERIALS AND METHODS
Medline and Embase databases were searched. Inclusion criteria were fetuses with NT >95 percentile, normal karyotype and CMA and no associated structural anomalies at the time of the 11-14 weeks scan. The primary outcome was to estimate the incremental yield of detecting pathogenic or likely pathogenic genetic variants by WES over standard karyotype and CMA analyses in fetuses with isolated increased nuchal translucency. The secondary outcomes were the detection of a genetic variant of unknown significance. Sub-analysis according to different NT cutoffs (between 3.0 and 5.5 mm and > 5.5 mm) and considering fetuses with isolated NT in which fetal anatomy was confirmed to be normal at the anomaly scan were also performed. Random effects model meta-analyses of proportion were used to analyze the data.
RESULTS
Eight articles (324 fetuses) were included in the systematic review. Of the fetuses with negative standard karyotype and CMA analysis, the 8.07% (95% CI 5.4-11.3) had pathogenic or likely pathogenic genetic variants detected exclusively by WES. When stratifying the analysis according to NT cutoffs, genetic anomalies detected exclusively at WES analysis were found in 44.70% (95% CI 26.8-63.4) of fetuses with NT between 3.0 mm and 5.5 mm and 55.3% (95% CI 36.6-73.2) in those fetuses with NT >5.5 mm and positive WES results. The 7.84% (95% CI 1.6-18.2) had variants of unknown significance identified by WES. When considering fetuses with isolated increased NT and normal fetal anatomy at the anomaly scan, the rate of pathogenic or likely pathogenic genetic variants detected by WES was 3.87% (95% CI 1.6-7.1), while variants of unknown significance were detected in 4.27% (95% CI 2.2-7.0) of cases.
CONCLUSIONS
Pathogenic and likely pathogenic genetic variants detected by WES are present in a significant proportion of fetuses with increased NT but normal standard karyotype and CMA analysis, also when no anomalies are detected at the anomaly scan. Further large studies sharing objective protocols of imaging assessment are needed to confirm these findings and to elucidate which gene panels should be assessed in fetuses with isolated increased NT to rule out associated genetic anomalies, which may potentially impact post-natal outcomes.
Topics: Pregnancy; Female; Humans; Nuchal Translucency Measurement; Exome Sequencing; Fetus; Karyotyping; Karyotype; Prenatal Diagnosis
PubMed: 37019452
DOI: 10.1080/14767058.2023.2193285 -
Prenatal Diagnosis May 2023The 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... (Meta-Analysis)
Meta-Analysis Review
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.
Topics: Pregnancy; Humans; Female; Fetal Growth Retardation; Exome Sequencing; Ultrasonography, Prenatal; Karyotyping; Microarray Analysis
PubMed: 36869857
DOI: 10.1002/pd.6339 -
Cancers Jan 2023Cervical cancer is the leading cause of cancer-related death among women in developing countries. However, no comprehensive molecular mechanism for cervical cancer has... (Review)
Review
Cervical cancer is the leading cause of cancer-related death among women in developing countries. However, no comprehensive molecular mechanism for cervical cancer has been established, as many studies were small-cohort studies conducted with small sample sizes. A thorough literature search was performed using the PubMed, Scopus, EBSCOhost, and Science Direct databases. Medical Subject Heading (MeSH) terms such as "Uterine Cervical Neoplasms" and "gene expression" were used as the keywords in all fields. A total of 4027 studies were retrieved, and only clinical studies, which used the microarray method to identify differentially expressed genes (DEGs) in the cervical tissue of cervical cancer patients, were selected. Following the screening, 6 studies were selected and 1128 DEGs were extracted from the data. Sixty-two differentially expressed genes from at least two studies were selected for further analysis by DAVID, STRING, and Cytoscape software. In cervical cancer pathogenesis, three significant clusters with high intermolecular interactions from the Protein-Protein Interaction (PPI) network complex revealed three major molecular mechanisms, including cell signaling, cell cycle, and cell differentiation. Subsequently, eight genes were chosen as the candidate genes based on their involvement in the relevant gene ontology (GO) and their interaction with other genes in the PPI network through undirected first neighbor nodes. The present systematic review improves our understanding of the molecular mechanism of cervical cancer and the proposed genes that can be used to expand the biomarker panel in the screening for cervical cancer. The targeted genes may be beneficial for the development of better treatment strategies.
PubMed: 36765810
DOI: 10.3390/cancers15030853 -
Diagnostics (Basel, Switzerland) Dec 2022Fetal Nuchal fluid collections can manifest with two distinct presentations attributable to the same phenotypic spectrum: increased nuchal translucency (iNT) and cystic... (Review)
Review
A Pain in the Neck: Lessons Learnt from Genetic Testing in Fetuses Detected with Nuchal Fluid Collections, Increased Nuchal Translucency versus Cystic Hygroma-Systematic Review of the Literature, Meta-Analysis and Case Series.
Fetal Nuchal fluid collections can manifest with two distinct presentations attributable to the same phenotypic spectrum: increased nuchal translucency (iNT) and cystic hygroma. The prenatal detection of these findings should prompt an accurate assessment through genetic counseling and testing, including karyotype, chromosomal microarray analysis (CMA) and multigene RASopathy panel. We performed a systematic review of the literature and meta-analysis, to calculate diagnostic yields of genetic testing in fetuses with iNT and cystic hygroma. We compared the results with a cohort of 96 fetuses with these isolated findings. Fetuses with isolated NT ≥ 2.5 mm showed karyotype anomalies in 22.76% of cases and CMA presented an incremental detection rate of 2.35%. Fetuses with isolated NT ≥ 3 mm presented aneuploidies in 14.36% of cases and CMA had an incremental detection rate of 3.89%. When the isolated NT measured at least 3.5 mm the diagnostic yield of karyotyping was 34.35%, the incremental CMA detection rate was 4.1%, the incremental diagnostic rate of the RASopathy panel was 1.44% and it was 2.44% for exome sequencing. Interestingly, CMA presents a considerable diagnostic yield in the group of fetuses with NT ≥ 3.5 mm. Similarly, exome sequencing appears to show promising results and could be considered after a negative CMA result.
PubMed: 36611340
DOI: 10.3390/diagnostics13010048 -
The European Journal of Neuroscience Jan 2023Regulator of G-protein signalling (RGS) proteins inhibit signalling by G-protein-coupled receptors (GPCRs). GPCRs mediate the functions of several important... (Meta-Analysis)
Meta-Analysis
Regulator of G-protein signalling (RGS) proteins inhibit signalling by G-protein-coupled receptors (GPCRs). GPCRs mediate the functions of several important neurotransmitters and serve as targets of many anti-psychotics. RGS2, RGS4, RGS5 and RGS16 are located on chromosome 1q23.3-31, a locus found to be associated with schizophrenia. Although previous gene expression analysis detected down-regulation of RGS4 expression in brain samples of patients with schizophrenia, the results were not consistent. In the present study, we performed a systematic meta-analysis of differential RGS2, RGS4, RGS5 and RGS16 expression in Brodmann Area 10 (BA10) samples of patients with schizophrenia and from healthy controls. Two microarray datasets met the inclusion criteria (overall, 41 schizophrenia samples and 38 controls were analysed). RGS2 and RGS16 were found to be up-regulated in BA10 samples of individuals with schizophrenia, whereas no differential expression of RGS4 and RGS5 was detected. Analysis of dorso-lateral prefrontal cortex samples of the CommonMind Consortium (258 schizophrenia samples vs. 279 controls) further validated the results. Given their central role in inactivating G-protein-coupled signalling pathways, our results suggest that differential gene expression might lead to enhanced inactivation of G-protein signalling in schizophrenia. This, in turn, suggests that additional studies are needed to further explore the consequences of the differential expression we detected, this time at the protein and functional levels.
Topics: Humans; Gene Expression; Gene Expression Profiling; Prefrontal Cortex; RGS Proteins; Schizophrenia; Up-Regulation; Gene Expression Regulation
PubMed: 36443250
DOI: 10.1111/ejn.15876 -
JAMA Neurology Dec 2022There are many known acquired risk factors for cerebral palsy (CP), but in some cases, CP is evident without risk factors (cryptogenic CP). Early CP cohort studies... (Meta-Analysis)
Meta-Analysis
IMPORTANCE
There are many known acquired risk factors for cerebral palsy (CP), but in some cases, CP is evident without risk factors (cryptogenic CP). Early CP cohort studies report a wide range of diagnostic yields for sequence variants assessed by exome sequencing (ES) and copy number variants (CNVs) assessed by chromosomal microarray (CMA).
OBJECTIVE
To synthesize the emerging CP genetics literature and address the question of what percentage of individuals with CP have a genetic disorder via ES and CMA.
DATA SOURCES
Searched articles were indexed by PubMed with relevant queries pertaining to CP and ES/CMA (query date, March 15, 2022).
STUDY SELECTION
Inclusion criteria were as follows: primary research study, case series with 10 or more nonrelated individuals, CP diagnosis, and ES and/or CMA data used for genetic evaluation. Nonblinded review was performed.
DATA EXTRACTION AND SYNTHESIS
Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were used for assessing data quality and validity. Data were extracted by a single observer.
MAIN OUTCOMES AND MEASURES
A separate meta-analysis was performed for each modality (ES, CMA). The primary outcome was proportion/molecular diagnostic yield (number of patients with a discovered genetic disorder divided by the total number of patients in the cohort), evaluated via meta-analysis of single proportions using random-effects logistic regression. A subgroup meta-analysis was conducted, using risk factor classification as a subgroup. A forest plot was used to display diagnostic yields of individual studies.
RESULTS
In the meta-analysis of ES yield in CP, the overall diagnostic yield of ES among the cohorts (15 study cohorts comprising 2419 individuals from 11 articles) was 23% (95% CI, 15%-34%). The diagnostic yield across cryptogenic CP cohorts was 35% (95% CI, 27%-45%), compared with 7% (95% CI, 4%-12%) across cohorts with known risk factors (noncryptogenic CP). In the meta-analysis of CMA yield in CP, the diagnostic yield of CMA among the cohorts (5 study cohorts comprising 294 individuals from 5 articles) was 5% (95% CI, 2%-12%).
CONCLUSIONS AND RELEVANCE
Results of this systematic review and meta-analysis suggest that for individuals with cryptogenic CP, ES followed by CMA to identify molecular disorders may be warranted.
Topics: Humans; Pathology, Molecular; Cerebral Palsy; Microarray Analysis; Exome Sequencing; DNA Copy Number Variations
PubMed: 36279113
DOI: 10.1001/jamaneurol.2022.3549 -
Frontiers in Physiology 2022Cancer is one of the top causes of death globally. Recently, microarray gene expression data has been used to aid in cancer's effective and early detection. The use of...
Cancer is one of the top causes of death globally. Recently, microarray gene expression data has been used to aid in cancer's effective and early detection. The use of DNA microarray technology to uncover information from the expression levels of thousands of genes has enormous promise. The DNA microarray technique can determine the levels of thousands of genes simultaneously in a single experiment. The analysis of gene expression is critical in many disciplines of biological study to obtain the necessary information. This study analyses all the research studies focused on optimizing gene selection for cancer detection using artificial intelligence. One of the most challenging issues is figuring out how to extract meaningful information from massive databases. Deep Learning architectures have performed efficiently in numerous sectors and are used to diagnose many other chronic diseases and to assist physicians in making medical decisions. In this study, we have evaluated the results of different optimizers on a RNA sequence dataset. The Deep learning algorithm proposed in the study classifies five different forms of cancer, including kidney renal clear cell carcinoma (KIRC), Breast Invasive Carcinoma (BRCA), lung adenocarcinoma (LUAD), Prostate Adenocarcinoma (PRAD) and Colon Adenocarcinoma (COAD). The performance of different optimizers like Stochastic gradient descent (SGD), Root Mean Squared Propagation (RMSProp), Adaptive Gradient Optimizer (AdaGrad), and Adaptive Momentum (AdaM). The experimental results gathered on the dataset affirm that AdaGrad and Adam. Also, the performance analysis has been done using different learning rates and decay rates. This study discusses current advancements in deep learning-based gene expression data analysis using optimized feature selection methods.
PubMed: 36246115
DOI: 10.3389/fphys.2022.952709 -
American Journal of Obstetrics and... Apr 2023This study aimed to determine the incremental yield of prenatal exome sequencing over chromosomal microarray or G-banding karyotype in fetuses with: (1) intrauterine... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
This study aimed to determine the incremental yield of prenatal exome sequencing over chromosomal microarray or G-banding karyotype in fetuses with: (1) intrauterine growth restriction related to placental insufficiency or (2) short long bones, in isolated and nonisolated instances for both scenarios.
DATA SOURCES
Data were collected via electronic searches for relevant citations from January 2010 to April 10, 2022 in MEDLINE, Embase, Web of Science, and Cochrane, and using relevant bibliographies and data generated in-house.
STUDY ELIGIBILITY CRITERIA
Included were prospective or retrospective cohort studies and/or case series with: (1) n>5 cases of short long bones and/or intrauterine growth restriction undergoing prenatal sequencing with a clearly defined phenotype including assessment of placental function; (2) testing based on prenatal phenotype only; (3) a nondiagnostic chromosomal microarray/karyotype; and (4) known results of genetic testing.
METHODS
Incremental yield was calculated for each study and as a pooled value for the aforementioned groups using a random-effects model. Results were displayed in forest plots with 95% confidence intervals. Heterogeneity was assessed statistically using Higgins' I. Publication bias was assessed graphically using funnel plots. Quality assessment was performed using modified Standards for Reporting of Diagnostic Accuracy criteria (International Prospective Register of Systematic Reviews registration number CRD42022324680).
RESULTS
Nineteen studies were included (n=452 cases). The apparent incremental yields with prenatal sequencing were: (1) 4% (95% confidence interval, -5.0 to 12; I=0%) in isolated intrauterine growth restriction with evidence of placental insufficiency, (2) 30% (95% confidence interval, 13-47; I=1%) in intrauterine growth restriction with additional structural anomalies, (3) 48% (95% confidence interval, 26-70; I=73%) in isolated short long bones, and (4) 68% (95% confidence interval, 58-77; I=51%) in short long bones with additional skeletal anomalies. Of the 37 short long bone cases with a diagnosis, 32 had a skeletal dysplasia, with thanatophoric dysplasia and osteogenesis imperfecta being the most common (both 21.6% [n=8/37]). In fetuses with short long bones and additional skeletal features, osteogenesis imperfecta was the most common diagnosis (28% [n=57/204]). Where documented, the inheritance patterns were de novo in 75.4% (n=150) of cases.
CONCLUSION
Prenatal sequencing adds substantially to incremental yield over chromosomal microarray in fetuses with short long bones or multisystem intrauterine growth restriction. Robust studies are required to assess the utility of fetal sequencing in isolated intrauterine growth restriction with evidence of placental insufficiency, which cannot be recommended on the basis of current evidence.
Topics: Humans; Pregnancy; Female; Fetal Growth Retardation; Placental Insufficiency; Exome Sequencing; Retrospective Studies; Osteogenesis Imperfecta; Placenta; Prenatal Diagnosis; Ultrasonography, Prenatal
PubMed: 36209938
DOI: 10.1016/j.ajog.2022.09.045