Genetics of Primary Ovarian Insufficiency in the Next-Generation Sequencing Era.
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ABSTRACT:
SUBMITTER: Franca MM
PROVIDER: S-EPMC7033037 | biostudies-literature | 2020 Feb
REPOSITORIES: biostudies-literature
Publications
Genetics of Primary Ovarian Insufficiency in the Next-Generation Sequencing Era.
França Monica Malheiros MM Mendonca Berenice Bilharinho BB
Journal of the Endocrine Society 20190219 2
Primary ovarian insufficiency (POI) is characterized by amenorrhea, increased follicle-stimulating hormone (FSH) levels, and hypoestrogenism, leading to infertility before the age of 40 years. Elucidating the cause of POI is a key point for diagnosing and treating affected women. Here, we review the genetic etiology of POI, highlighting new genes identified in the last few years using next-generation sequencing (NGS) approaches. We searched the MEDLINE/PubMed, Cochrane, and Web of Science databa ...[more]
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Project description:ContextPrimary ovarian insufficiency (POI) affects 1% of women under 40 years of age. POI is idiopathic in more than 70% of cases. Though many candidate genes have been identified in recent years, the prevalence and pathogenicity of abnormalities are still difficult to establish.ObjectiveOur primary objective was to evaluate the prevalence of gene variations in a large prospective multicentric POI cohort. Our secondary objective was to evaluate the correlation between phenotype and genotype.MethodsTwo hundred and sixty-nine well-phenotyped POI patients were screened for variants of 18 known POI genes (BMP15, DMC1, EIF2S2, FIGLA, FOXL2, FSHR, GDF9, GPR3, HFM1, LHX8, MSH5, NOBOX, NR5A1, PGRMC1, STAG3, XPNPEP2, BHLB, and FSHB) by next generation sequencing (NGS). Abnormalities were classified as "variant" or "variant of unknown signification" (VUS) according to available functional tests or algorithms (SIFT, Polyphen-2, MutationTaster).ResultsOne hundred and two patients (38%) were identified as having at least 1 genetic abnormality. Sixty-seven patients (25%) presented at least 1 variant. Forty-eight patients presented at least 1 VUS (18%). Thirteen patients (5%) had combined abnormalities. NOBOX variants were the most common gene variants involved in POI (9%). Interestingly, we saw no significant differences in the previous family history of POI, ethnic origin, age at onset of POI, primary amenorrhea, or secondary menstrual disturbances between the different genotypes.ConclusionIn our study, a high percentage of patients presented gene variants detected by NGS analysis (38%). Every POI patient should undergo NGS analysis to improve medical cares of the patients.
| S-EPMC8169040 | biostudies-literature
Project description:Primary ovarian insufficiency (POI) is one of the major causes of female infertility associated with the premature loss of ovarian function in about 3.7% of women before the age of 40. This disorder is highly heterogeneous and can manifest with a wide range of clinical phenotypes, ranging from ovarian dysgenesis and primary amenorrhea to post-pubertal secondary amenorrhea, with elevated serum gonadotropins and hypoestrogenism. The ovarian defect still remains idiopathic in some cases; however, a strong genetic component has been demonstrated by the next-generation sequencing (NGS) approach of familiar and sporadic POI cases. As recent evidence suggested an oligogenic architecture for POI, we developed a target NGS panel with 295 genes including known candidates and novel genetic determinants potentially involved in POI pathogenesis. Sixty-four patients with early onset POI (range: 10-25 years) of our cohort have been screened with 90% of target coverage at 50×. Here, we report 48 analyzed patients with at least one genetic variant (75%) in the selected candidate genes. In particular, we found the following: 11/64 patients (17%) with two variants, 9/64 (14%) with three variants, 9/64 (14%) with four variants, 3/64 (5%) with five variants, and 2/64 (3%) with six variants. The most severe phenotypes were associated with either the major number of variations or a worse prediction in pathogenicity of variants. Bioinformatic gene ontology analysis identified the following major pathways likely affected by gene variants: 1) cell cycle, meiosis, and DNA repair; 2) extracellular matrix remodeling; 3) reproduction; 4) cell metabolism; 5) cell proliferation; 6) calcium homeostasis; 7) NOTCH signaling; 8) signal transduction; 9) WNT signaling; 10) cell death; and 11) ubiquitin modifications. Consistently, the identified pathways have been described in other studies dissecting the mechanisms of folliculogenesis in animal models of altered fertility. In conclusion, our results contribute to define POI as an oligogenic disease and suggest novel candidates to be investigated in patients with POI.
| S-EPMC8600266 | biostudies-literature
Project description:Ovarian cancer is one of the cancers most influenced by hereditary factors. Testing for hereditary susceptibility genes is recommended for every woman with epithelial ovarian cancer (EOC). Pathogenic germline variants in BRCA1 and BRCA2 genes are responsible for a substantial fraction of hereditary ovarian cancer. However, alterations in other genes, such as BRIP1, RAD51C, RAD51D, and mismatch repair genes, also enhance ovarian cancer risk. Other genes may also participate in ovarian carcinogenesis, but their role as ovarian cancer susceptibility genes still needs to be clarified. With several genes involved, the complexity of genetic testing increases. In this context, next-generation sequencing (NGS) allows testing for multiple genes simultaneously, with rapid turn-around time. However, the incorporation of this technology into clinical practice faces some challenges. In this review, we will discuss the ovarian cancer risk assessment in the era of NGS.
| S-EPMC7812181 | biostudies-literature
Project description:Primary ovarian insufficiency is one of the main causes of female infertility owing to an abnormal ovarian reserve. Its relevance has increased in more recent years due to the fact that age of motherhood is being delayed in developed countries, with the risk of having either primary ovarian insufficiency or less chances of pregnancy when women consider the option of having their first baby. Several exogenous factors can lead to this event, such us viral infections, metabolomic dysfunction, autoimmune diseases, and environmental or iatrogenic factors, although in most cases the mechanism that leads to the disorder is unknown. Genetic factors represent the most commonly identified cause and the impact of sex chromosome abnormalities (e.g., Turner syndrome or X structural abnormalities), autosomal and X-linked mutations on the genesis of primary ovarian insufficiency has also been well described. Yet in most cases, the genetic origin remains unknown and there are multiple candidate genes. This review aims to collect all the genetic abnormalities and genes associated with syndromic and non syndromic primary ovarian insufficiency that have been published in the literature to date using the candidate-gene approach and a genome-wide analysis.
| S-EPMC4250468 | biostudies-literature
Project description:ObjectivePrimary ovarian insufficiency (POI) and Non-obstructive azoospermia (NOA) both represent disease states of early, and often complete, failure of gametogenesis. Because oogenesis and spermatogenesis share the same conserved steps in meiosis I, it is possible that inherited defects in meiosis I could lead to shared causes of both POI and NOA. Currently, known genes that contribute to both POI and NOA are limited. In this review article, we provide a systematic review of genetic mutations in which both POI and NOA phenotypes exist.Evidence reviewA PubMed literature review was conducted from January 1, 2000 through October 2020. We included all studies that demonstrated human cases of POI or NOA due to a specific genetic mutation either within the same family or in separate families.ResultsWe identified 33 papers that encompassed 10 genes of interest with mutations implicated in both NOA and POI. The genes were all involved in processes of meiosis I.ConclusionMutations in genes involved in processes of meiosis I may cause both NOA and POI. Identifying these unique phenotypes among shared genotypes leads to biologic plausibility that the key error occurs early in gametogenesis with an etiology shared among both male and female offspring. From a clinical standpoint, this shared relationship may help us better understand and identify individuals at high risk for gonadal failure within families and suggests that clinicians obtain history for opposite sex family members when approaching a new diagnosis of POI or NOA.
| S-EPMC9518791 | biostudies-literature
Project description:BackgroundPrimary ovarian insufficiency (POI) is characterized by marked heterogeneity, but with a significant genetic contribution. Identifying exact causative genes has been challenging, with many discoveries not replicated. It is timely to take stock of the field, outlining the progress made, framing the controversies and anticipating future directions in elucidating the genetics of POI.MethodsA search for original articles published up to May 2015 was performed using PubMed and Google Scholar, identifying studies on the genetic etiology of POI. Studies were included if chromosomal analysis, candidate gene screening and a genome-wide study were conducted. Articles identified were restricted to English language full-text papers.ResultsChromosomal abnormalities have long been recognized as a frequent cause of POI, with a currently estimated prevalence of 10-13%. Using the traditional karyotype methodology, monosomy X, mosaicism, X chromosome deletions and rearrangements, X-autosome translocations, and isochromosomes have been detected. Based on candidate gene studies, single gene perturbations unequivocally having a deleterious effect in at least one population include Bone morphogenetic protein 15 (BMP15), Progesterone receptor membrane component 1 (PGRMC1), and Fragile X mental retardation 1 (FMR1) premutation on the X chromosome; Growth differentiation factor 9 (GDF9), Folliculogenesis specific bHLH transcription factor (FIGLA), Newborn ovary homeobox gene (NOBOX), Nuclear receptor subfamily 5, group A, member 1 (NR5A1) and Nanos homolog 3 (NANOS3) seem likely as well, but mostly being found in no more than 1-2% of a single population studied. Whole genome approaches have utilized genome-wide association studies (GWAS) to reveal loci not predicted on the basis of a candidate gene, but it remains difficult to locate causative genes and susceptible loci were not always replicated. Cytogenomic methods (array CGH) have identified other regions of interest but studies have not shown consistent results, the resolution of arrays has varied and replication is uncommon. Whole-exome sequencing in non-syndromic POI kindreds has only recently begun, revealing mutations in the Stromal antigen 3 (STAG3), Synaptonemal complex central element 1 (SYCE1), minichromosome maintenance complex component 8 and 9 (MCM8, MCM9) and ATP-dependent DNA helicase homolog (HFM1) genes. Given the slow progress in candidate-gene analysis and relatively small sample sizes available for GWAS, family-based whole exome and whole genome sequencing appear to be the most promising approaches for detecting potential genes responsible for POI.ConclusionTaken together, the cytogenetic, cytogenomic (array CGH) and exome sequencing approaches have revealed a genetic causation in ∼20-25% of POI cases. Uncovering the remainder of the causative genes will be facilitated not only by whole genome approaches involving larger cohorts in multiple populations but also incorporating environmental exposures and exploring signaling pathways in intragenic and intergenic regions that point to perturbations in regulatory genes and networks.
| S-EPMC4594617 | biostudies-literature
Project description:ObjectivesTo identify the role of next-generation sequencing (NGS) in male infertility, as advances in NGS technologies have contributed to the identification of novel genes responsible for a wide variety of human conditions and recently has been applied to male infertility, allowing new genetic factors to be discovered.Materials and methodsPubMed was searched for combinations of the following terms: 'exome', 'genome', 'panel', 'sequencing', 'whole-exome sequencing', 'whole-genome sequencing', 'next-generation sequencing', 'azoospermia', 'oligospermia', 'asthenospermia', 'teratospermia', 'spermatogenesis', and 'male infertility', to identify studies in which NGS technologies were used to discover variants causing male infertility.ResultsAltogether, 23 studies were found in which the primary mode of variant discovery was an NGS-based technology. These studies were mostly focused on patients with quantitative sperm abnormalities (non-obstructive azoospermia and oligospermia), followed by morphological and motility defects. Combined, these studies uncover variants in 28 genes causing male infertility discovered by NGS methods.ConclusionsMale infertility is a condition that is genetically heterogeneous, and therefore remarkably amenable to study by NGS. Although some headway has been made, given the high incidence of this condition despite its detrimental effect on reproductive fitness, there is significant potential for further discoveries.
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Project description:Linkage analysis was developed to detect excess co-segregation of the putative alleles underlying a phenotype with the alleles at a marker locus in family data. Many different variations of this analysis and corresponding study design have been developed to detect this co-segregation. Linkage studies have been shown to have high power to detect loci that have alleles (or variants) with a large effect size, i.e. alleles that make large contributions to the risk of a disease or to the variation of a quantitative trait. However, alleles with a large effect size tend to be rare in the population. In contrast, association studies are designed to have high power to detect common alleles which tend to have a small effect size for most diseases or traits. Although genome-wide association studies have been successful in detecting many new loci with common alleles of small effect for many complex traits, these common variants often do not explain a large proportion of disease risk or variation of the trait. In the past, linkage studies were successful in detecting regions of the genome that were likely to harbor rare variants with large effect for many simple Mendelian diseases and for many complex traits. However, identifying the actual sequence variant(s) responsible for these linkage signals was challenging because of difficulties in sequencing the large regions implicated by each linkage peak. Current 'next-generation' DNA sequencing techniques have made it economically feasible to sequence all exons or the whole genomes of a reasonably large number of individuals. Studies have shown that rare variants are quite common in the general population, and it is now possible to combine these new DNA sequencing methods with linkage studies to identify rare causal variants with a large effect size. A brief review of linkage methods is presented here with examples of their relevance and usefulness for the interpretation of whole-exome and whole-genome sequence data.
| S-EPMC3267991 | biostudies-literature
Project description:Metabolic myopathies are rare inherited disorders that deserve more attention from neurologists and pediatricians. Pompe disease and McArdle disease represent some of the most common diseases in clinical practice; however, other less common diseases are now better-known. In general the pathophysiology of metabolic myopathies needs to be better understood. Thanks to the advent of next-generation sequencing (NGS), genetic testing has replaced more invasive investigations and sophisticated enzymatic assays to reach a final diagnosis in many cases. The current diagnostic algorithms for metabolic myopathies have integrated this paradigm shift and restrict invasive investigations for complicated cases. Moreover, NGS contributes to the discovery of novel genes and proteins, providing new insights into muscle metabolism and pathophysiology. More importantly, a growing number of these conditions are amenable to therapeutic approaches such as diets of different kinds, exercise training protocols, and enzyme replacement therapy or gene therapy. Prevention and management-notably of rhabdomyolysis-are key to avoiding serious and potentially life-threatening complications and improving patients' quality of life. Although not devoid of limitations, the newborn screening programs that are currently mushrooming across the globe show that early intervention in metabolic myopathies is a key factor for better therapeutic efficacy and long-term prognosis. As a whole NGS has largely increased the diagnostic yield of metabolic myopathies, but more invasive but classical investigations are still critical when the genetic diagnosis is unclear or when it comes to optimizing the follow-up and care of these muscular disorders.
| S-EPMC10217901 | biostudies-literature
Project description:There are challenges in the genetic diagnosis of rare diseases, and pursuing an optimal strategy to identify the cause of the disease is one of the main objectives of any clinical genomics unit. A range of techniques are currently used to characterize the genomic variability within the human genome to detect causative variants of specific disorders. With the introduction of next-generation sequencing (NGS) in the clinical setting, geneticists can study single-nucleotide variants (SNVs) throughout the entire exome/genome. In turn, the number of variants to be evaluated per patient has increased significantly, and more information has to be processed and analyzed to determine a proper diagnosis. Roughly 50% of patients with a Mendelian genetic disorder are diagnosed using NGS, but a fair number of patients still suffer a diagnostic odyssey. Due to the inherent diversity of the human population, as more exomes or genomes are sequenced, variants of uncertain significance (VUSs) will increase exponentially. Thus, assigning relevance to a VUS (non-synonymous as well as synonymous) in an undiagnosed patient becomes crucial to assess the proper diagnosis. Multiple algorithms have been used to predict how a specific mutation might affect the protein's function, but they are far from accurate enough to be conclusive. In this work, we highlight the difficulties of genomic variability determined by NGS that have arisen in diagnosing rare genetic diseases, and how molecular modelling has to be a key component to elucidate the relevance of a specific mutation in the protein's loss of function or malfunction. We suggest that the creation of a multi-omics data model should improve the classification of pathogenicity for a significant amount of the detected genomic variability. Moreover, we argue how it should be incorporated systematically in the process of variant evaluation to be useful in the clinical setting and the diagnostic pipeline.
| S-EPMC9266691 | biostudies-literature