Which genes are confidently linked to human monogenic male infertility? Our systematic literature search and clinical validity assessment reveals that a total of 78 genes are currently confidently linked to 92 human male infertility phenotypes. The discovery of novel male infertility genes is rapidly accelerating with the availability of next-generating sequencing methods, but the quality of evidence for gene–disease relationships varies greatly. In order to improve genetic research, diagnostics and counseling, there is a need for an evidence-based overview of the currently known genes. We performed a systematic literature search and evidence assessment for all publications in Pubmed until December 2018 covering genetic causes of male infertility and/or defective male genitourinary development. Two independent reviewers conducted the literature search and included papers on the monogenic causes of human male infertility and excluded papers on genetic association or risk factors, karyotype anomalies and/or copy number variations affecting multiple genes. Next, the quality and the extent of all evidence supporting selected genes was weighed by a standardized scoring method and used to determine the clinical validity of each gene–disease relationship as expressed by the following six categories: no evidence, limited, moderate, strong, definitive or unable to classify. From a total of 23 526 records, we included 1337 publications about monogenic causes of male infertility leading to a list of 521 gene–disease relationships. The clinical validity of these gene–disease relationships varied widely and ranged from definitive (n = 38) to strong (n = 22), moderate (n = 32), limited (n = 93) or no evidence (n = 160). A total of 176 gene–disease relationships could not be classified because our scoring method was not suitable. Not applicable. Our literature search was limited to Pubmed. The comprehensive overview will aid researchers and clinicians in the field to establish gene lists for diagnostic screening using validated gene–disease criteria and help to identify gaps in our knowledge of male infertility. For future studies, the authors discuss the relevant and important international guidelines regarding research related to gene discovery and provide specific recommendations for the field of male infertility. This work was supported by a VICI grant from The Netherlands Organization for Scientific Research (918-15-667 to J.A.V.), the Royal Society, and Wolfson Foundation (WM160091 to J.A.V.) as well as an investigator award in science from the Wellcome Trust (209451 to J.A.V.). None.

Successful whole genome amplification (WGA) is a cornerstone of contemporary preimplantation genetic testing (PGT). Choosing the most suitable WGA technique for PGT can be particularly challenging because each WGA technique performs differently in combination with different downstream processing and detection methods. The aim of this review is to provide insight into the performance and drawbacks of DOP-PCR, MDA and MALBAC, as well as the hybrid WGA techniques most widely used in PGT. As the field of PGT is moving towards a wide adaptation of comprehensive massively parallel sequencing (MPS)-based approaches, we especially focus our review on MPS parameters and detection opportunities of WGA-amplified material, i.e., mappability of reads, uniformity of coverage and its influence on copy number variation analysis, and genomic coverage and its influence on single nucleotide variation calling. The ability of MDA-based WGA solutions to better cover the targeted genome and the ability of PCR-based solutions to provide better uniformity of coverage are highlighted. While numerous comprehensive PGT solutions exploiting different WGA types and adjusted bioinformatic pipelines to detect copy number and single nucleotide changes are available, the ones exploiting MDA appear more advantageous. The opportunity to fully analyse the targeted genome is influenced by the MPS parameters themselves rather than the solely chosen WGA.

Preterm delivery is both a traumatizing experience for the patient and a burden on the healthcare system. A condition distinguishable by its phenotype in prematurity is cervical insufficiency, where certain cases exhibit a strong genetic component. Despite genomic advancements, little is known about the genetics of human cervix remodeling during pregnancy. Using selected gene approaches, a few studies have demonstrated an association of common gene variants with cervical insufficiency. However, until now, no study has employed comprehensive methods to investigate this important subject matter. In this study, we asked: i) are there genes reliably linked to cervical insufficiency and, if so, what are their roles? and ii) what is the proportion of cases of non-syndromic cervical insufficiency attributable to these genetic variations? We performed next-generation sequencing on 21 patients with a clinical presentation of cervical insufficiency. To assist the sequencing data interpretation, we retrieved all known genes implicated in cervical functioning through a systematic literature analysis and additional gene searches. These genes were then classified according to their relation to the questions being posed by the study. Patients’ sequence variants were filtered for pathogenicity and assigned a likelihood of being contributive to phenotype development. Gene extraction and analysis revealed 12 genes primarily linked to cervical insufficiency, the majority of which are known to cause collagenopathies. Ten patients carried disruptive variants potentially contributive to the development of non-syndromic cervical insufficiency. Pathway enrichment analysis of variant genes from our cohort revealed an increased variation burden in genes playing roles in tissue mechanical and biomechanical properties, i.e. collagen biosynthesis and cell-extracellular matrix communications. Consequently, the proposed idea of cervical insufficiency being a subtle form of collagenopathy, now strengthened by our genetic findings, might open up new opportunities for improved patient evaluation and management.

Genetic testing is becoming increasingly required at almost every stage of failed female reproduction/infertility. Nonetheless, clinical evidence for the majority of identified gene–disease relationships is ill-defined, thus leading to difficult gene variant interpretation and poor translation of existing knowledge into clinics. We aimed to identify the genes that have ever been implicated in monogenic female reproductive failure in humans and to classify the identified gene–disease relationship pairs using a standardized clinical validity assessment. A PubMed search following PRISMA guidelines was conducted on 20 September 2021 aiming to identify studies pertaining to genetic causes of phenotypes of female reproductive failure. The clinical validity of identified gene–disease pairs was assessed using standardized criteria, counting whether sufficient genetic and experimental evidence has been accumulated to consider a single gene ‘characterized’ for a single Mendelian disease. In total, 1256 articles were selected for the data extraction; 183 unique gene–disease pairs were classified spanning the following phenotypes: hypogonadotropic hypogonadism, ovarian dysgenesis, premature ovarian failure/insufficiency, ovarian hyperstimulation syndrome, empty follicle syndrome, oocyte maturation defect, fertilization failure, early embryonic arrest, recurrent hydatidiform mole, adrenal disfunction and Mullerian aplasia. Twenty-four gene–disease pairs showed definitive evidence, 36 – strong, 19 – moderate, 81 – limited and 23 – showed no evidence. Here, we provide comprehensive, systematic and timely information on the genetic causes of female infertility. Our classification of genetic causes of female reproductive failure will facilitate the composition of up-to-date guidelines on genetic testing in female reproduction, the development of diagnostic gene panels and the advancement of reproductive decision-making.

Background and Objectives: Preterm birth is the leading cause of neonatal mortality worldwide and may be responsible for lifelong morbidities in the survivors. Cervical shortening is one of the common pathways to preterm birth associated with its own diagnostic and management challenges. The preventive modalities that have been tested include progesterone supplementation and cervical cerclage and pessaries. The study aimed to assess the management strategies and outcomes in a group of patients with a short cervix during pregnancy or cervical insufficiency. Materials and Methods: Seventy patients from the Riga Maternity Hospital in Riga, Latvia, were included in the prospective longitudinal cohort study between 2017 and 2021. Patients were treated with progesterone, cerclage, and/or pessaries. The signs of intra-amniotic infection/inflammation were assessed, and antibacterial therapy was given when the signs were positive. Results: The rates of PTB were 43.6% (n = 17), 45.5% (n = 5), 61.1% (n = 11), and 50.0% (n = 1) in progesterone only, cerclage, pessary, and cerclage plus pesssary groups, respectively. The progesterone therapy was associated with a reduced preterm birth risk (x2(1) = 6.937, p = 0.008)), whereas positive signs of intra-amniotic infection/inflammation significantly predicted the risk of preterm birth (p = 0.005, OR = 3.82, 95% [CI 1.31–11.11]). Conclusions: A short cervix and bulging membranes, both indicators of intra-amniotic infection/inflammation, are the key risk factors in preterm birth risk predictions. Progesterone supplementation should remain at the forefront of preterm birth prevention. Among patients with a short cervix and especially complex anamnesis, the preterm rates remain high. The successful management of patients with cervical shortening lies between the consensus-based approach for screening, follow-up, and treatment on the one side and personalising medical therapy on the other.

To compare multiple displacement amplification and OmniPlex whole genome amplification technique performance during array comparative genome hybridization (aCGH), Sanger sequencing, SNaPshot and fragment size analysis downstream applications in frame of multifactor embryo preimplantation genetic testing.