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Dapkūnas J, Timinskas A, Olechnovič K, Tomkuvienė M, Venclovas Č. PPI3D: a web server for searching, analyzing and modeling protein-protein, protein-peptide and protein-nucleic acid interactions. Nucleic Acids Res 2024; 52:W264-W271. [PMID: 38619046 PMCID: PMC11223826 DOI: 10.1093/nar/gkae278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 03/19/2024] [Accepted: 04/03/2024] [Indexed: 04/16/2024] Open
Abstract
Structure-resolved protein interactions with other proteins, peptides and nucleic acids are key for understanding molecular mechanisms. The PPI3D web server enables researchers to query preprocessed and clustered structural data, analyze the results and make homology-based inferences for protein interactions. PPI3D offers three interaction exploration modes: (i) all interactions for proteins homologous to the query, (ii) interactions between two proteins or their homologs and (iii) interactions within a specific PDB entry. The server allows interactive analysis of the identified interactions in both summarized and detailed manner. This includes protein annotations, structures, the interface residues and the corresponding contact surface areas. In addition, users can make inferences about residues at the interaction interface for the query protein(s) from the sequence alignments and homology models. The weekly updated PPI3D database includes all the interaction interfaces and binding sites from PDB, clustered based on both protein sequence and structural similarity, yielding non-redundant datasets without loss of alternative interaction modes. Consequently, the PPI3D users avoid being flooded with redundant information, a typical situation for intensely studied proteins. Furthermore, PPI3D provides a possibility to download user-defined sets of interaction interfaces and analyze them locally. The PPI3D web server is available at https://bioinformatics.lt/ppi3d.
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Affiliation(s)
- Justas Dapkūnas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio av. 7, Vilnius LT-10257, Lithuania
| | - Albertas Timinskas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio av. 7, Vilnius LT-10257, Lithuania
| | - Kliment Olechnovič
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio av. 7, Vilnius LT-10257, Lithuania
- Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
| | - Miglė Tomkuvienė
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio av. 7, Vilnius LT-10257, Lithuania
| | - Česlovas Venclovas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Saulėtekio av. 7, Vilnius LT-10257, Lithuania
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Lillepea K, Juchnewitsch AG, Kasak L, Valkna A, Dutta A, Pomm K, Poolamets O, Nagirnaja L, Tamp E, Mahyari E, Vihljajev V, Tjagur S, Papadimitriou S, Riera-Escamilla A, Versbraegen N, Farnetani G, Castillo-Madeen H, Sütt M, Kübarsepp V, Tennisberg S, Korrovits P, Krausz C, Aston KI, Lenaerts T, Conrad DF, Punab M, Laan M. Toward clinical exomes in diagnostics and management of male infertility. Am J Hum Genet 2024; 111:877-895. [PMID: 38614076 PMCID: PMC11080280 DOI: 10.1016/j.ajhg.2024.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/22/2024] [Accepted: 03/22/2024] [Indexed: 04/15/2024] Open
Abstract
Infertility, affecting ∼10% of men, is predominantly caused by primary spermatogenic failure (SPGF). We screened likely pathogenic and pathogenic (LP/P) variants in 638 candidate genes for male infertility in 521 individuals presenting idiopathic SPGF and 323 normozoospermic men in the ESTAND cohort. Molecular diagnosis was reached for 64 men with SPGF (12%), with findings in 39 genes (6%). The yield did not differ significantly between the subgroups with azoospermia (20/185, 11%), oligozoospermia (18/181, 10%), and primary cryptorchidism with SPGF (26/155, 17%). Notably, 19 of 64 LP/P variants (30%) identified in 28 subjects represented recurrent findings in this study and/or with other male infertility cohorts. NR5A1 was the most frequently affected gene, with seven LP/P variants in six SPGF-affected men and two normozoospermic men. The link to SPGF was validated for recently proposed candidate genes ACTRT1, ASZ1, GLUD2, GREB1L, LEO1, RBM5, ROS1, and TGIF2LY. Heterozygous truncating variants in BNC1, reported in female infertility, emerged as plausible causes of severe oligozoospermia. Data suggested that several infertile men may present congenital conditions with less pronounced or pleiotropic phenotypes affecting the development and function of the reproductive system. Genes regulating the hypothalamic-pituitary-gonadal axis were affected in >30% of subjects with LP/P variants. Six individuals had more than one LP/P variant, including five with two findings from the gene panel. A 4-fold increased prevalence of cancer was observed in men with genetic infertility compared to the general male population (8% vs. 2%; p = 4.4 × 10-3). Expanding genetic testing in andrology will contribute to the multidisciplinary management of SPGF.
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Affiliation(s)
- Kristiina Lillepea
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Anna-Grete Juchnewitsch
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Laura Kasak
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Anu Valkna
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Avirup Dutta
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Kristjan Pomm
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Olev Poolamets
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Liina Nagirnaja
- Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006, USA
| | - Erik Tamp
- Center of Pathology, Diagnostic Clinic, East Tallinn Central Hospital, 10138 Tallinn, Estonia
| | - Eisa Mahyari
- Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006, USA
| | | | - Stanislav Tjagur
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Sofia Papadimitriou
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium; Department of Biomolecular Medicine, Faculty of Medicine and Health Science, Ghent University, 9000 Ghent, Belgium
| | - Antoni Riera-Escamilla
- Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006, USA; Andrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau, 08025 Barcelona, Catalonia, Spain
| | - Nassim Versbraegen
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Ginevra Farnetani
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50134 Florence, Italy
| | - Helen Castillo-Madeen
- Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006, USA
| | - Mailis Sütt
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Viljo Kübarsepp
- Department of Surgery, Institute of Clinical Medicine, University of Tartu, 50406 Tartu, Estonia; Department of Pediatric Surgery, Clinic of Surgery, Tartu University Hospital, 51014 Tartu, Estonia
| | - Sven Tennisberg
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Paul Korrovits
- Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia
| | - Csilla Krausz
- Andrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau, 08025 Barcelona, Catalonia, Spain; Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50134 Florence, Italy
| | - Kenneth I Aston
- Andrology and IVF Laboratory, Department of Surgery (Urology), University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050 Brussels, Belgium; Machine Learning Group, Université Libre de Bruxelles, 1050 Brussels, Belgium; Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Donald F Conrad
- Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006, USA; Center for Embryonic Cell & Gene Therapy, Oregon Health & Science University, Beaverton, OR 97239, USA
| | - Margus Punab
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; Andrology Clinic, Tartu University Hospital, 50406 Tartu, Estonia; Department of Surgery, Institute of Clinical Medicine, University of Tartu, 50406 Tartu, Estonia.
| | - Maris Laan
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia.
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Juchnewitsch AG, Pomm K, Dutta A, Tamp E, Valkna A, Lillepea K, Mahyari E, Tjagur S, Belova G, Kübarsepp V, Castillo-Madeen H, Riera-Escamilla A, Põlluaas L, Nagirnaja L, Poolamets O, Vihljajev V, Sütt M, Versbraegen N, Papadimitriou S, McLachlan RI, Jarvi KA, Schlegel PN, Tennisberg S, Korrovits P, Vigh-Conrad K, O’Bryan MK, Aston KI, Lenaerts T, Conrad DF, Kasak L, Punab M, Laan M. Undiagnosed RASopathies in infertile men. Front Endocrinol (Lausanne) 2024; 15:1312357. [PMID: 38654924 PMCID: PMC11035881 DOI: 10.3389/fendo.2024.1312357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 03/11/2024] [Indexed: 04/26/2024] Open
Abstract
RASopathies are syndromes caused by congenital defects in the Ras/mitogen-activated protein kinase (MAPK) pathway genes, with a population prevalence of 1 in 1,000. Patients are typically identified in childhood based on diverse characteristic features, including cryptorchidism (CR) in >50% of affected men. As CR predisposes to spermatogenic failure (SPGF; total sperm count per ejaculate 0-39 million), we hypothesized that men seeking infertility management include cases with undiagnosed RASopathies. Likely pathogenic or pathogenic (LP/P) variants in 22 RASopathy-linked genes were screened in 521 idiopathic SPGF patients (including 155 CR cases) and 323 normozoospermic controls using exome sequencing. All 844 men were recruited to the ESTonian ANDrology (ESTAND) cohort and underwent identical andrological phenotyping. RASopathy-specific variant interpretation guidelines were used for pathogenicity assessment. LP/P variants were identified in PTPN11 (two), SOS1 (three), SOS2 (one), LZTR1 (one), SPRED1 (one), NF1 (one), and MAP2K1 (one). The findings affected six of 155 cases with CR and SPGF, three of 366 men with SPGF only, and one (of 323) normozoospermic subfertile man. The subgroup "CR and SPGF" had over 13-fold enrichment of findings compared to controls (3.9% vs. 0.3%; Fisher's exact test, p = 5.5 × 10-3). All ESTAND subjects with LP/P variants in the Ras/MAPK pathway genes presented congenital genitourinary anomalies, skeletal and joint conditions, and other RASopathy-linked health concerns. Rare forms of malignancies (schwannomatosis and pancreatic and testicular cancer) were reported on four occasions. The Genetics of Male Infertility Initiative (GEMINI) cohort (1,416 SPGF cases and 317 fertile men) was used to validate the outcome. LP/P variants in PTPN11 (three), LZTR1 (three), and MRAS (one) were identified in six SPGF cases (including 4/31 GEMINI cases with CR) and one normozoospermic man. Undiagnosed RASopathies were detected in total for 17 ESTAND and GEMINI subjects, 15 SPGF patients (10 with CR), and two fertile men. Affected RASopathy genes showed high expression in spermatogenic and testicular somatic cells. In conclusion, congenital defects in the Ras/MAPK pathway genes represent a new congenital etiology of syndromic male infertility. Undiagnosed RASopathies were especially enriched among patients with a history of cryptorchidism. Given the relationship between RASopathies and other conditions, infertile men found to have this molecular diagnosis should be evaluated for known RASopathy-linked health concerns, including specific rare malignancies.
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Affiliation(s)
- Anna-Grete Juchnewitsch
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Kristjan Pomm
- Andrology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Avirup Dutta
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Erik Tamp
- Centre of Pathology, East Tallinn Central Hospital, Tallinn, Estonia
| | - Anu Valkna
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Kristiina Lillepea
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Eisa Mahyari
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | | | - Galina Belova
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Viljo Kübarsepp
- Department of Surgery, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Department of Pediatric Surgery, Clinic of Surgery, Tartu University Hospital, Tartu, Estonia
| | - Helen Castillo-Madeen
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | - Antoni Riera-Escamilla
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | - Lisanna Põlluaas
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Liina Nagirnaja
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | - Olev Poolamets
- Andrology Clinic, Tartu University Hospital, Tartu, Estonia
| | | | - Mailis Sütt
- Andrology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Nassim Versbraegen
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
| | - Sofia Papadimitriou
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Department of Biomolecular Medicine, Faculty of Medicine and Health Science, Ghent University, Ghent, Belgium
| | - Robert I. McLachlan
- Hudson Institute of Medical Research and the Department of Obstetrics and Gynecology, Monash University, Clayton, VIC, Australia
| | - Keith A. Jarvi
- Division of Urology, Department of Surgery, Mount Sinai Hospital, University of Toronto, Toronto, ON, Canada
| | - Peter N. Schlegel
- Department of Urology, Weill Cornell Medical College, New York, NY, United States
| | | | - Paul Korrovits
- Andrology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Katinka Vigh-Conrad
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
| | - Moira K. O’Bryan
- School of BioSciences, Faculty of Science, The University of Melbourne, Parkville, VIC, Australia
| | - Kenneth I. Aston
- Andrology and IVF Laboratory, Department of Surgery (Urology), University of Utah School of Medicine, Salt Lake City, UT, United States
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Brussels, Belgium
| | - Donald F. Conrad
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, United States
- Center for Embryonic Cell and Gene Therapy, Oregon Health and Science University, Beaverton, OR, United States
| | - Laura Kasak
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Margus Punab
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
- Andrology Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Surgery, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Maris Laan
- Chair of Human Genetics, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
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Roman-Naranjo P, Parra-Perez AM, Lopez-Escamez JA. A systematic review on machine learning approaches in the diagnosis and prognosis of rare genetic diseases. J Biomed Inform 2023:104429. [PMID: 37352901 DOI: 10.1016/j.jbi.2023.104429] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 06/05/2023] [Accepted: 06/17/2023] [Indexed: 06/25/2023]
Abstract
BACKGROUND The diagnosis of rare genetic diseases is often challenging due to the complexity of the genetic underpinnings of these conditions and the limited availability of diagnostic tools. Machine learning (ML) algorithms have the potential to improve the accuracy and speed of diagnosis by analyzing large amounts of genomic data and identifying complex multiallelic patterns that may be associated with specific diseases. In this systematic review, we aimed to identify the methodological trends and the ML application areas in rare genetic diseases. METHODS We performed a systematic review of the literature following the PRISMA guidelines to search studies that used ML approaches to enhance the diagnosis of rare genetic diseases. Studies that used DNA-based sequencing data and a variety of ML algorithms were included, summarized, and analyzed using bibliometric methods, visualization tools, and a feature co-occurrence analysis. FINDINGS Our search identified 22 studies that met the inclusion criteria. We found that exome sequencing was the most frequently used sequencing technology (59%), and rare neoplastic diseases were the most prevalent disease scenario (59%). In rare neoplasms, the most frequent applications of ML models were the differential diagnosis or stratification of patients (38.5%) and the identification of somatic mutations (30.8%). In other rare diseases, the most frequent goals were the prioritization of rare variants or genes (55.5%) and the identification of biallelic or digenic inheritance (33.3%). The most employed method was the random forest algorithm (54.5%). In addition, the features of the datasets needed for training these algorithms were distinctive depending on the goal pursued, including the mutational load in each gene for the differential diagnosis of patients, or the combination of genotype features and sequence-derived features (such as GC-content) for the identification of somatic mutations. CONCLUSIONS ML algorithms based on sequencing data are mainly used for the diagnosis of rare neoplastic diseases, with random forest being the most common approach. We identified key features in the datasets used for training these ML models according to the objective pursued. These features can support the development of future ML models in the diagnosis of rare genetic diseases.
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Affiliation(s)
- P Roman-Naranjo
- Division of Otolaryngology, Department of Surgery, Instituto de Investigación Biosanitaria, ibs.GRANADA, Universidad de Granada, Granada, Spain; Otology and Neurotology Group CTS495, Department of Genomic Medicine, GENYO - Centre for Genomics and Oncological Research - Pfizer, University of Granada, Junta de Andalucía, PTS, Granada, Spain; Sensorineural Pathology Programme, Centro de Investigación Biomédica en Red en Enfermedades Raras, CIBERER, Madrid, Spain.
| | - A M Parra-Perez
- Division of Otolaryngology, Department of Surgery, Instituto de Investigación Biosanitaria, ibs.GRANADA, Universidad de Granada, Granada, Spain; Otology and Neurotology Group CTS495, Department of Genomic Medicine, GENYO - Centre for Genomics and Oncological Research - Pfizer, University of Granada, Junta de Andalucía, PTS, Granada, Spain; Sensorineural Pathology Programme, Centro de Investigación Biomédica en Red en Enfermedades Raras, CIBERER, Madrid, Spain
| | - J A Lopez-Escamez
- Division of Otolaryngology, Department of Surgery, Instituto de Investigación Biosanitaria, ibs.GRANADA, Universidad de Granada, Granada, Spain; Otology and Neurotology Group CTS495, Department of Genomic Medicine, GENYO - Centre for Genomics and Oncological Research - Pfizer, University of Granada, Junta de Andalucía, PTS, Granada, Spain; Sensorineural Pathology Programme, Centro de Investigación Biomédica en Red en Enfermedades Raras, CIBERER, Madrid, Spain; Meniere's Disease Neuroscience Research Program, Faculty of Medicine & Health, School of Medical Sciences, The Kolling Institute, University of Sydney, Sydney, New South Wales, Australia
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Teoli J, Mallet D, Renault L, Gay CL, Labrune E, Bretones P, Giscard D’Estaing S, Cuzin B, Dijoud F, Roucher-Boulez F, Plotton I. Case Report: Longitudinal follow-up and testicular sperm extraction in a patient with a pathogenic NR5A1 (SF-1) frameshift variant: p.(Phe70Ser fs*5). Front Endocrinol (Lausanne) 2023; 14:1171822. [PMID: 37409232 PMCID: PMC10319352 DOI: 10.3389/fendo.2023.1171822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/26/2023] [Indexed: 07/07/2023] Open
Abstract
Background Steroidogenic factor 1 (SF-1), encoded by the nuclear receptor subfamily 5 group A member 1 (NR5A1) gene, is a transcriptional factor crucial for adrenal and gonadal organogenesis. Pathogenic variants of NR5A1 are responsible for a wide spectrum of phenotypes with autosomal dominant inheritance including disorders of sex development and oligospermia-azoospermia in 46,XY adults. Preservation of fertility remains challenging in these patients. Objective The aim was to offer fertility preservation at the end of puberty in an NR5A1 mutated patient. Case report The patient was born of non-consanguineous parents, with a disorder of sex development, a small genital bud, perineal hypospadias, and gonads in the left labioscrotal fold and the right inguinal region. Neither uterus nor vagina was detected. The karyotype was 46,XY. Anti-Müllerian hormone (AMH) and testosterone levels were low, indicating testicular dysgenesis. The child was raised as a boy. At 9 years old, he presented with precocious puberty treated by triptorelin. At puberty, follicle-stimulating hormone (FSH), luteinising hormone (LH), and testosterone levels increased, whereas AMH, inhibin B, and testicular volume were low, suggesting an impaired Sertoli cell function and a partially preserved Leydig cell function. A genetic study performed at almost 15 years old identified the new frameshift variant NM_004959.5: c.207del p.(Phe70Serfs*5) at a heterozygous state. He was thus addressed for fertility preservation. No sperm cells could be retrieved from three semen collections between the ages of 16 years 4 months and 16 years 10 months. A conventional bilateral testicular biopsy and testicular sperm extraction were performed at 17 years 10 months of age, but no sperm cells were found. Histological analysis revealed an aspect of mosaicism with seminiferous tubules that were either atrophic, with Sertoli cells only, or presenting an arrest of spermatogenesis at the spermatocyte stage. Conclusion We report a case with a new NR5A1 variant. The fertility preservation protocol proposed at the end of puberty did not allow any sperm retrieval for future parenthood.
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Affiliation(s)
- Jordan Teoli
- Service de Biochimie et Biologie Moléculaire, Unité Médicale de Biologie Endocrinienne, Centre de Biologie et Pathologie Est, Hospices Civils de Lyon, Bron, France
- Département des sciences biomédicales B, Institut des sciences pharmaceutiques et biologiques, Université Claude Bernard Lyon 1, Lyon, France
- Institut Cellule Souche et Cerveau (SBRI), Unité de Institut national de la recherche médicale (INSERM) 1208, Centre de Recherche INSERM, Bron, France
| | - Delphine Mallet
- Service de Biochimie et Biologie Moléculaire, Unité Médicale de Biologie Endocrinienne, Centre de Biologie et Pathologie Est, Hospices Civils de Lyon, Bron, France
- Centre de Référence Maladies Rares du Développement Génital: du Fœtus à l’Adulte, Filière Maladies Rares Endocriniennes, Bron, France
| | - Lucie Renault
- Service de médecine de la reproduction, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Bron, France
| | - Claire-Lise Gay
- Centre de Référence Maladies Rares du Développement Génital: du Fœtus à l’Adulte, Filière Maladies Rares Endocriniennes, Bron, France
- Service d’endocrinologie pédiatrique, Institut Saint-Pierre, Palavas-Les-Flots, France
| | - Elsa Labrune
- Institut Cellule Souche et Cerveau (SBRI), Unité de Institut national de la recherche médicale (INSERM) 1208, Centre de Recherche INSERM, Bron, France
- Service de médecine de la reproduction, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Bron, France
- Faculté de médecine, Université Claude Bernard Lyon 1, Lyon, France
| | - Patricia Bretones
- Centre de Référence Maladies Rares du Développement Génital: du Fœtus à l’Adulte, Filière Maladies Rares Endocriniennes, Bron, France
- Service d’endocrinologie pédiatrique, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Bron, France
| | - Sandrine Giscard D’Estaing
- Institut Cellule Souche et Cerveau (SBRI), Unité de Institut national de la recherche médicale (INSERM) 1208, Centre de Recherche INSERM, Bron, France
- Service de médecine de la reproduction, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Bron, France
- Faculté de médecine, Université Claude Bernard Lyon 1, Lyon, France
| | - Béatrice Cuzin
- Chirurgie Urologique, Centre Lyonnais d’Urologie Bellecour, Lyon, France
| | - Frédérique Dijoud
- Institut Cellule Souche et Cerveau (SBRI), Unité de Institut national de la recherche médicale (INSERM) 1208, Centre de Recherche INSERM, Bron, France
- Faculté de médecine, Université Claude Bernard Lyon 1, Lyon, France
- Service d’Anatomie Pathologique, Centre de Biologie et de Pathologie Est, Hospices Civils de Lyon, Bron, France
| | - Florence Roucher-Boulez
- Service de Biochimie et Biologie Moléculaire, Unité Médicale de Biologie Endocrinienne, Centre de Biologie et Pathologie Est, Hospices Civils de Lyon, Bron, France
- Centre de Référence Maladies Rares du Développement Génital: du Fœtus à l’Adulte, Filière Maladies Rares Endocriniennes, Bron, France
- Faculté de médecine, Université Claude Bernard Lyon 1, Lyon, France
- Institut Génétique, Reproduction & Développement (iGReD), Centre national de la recherche scientifique (CNRS), INSERM, Université Clermont Auvergne, Clermont–Ferrand, France
| | - Ingrid Plotton
- Service de Biochimie et Biologie Moléculaire, Unité Médicale de Biologie Endocrinienne, Centre de Biologie et Pathologie Est, Hospices Civils de Lyon, Bron, France
- Institut Cellule Souche et Cerveau (SBRI), Unité de Institut national de la recherche médicale (INSERM) 1208, Centre de Recherche INSERM, Bron, France
- Centre de Référence Maladies Rares du Développement Génital: du Fœtus à l’Adulte, Filière Maladies Rares Endocriniennes, Bron, France
- Service de médecine de la reproduction, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, Bron, France
- Faculté de médecine, Université Claude Bernard Lyon 1, Lyon, France
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Versbraegen N, Gravel B, Nachtegael C, Renaux A, Verkinderen E, Nowé A, Lenaerts T, Papadimitriou S. Faster and more accurate pathogenic combination predictions with VarCoPP2.0. BMC Bioinformatics 2023; 24:179. [PMID: 37127601 PMCID: PMC10152795 DOI: 10.1186/s12859-023-05291-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 04/14/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND The prediction of potentially pathogenic variant combinations in patients remains a key task in the field of medical genetics for the understanding and detection of oligogenic/multilocus diseases. Models tailored towards such cases can help shorten the gap of missing diagnoses and can aid researchers in dealing with the high complexity of the derived data. The predictor VarCoPP (Variant Combinations Pathogenicity Predictor) that was published in 2019 and identified potentially pathogenic variant combinations in gene pairs (bilocus variant combinations), was the first important step in this direction. Despite its usefulness and applicability, several issues still remained that hindered a better performance, such as its False Positive (FP) rate, the quality of its training set and its complex architecture. RESULTS We present VarCoPP2.0: the successor of VarCoPP that is a simplified, faster and more accurate predictive model identifying potentially pathogenic bilocus variant combinations. Results from cross-validation and on independent data sets reveal that VarCoPP2.0 has improved in terms of both sensitivity (95% in cross-validation and 98% during testing) and specificity (5% FP rate). At the same time, its running time shows a significant 150-fold decrease due to the selection of a simpler Balanced Random Forest model. Its positive training set now consists of variant combinations that are more confidently linked with evidence of pathogenicity, based on the confidence scores present in OLIDA, the Oligogenic Diseases Database ( https://olida.ibsquare.be ). The improvement of its performance is also attributed to a more careful selection of up-to-date features identified via an original wrapper method. We show that the combination of different variant and gene pair features together is important for predictions, highlighting the usefulness of integrating biological information at different levels. CONCLUSIONS Through its improved performance and faster execution time, VarCoPP2.0 enables a more accurate analysis of larger data sets linked to oligogenic diseases. Users can access the ORVAL platform ( https://orval.ibsquare.be ) to apply VarCoPP2.0 on their data.
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Affiliation(s)
- Nassim Versbraegen
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium.
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium.
| | - Barbara Gravel
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Charlotte Nachtegael
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Alexandre Renaux
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Emma Verkinderen
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Ann Nowé
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Tom Lenaerts
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium
| | - Sofia Papadimitriou
- Machine Learning Group, Université Libre de Bruxelles, 1050, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, 1050, Brussels, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium
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Gozar H, Bara Z, Dicu E, Derzsi Z. Current perspectives in hypospadias research: A scoping review of articles published in 2021 (Review). Exp Ther Med 2023; 25:211. [PMID: 37090085 PMCID: PMC10119991 DOI: 10.3892/etm.2023.11910] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/09/2023] [Indexed: 04/25/2023] Open
Abstract
Hundreds of papers are written about hypospadias every year referring to all aspects of the pathology, being one of the most common congenital malformations. The present study conducted a scoping review of articles published in 2021 to present the main issues and summarize current perspectives and achievements in the field. It searched for the keyword 'hypospadias' in the three most popular databases (PubMed, Scopus and Web of Science). After the analysis of the publications, they were categorized into different domains. The present review was performed respecting the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA ScR) guidelines. A total of 284 articles were included. These were published in 142 different journals. The most accessed was the Journal of Paediatric Urology with 54 articles. The main identified domains were related to surgical techniques, postoperative care, complications, anesthesia, anatomical factors, genetics, environmental factors, endocrinology, associated malformations, questionnaires and recommendations, management, biological materials, animal models, retrospective studies of centers, social media, bibliometrics, small gestational age, neoplasm, or fertility. Promising modifications of existing surgical techniques were presented with improved outcomes for both the proximal and distal types of hypospadias. Relevant anatomical and etiological, and also genetic factors were clarified. Aspects of the peri- and postoperative management referring to the antibiotherapy, analgesia, dressing techniques, and the future use of novel bioengineering agents to prevent, reduce or treat the occurring complications were discussed.
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Affiliation(s)
- Horea Gozar
- Clinic of Pediatric Surgery and Orthopedics, Târgu Mureș, County Emergency Clinical Hospital, Târgu Mureș 540136, Romania
- Department of Pediatric Surgery, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, Târgu Mureș 540142, Romania
| | - Zsolt Bara
- Clinic of Pediatric Surgery and Orthopedics, Târgu Mureș, County Emergency Clinical Hospital, Târgu Mureș 540136, Romania
| | - Emilia Dicu
- Clinic of Pediatric Surgery and Orthopedics, Târgu Mureș, County Emergency Clinical Hospital, Târgu Mureș 540136, Romania
| | - Zoltán Derzsi
- Clinic of Pediatric Surgery and Orthopedics, Târgu Mureș, County Emergency Clinical Hospital, Târgu Mureș 540136, Romania
- Department of Pediatric Surgery, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureș, Târgu Mureș 540142, Romania
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Xie Y, Wu C, Li Z, Wu Z, Hong L. Early Gonadal Development and Sex Determination in Mammal. Int J Mol Sci 2022; 23:ijms23147500. [PMID: 35886859 PMCID: PMC9323860 DOI: 10.3390/ijms23147500] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/29/2022] [Accepted: 07/05/2022] [Indexed: 02/04/2023] Open
Abstract
Sex determination is crucial for the transmission of genetic information through generations. In mammal, this process is primarily regulated by an antagonistic network of sex-related genes beginning in embryonic development and continuing throughout life. Nonetheless, abnormal expression of these sex-related genes will lead to reproductive organ and germline abnormalities, resulting in disorders of sex development (DSD) and infertility. On the other hand, it is possible to predetermine the sex of animal offspring by artificially regulating sex-related gene expression, a recent research hotspot. In this paper, we reviewed recent research that has improved our understanding of the mechanisms underlying the development of the gonad and primordial germ cells (PGCs), progenitors of the germline, to provide new directions for the treatment of DSD and infertility, both of which involve manipulating the sex ratio of livestock offspring.
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Affiliation(s)
- Yanshe Xie
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510630, China; (Y.X.); (C.W.); (Z.L.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510630, China
| | - Changhua Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510630, China; (Y.X.); (C.W.); (Z.L.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510630, China
| | - Zicong Li
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510630, China; (Y.X.); (C.W.); (Z.L.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510630, China
| | - Zhenfang Wu
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510630, China; (Y.X.); (C.W.); (Z.L.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510630, China
- Correspondence: (Z.W.); (L.H.)
| | - Linjun Hong
- National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510630, China; (Y.X.); (C.W.); (Z.L.)
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou 510630, China
- Correspondence: (Z.W.); (L.H.)
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Nachtegael C, Gravel B, Dillen A, Smits G, Nowé A, Papadimitriou S, Lenaerts T. Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database (Oxford) 2022; 2022:6566807. [PMID: 35411390 PMCID: PMC9216476 DOI: 10.1093/database/baac023] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 11/19/2022]
Abstract
Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature. The application of this protocol on the oligogenic literature generated a new repository containing 916 oligogenic variant combinations linked to 159 distinct diseases. Information extracted from the scientific literature is supplemented with current knowledge support obtained from public databases. Each entry is an oligogenic combination linked to a disease, labelled with a confidence score based on the level of genetic and functional evidence that supports its involvement in this disease. These scores allow users to assess the relevance and proof of pathogenicity of each oligogenic combination in the database, constituting markers for reporting improvements on disease-causing oligogenic variant combinations. OLIDA follows the FAIR principles, providing detailed documentation, easy data access through its application programming interface and website, use of unique identifiers and links to existing ontologies.
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Affiliation(s)
- Charlotte Nachtegael
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
| | - Barbara Gravel
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Arnau Dillen
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
- Human Physiology and Sports Physiotherapy research group, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Guillaume Smits
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Hôpital Universitaire des Enfants Reine Fabiola, Université Libre de Bruxelles, Avenue Jean Joseph Crocq 15, Brussels 1020, Belgium
- Center of Human Genetics, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, Brussels 1070, Belgium
| | - Ann Nowé
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Sofia Papadimitriou
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
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Laan M, Kasak L, Punab M. Translational aspects of novel findings in genetics of male infertility-status quo 2021. Br Med Bull 2021; 140:5-22. [PMID: 34755838 PMCID: PMC8677437 DOI: 10.1093/bmb/ldab025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/22/2021] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Male factor infertility concerns 7-10% of men and among these 40-60% remain unexplained. SOURCES OF DATA This review is based on recent published literature regarding the genetic causes of male infertility. AREAS OF AGREEMENT Screening for karyotype abnormalities, biallelic pathogenic variants in the CFTR gene and Y-chromosomal microdeletions have been routine in andrology practice for >20 years, explaining ~10% of infertility cases. Rare specific conditions, such as congenital hypogonadotropic hypogonadism, disorders of sex development and defects of sperm morphology and motility, are caused by pathogenic variants in recurrently affected genes, which facilitate high diagnostic yield (40-60%) of targeted gene panel-based testing. AREAS OF CONTROVERSY Progress in mapping monogenic causes of quantitative spermatogenic failure, the major form of male infertility, has been slower. No 'recurrently' mutated key gene has been identified and worldwide, a few hundred patients in total have been assigned a possible monogenic cause. GROWING POINTS Given the high genetic heterogeneity, an optimal approach to screen for heterogenous genetic causes of spermatogenic failure is sequencing exomes or in perspective, genomes. Clinical guidelines developed by multidisciplinary experts are needed for smooth integration of expanded molecular diagnostics in the routine management of infertile men. AREAS TIMELY FOR DEVELOPING RESEARCH Di-/oligogenic causes, structural and common variants implicated in multifactorial inheritance may explain the 'hidden' genetic factors. It is also critical to understand how the recently identified diverse genetic factors of infertility link to general male health concerns across lifespan and how the clinical assessment could benefit from this knowledge.
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Affiliation(s)
- Maris Laan
- Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Laura Kasak
- Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Margus Punab
- Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia.,Andrology Centre, Tartu University Hospital, 50406 Tartu, Estonia.,Institute of Clinical Medicine, University of Tartu, 50406 Tartu, Estonia
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